cd-rixs-data-on-cuo

en: Resonant inelastic x-ray scattering (RIXS) has become a prominent technique to study quasiparticle excitations. With advances in polarization analysis capabilities at different facilities, RIXS offers exceptional potential for investigating symmetry-broken quasiparticles like chiral phonons and magnons. At optical wavelengths birefringence can severely affect polarization states in low-symmetry systems. Here we show its importance for soft x-ray resonances. Given the growing interest in Circular Dichroism (CD) in RIXS, it is important to evaluate how birefringence may affect the RIXS spectra of anisotropic systems. We investigate CuO, a well-known anisotropic material, using Cu L3-edge RIXS and detect significant CD in both magnetic and orbital excitations in the collinear antiferromagnetic phase. We demonstrate that the CD can be modeled by a proper treatment of RIXS scattering amplitudes derived from single-ion calculations with birefringence. Recognizing these effects is crucial for unambiguous identification of subtle dichroic effects induced by symmetry-broken quasiparticles. Furthermore, the combined sensitivity of RIXS and birefringence to local symmetry presents an opportunity to study microscopic changes driven by external perturbations.

en: CD RIXS data on CuO

title_for_slug: cd-rixs-data-on-cuo


$oid: OBSOLETE

en:
Background: The Thiel embalming method offers lifelike tissue preservation, yet its suitability for biomechanical studies remains debated.
Methods: Here, we investigated two human temporal bones, one Thiel-fixed and one fresh-frozen, using dynamic synchrotron-based X-ray imaging under acoustic stimulation.

en: Comparison of Thiel-fixed and fresh-frozen temporal bones with dynamic synchrotron-based X-ray imaging

approval_status: approved

en: The PSI Data Catalog is the central repository directory for scientific metadata generated at the Paul Scherrer Institut (PSI). Powered by SciCat—a community-driven, open-source metadata management framework co-developed by PSI—the catalog provides discoverability and standardized access pathways to petabyte-scale datasets produced across PSI’s large-scale research facilities, including the Swiss Light Source (SLS), the Swiss Spallation Neutron Source (SINQ), and the SwissFEL X-ray free-electron laser.

en: PSI Data Catalog

de: PSI Data Catalog

fr: PSI Data Catalog

it: PSI Data Catalog

political_level: other

state: active

type: organization

psi

capacity: public

de: PSI Open Data Provider

type: dataset

key: guid

key: uri

value: DCAT Harvester SciCat

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente


en: Chirality is a fundamental symmetry element existing at disparate scales and in many categories of scientific fields. Even though symmetry breaking is an indispensable concept for describing qualitatively distinct phenomena, symmetry cannot quantitatively predict measurable quantities. Since chirality is ternary, i.e., left-handed, right-handed, or achiral, the role of its “amplitude” in material properties is habitually not addressed. Considering the role of “amplitude” for time-reversal symmetry breaking, which can be described by magnetization, chirality amplitude is intuitively a key quantity for controlling emergent phenomena. Here, we propose two types of chiral order parameters and demonstrate the tunability of their amplitude at ultrafast timescales. Resonant X-ray diffraction with circular polarization is an established technique to measure crystal chirality directly. Extending this technique to the time domain, we quantify the ultrafast change in chirality amplitude in real time after an optical excitation. Besides, using a THz excitation, we observe oscillations in the resonant diffraction intensities with specific phonon frequencies. This indicates the creation of additional asymmetry, which could also be described as an enhancement in chirality amplitude. Our proposed concept of chirality amplitude and its ultrafast control may lead to a unique approach to control chirality-induced emergent phenomena at ultrafast timescales.

en: Tuning chirality amplitude at ultrafast timescales


en: The purpose of this experiment was to measure a brain specimen by nf-PXCT, with the aim to measure it afterwards at the ID16A beamline of the ESRF.

en: Raw datasets corresponding to the near-field ptychographic X-ray computed tomography acquisition of a resin-embedded, heavy-metal stained brain speciamen of about 100 micron diameter


en: Near-field PXCT dataset of a resin-embedded, heavy meatal stained brain specimen of about 100 micron diameter. The same sample was measured afterwards at the ID16A beamline of he ESRF


en: The MEG II experiment, based at the Paul Scherrer Institut in Switzerland, reports the result of a search for the decay μ^+->e^+γ from data taken in the first physics run in 2021. No excess of events over the expected background is observed, yielding an upper limit on the branching ratio of B(μ^+->e^+γ) < 7.5 x 10^-13 (90% CL). The combination of this result and the limit obtained by MEG gives B(μ^+->e^+γ) < 3.1 x 10^-13 (90% CL), which is the most stringent limit to date. A ten-fold larger sample of data is being collected during the years 2022–2023, and data-taking will continue in the coming years.

en: A search for  μ^+ -> e^+ γ  with the first dataset of the MEG II experiment

en: physics aod offline database meg2

aod

display_name: aod

database

display_name: database

offline

display_name: offline

physics

display_name: physics


en: Van der Waals (vdW) materials exhibit a variety of states that can be switched with low power at low temperatures, offering a viable cryogenic "flash memory" required for the classical control electronics for solid-state quantum information processing. In 1T-TaS2, a non-volatile metallic 'hidden' state can be induced from an insulating equilibrium charge-density wave ground state using either optical or electrical pulses. Given that conventional memristors form localized, filamentary channels which support the current, a key question for design concerns the geometry of the conduction region in highly energy-efficient 1T-TaS2 devices. Here, we report in operando micro-beam X-ray diffraction, fluorescence, and concurrent transport measurements, allowing us to spatially image the non-thermal hidden state induced by electrical switching of 1T-TaS2. Our results reveal a long-range ordered, non-filamentary switched state that extends well below the electrodes, implying that the self-organized, collective growth of the hidden phase is driven by a combination of charge flow and lattice strain. Our unique combination of techniques showcases the potential of non-destructive, three-dimensional X-ray imaging to study bulk switching properties in microscopic detail, namely electrical control of the vdW layer stacking.

en: Imaging of electrically controlled van der Waals layer stacking in 1T-TaS2


en:
n this work, we introduce the first single-photon-counting hybrid pixel detec-27
tor capable of detecting X-ray energies as low as 550 eV, utilizing the internal28
amplification of Low-Gain Avalanche Diode (LGAD) sensors. This detector is29
thoroughly characterized in terms of Signal-to-Noise Ratio and Detective Quan-30
tum Efficiency. We demonstrate its capabilities through ptychographic imaging31
at MAX IV 4th generation synchrotron light source at the Fe L3-edge (707 eV),32
showcasing the enhanced detection performance of the system. This development33
sets a new benchmark for soft X-ray applications at synchrotrons, paving the way34
for significant advancements in imaging and analysis at lower photon energies.

en: Single-photon counting pixel detector for soft X-rays - raw data


en: We have quantified the complex motion patterns of the human tympanic membrane during acoustic stimulation using dynamic synchrotron-based X-ray microtomography combined with non-rigid registration. Here, we present the datasets used in this study, which were measured at the TOMCAT Beamline X02DA of the Swiss Light Source (Paul Scherrer Institute, Villigen, Switzerland). Three fresh-frozen samples were acoustically stimulated with frequencies ranging from 128 to 512 Hz and sound pressure level ranging from 120 to 151 dB. The datasets, which have 2.75 um pixel size, were reconstructed across 10 phases of motion. The non-rigid registration results, namely spatial transformations from one reference phase to all subsequent phases of motion, are also provided. The complex motion patterns showed displacement 'hot spots' in the posterosuperior quadrant of the tympanic membrane and the pars flaccida for all three specimens, though variation in displacement amplitudes strongly varied between specimens, ranging from <0.15 to nearly 2 um/Pa.

en: Dynamic synchrotron-based microtomography of human tympanic membrane motions


en: Raw data from dataset Y357_3dot_cSAXS_853_S14468-S15686, obtained at the cSAXS beamline at the Swiss Light Source during beamtime 20211852 (e19533).

en: Non-destructive X-ray tomography of brain tissue ultrastructure. Supporting raw data. Dataset Y357_3dot_cSAXS_853_S14468-S15686.

en: The PSI Data Catalog is the central repository directory for scientific metadata generated at the Paul Scherrer Institut (PSI). Powered by SciCat—a community-driven, open-source metadata management framework co-developed by PSI—the catalog provides discoverability and standardized access pathways to petabyte-scale datasets produced across PSI’s large-scale research facilities, including the Swiss Light Source (SLS), the Swiss Spallation Neutron Source (SINQ), and the SwissFEL X-ray free-electron laser.


en: CT data (few raw slice time series, segmented dry and 1Hz operando cathode water) used Mularczyk, A., et al. (2021). 'Operando Liquid Pressure Determination in Polymer Electrolyte Fuel Cells.' ACS Applied Materials & Interfaces 13(29): 34003-34011. https://doi.org/10.1021/acsami.1c04560

en: Tomographic data set of 1Hz 4D imaging of water percolation and percolation path instability in Toray TGP-H-060 gas diffusion layer

en: PSI Data Catalog

envi

en: Environment

tomcat

display_name: tomcat


en: This letter reports the result of the search for the decay mu+ -> e+ gamma undertaken at the Paul Scherrer Institut in Switzerland with the MEG II experiment using the data collected in the 2021–2022 physics runs. The sensitivity of the branching ratio measurement in this search is 2.2 \times 10^{-13}, a factor of 2.4 better than that of the full MEG dataset and obtained in a data taking period of about one fourth that of MEG, thanks to the superior performances of the new detector. The observed data are consistent with the expected background, yielding an upper limit on the branching ratio of mu+->e+gamma < 1.5 \times 10^{-13} (90% C.L.). Additional improvements are expected with the data collected during the years 2023–2024. The data-taking will continue in the coming years.

en: New limit on mu ^+ -> e^+ gamma decay with the MEG II experiment

en: database meg2 physics aod offline


en: Analyzing the structure and dynamics of the human middle ear is crucial for understanding biomechanics and improving clinical practice; however, characterizing the motion of middle ear structures is challenging due to their small sizes, location inside the temporal bone, and minute displacements. Synchrotron radiation-based X-ray microtomography can visualize the entire intact middle ear with micrometer resolution and, combined with dynamic acquisition, reveal motion in response to acoustic stimulation. Unfortunately, access to synchrotron radiation facilities is limited, time-resolved experiments require specialized experimental setups, and handling the related TB-scale data volumes requires high performance computing infrastructure. Data sharing efforts can increase accessibility and encourage development of new research directions. Here, we share dynamic microtomography datasets of 12 of the same samples acquired during acoustic stimulation at a frequency of 128 Hz and sound pressure level of 120 dB. These datasets allow for the combined analysis of rich anatomical information and motion patterns across the entire middle ear.

en: Dynamic synchrotron X-ray microtomography of 12 intact human middle ears during acoustic stimulation

en: middle-ear time-resolved-imaging dynamic-x-ray-microtomography hearing-research

dynamic-x-ray-microtomography

display_name: dynamic-x-ray-microtomography

hearing-research

display_name: hearing-research

middle-ear

display_name: middle-ear

time-resolved-imaging

display_name: time-resolved-imaging


en: Analyzing the structure and dynamics of the human middle ear is crucial for understanding biomechanics and improving clinical practice; however, characterizing middle ear structures is challenging due to their small sizes, location inside the temporal bone, and minute displacements. Synchrotron radiation-based X-ray microtomography can visualize both the soft and hard tissues of the entire intact middle ear with micrometer resolution. Unfortunately, access to synchrotron radiation facilities is limited and handling the related TB-scale data volumes requires high performance computing infrastructure. Data sharing efforts can increase accessibility and encourage development of new research directions. Here, we share static microtomography datasets covering the entire middle ear and surroundings for 15 fresh-frozen human temporal bones with voxel sizes of 2.75 or 5.8 µm. For convenience, we the data are re-oriented to an anatomical coordinate system where the main axis of the malleus runs approximately along the y-axis (from head to umbo) and the stapes runs approximately along the z-axis (from incudostapedial joint to footplate). These re-oriented volumes were cropped to the middle ear including joints, tendons, and ligaments. These datasets allow for the analysis of rich anatomical information across a range of specimens.

en: Anatomically oriented static synchrotron X-ray microtomography of 15 intact human middle ears

en: anatomy hearing-research synchrotron-radiation x-ray-microtomography middle-ear

anatomy

display_name: anatomy

synchrotron-radiation

display_name: synchrotron-radiation

x-ray-microtomography

display_name: x-ray-microtomography


en: In the associated article to these datasets, we investigate the effect of lossy compression of original X-ray projections onto the final tomographic reconstructions. We demonstrate that a compression factor of at least 3-4x does generally not impact the reconstruction quality. Potentially, compression with this factor could therefore be used in a transparent way to the user community for instance prior to data archiving. Higher factors (6-8x) can be achieved for tomographic volumes with a high signal-to-noise ratio as it is the case for phase retrieved datasets.

en: Selection of representative datasets for data compression investigations


en: Raw data associated with the paper entitled 'Pinning of antiferromagnetic domain walls and domain structure in ultrathin La0.45Sr0.55MnO3 films'.


en:
The experimental realisation of unconventional superconductivity and charge order
in kagome systems AV3Sb5 is of critical importance. This work presents the most
systematic study to date, employing tuning parameters such as doping, hydrostatic
pressure, magnetic fields, and depth, using muon spin rotation, AC susceptibility, and
STM, to uncover tunable exotic magnetism in the normal state of Cs(V1−xNbx)3Sb5
with x=0.07 (Nb0.07-CVS), which transitions to a chiral superconducting state under
pressure. Our findings reveal that the bulk of Nb0.07-CVS (at depths >20 nm from the
surface) experiences time-reversal symmetry (TRS) breaking below T ∗ = 40 K, lower
than the charge order onset temperature, TCO = 58 K. However, near the surface (<20
nm), the TRS breaking signal doubles and onsets at TCO, indicating that Nb-doping
decouples TRS breaking from charge order in the bulk but synchronises them near
the surface. Additionally, Nb-doping raises the superconducting critical temperature
TC from 2.5 K to 4.4 K. Applying hydrostatic pressure enhances both TC and the
superfluid density by a factor of two, with a critical pressure pcr ≃ 0.85 GPa, suggesting
competition with charge order. Notably, above pcr, we observe nodeless electron pairing
and weak internal fields below TC, pointing to chiral superconducting pairing. Overall,
these results demonstrate a highly unconventional normal state with a tunable onset of
TRS breaking, and a transition to chiral superconductivity under low pressures, with
an unconventional correlation between TC and the superfluid density.

en: Pressure induced transition from chiral charge order to time-reversal symmetry-breaking superconducting state in Nb-doped CsV3Sb5 - LEM data

en: The PSI Data Catalog is the central repository directory for scientific metadata generated at the Paul Scherrer Institut (PSI). Powered by SciCat—a community-driven, open-source metadata management framework co-developed by PSI—the catalog provides discoverability and standardized access pathways to petabyte-scale datasets produced across PSI’s large-scale research facilities, including the Swiss Light Source (SLS), the Swiss Spallation Neutron Source (SINQ), and the SwissFEL X-ray free-electron laser.


en: Aligned complex-valued projections and tomographic datasets from 3 PXCT acquisitions on the same catalyst specimen primarily composed of zeolite, alumina, and nickel, acquired at 3 different photon energies close to the nickel absorption edge. The file information.txt contains a description of the data. We also include the software scripts used to process the data.

en: Aligned complex-valued projections and 3D tomographic datasets from a catalyst specimen

en: PSI Data Catalog


en: Multiphase fluid flow through porous media occurs in various natural and engineered settings. How local wetting phenomena, such as those induced by pore-scale roughness, translate into effective multiphase fluid flow behavior observed at larger scales remains poorly understood. In this study, an unsteady-state waterflooding experiment in a sandstone sample with pronounced surface roughness was conducted and imaged using synchrotron-based sub-micron time-resolved X-ray tomography at the TOMCAT beamline of the Swiss Light Source. The data shows how local roughness features cause fluid displacements to occur as a series of smaller sub-pore scale events controlled by (de-)pinning of the fluid-fluid interface and wetting layer growth. Our data offers quantitative insights into multiphase fluid displacement process and provides a basis to verify numerical simulations of pore-scale multiphase fluid flow.

en: A submicron time-resolved X-ray tomography dataset investigating the role of surface roughness during multiphase flow in porous media

envi

en: Environment


en: In the publication associated with this data collection, we present a methodological framework suitable for reconstruction of the whole mouse brain cerebral microvasculature by synchrotron radiation X-ray tomographic phase-contrast microscopy with isotropic pixel size of 0.65 μm. The technique allows morphological measurements of even the smallest capillary vessel branches over the entire brain. In this data collection we provide some original tomographic images produced by the method, and an analysis code that can make a segmentation of the vessels and extract the vessel graph from the images.

en: Micrometer-resolution tomographic reconstructions of whole mouse brain microvasculature and an analysis program


en: Ptychographic and tomographic reconstructions of a triblock copolymer soft matter crystal replicated into gold


en: Time-resolved SRµCT study of the pore and lamella evolution of bread samples in-situ during baking inside a microwave-convective oven.

en: In-situ microwave-convective baking of bread using 4D SRµCT


en: This dataset contains time-resolved X-ray tomographic microscopy on wicking in interlacing polyethylene terephthalate (PET) yarns.  Wicking is a two-phase flow phenomenon in porous media where a wetting fluid replaces spontaneously the non-wetting fluid, here water and air. The employed setup provides high-quality four-dimensional imaging of water uptake in yarn interlaces in a FOV of 5.5 mm height at 2.75 um voxel size and up to 2.5 full scans per second. The segmented data gives the detailed inter-fiber pore structure and allows to track the evolution of the water configuration at pore level with its evolution of free (interfacial) energy.  Yarn-to-yarn transition is found to coincide with slow water advance in a thin interface zone at the yarn contact. The pore spaces of the two yarns merge within this interface zone and provide a transition path. A deep capillary pressure minimum occurs while water passes through the center of the interface zone, effectively delaying the wicking flow.

en: Wicking through complex interfaces at interlacing yarns


en: This dataset has been used in the work titled ‘Metamorphic fabrics can be formed by stress without significant strain’ by Gilgannon et al. (2023). It was acquired at the TOMCAT beamline as part of a long term science proposal called ‘Implementing novel X-ray transparent triaxial deformation rigs to study fluid-rock interaction at mid-crustal conditions’. This research was funded through NERC standard grant NE/T001615/1.

en: Metamorphic fabrics can be formed by stress without significant strain - sample VA18


en:
Double hydroxide perovskites with magnetic transition-metal ions were recently identified as a unique class of materials that combine magnetic frustration with correlated proton disorder - a prerequisite for quantum-disordered fluctuating magnetic ground states resembling spin liquids. Here we present the results of muon spin relaxation (muSR) measurements carried out on fully deuterated samples of the double hydroxyperovskites CuSn(OH)6 (S=1/2) and MnSn(OH)6 (S=5/2) over the temperature range 0.053-50 K. The absence of any long-range magnetic order is confirmed down to 0.053 K. We observe no oscillations of the muon asymmetry down to the lowest temperature. The muon relaxation rates show a continuous increase with decreasing temperature, indicating persistent spin fluctuations in both compounds. Spin correlations are consistent with homogeneous spin dynamics. These observations reinforce the assertion that both compounds have a quantum-dynamic magnetic ground state that is consistent with a spin-liquid-like phase stabilized by proton disorder.
This dataset contains the corresponding muon spin spectroscopy raw time histograms, measured on CuSn(OD)6 and MnSn(OD)6.

en: Dataset: Spin-liquid-like ground states in the double hydroxyperovskites CuSn(OD)6 and MnSn(OD)6 evidenced by muSR spectroscopy

flame

display_name: flame

smus

display_name: smus


en: Analyzing the structure and dynamics of the human middle ear is crucial for understanding biomechanics and improving clinical practice; however, characterizing middle ear structures is challenging due to their small sizes, location inside the temporal bone, and minute displacements. Synchrotron radiation-based X-ray microtomography can visualize both the soft and hard tissues of the entire intact middle ear with micrometer resolution. Unfortunately, access to synchrotron radiation facilities is limited and handling the related TB-scale data volumes requires high performance computing infrastructure. Data sharing efforts can increase accessibility and encourage development of new research directions. Here, we share static microtomography datasets covering the entire middle ear and surroundings for 15 fresh-frozen human temporal bones with voxel sizes of 2.75 or 5.8 µm. These datasets allow for the analysis of rich anatomical information across a range of specimens.

en: Static synchrotron X-ray microtomography of 15 intact human middle ears

en: middle-ear synchrotron-radiation x-ray-microtomography hearing-research anatomy

en: The PSI Data Catalog is the central repository directory for scientific metadata generated at the Paul Scherrer Institut (PSI). Powered by SciCat—a community-driven, open-source metadata management framework co-developed by PSI—the catalog provides discoverability and standardized access pathways to petabyte-scale datasets produced across PSI’s large-scale research facilities, including the Swiss Light Source (SLS), the Swiss Spallation Neutron Source (SINQ), and the SwissFEL X-ray free-electron laser.


en: The data available here consists of XPEEM, SQUID, transport, RHEED, and atomic force probe microscopy raw data that was used for a publication entitled "Direct Imaging of the Magnetoelectric Coupling in BaTiO3/La0.9Ba0.1MnO3 Multiferroic Heterostructures" by F. Stramaglia, G. Panchal, L. Tovaglieri, C. Lichtensteiger, F. Nolting, and C. A. F. Vaz.

en: PSI Data Catalog


en:
In the original article associated with this dataset, we present synchrotron radiation-based X-ray phase-contrast imaging (X-PCI) as an efficient and non-destructive imaging technique to provide high resolution, three-dimensional (3D) information on myocardial microstructure in left ventricular hypertrophy. In the pilot study, the methodology was applied on tissue samples obtained from three patients that underwent septal myectomy. This technique allows for multi-scale investigation - to localize regions of interest, low resolution overlapping scans, at 5.8um effective pixel size, were achieved to cover the entire sample, whereas high resolution datasets, at 0.65 um pixel size, were collected locally allowing assessment of myocyte organization, 3D connective tissue distribution and vasculature.
X-PCI data was visualized and analyzed. 3D myocyte arrangement, interstitial fibrosis, collagen disarray, and vascular remodelling were identified and related to findings of non-invasive cardiac imaging. The integration of imaging data data illustrates the correspondence of macrostructural and functional non-invasive phenotypes with invasive microstructural phenotypes, suggesting the potential clinical utility of non-invasive myocardial deformation patterns in phenotyping left ventricular hypertrophy.

en: Etiology-Discriminative Multimodal Imaging of Left Ventricular Hypertrophy and Synchrotron-Based Assessment of Microstructural Tissue Remodeling

envi

en: Environment


en: The data is part of a manuscript submitted to the journal Phys. Chem. Chem. Phys., entitled " On the absolute photoionization cross section and threshold photoelectron spectrum of two reactive ketenes in lignin valorization: fulvenone and 2-carbonyl cyclohexadienone†". [https://doi.org/10.1039/D1CP05206C, Phys. Chem. Chem. Phys., 2022,24, 3655-3663 ]  This work is supported by the Swiss National Science Foundation (project number 200021_178952).

en: Dataset: On the absolute photoionization cross section and threshold photoelectron spectrum of two reactive ketenes in lignin valorization: fulvenone and 2-carbonyl cyclohexadienone


en: X-ray photon correlation scattering measurements are undertaken on a thermally active artificial spin ice based on the square lattice, referred to as artificial square ice, to probe the fluctuation timescales as a function of temperature as the system passes through the paramagnetic- antiferromagnetic phase transition, which belongs to the two-dimensional Ising universality class.

en: Stretched exponential magnetic relaxation dynamics in artificial square ice revealed through x-ray photon correlation spectroscopy

en: x-ray-photon-correlation-spectroscopy detector-frames synchrotron 23-id-1 nsls-ii csx coherent-soft-x-ray-scattering

coherent-soft-x-ray-scattering

display_name: coherent-soft-x-ray-scattering

csx

display_name: csx

detector-frames

display_name: detector-frames

nsls-ii

display_name: nsls-ii

synchrotron

display_name: synchrotron

x-ray-photon-correlation-spectroscopy

display_name: x-ray-photon-correlation-spectroscopy


en: The binding and release of ligands from their protein targets is central to fundamental biological processes as well as to drug discovery. Photopharmacology introduces chemical triggers that allow the changing of ligand affinities and thus biological activity by light. Insight into the molecular mechanisms of photopharmacology is largely missing because the relevant transitions during the light-triggered reaction cannot be resolved by conventional structural biology. Using time-resolved serial crystallography at a synchrotron and X-ray free-electron laser, we have captured the release of azo-combretastatin A4 and the resulting conformational changes in tubulin. Nine structural snapshots from 1 ns to 100 ms complemented by simulations show how cis-to-trans isomerization of the azobenzene bond leads to a switch in ligand affinity, opening of an exit channel, and collapse of the binding pocket upon ligand release. The resulting global backbone rearrangements are related to the action mechanism of tubulin-binding drugs against gout, cancer, and COVID-19.

en: Watching the release of a photopharmacological drug from tubulin using time-resolved serial crystallography: 10 microseconds after photoactivation.


en: This dataset has been used in the work titled ‘Metamorphic fabrics can be formed by stress without significant strain’ by Gilgannon et al. (2023). It was acquired at the TOMCAT beamline as part of a long term science proposal called ‘Implementing novel X-ray transparent triaxial deformation rigs to study fluid-rock interaction at mid-crustal conditions’. This research was funded through NERC standard grant NE/T001615/1.

en: Metamorphic fabrics can be formed by stress without significant strain - sample VA17


en:
The extinct plant group Bennettitales (Cycadeoidales) was a prominent part of Mesozoic vegetation. The group has been studied extensively and for more than 100 years it has been central in discussions of the relationships among the major groups of seed plants in which extinct plants were also considered. Despite much effort the phylogenetic position of the Bennettitales is still unresolved with a major obstacle being uncertainty about how to interpret the organisation and structure of the seed. The most widely accepted interpretation has been that the seed, like the seeds of most conifers, has a single integument around the nucellus and lacks any additional coverings. An alternative interpretation is that the seed integument is surrounded by an envelope comparable to the situation in extant Gnetales and extinct Erdtmanithecales. The petrified seed cone of Cycadeoidea (Bennettites) morierei described in the late nineteenth century from the Early Cretaceous of Normandy is one of the most informative bennettitalean reproductive structures with its superb preservation offering great potential for resolving the unsettled discussion regarding seed structure in Bennettitales.
	C. morierei was carefully documented by Octave Lignier in his monumental study “Végétaux fossiles de Normandie. Structure et affinités du Bennettites morierei Sap. & Mar. (sp.)” from 1894, but despite his meticulous analysis of the fossil, Lignier left certain questions open in his interpretation and in his widely cited reconstruction of the structure of the seed. In the paper associated with the datasets provided here we have re-examined fragments of Cycadeoidea morierei using synchrotron X-ray tomographic microscopy (SRXTM) to attempt to answer some of these open questions.
	Cycadeoidea morierei is based on a single petrified seed cone. The specimen was fractured by Lignier, who prepared several thin sections, in longitudinal as well as transverse directions in preparing his account. The original material was stored at the University of Caen, France, but most was lost during the second World War. However, several larger and smaller fragments of the seed cone were later recovered at the university and made available for the present study. Among the fragments studied using SRXTM were small isolated, abraded seeds and interseminal scales (e.g., fragments 6 and 8) and a few small groups of fractured seeds and interseminal scales still tightly packed together (e.g., fragment 17). Typically, these small fragments are broken at the base and only rarely are remains of the seed stalk preserved. One larger fragment (fragment 24) consists of several seeds with seed stalks intact. For comparison with Cycadeoidea morierei we also examined a fragment of another classic petrified seed cone, Cycadeoidea gibsoniana from the Early Cretaceous of isle of Wight, Southern England, using SRXTM. The results, combined with a comparative survey of other fossil material, indicate that the seeds of Bennettitales had at least one, perhaps two, envelopes covering the integument, comparable to what is seen among extant Gnetales, extinct Erdtmanithecales, and diverse fossil seeds recovered from Early Cretaceous mesofossil assemblages. Most of the SRXTM analyses of the Cycadeoidea material were carried during 2009-2023 on the TOMCAT beamline, SLS, Paul Scherrer Institute, Villigen, Switzerland. Fragment 24 was analysed at the new I-TOMCAT beamline at SLS in November 2025.

en: Synchrotron radiation X-ray tomographic microscopy datasets for seed structure in Cycadeoidea morierei


en:
The articles based on this dataset discuss wicking in polyethylene terephthalate (PET) yarns using time-resolved X-ray tomographic microscopy. Wicking is a two-phase flow phenomenon in porous media where a wetting fluid replaces spontaneously the non-wetting fluid, here water and air.
The employed setup provides high-quality four-dimensional imaging of water uptake in yarns in a FOV of 3.3 mm height at 2.75 um voxel size and up to one full scan per second. The segmented data gives the detailed inter-fiber pore structure and allows to track the evolution of the water configuration at pore level with its evolution of free (interfacial) energy. We find that water wicking in yarns happens as network propagation with two types of steps: rapid pore filling events and long delays between those events. The long delays are caused by an unfavorable free energy evolution at structure-induced quasi-equilibria. Due to the sparsity of the pore network and the lack of alternative propagation paths, macroscopic wicking in yarns shows irregular step-wise dynamics with high variability.

en: Wicking dynamics in complex yarn pore networks

en: The PSI Data Catalog is the central repository directory for scientific metadata generated at the Paul Scherrer Institut (PSI). Powered by SciCat—a community-driven, open-source metadata management framework co-developed by PSI—the catalog provides discoverability and standardized access pathways to petabyte-scale datasets produced across PSI’s large-scale research facilities, including the Swiss Light Source (SLS), the Swiss Spallation Neutron Source (SINQ), and the SwissFEL X-ray free-electron laser.


en: Metamorphic fabrics can be formed by stress without significant strain - sample VA20

en: PSI Data Catalog


en: Metamorphic fabrics can be formed by stress without significant strain - sample VA10

envi

en: Environment


en:
Ptychographic hard X-ray computed tomography (PXCT) is a recent method allowing imaging with quantitative electron-density contrast. Here, we imaged at cryogenic temperature and without sectioning, cellular and subcellular structures of a chemically-fixed and stained wild-type mouse retina (tomogram 1), including axons and synapses with complete isotropic 3D information over tens of microns. Comparison with tomograms of degenerative retina from a mouse model of retinitis pigmentosa (tomogram 2) illustrates the potential of this method for analysing disease processes like neurodegeneration at sub-200 nm resolution.

As a non-destructive imaging method, PXCT is very suitable for correlative imaging. Within the outer plexiform layer containing the photoreceptors synapses, we identified somatic synapses. We used a small region inside the X-ray-imaged sample for further high-resolution focused ion beam / scanning electron microscope (FIB/SEM) tomography (tomogram 3). The subcellular structures of synapses obtained with the X-ray technique matched the EM data demonstrating that PXCT is a powerful scanning method for tissue volumes of more than 60 cells and sensitive enough for identification of regions as small as 200 nm, remaining available for further structural and biochemical investigations.

en: Imaging of retina cellular and subcellular structures using ptychographic hard X-ray tomography.

en: neurobiology retinitis tomography hard electron ptychography mouse synapse photoreceptors x-ray sem neurodegeneration pigmentosa retina

electron

display_name: electron

hard

display_name: hard

mouse

display_name: mouse

neurobiology

display_name: neurobiology

neurodegeneration

display_name: neurodegeneration

photoreceptors

display_name: photoreceptors

pigmentosa

display_name: pigmentosa

ptychography

display_name: ptychography

retina

display_name: retina

retinitis

display_name: retinitis

sem

display_name: sem

synapse

display_name: synapse

tomography

display_name: tomography

x-ray

display_name: x-ray


en: Raw data from dataset C319_EPL1_cSAXS_273_S01394-S02309, obtained at the cSAXS beamline at the Swiss Light Source during beamtime 20190654 (e17964).

en: Non-destructive X-ray tomography of brain tissue ultrastructure. Supporting raw data. Dataset C319_EPL1_cSAXS_273_S01394-S02309.


en: Low-energy muSR (LE-muSR) enables depth-resolved studies of magnetic and electronic properties from the surface into the near-surface region, but the measured transverse-field asymmetry is not an intrinsic constant but depends on implantation energy and beamline conditions. Following an upgrade of the single-muon tagging system at the LEM beamline at PSI in 2023, updated asymmetry calibrations are required. Here, we present updated reference measurements that establish the energy-dependent maximum asymmetry using a silver reference and quantify spurious contributions from reflected muons using a nickel reference. In addition, we address systematic reductions of the measured asymmetry arising from incomplete beam--sample overlap by introducing a sample-size-dependent correction factor. This factor is obtained from musrSim/Geant4 simulations incorporating an updated electrostatic field map of the sample environment and is benchmarked using implantation-energy scans on SrTiO3 samples of different dimensions. Together, these updated calibrations and the simulation-based overlap correction provide a practical and up-to-date framework for LE-muSR data correction under current beam conditions and enable quantitative depth-resolved analysis of (dia)magnetic volume fractions.

en: Correcting the Depth-Dependent Asymmetry in Low-Energy muSR


en:
The articles based on this dataset discuss structural dynamics in an operating zero-gap forward-bias bipolar membrane CO2 electrolyzer using time-resolved X-ray tomographic microscopy. The employed setup provides high-quality four-dimensional imaging in a FOV of 5 mm height at 2.75 um voxel size and one full scan (1s acquisition) every minute. Different routes for segmentation yield the membrane with forming cavities, the catalyst layer and the porous cathode gas diffusion layer including pore and flow field filling with liquid water.
We find strong swelling of the membrane, membrane delamination, anode catalyst layer degradation, but no flooding of the cathode.

en: Operando X-ray tomography in bipolar membrane electrolyte CO2-electrolysis


en: The ability of photofunctional organic molecules to perform chemical/mechanical work or convert photons into electrons results from a complex interplay between charge transfer and transient atomic rearrangements involving the local environment. These ultrafast structural dynamics have remained elusive experimentally, preventing a mechanistic understanding of the electronic-nuclear couplings. We will use the high X-ray photon flux and sub ps time resolution of the SwissFEL to realize the first X-ray scattering observation of solute-solvent dynamics following photoinduced charge transfer in an organic chromophore. The sensitivity of the scattering to changes in atomic distances will be exploited not only to track in real time the intra- and intermolecular structural dynamics but also to identify the electronic changes that trigger them. The results will pave the way for a better understanding of the factors governing the outcomes of photoreactions across chemistry and biology.

en: Photoinduced intramolecular and solvation dynamics of an organic chromophore in polar solvent


en: This dataset has been used in the work titled ‘Metamorphic fabrics can be formed by stress without significant strain’ by Gilgannon et al. (2023). It was acquired at the TOMCAT beamline as part of a long term science proposal called ‘Implementing novel X-ray transparent triaxial deformation rigs to study fluid-rock interaction at mid-crustal conditions’. This research was funded through NERC standard grant NE/T001615/1.

en: Metamorphic fabrics can be formed by stress without significant strain - sample VA_A


en: The associated article to this dataset describes a new genus and species, Renbernia zhoui E.M.Friis, P.R.Crane & K.R.Pedersen from the Early Cretaceous (early-middle Albian) mesofossil flora collected in Potomac Group sediments at the Puddledock locality, Virginia, U.S.A. The new taxon is based on microsporangiate structures with Decussosporites-type pollen in situ in densely arranged microsporangiophores. The microsporangia are elongate with extrorse and valvate dehiscence. Synchrotron radiation X-ray tomographic microscopy shows that they are bisporangiate. The in situ Decussosporites-type pollen is elliptical with an unusual arrangement of apertures. On the presumed distal face there is a long median colpus flanked laterally by two equally long lateral colpi. On the presumed proximal side there is a short transverse colpus perpendicular to the longitudinal colpi. Renbernia zhoui is compared to Brenneria potomacensis, another microsporangiate structure from the Potomac Group sediments with Decussosporites-type pollen in situ. B. potomacensis is slightly older than Renbernia zhoui and is distinguished by the more rounded microsporangia and the pollen is more distinctly saccate. A comparison with the extinct pollen genus Eucommiidites and a possible link of Renbernia zhoui to the Bennettitales-Erdtmanithecales-Gnetales group, which is diverse and common in the Puddledock mesofossil flora, is discussed.

en: Extinct seed plant diversity in the Early Cretaceous: An enigmatic new microsporangiate fossil with Decussosporites pollen in situ

en: The PSI Data Catalog is the central repository directory for scientific metadata generated at the Paul Scherrer Institut (PSI). Powered by SciCat—a community-driven, open-source metadata management framework co-developed by PSI—the catalog provides discoverability and standardized access pathways to petabyte-scale datasets produced across PSI’s large-scale research facilities, including the Swiss Light Source (SLS), the Swiss Spallation Neutron Source (SINQ), and the SwissFEL X-ray free-electron laser.


en: Metamorphic fabrics can be formed by stress without significant strain - sample VA_s_1

en: PSI Data Catalog

envi

en: Environment


en:
Circular dichroism observed by resonant x-ray diffraction at the Cu L3 edge was investigated in a chiral antiferromagnet, Pb(TiO)Cu4(PO4)4, which shows magnetic quadrupole order (TN = 7K). At temperatures
above TN, space-group-forbidden reflection 100 is observed due to the anisotropic tensor of susceptibility (ATS) scattering. With decreasing temperature, the reflection intensity shows substantial circular dichroism below
TN. We found one-to-one correspondence between the sign of the circular dichroism and that of the sample’s crystallographic chirality. In addition, the reflection intensity depends on the product of poling magnetic and
electric fields. The circular dichroism observed in this study is interpreted as the interference between the ATS and the magnetic scatterings. This finding shows that the interference scattering probes both the chirality and the
order parameter of the magnetic quadrupole order in this chiral antiferromagnetic.

en: Chirality and magnetic quadrupole order in Pb(TiO)Cu4(PO4)4 probed by interference scattering in resonant x-ray diffraction


en: This repository contain the experimental data for  the magnetic orders and excitations of the distorted kagome intermetallic magnet TmAgGe published in Phys. Rev. B 107, 224419 (2023). Single crystal diffraction and inelastic neutron diffraction was carried out on the Zebra and CAMEA beamlines at the Paul Scherrer Institut.

en: Magnetic ground state and perturbations of the distorted kagome Ising metal TmAgGe

en: sinq magnetic-structure camea zebra magnetic-excitations tmagge

camea

display_name: camea

magnetic-excitations

display_name: magnetic-excitations

magnetic-structure

display_name: magnetic-structure

sinq

display_name: sinq

tmagge

display_name: tmagge

zebra

display_name: zebra


en:
X-ray tomographic microscopy of structural damages in a forward-bias bipolar membrane CO2-electrolyzer
TO BE EXTENDED


en: Data to reproduce the experiments described in the paper: "Image2Reg: Linking Chromatin Images to Gene Regulation using Genetic perturbations screens" by Daniel Paysan, Adityanarayanan Radhakrishnan, G.V. Shivashankar and Caroline Uhler. The raw imaging data from Rohban et al. (2017) and from the Joint Undertaking in Morphological Profiling Cell Painting Consortium (Chandrasekaran et al., 2023) used in the study was obtained from IDR0033 available at "http://idr-demo.openmicroscopy.org/webclient/?show=screen-1751" , respectively from the Cell Painting Gallery on the Registry of Open Data on AWS "https://registry.opendata.aws/cellpainting-gallery/". Please note that these data resources need to be appropriately referenced if this dataset is used. Please refer to the above mentioned paper for a complete list of the used data sets.

en: Data for Image2Reg


en:
This time-resolved tomographic microscopy dataset captures disintegration dynamics of pharmaceutical tablets. A diverse set of mini-tablets of 2 mm diameter with compositions varied according to a full factorial design of experiments were individually imaged as they underwent disintegration in water. We established a predominantly GPU based software pipeline for raw data reconstruction, including phase contrast filtering, and reconstructed image segmentation to enable visualization and quantitative analysis. The experimental system was highly dynamic, such that the quality of reconstructed images is impeded by motion artefacts, especially at advanced stages of tablet disintegration. To meet the challenges of varying image quality, we devised and trained a convolutional neural network (CNN) based on the U-Net architecture to segment the reconstructed images. Only the segmented data enables visualization for qualitative analysis and allows for quantification of the captured disintegration process.

Detailed descriptions of data acquisition parameters, the custom software pipeline used for image reconstruction and image segmentation, as well as a sample analysis of the data are discussed in the associated publicaton : https://doi.org/10.1016/j.heliyon.2024.e26025
The source code of the software pipeline used to reconstruct and segment the data is available here: https://github.com/walsam00/4D_CT_code
Videos visualizing the entire dataset are available here: https://zenodo.org/doi/10.5281/zenodo.7180040 as well as here:
https://www.youtube.com/watch?v=yESTXXv6wbM&list=PLPnSoY_iHSc410wtWpewTeFN3koH3gkQw&index=1

en: Three - dimensional reconstruction of time-resolved disintegration process in pharmaceutical tablets


en: Multiple genomic and proteomic studies have suggested that peripheral blood mononuclear cells (PBMCs) respond to tumor secretomes and thus could provide possible avenues for tumor prognosis and treatment evaluation. We hypothesized that the chromatin organization of PBMCs obtained from liquid biopsies, which integrates secretome signals with gene expression programs, provides efficient biomarkers to characterize tumor signals and the efficacy of proton therapy in tumor patients. In the paper associated to the enclosed data set, we show that chromatin imaging of PBMCs combined with machine learning methods provides such robust and predictive chromatin biomarkers. Our work shows that such chromatin biomarker enable the accurate diagnoses of different tumor types and monitoring of treatment effects of patients undergoing proton therapy and thus highlights their potential for accurate cancer diagnostics and therapy evaluation.

en: Imaging data related to the paper: "Imaging and AI based Chromatin Biomarkers for Diagnosis and Therapy Evaluation from Liquid Biopsies" by Kiran Challa* and Daniel Paysan*, Dominic Leiser, Nadia Sauder, Damien C. Weber and G.V. Shivashankar.


en: The controlled rotation of acoustically levitated samples is beneficial for analyzing sample properties, e.g., in a recently reported room temperature x-ray diffraction experiment, wherein thin film sample holders comprising thin film disks with short blades attached around their circumference were utilized. However, the mechanism of producing the torque and the determinant factor of the rotation direction for these planar ultrasonic rotors have been elusive. We, therefore, study the impact of the size and shape on the rotation characteristics of these ultrasonic rotors in air and further study the influence of the viscosity of fluid. Theory and experiment demonstrate the essential role of the short blades in producing the acoustic torque both in air and water. In the airborne case, the shape and arrangement of the blades are found to determine the rotation direction. In water, with a dynamic viscosity 55 times higher than that of air, we demonstrate that ultrasonic rotors down to 25-μm-disk-diameter function in an optimized experimental geometry with approximately the same actuation efficiency as in air. Our results will be beneficial to further improve the applicability of the ultrasonic rotors as sample holders for airborne experiments and to explore the micrometer-scale ultrasonic rotors in liquid.

en: Data for Size and shape dependent rotation characteristics of thin film ultrasonic rotors


en: This dataset has been used in the work titled ‘Metamorphic fabrics can be formed by stress without significant strain’ by Gilgannon et al. (2023). It was acquired at the TOMCAT beamline as part of a long term science proposal called ‘Implementing novel X-ray transparent triaxial deformation rigs to study fluid-rock interaction at mid-crustal conditions’. This research was funded through NERC standard grant NE/T001615/1.

en: Metamorphic fabrics can be formed by stress without significant strain - sample VA22

en: The PSI Data Catalog is the central repository directory for scientific metadata generated at the Paul Scherrer Institut (PSI). Powered by SciCat—a community-driven, open-source metadata management framework co-developed by PSI—the catalog provides discoverability and standardized access pathways to petabyte-scale datasets produced across PSI’s large-scale research facilities, including the Swiss Light Source (SLS), the Swiss Spallation Neutron Source (SINQ), and the SwissFEL X-ray free-electron laser.


en: High-temperature and high-magnetic-field-induced re-entrant superconductivity has been discovered in the infinite-layer nickelate Sm1−x−yEuxCayNiO2 (SECNO). Infinite-layer nickelates are the closest known analogues of high-Tc cuprate superconductors, yet they host distinct magnetic ground states. Using low-energy muon spin relaxation and polarized neutron reflectometry, we reveal the magnetic order in SECNO. We find that magnetic freezing occurs at a higher-temperature than in other nickelate compounds, and that a substantial net magnetization of 55 kA m−1 ±10 kA m−1 emerges and remains largely unchanged across the superconducting transition. The magnetism in SECNO is disordered and nonuniform.

en: Net Magnetization and Inhomogeneous Magnetic Order in a High-Tc Nickelate Superconductor

en: PSI Data Catalog

envi

en: Environment


en: Plasticity in amorphous SiO2 at the micro-scale is an unsolved problem. We aim to study the responsible deformation mechanisms (densification, shear flow, and shear band formation) and propose a Ptychographic X-ray Computed Tomography (PXCT) experiment to image the three-dimensional density distribution in plastically deformed silica micro-pillars. Understanding the spatial extend and geometric aspects of these mechanisms will contribute to the technological exploitation of these phenomena.

en: Direct observation of micro-plasticity in fused silica glass


en: Recently, we have fabricated heterostructures formed by a ferromagnetic topological insulator Cr-doped (Bi,Sb)2Te3 (CBST) and a non-superconducting antiferromagnet FeTe. Combining electrical transport and ARPES measurements, we demonstrate the coexistence of emergent superconductivity, ferromagnetism, and topological order in these heterostructures; these three essential ingredients make this an ideal candidate to host chiral topological superconductivity. We propose performing low-energy muSR measurements to study the nature of this interface-induced superconducting state, and to determine whether the superconductivity and magnetic order coexist in the same region.

en: Coexistence of Superconductivity and Magnetic Order in Magnetic Topological Insulator Heterostructures


en: The data is part of a manuscript submitted to the journal Chem. Sci., entitled "Isomer-dependent catalytic pyrolysis mechanism of the lignin model compounds catechol, resorcinol and hydroquinone". [DOI	https://doi.org/10.1039/D1SC00654A, Chem. Sci., 2021,12, 3161-3169 ] This work is supported by the Swiss National Science Foundation (project number 200021_178952).

en: Dataset: Isomer-dependent catalytic pyrolysis mechanism of the lignin model compounds catechol, resorcinol and hydroquinone


en: Metamorphic fabrics can be formed by stress without significant strain - sample VA_B


en: The article associated with these data collection describes the development of an image analysis pipeline suitable for analysis of all airspaces of an entire mouse lung. The classical stereology contributed to understanding the lung structure of the healthy and homogeneous lung, but has its limit in the analysis of heterogeneous structures such as diseased lung. Expanding stereology to the entire lung volume will allow for better comprehension of unevenly distributed lung damage. The proposed pipeline consists of several steps and starts with (i) image acquisition with high-resolution synchrotron radiation-based X-ray tomographic microscopy, as well as reconstruction and stitching of the individual scans, followed by (ii) image segmentation with free machine learning tool ilastik and ImageJ and (iii) calculation of the airspace diameter distribution with the thickness map function from the image analysis program pi2. To test the efficacy of the pipeline we analyzed adult mice lungs with cystic fibrosis-like disease or elastase-induced emphysema and their littermate controls. We were able to separately analyze two main lung compartments, the conducting airways and gas-exchange area. The distribution of airspace dimeters indicates the presence of enlarged lung airspaces in both compartments for both disease models. Finally, comparable results were obtained when applying the pipeline to images acquired with μCT, suggesting that our pipeline is applicable to a broader range of imaging modalities.

en: Airspace diameter map - a quantitative measurement of all pulmonary airspaces to characterize structural lung diseases


en: The experimental realisation of unconventional superconductivity and charge order in kagome systems AV3Sb5 is of critical importance. This work presents the most systematic study to date, employing tuning parameters such as doping, hydrostatic pressure, magnetic fields, and depth, using muon spin rotation, AC susceptibility, and STM, to uncover tunable exotic magnetism in the normal state of Cs(V1−xNbx)3Sb5 with x=0.07 (Nb0.07-CVS), which transitions to a chiral superconducting state under pressure. Our findings reveal that the bulk of Nb0.07-CVS (at depths >20 nm from the surface) experiences time-reversal symmetry (TRS) breaking below T ∗ = 40 K, lower than the charge order onset temperature, TCO = 58 K. However, near the surface (<20 nm), the TRS breaking signal doubles and onsets at TCO, indicating that Nb-doping decouples TRS breaking from charge order in the bulk but synchronises them near the surface. Additionally, Nb-doping raises the superconducting critical temperature TC from 2.5 K to 4.4 K. Applying hydrostatic pressure enhances both TC and the superfluid density by a factor of two, with a critical pressure pcr ≃ 0.85 GPa, suggesting competition with charge order. Notably, above pcr, we observe nodeless electron pairing and weak internal fields below TC, pointing to chiral superconducting pairing. Overall, these results demonstrate a highly unconventional normal state with a tunable onset of TRS breaking, and a transition to chiral superconductivity under low pressures, with an unconventional correlation between TC and the superfluid density.

en: Pressure induced transition from chiral charge order to time-reversal symmetry-breaking superconducting state in Nb-doped CsV3Sb5 - GPS data

gps

display_name: gps

smus

display_name: smus


en: Here we present 1,000 structures each of a water monomer, water dimer, Zundel cation and bulk water used to train tensorial machine-learning models in Phys. Rev. Lett. 120, 036002 (2018). The archive entry contains files in extended-XYZ format including the structures and several tensorial properties: for the monomer, dimer and Zundel cation, the dipole moment, polarizability and first hyperpolarizability are included, and for bulk water the dipole moment, polarizability and dielectric tensor are given.

en: Symmetry-Adapted Machine Learning for Tensorial Properties of Atomistic Systems

materialscloud

en:
Materials Cloud is a platform built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.

In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).

en: Materials Cloud

de: Materials Cloud

fr: Materials Cloud

it: Materials Cloud

value: DCAT Harvester Materials Cloud

bulk

display_name: bulk

dielectric-tensor

display_name: dielectric-tensor

dipole-moment

display_name: dipole-moment

hyperpolarizability

display_name: hyperpolarizability

machine-learning

display_name: machine-learning

molecular

display_name: molecular

polarizability

display_name: polarizability

water

display_name: water


en: Biomolecular simulations have a great potential in protein engineering, drug discovery and many other fields. Unfortunately, this method is computationally expensive, so many interesting processes cannot be routinely studied. In order to address this problem we developed Flying Gaussian method [Journal of Chemical Theory and Computation 12, 4644-4650 (2016)]. This method simultaneously simulates multiple replicas of the studied system and disfavor replicas with similar structures by artificial bias potential. The question arises how to calculate an unbiased free energy surface from a biased simulation. This dataset demonstrates together with mathematical arguments supports application of Umbrella Sampling reweighing method, despite the fact that this method is designed for methods with a time-independent bias potential.

en: Free-Energy Surface Prediction by Flying Gaussian Method: Numerical Proof

flying-gaussian-method

display_name: flying-gaussian-method

metadynamics

display_name: metadynamics

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation

sampling

display_name: sampling


barcodes-for-nanoporous-materials

en: In most applications of nanoporous materials the pore structure is as important as the chemical composition as a determinant of performance. For example, one can alter performance in applications like carbon capture or methane storage by orders of magnitude by only modifying the pore structure. For these applications it is therefore important to identify the optimal pore geometry and use this information to find similar materials. However, the mathematical language and tools to identify materials with similar pore structures, but different composition, has been lacking. Recently, we developed a pore recognition approach to quantify similarity of pore structures using topological data analysis. Barcodes generated with using this approach allow us to identify materials with similar pore geometries, and to screen for materials that are similar to given top-performing structures. This database has barcodes for zeolites, metal organic frameworks, and zeolitic imidazolate frameworks.

en: Barcodes for nanoporous materials

title_for_slug: barcodes-for-nanoporous-materials

envi

en: Environment

marvel

display_name: marvel

metal-organic-frameworks

display_name: metal-organic-frameworks

nanoporous-materials

display_name: nanoporous-materials

persistence-homology

display_name: persistence-homology

topological-data-analysis

display_name: topological-data-analysis

zeolites

display_name: zeolites


en: We report a large-scale density-functional-theory study of the configuration space of water ice. We geometry optimise 74,963 ice structures, which are selected and constructed from over five million tetrahedral networks listed in the databases of Treacy and Deem, and the International Zeolite Association database. All prior knowledge of ice is set aside and we introduce generalised convex hulls to identify configurations stabilised by appropriate thermodynamic constraints. We thereby rediscover all known phases (I to XVII, i, 0 and the quartz phase) except the metastable ice IV. Crucially, we also find promising candidates for ices XVIII through LI. Using the sketch-map dimensionality-reduction algorithm we construct an a priori, navigable map of configuration space, which reproduces similarity relations between structures and highlights the novel candidates. By relating the known phases to the tractably small, yet structurally diverse set of synthesisable candidate structures, we provide an excellent starting point for identifying formation pathways.

en: Mapping uncharted territory in ice from zeolite networks to ice structures

database

display_name: database

dft

display_name: dft

first-principles

display_name: first-principles

high-throughput

display_name: high-throughput

ice

display_name: ice

three-dimensional

display_name: three-dimensional


en: The nature of the bulk hydrated electron has been a challenge for both experiment and theory due to its short lifetime and high reactivity, and the need for a high-level of electronic structure theory to achieve predictive accuracy. The lack of a classical atomistic structural formula makes it exceedingly difficult to model the solvated electron using conventional empirical force fields, which describe the system in terms of interactions between point particles associated with atomic nuclei. Here we overcome this problem using a machine-learning model, that is sufficiently flexible to describe the effect of the excess electron on the structure of the surrounding water, without including the electron in the model explicitly. The resulting potential is not only able to reproduce the stable cavity structure but also recovers the correct localization dynamics that follow the injection of an electron in neat water. The machine learning model achieves the accuracy of the state-of-the-art correlated wave function method it is trained on. It is sufficiently inexpensive to afford a full quantum statistical and dynamical description and allows us to achieve accurate determination of the structure, diffusion mechanisms, and vibrational spectroscopy of the solvated electron.

en: Simulating the ghost: quantum dynamics of the solvated electron

cscs

display_name: cscs

machine-learning

display_name: machine-learning

moller-plesset-perturbation-theory

display_name: moller-plesset-perturbation-theory

quantum-dynamics

display_name: quantum-dynamics

snsf

display_name: snsf

solvated-electron

display_name: solvated-electron


en: We introduce and discuss the phenomenon of adatom-induced surface local melting, using extensive first-principles molecular dynamics simulations of Al(100) taken as a paradigmatic case of a non-premelting surface that nevertheless displays facile adatom diffusion with single and multiple exchange pathways. Here, a single adatom deposited on the surface is sufficient to nucleate a localized and diffusing liquid-like region that remains confined to the surface layer, but with an area that increases with temperature; in the absence of the adatom, the surface instead remains crystalline until reaching the bulk melting temperature.

en: Adatom-Induced Local Melting

aluminum

display_name: aluminum

defects

display_name: defects

first-principles-molecular-dynamics

display_name: first-principles-molecular-dynamics

marvel

display_name: marvel

surface-melting

display_name: surface-melting


en:
We provide the input files needed to reproduce the results of the article

Toward GW Calculations on Thousands of Atoms
J. Wilhelm, D. Golze, L. Talirz, J. Hutter, C. A. Pignedoli
J. Phys. Chem. Lett.  9, 306–312 (2018) DOI:10.1021/acs.jpclett.7b02740

The GW approximation of many-body perturbation theory is an accurate method
for computing electron addition and removal energies of molecules and solids.
In a canonical implementation, however, its computational cost is  in the
system size N, which prohibits its application to many systems of interest.
We present a full-frequency GW algorithm in a Gaussian-type basis,
whose computational cost scales with N2 to N3.
The implementation is optimized for massively parallel execution on
state-of-the-art supercomputers and is suitable for nanostructures and molecules in the gas,
liquid or condensed phase, using either pseudopotentials or all electrons.
We validate the accuracy of the algorithm on the GW100 molecular test set,
finding mean absolute deviations of 35 meV for ionization potentials and 27 meV
for electron affinities. Furthermore, we study the length-dependence of quasiparticle
energies in armchair graphene nanoribbons of up to 1734 atoms in size, and compute the
local density of states across a nanoscale heterojunction.

abinitio

display_name: abinitio

graphene

display_name: graphene

gw

display_name: gw

high-performance-computing

display_name: high-performance-computing

nanoribbon

display_name: nanoribbon

scaling

display_name: scaling


en: Porous polymer networks (PPNs) are a class of advanced porous materials that combine the advantages of cheap and stable polymers with the high surface areas and tunable chemistry of metal–organic frameworks. They are of particular interest for gas separation or storage applications, for instance, as methane adsorbents for a vehicular natural gas tank or other portable applications. PPNs are self-assembled from distinct building units; here, we utilize commercially available chemical fragments and two experimentally known synthetic routes to design in silico a large database of synthetically realistic PPN materials. All structures from our database of 18,000 materials have been relaxed with semiempirical electronic structure methods and characterized with Grand-canonical Monte Carlo simulations for methane uptake and deliverable (working) capacity. A number of novel structure–property relationships that govern methane storage performance were identified. The relationships are translated into experimental guidelines to realize the ideal PPN structure. We found that cooperative methane–methane attractions were present in all of the best-performing materials, highlighting the importance of guest interaction in the design of optimal materials for methane storage.

en: In Silico Design of Porous Polymer Networks: High Throughput Screening for Methane Storage Materials

database

display_name: database

dc

display_name: dc

deliverable-capacities

display_name: deliverable-capacities

gcmc

display_name: gcmc

grand-canonical-monte-carlo

display_name: grand-canonical-monte-carlo

high-throughput

display_name: high-throughput

methane-storage

display_name: methane-storage

nanoporous

display_name: nanoporous

porous-polymer-networks

display_name: porous-polymer-networks

ppn

display_name: ppn

three-dimensional

display_name: three-dimensional


en: In this work, we present a comprehensive dataset designed to facilitate the prediction of metal fatigue life using deep learning techniques. The dataset includes detailed experimental data from 40 different metallic materials, comprising a total of 1195 data points under 48 distinct loading paths. Each data point is stored in a CSV file, capturing the loading path as a time-series with axial and tangential stress or strain values.The primary purpose of this dataset is to support the development and validation of deep learning models aimed at accurately predicting the fatigue life of metals under various loading conditions. This dataset includes stress-controlled and strain-controlled data, ensuring a broad representation of experimental scenarios. Additionally, an Excel file accompanies the dataset, providing detailed mechanical properties of each material, such as elastic modulus, tensile strength, yield strength, and Poisson's ratio, along with references to the original experimental sources.This dataset is intended for researchers in materials science and mechanical engineering, offering a robust foundation for training and testing deep learning algorithms in fatigue analysis. By making this dataset publicly available, we aim to foster collaboration and further advancements in the field of metal fatigue prediction. Researchers are encouraged to utilize and contribute to the dataset, thereby enhancing its scope and applicability.

en: A deep learning dataset for metal multiaxial fatigue life prediction

deep-learning

display_name: deep-learning

fatigue-life-prediction

display_name: fatigue-life-prediction

metal-fatigue

display_name: metal-fatigue

multiaxial-fatigue

display_name: multiaxial-fatigue


en: Solid-state electrolytes for Li-ion batteries are attracting growing interest as they allow building safer batteries, also using lithium-metal anodes. Here, we studied a compound in the lithium superionic conductor (LISICON) family, i.e. Li₄₋ₓGe₁₋ₓPₓO₄ (LGPO). Thin films were deposited via pulsed laser deposition, and their electrical properties were compared to those of ceramic pellets. A detailed characterization of their microstructures shows that thin films can be deposited fully crystalline at higher temperatures but also partially amorphous at room temperature. The conductivity is not strongly influenced by the presence of grain boundaries, exposure to air, or lithium deficiencies. First-principles molecular dynamics simulations were employed to calculate the lithium-ion diffusion profile and the conductivity at various temperatures of the ideal LGPO crystal. Simulations give the upper limit of conductivity for a defect-free crystal, which is in the range of 10–2 S cm–1 at 300 °C. The ease of thin-film fabrication and room-temperature Li-ion conductivity in the range of a few μS cm–1 make LGPO a very appealing electrolyte material for thin-film all-solid-state all-oxide microbatteries.

en: Li₄₋ₓGe₁₋ₓPₓO₄, a potential solid-state electrolyte for all-oxide microbatteries

materialscloud

en:
Materials Cloud is a platform built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.

In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).

en: Materials Cloud

big-map

display_name: big-map

first-principles-molecular-dynamics

display_name: first-principles-molecular-dynamics

ionic-transport

display_name: ionic-transport

lgpo

display_name: lgpo

lisicon

display_name: lisicon

microbatteries

display_name: microbatteries

solid-state-electrolytes

display_name: solid-state-electrolytes

thin-films

display_name: thin-films


en: A transient state of the excess electron in liquid water preceding the development of the solvation shell, the so-called wet electron, has been invoked to explain spectroscopic observations, but its binding energy and atomic structure have remained highly elusive. Here, we carry out hybrid functional molecular dynamics to unveil the ultrafast solvation mechanism leading to the hydrated electron. In the pre-hydrated regime, the electron is found to repeatedly switch between a quasi-free electron state in the conduction band and a localized state with a binding energy of 0.26 eV, which we assign to the wet electron. This transient state self-traps in a region of the liquid which extends up to ∼4.5 Å and involves a severe disruption of the hydrogen-bond network. Our picture provides an unprecedented view on the nature of the wet electron, which is instrumental to understand the properties of this fundamental species in liquid water.

en: Picture of Wet Electron: A Localized Transient State in Liquid Water

first-principles

display_name: first-principles

hydrated-electron

display_name: hydrated-electron

liquid-water

display_name: liquid-water

molecular-dynamics

display_name: molecular-dynamics

wet-electron

display_name: wet-electron


en:
Project abstract: Frustrated magnets are one class of fascinating materials that host many intriguing phases such as spin ice, spin liquid and complex long-range magnetic orderings at low temperatures. In this work we use first-principles calculations to find that in a wide range of magnetically frustrated oxides, at zero temperature a number of non-collinear magnetic orderings are more stable than the type-I collinear ordering that is observed at finite temperatures. The emergence of non-collinear orderings in those complex oxides is due to higher-order exchange interactions that originate from second-row and third-row transition metal elements. This implies a collinear-to-noncollinear spin transition at sufficiently low temperatures in those frustrated complex oxides. Furthermore, we find that in a particular oxide Ba2YOsO6, experimentally feasible uniaxial strain can tune the material between two different non-collinear magnetic orderings. Our work predicts new non- collinear magnetic orderings in frustrated complex oxides at very low temperatures and provides a mechanical route to tuning complex non-collinear magnetic orderings in those materials.

About this entry:  We provide the input files of our DFT calculations for the studied complex oxides.  The structures in POSCAR format and the INCAR files for all stabilized magnetic orderings in our study are all included. These files can be directly used into DFT calculations with VASP.

en: The complex non-collinear magnetic orderings in Ba2YOsO6: A new approach to tuning spin-lattice interactions and controlling magnetic orderings in frustrated complex oxides

envi

en: Environment

double-perovskite

display_name: double-perovskite

first-principles-calculations

display_name: first-principles-calculations

frustrated-complex-oxides

display_name: frustrated-complex-oxides

non-collinear-magnetic-ordering

display_name: non-collinear-magnetic-ordering

spin-orbital-coupling

display_name: spin-orbital-coupling


en:
Here we present 69,840 covalent organic frameworks (COFs) assembled in silico from a set of 666 distinct organic linkers into 2D-layered and 3D configurations. We investigate the feasibility of using these frameworks for methane storage by using grand-canonical Monte Carlo (GCMC) simulations to calculate their deliverable capacities (DCs). From these calculations, we predict that the best structure in the database is linker91_C_linker91_C_tbd, a structure composed of carbon-carbon bonded triazine linkers in the tbd topology. This structure has a predicted 65-bar DC of 216 v STP/v, greater than that of the best current methane storage material. We also predict other top performing materials, with 305 structures having DCs of over 190 v STP/v, and 34 of these having DCs of over 200 v STP/v.
This archive entry contains the database of assembled COF structures (in CIF file format) together with all of their properties, which can be explored using interactive figures. Among the calculated properties for each structure are the framework density, the methane heats of desorption at the storage and depletion pressures, the methane uptakes at the storage and deplation pressures, the supercell volume, and the geometric surface area. Structures are also labeled according to their bond types (amide, amine, imine, carbon-carbon, or mixed) and their dimensionalities (2D or 3D).

en: In Silico Design of 2D and 3D Covalent Organic Frameworks for Methane Storage Applications

cof

display_name: cof

covalent-organic-frameworks

display_name: covalent-organic-frameworks

database

display_name: database

dc

display_name: dc

deliverable-capacities

display_name: deliverable-capacities

gcmc

display_name: gcmc

grand-canonical-monte-carlo

display_name: grand-canonical-monte-carlo

high-throughput

display_name: high-throughput

layered

display_name: layered

marvel

display_name: marvel

methane-storage

display_name: methane-storage

nanoporous

display_name: nanoporous

three-dimensional

display_name: three-dimensional

two-dimensional

display_name: two-dimensional


the-geometric-blueprint-of-perovskites

en: Perovskite minerals form an essential component of the Earth's mantle, and synthetic crystals are ubiquitous in electronics, photonics, and energy technology. The extraordinary chemical diversity of these crystals raises the question of how many and which perovskites are yet to be discovered. Here we show that the "no-rattling" principle postulated by Goldschmidt in 1926, describing the geometric conditions under which a perovskite can form, is much more effective than previously thought and allows us to predict perovskites with a fidelity of 80%. By supplementing this principle with inferential statistics and internet data mining we establish that currently known perovskites are only the tip of the iceberg, and we enumerate 90,000 hitherto-unknown compounds awaiting to be studied. Our results suggest that geometric blueprints may enable the systematic screening of millions of compounds and offer untapped opportunities in structure prediction and materials design.

en: The geometric blueprint of perovskites

title_for_slug: the-geometric-blueprint-of-perovskites

data-mining

display_name: data-mining

goldschmidt

display_name: goldschmidt

perovskites

display_name: perovskites

structure-predictions

display_name: structure-predictions


en: We report a methodology using machine learning to capture chemical intuition from a set of (partially) failed attempts to synthesize a metal organic framework. We define chemical intuition as the collection of unwritten guidelines used by synthetic chemists to find the right synthesis conditions. As (partially) failed experiments usually remain unreported, we have reconstructed a typical track of failed experiments in a successful search for finding the optimal synthesis conditions that yields HKUST-1 with the highest surface area reported to date. We illustrate the importance of quantifying this chemical intuition for the synthesis of novel materials.

en: Capturing chemical intuition in synthesis of metal-organic frameworks

genetic-algorithms

display_name: genetic-algorithms

machine-learning

display_name: machine-learning

metal-organic-frameworks

display_name: metal-organic-frameworks

optimisation

display_name: optimisation

robotic-synthesi

display_name: robotic-synthesi

synthesis

display_name: synthesis


en: Biomolecular simulations are computationally expensive. This limits their application in drug or protein design and related fields. Several methods have been developed to address this problem. These methods often use an artificial force or potential acting on selected degrees of freedom known as collective variables. This requires explicit calculation of a collective variable (and its derivatives) from molecular structure. For collective variables that cannot be calculated explicitly or such calculations is slow we developed anncolvar package (https://github.com/spiwokv/anncolvar). This package approximates collective variables using artificial neural networks. It was tested on Isomap low dimensional representation of cyclooctane derivative or solvent-accessible surface area of Trp-cage miniprotein.

en: Approximation of Collective Variables by anncolvar

artificial-neural-networks

display_name: artificial-neural-networks

collective-variable

display_name: collective-variable

metadynamics

display_name: metadynamics


en:
Project Abstract: For applications of metal-organic frameworks (MOFs) such as gas storage and separation, flexibility is often seen as a parameter that can tune material performance. In this work we aim to determine the optimal flexibility for the shape selective separation of similarly sized molecules (e.g., Xe/Kr mixtures). To obtain systematic insight into how the flexibility impacts this type of separation we develop a simple analytical model that predicts a material's Henry regime adsorption and selectivity as a function of flexibility. We elucidate the complex dependence of selectivity on a framework's intrinsic flexibility whereby performance is either improved or reduced with increasing flexibility, depending on the material's pore size characteristics. However, the selectivity of a material with the pore size and chemistry that already maximizes selectivity in the rigid approximation is continuously diminished with increasing flexibility, demonstrating that the globally optimal separation exists within an entirely rigid pore. Molecular simulations show that our simple model predicts performance trends that are observed when screening the adsorption behavior of flexible MOFs. These flexible simulations provide better agreement with experimental adsorption data in a high performance material that is not captured when modeling this framework as rigid, an approximation typically made in high-throughput screening studies. We conclude that, for shape selective adsorption applications, the globally optimal material will have the optimal pore size/chemistry and minimal intrinsic flexibility even though other non-optimal materials' selectivity can actually be improved by flexibility. Equally important, we find that flexible simulations can be critical for correctly modeling adsorption in these types of systems.

About this entry: You can find the Xe/Kr Henry coefficients and the infinite dilution selectivity of more than 2000 CoRE MOF structures obtained via computational screening when materials are simulated as both flexible and rigid.  For details about the methods used to obtain these results, please see the corresponding paper (DOI: 10.1021/jacs.7b01688).  The data provided here was used to create the scatter plots presented in the original paper and can be used to find the adsorption properties for any material in the CoRE MOF screening.

Version 2 includes a minor formatting correction to make the CIF files compliant with the CIF standard.

en: The Influence of Intrinsic Framework Flexibility on Adsorption in Nanoporous Materials (Data Download)

flexibility

display_name: flexibility

nanoporous-materials

display_name: nanoporous-materials

xekr-separations

display_name: xekr-separations


en: Biomolecular simulations are computationally expensive. This limits their application in protein folding simulations, protein engineering, drug design and related fields. Enhanced sampling techniques such as metadynamics accelerates slow events in molecular simulation. This and other method apply artificial forces in directions of collective degrees of freedom (aka collective variables). Path collective variables and Property Map collective variables are defined using a series of reference structures of the studied molecular system. They require a huge number of mean square deviation calculations along the simulation. Close Structure algorithm reduces the number of these operations.

en: Reducing the Number of Mean-Square Deviation Calculations with Floating Close Structure in Metadynamics

materialscloud

en:
Materials Cloud is a platform built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.

In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).

mean-square-deviation

display_name: mean-square-deviation


en:
Project abstract: In this work, a theoretical framework is developed to explain and predict changes in the product distribution of the propene dimerization reaction, which yields a mixture of C6 olefin isomers, resulting from the use of different porous materials as catalysts. The MOF-74 class of materials has shown promise in catalyzing the dimerization of propene with high selectivity for valuable linear olefin products. We show that experimentally observed changes in the product distribution can be explained in terms of the contribution of the pores to the free energy of formation, which are directly computed using molecular simulation. Our model is used to screen a library of 118 existing and hypothetical MOF and zeolite structures to study how product distribution can be tuned by changing pore size, shape, and composition of porous materials. Using these molecular descriptors, catalyst properties are identified that increase the selective reaction of linear olefin isomers, which are valued as industrial feedstocks. A pore size commensurate with the size of the desired linear products enhances linear conversion by sterically hindering the branched isomers. Another promising feature is the presence of open metal sites, which interact with the olefin π-bond to provide favorable binding sites for the linear isomers.

About this entry: We provide the geometrical framework descriptors, linear conversions, and thermodynamic data for the 118 frameworks screened in this study, as well as thermodynamics of adsorption properties computed for 12 C6 olefin isomers in each framework. For details about the methods used to obtain these data, please see the corresponding paper (DOI: 10.1021/acscatal.7b00712). The data provided here was used to create the scatter plots in the original paper and can be used to find the product distribution and adsorption properties for all of the materials considered in the study.

en: Predicting Product Distribution of Propene Dimerization in Nanoporous Materials (Data Download)

materialscloud

en: Materials Cloud

metalorganic-frameworks

display_name: metalorganic-frameworks

molecular-simulation

display_name: molecular-simulation

monte-carlo

display_name: monte-carlo

product-distribution

display_name: product-distribution

propene-dimerization

display_name: propene-dimerization

zeolites

display_name: zeolites


en:
Charge equilibration (Qeq) methods can estimate the electrostatic potential of molecules and periodic frameworks by assigning point charges to each atom, using only a small fraction of the resources needed to compute density functional (DFT)-derived charges. This makes possible, for example, the computational screening of thousands of microporous structures to assess their performance for the adsorption of polar molecules. Recently, different variants of the original Qeq scheme were proposed to improve the quality of the computed point charges. One focus of this research was to improve the gas adsorption predictions in Metal Organic Frameworks (MOFs), for which many different structures are available. In this work, we review the evolution of the method from the original Qeq scheme, understanding the role of the different modifications on the final output. We evaluated the result of combining different protocols and set of parameters, by comparing the Qeq charges with high quality DFT-derived DDEC charges for 2338 MOF structures. We focused on the systematic errors that are attributable to specific atom types to quantify the final precision that one can expect from Qeq methods in the context of gas adsorption where the electrostatic potential plays a significant role, namely CO2 and H2S adsorption. In conclusion, both the type of algorithm and the input parameters have a large impact on the resulting charges and we draw some guidelines to help the user to choose the proper combination of the two for obtaining a meaningful set of charges. We show that, considering this set of MOFs, the accuracy of the original Qeq scheme is often still comparable with the most recent variants, even if it clearly fails in the presence of certain atom types, such as alkali metals.

Version 2 of the record adds the data underlying the figures in CSV format.

en: Evaluating charge equilibration methods to generate electrostatic fields in nanoporous materials

envi

en: Environment

charge-equilibration-methods

display_name: charge-equilibration-methods

marvel

display_name: marvel

partial-charges

display_name: partial-charges

qeq

display_name: qeq


en: Project Abstract: Pore volume is one of the main properties for the characterization of microporous crystals. It is experimentally measurable and it can also be obtained from the refined unit cell by a number of computational techniques. In this work we assess the accuracy and the discrepancies between the different computational methods which are commonly used for this purpose, i.e, geometric, helium and probe center pore volume, by studying a database of more than 5000 frameworks. We developed a new technique to fully characterize the internal void of a microporous material and to compute the probe accessible and occupiable pore volume. We show that unlike the other definitions of pore volume, the occupiable pore volume can be directly related to the experimentally measured pore volumes from nitrogen isotherms.

en: Accurate Characterization of the Pore Volume in Microporous Crystalline Materials (Data Download)

pore-volume

display_name: pore-volume

void-fraction

display_name: void-fraction


en: Zeolite-templated carbons (ZTCs) comprise a relatively recent material class synthesized via the chemical vapor deposition of a carbon-containing precursor on a zeolite template, followed by the removal of the template. We have developed a theoretical framework to generate a ZTC model from any given zeolite structure, which we show can successfully predict the structure of known ZTCs. We use our method to generate a library of ZTCs from all known zeolites, to establish criteria for which zeolites can produce experimentally accessible ZTCs, and to identify over 10 ZTCs that have never before been synthesized. We show that ZTCs partition space into two disjoint labyrinths that can be described by a pair of interpenetrating nets. Since such a pair of nets also describes a triply periodic minimal surface (TPMS), our results establish the relationship between ZTCs and schwarzites—carbon materials with negative Gaussian curvature that resemble TPMSs—linking the research topics and demonstrating that schwarzites should no longer be thought of as purely hypothetical materials.

en: Generating carbon schwarzites via zeolite-templating

carbon-materials

display_name: carbon-materials

schwarzites

display_name: schwarzites

tpms

display_name: tpms

ztc

display_name: ztc


en: The application of modern machine learning to challenges in atomistic simulation is gaining attraction. We present new machine learning models that can predict the energy of the oxidative addition process between a transition metal complex and a substrate for C-C cross-coupling reaction. In turn, this quantity can be used as a descriptor to estimate the activity of homogeneous catalysts using molecular volcano plots. The versatility of this approach is illustrated for vast libraries of organometallic catalysts based on Pt, Pd, Ni, Cu, Ag, and Au combined with 91 ligands. Out-of-sample machine learning predictions were made on a total of 18,062 compounds leading to 557 catalyst candidates falling into the ideal thermodynamic window. This number was further refined by searching for candidates with an estimated price lower than 10 US$/mmol. The 37 catalyst finalists are dominated by palladium phosphine ligand combinations but also include earth abundant (Cu) transition metal with less common ligands. Our results indicate that modern statistical learning techniques can be applied to the computational discovery of readily available and promising catalyst candidates.

en: Machine learning meets volcano plots: Computational discovery of cross-coupling catalysts

homogeneous-catalysis

display_name: homogeneous-catalysis

machine-learning

display_name: machine-learning

transition-metal-complexes

display_name: transition-metal-complexes

volcano-plot

display_name: volcano-plot


en: Canonical molecular dynamics simulations of crystal growth from solution suffer from severe finite-size effects. As the crystal grows, the solute molecules are drawn from the solution to the crystal, leading to a continuous drop in the solution concentration. This is in contrast to experiments in which the crystal grows at an approximately constant supersaturation of a bulk solution. Recently, Perego et al. [J. Chem. Phys.2015, 142, 144113] showed that in a periodic setup in which the crystal is represented as a slab, the concentration in the vicinity of the two surfaces can be kept constant while the molecules are drawn from a part of the solution that acts as a molecular reservoir. This method is quite effective in studying crystallization under controlled supersaturation conditions. However, once the reservoir is depleted, the constant supersaturation conditions cannot be maintained. We propose a variant of this method to tackle this depletion problem by simultaneously dissolving one side of the crystal while letting the other side grow. A continuous supply of particles to the solution due to the crystal dissolution maintains a steady solution concentration and avoids reservoir depletion. In this way, a constant supersaturation condition can be maintained for as long as necessary. We have applied this method to study the growth and dissolution of urea crystal from water solution under constant supersaturation and undersaturation conditions, respectively. The computed growth and dissolution rates are in good agreement with those obtained in previous studies.

en: A Cannibalistic Approach to Grand Canonical Crystal Growth

crystal-nucleation-and-growth

display_name: crystal-nucleation-and-growth

erc

display_name: erc

solution-crystallization

display_name: solution-crystallization


en:
Classical turning surfaces of Kohn-Sham potentials separate classically-allowed regions (CARs) from classically-forbidden regions (CFRs). They are useful for understanding many chemical properties of molecules, but need not exist in solids, where the density never decays to zero. At equilibrium geometries, we find that CFRs are absent in perfect metals, rare in covalent semiconductors at equilibrium, but common in ionic and molecular crystals. In all materials, CFRs appear or grow as the internuclear distances are uniformly expanded. They can also appear at a monovacancy in a metal. Calculations with several approximate density functionals and codes confirm these behaviors. A classical picture of conduction suggests that CARs should be connected in metals, and disconnected in wide-gap insulators, and is confirmed in the limits of extreme compression and expansion. Surprisingly, many semiconductors have no CFR at equilibrium, a key finding for density functional construction. Nonetheless, a strong correlation with insulating behavior can still be inferred. Moreover, equilibrium bond lengths for all cases can be estimated from the bond type and the sum of the classical turning radii of the free atoms or ions.

This record contains machine readable data for this work

en: Calculation and interpretation of classical turning surfaces in solids

density-functional-theory

display_name: density-functional-theory

dft

display_name: dft

kohn-sham-potential

display_name: kohn-sham-potential

turning-surface

display_name: turning-surface