en: Many environmental and industrial processes depend on how fluids displace each other in porous materials. However, the flow dynamics that govern this process are still poorly understood. This dataset introduces a novel 4D micro-velocimetry method to study this, based on tracking flow-tracing micro-particles  (silver-coated hollow glass spheres of 10 µm diameter) using high-resolution X-ray computed tomography with fast imaging rates. The measurement was done at the TOMCAT beamline of the Swiss Light Source. The dataset pertains to unsteady-state multiphase flow in a porous sintered glass filter sample, in which a non-wetting phase (silicon oil) was injected at constant rate to displace the wetting phase (water doped with potassium iodide: 10%wt KI brine). The tracer particles were dispersed in the non-wetting phase. The dataset spans a time window of 50 seconds during which 200 tomograms were acquired (i.e. 4 Hz imaging rate), each with a 2.75 micrometer voxel size. During this time window, the dynamics prior, during and after a Haines jump were captured. We provide reconstructions without phase retrieval which maximize the contrast between the tracer particles and the non-wetting phase, and reconstructions with Paganin phase retrieval that maximize the contrast between the non-wetting and the wetting phase. The data shows that Haines jumps cause perturbations to the 3D flow field in the porous medium and makes it possible to investigate the non-equilibrium energy dynamics.

en: 4D X-ray micro-velocimetry data of multiphase flow perturbations in porous media

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.


$oid: OBSOLETE

en:
001 - UV-Vis spectra JSR1 reconstituted with all-trans retinal, 9-cis retinal, ATR6.11 and 9CR6.11
002 - UV-Vis spectra of JSR1 reconstituted with ATR6.11 and 9CR6.11, before and after acid denaturation
003 - UV-Vis spectra of JSR1 reconstituted with ATR6.11, after addition of hydroxylamine
004 - UV-Vis spectra of JSR1 reconstituted with 9CR6.11, after addition of hydroxylamine
005 - UV-Vis spectra of illuminated JSR/ATR6.11 and JSR/9CR6.11
006 - GTPase Glo Assay data measuring catalysis of nucleotide exchange in human G protein heterotrimers by JSR1/ATR6.11, JSR/9CR6.11 and JSR/9-cis retinal, with and without illumination
007 - Size exclusion chromatograms JSR1/ATR6.11 after incubations with human Gi or human Gq heterotrimers
008 - SDS-PAGE analysis of size exclusion chromatography peaks with JSR/ATR6.11 and human Gi or human Gq heterotrimers

en: Datasets relating to characterisation of Jumping Spider Rhodopsin-1 after reconstitution with retinal and retinal analogues

approval_status: approved

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:
Two-dimensional magnetic materials attract a lot of attention since
they potentially exhibit new magnetic properties due to, e.g., strongly
enhanced spin fluctuations. However, the suppression of the long-range
magnetic order in two dimensions due to long-wavelength spin fluctuations,
as suggested by the Mermin-Wagner theorem, has been questioned
for finite-size laboratory samples. Here we study the magnetic properties
of a dimensional crossover in superlattices composed of the antiferromagnetic
LaFeO3 and SrTiO3 that, thanks to their large lateral size, allowed
examination using a sensitive magnetic probe — muon spin rotation spectroscopy.
We show that the iron electronic moments in superlattices with
3 and 2 monolayers of LaFeO3 exhibit a static antiferromagnetic order. In
contrast, in the superlattices with single LaFeO3 monolayer, the moments
do not order and fluctuate to the lowest measured temperature as expected
from the Mermin-Wagner theorem. Our work shows how dimensionality
can be used to tune the magnetic properties of ultrathin films.

en: Magnetic properties of LaFeO3/SrTiO3 superlattices


en:
Tomographic data set of dynamic liquid water injection into SGL 24 BA gas diffusion layer

Data collected at TOMCAT beamline of SLS.

en: Tomographic data set of dynamic liquid water injection into SGL 25 BA gas diffusion layer

lamibracmularczyk-paper

display_name: lamibracmularczyk-paper

liquid-injection

display_name: liquid-injection

sgl

display_name: sgl

tomcat

display_name: tomcat


en:
Tomography data published in A. Mularczyk et al. (2020). 'Droplet and Percolation Network Interactions in a Fuel Cell Gas Diffusion Layer', Journal of The Electrochemical Society 167(8): 084506.  https://doi.org/10.1149/1945-7111/ab8c85
#####
The tomographic data of liquid water observed in the flow field channel was used also in Andersson, M., et al. (2018). "Modeling and synchrotron imaging of droplet detachment in gas channels of polymer electrolyte fuel cells." Journal of Power Sources 404: 159-171. https://doi.org/10.1016/j.jpowsour.2018.10.021
###### The tomographic data of liquid water observed in the GDL and flow field channel was also used in Niblett, D., et al. (2020). "Two-phase flow dynamics in a gas diffusion layer - gas channel - microporous layer system." Journal of Power Sources 471: 228427.  https://doi.org/10.1016/j.jpowsour.2020.228427
###### A small ROI segmentation around the water cluster in GDL of this dataset can be accessed under https://doi.org/10.16907/13dc29a3-733b-419b-ad61-838d17ddfa47
###### The Large ROI segmentation of this dataset can be accessed under https://doi.org/10.16907/a27fda1c-e6bb-47f0-ba14-31b407179756

en: Tomographic data set of dynamic liquid water injection into SGL 25 BA gas diffusion layer: Raw reconstruction


en:
Tomography data published in A. Mularczyk et al. (2020). 'Droplet and Percolation Network Interactions in a Fuel Cell Gas Diffusion Layer', Journal of The Electrochemical Society 167(8): 084506. https://doi.org/10.1149/1945-7111/ab8c85
###### The tomographic data of liquid water observed in the flow field channel was used also in Andersson, M., et al. (2018). "Modeling and synchrotron imaging of droplet detachment in gas channels of polymer electrolyte fuel cells." Journal of Power Sources 404: 159-171. https://doi.org/10.1016/j.jpowsour.2018.10.021
###### The tomographic data of liquid water observed in the GDL and flow field channel was also used in Niblett, D., et al. (2020). "Two-phase flow dynamics in a gas diffusion layer - gas channel - microporous layer system." Journal of Power Sources 471: 228427.  https://doi.org/10.1016/j.jpowsour.2020.228427
###### A small ROI segmentation around the water cluster in GDL of this dataset can be accessed under https://doi.org/10.16907/13dc29a3-733b-419b-ad61-838d17ddfa47
###### The Raw CT data of this dataset can be accessed under https://doi.org/10.16907/63ac1a63-8ab6-4a92-be5a-db499c9e7e6a

en: Tomographic data set of dynamic liquid water injection into SGL 25 BA gas diffusion layer: Large ROI segmentation


en:
Tomography data published in A. Mularczyk et al. (2020). 'Droplet and Percolation Network Interactions in a Fuel Cell Gas Diffusion Layer', Journal of The Electrochemical Society 167(8): 084506. https://doi.org/10.1149/1945-7111/ab8c85
######
The tomographic data of liquid water observed in the flow field channel was used also in Andersson, M., et al. (2018). "Modeling and synchrotron imaging of droplet detachment in gas channels of polymer electrolyte fuel cells." Journal of Power Sources 404: 159-171. https://doi.org/10.1016/j.jpowsour.2018.10.021
###### The tomographic data of liquid water observed in the GDL and flow field channel was also used in Niblett, D., et al. (2020). "Two-phase flow dynamics in a gas diffusion layer - gas channel - microporous layer system." Journal of Power Sources 471: 228427.  https://doi.org/10.1016/j.jpowsour.2020.228427

######
The Large ROI segmentation of this dataset can be accessed under 	https://doi.org/10.16907/a27fda1c-e6bb-47f0-ba14-31b407179756
######
The Raw CT data of this dataset can be accessed under 	https://doi.org/10.16907/63ac1a63-8ab6-4a92-be5a-db499c9e7e6a

en: Tomographic data set of dynamic liquid water injection into SGL 25 BA gas diffusion layer: SmallROI segmentation


en: We investigate solvent effects in the hydrodeoxygenation of 4-propylguaiacol (4PG, 166 amu), a key lignin-derived monomer, over Ru/C catalyst by combined operando synchrotron photoelectron photoion coincidence (PEPICO) spectroscopy and molecular dynamics simulations. With and without isooctane co-feeding, ring-hydrogenated 2-methoxy-4-propylcyclohexanol (172 amu) is the first product, due to the favorable flat adsorption configuration of 4PG on the catalyst surface. In contrast, tetrahydrofuran (THF)—a polar aprotic solvent that is representative of those used for lignin solubilization and upgrading—strongly coordinates to the catalyst surface at the oxygen atom. This induces a local steric hindrance, blocking the flat adsorption of 4PG more effectively, as it needs more Ru sites than the tilted adsorption configuration revealed by molecular dynamics simulations. Therefore, THF suppresses benzene ring hydrogenation, favoring a demethoxylation route that yields 4-propylphenol (136 amu), followed by dehydroxylation to propylbenzene (120 amu). Solvent selection may provide new avenues to controlling catalytic selectivity.

en: Dataset: A Solution for 4-Propylguaiacol Hydrodeoxygenation without Ring Saturation


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

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 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: 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

en: PSI Data Catalog

envi

en: Environment


en: The data is part of a manuscript submitted to the journal Green Chemistry, entitled "Catalytic pyrolysis mechanism of lignin moieties driven by aldehyde, hydroxyl, methoxy, and allyl functionalization: the role of reactive quinone methide and ketene intermediates". [DOI https://doi.org/10.1039/d4gc03143a. This work is supported by the Swiss National Science Foundation (project number 200021_178952)

en: Dataset: Catalytic pyrolysis mechanism of lignin moieties driven by aldehyde, hydroxyl, methoxy, and allyl functionalization: the role of reactive quinone methide and ketene intermediates


en: Understanding the biomechanics of the human middle ear remains a challenge, primarily due to the auditory ossicles’ size, its location in the temporal bone, and subtle movements. In a recent study, dynamic synchrotron-based X-ray microtomography has been used on acoustically stimulated intact human ears, allowing the three-dimensional visualization of the ossicular chain in intact human ears for the first time. The implementation of a dedicated analysis pipeline has demonstrated the ability to resolve fast micromotions at 128 Hz for two acoustic stimuli (110 and 120 dB Sound Pressure Level (SPL)) on fresh-frozen human temporal bones. Measuring at lower sound pressure levels is challenging, because the ossicular vibrations become smaller, and the spatial resolution limit of the current detection system is reached. Increasing the spatial resolution without compromising the image quality or the temporal resolution would significantly extend the dynamic imaging capabilities. Here, a comparative study is conducted for a stimulation frequency of 128 Hz at 120 dB SPL between two synchrotron-based X-ray magnification setups: a 4x high NA macroscope (pixel size 2.75 \textmu m) versus a x10 high NA microscope (pixel size 1.1 \textmu m) in combination with the GigaFRoST fast read-out detector. It shows that an increase in resolution can indeed improve the detection of the micromovements, at the compromise of a more limited field of view.

en: High-resolution dynamic synchrotron-based X-ray microtomography of the human middle ear


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 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: In the corresponding article to these data sets, we explore the flow dynamics for two-phase flow in a porous medium (a bioclastic carbonate rock). We use state-of-the-art synchrotron X-ray tomography to capture the fluid dynamics within the pore space, with a temporal resolution of 1 s. The rock sample was initially saturated with brine (DI water doped with 15%wt. KI) before brine and nitrogen gas were injected simultaneously. As the gas establishes a path through the pore space, the flow dynamics are transient. Eventually, an equilibrium is established, where the gas saturation oscillates about a constant mean value; this is referred to as steady state. There are 9 data sets, with all the dynamics captured during steady state. We explore 3 total flow rates (brine flow rate + nitrogen flow rate): 0.1ml/min, 0.4ml/min, 0.7ml/min. With 3 fractional flows (brine flow rate / total flow rate) explored for each total flow rate: 0.85, 0.7 and 0.5. The images were captured with a voxel size of 2.75 µm3. In these data sets we observe the development of intermittent flow pathways, and the stability of these pathways when perturbed by a change in the flow rate .

en: Dynamic fluid interface rearrangement during steady-state multiphase flow in rocks


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

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 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: PSI Data Catalog


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: offline aod database physics meg2

envi

en: Environment

aod

display_name: aod

database

display_name: database

offline

display_name: offline

physics

display_name: physics


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


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

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: 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: 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


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: aod database physics meg2 offline

envi

en: Environment


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

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

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: Ultrafast magnetism triggered by circularly polarized radiation underpins ultrafast spin control, relevant to future technologies, e.g., opto-spintronics and magnonics. The dynamics are often complicated and intertwined among correlated subsystems, such as electrons, spins, phonons, plasmons, topology, and lattice, due to many-body quantum coupling at ultrafast timescales. Here, we demonstrate light-induced effective magnetic fields generated by selective excitation between non-equidistant Landau quantized states in graphene, a prototypical Dirac material, using circularly polarized pulses. By magnetically tuning the Landau-level transition resonance away from other low-energy excitations, we obtain a clean electrostatically controllable platform and identify the microscopic origin of the light-induced magnetic signals, independent of sublattice coupling. Because different Landau levels carry distinct optical Hall conductivities, direct modification of their occupancies via optical excitations creates transient Faraday rotation signals with dispersive magnetic-field dependence, mirroring the static magneto-optical lineshape. The induced effective magnetic field normalized by the pump electric field exceeds typical reported  values for the inverse Faraday effect of electronic origin. Our results establish a clear microscopic picture of the inverse Faraday effect of electronic origin, which can trigger hierarchical dynamics among correlated sublattices once Landau-level transitions are magnetically tuned to coincide with other low-energy excitations in Dirac systems and related materials.

en: Light-induced effective magnetic fields in Landau quantized graphene


en: In the corresponding article to these data sets, we explore the flow dynamics for two-phase flow in a porous medium (a bioclastic carbonate rock). We use state-of-the-art synchrotron X-ray tomography to capture the fluid dynamics within the pore space, with a temporal resolution of 1 s. The rock sample was initially saturated with brine (DI water doped with 15%wt. KI) before brine and nitrogen gas were injected simultaneously. As the gas establishes a path through the pore space, the flow dynamics are transient. Eventually, an equilibrium is established, where the gas saturation oscillates about a constant mean value; this is referred to as steady state. There are 9 data sets, with all the dynamics captured during steady state. We explore 3 total flow rates (brine flow rate + nitrogen flow rate): 0.1ml/min, 0.4ml/min, 0.7ml/min. With 3 fractional flows (brine flow rate / total flow rate) explored for each total flow rate: 0.85, 0.7 and 0.5. The images were captured with a voxel size of 2.75 µm3. In these data sets we observe the development of intermittent flow pathways, and the stability of these pathways when perturbed by a change in the flow rate .

en: The development and stability of intermittent fluid flow pathways during multiphase flow in porous media.

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: In this work, we map the charge carrier concentration as a function of depth and electric field across the SiO2/Si interface up to a depth of 100 nm in Si-based MOS capacitors using low-energy muons. The results show that the formation of the anisotropic bond-centered muonium MuBC state in Si serves as a direct measure of the local changes in electronic structures, which were detected and scanned for a range of depths. In general, any muonium state in a semiconductor can be used as a sensitive probe for the presence of free charge carriers. Therefore, our work represents a significant extension of the application of the muon spin rotation technique (μSR) and lays the foundation for further research on direct observation of charge carrier density manipulation at technologically important semiconductor device interfaces.

en: Charge carrier distribution observation and manipulation in Si-MOS

en: PSI Data Catalog


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 VA20

envi

en: Environment


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


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


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 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: 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 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: 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


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: 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

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 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

dft

display_name: dft

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: 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

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:
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)

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

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

envi

en: Environment

mean-square-deviation

display_name: mean-square-deviation


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)

marvel

display_name: marvel

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


en:
We provide the input files to reproduce the data presented in the work:
Hidden Beneath the Surface: Origin of the Observed Enantioselective Adsorption on PdGa(111)
The files are subdivided in directories named after the figures/table of the manuscript
A. V. Yakutovich, J. Hoja, D. Passerone, Alexandre Tkatchenko, C. A. Pignedoli
J. Am. Chem. Soc., 140, 1401-1408 (2018) DOI: 10.1021/jacs.7b10980
In the work, we unravel the origin of the recently observed striking enantioselectivity of the PdGa(111) surface with respect to the adsorption of a small organic molecule, 9-ethynylphenanthrene, using first-principles calculations. It turns out that the key ingredient to understand the experimental evidence is the appropriate description of van der Waals interactions beyond the widely employed atomic pairwise approximation. A recently developed van der Waals-inclusive density functional method, which encompasses dielectric screening effects, reveals the origin of the experimentally observed enantioselectivity and provides conclusive evidence of chiral recognition on a bimetallic surface driven by dispersion interactions.

chirality

display_name: chirality

many-body-dispersion

display_name: many-body-dispersion

marvel

display_name: marvel

pdga

display_name: pdga


en:
Fast-charging batteries typically employ electrodes capable of accommodating lithium continuously via solid-solution transformation because they have few kinetic barriers apart from Li+ diffusion. One exception is lithium titanate, an anode that exhibits extraordinary rate capability seemingly inconsistent with its two-phase reaction and slow diffusion within the two phases. Through real-time tracking of Li+ migration using operando electron energy-loss spectroscopy (EELS) along with simulation of the EELS spectra, we observe that the kinetic pathway that enables facile ionic transport in lithium titanate consists of distorted Li polyhedra in metastable intermediate states. Thus, fast-charging electrodes may not be controlled solely by the intrinsic ionic diffusivity of macroscopic phases, but also by the transport via kinetically accessible low-energy landscapes.

In order to understand the origin of various EELS spectra features, we simulate EELS spectra using the Vienna Ab initio Simulation (VASP) package. For a specific Li in a given configuration, this is done by calculating the DOS and integrated DOS considering a Li core-hole on the position of the specific Li and calculating the EELS based on the DOS. We also calculated the minimum energy paths (MEP) and migration energy of Li in various compositions, including Li4Ti5O12 with an additional Li carrier, Li5Ti5O12 with an additional Li carrier, and Li7Ti5O12 with a Li vacancy carrier. The calculation was performed using the nudged elastic band (NEB) method in VASP. Analysis of the VASP outputs was done using scripts from Transition State Tools for VASP (VTST, https://theory.cm.utexas.edu/vtsttools/index.html). We present here the relevant input and output files from the VASP calculations, the python code used to generate EELS spectra from VASP outputs, and the outputs of the VTST scripts that were used to generate MEP plots.

en: Kinetic Pathways of Ionic Transport in Fast Charging Lithium Titanate

ionic-transport

display_name: ionic-transport

nudged-elastic-band

display_name: nudged-elastic-band

vasp

display_name: vasp


en: The study of organic molecular crystals under high pressure provides fundamental insight into crystal packing distortions and reveals mechanisms of phase transitions and the crystallization of polymorphs. These solid state transformations can be monitored directly by analyzing electron charge densities that are experimentally obtained at high pressure. However, restricting the analysis to the featureless electron density does not reveal the chemical bonding nature and the existence of intermolecular interactions. This shortcoming can be resolved by the use of the DORI (Density Overlap Region Indicator) descriptor, which is capable of detecting simultaneously both covalent patterns and non-covalent interactions from electron density and its derivatives. Using the biscarbonyl[14]annulene crystal under pressure as an example, we demonstrate how DORI can be exploited on experimental electron densities to reveal and monitor changes in electronic structure patterns resulting from molecular compression. A novel approach based on a flood fill type algorithm is proposed for analyzing the topology of the DORI isosurface. This approach avoids the arbitrarily selection of DORI isovalues and provides an intuitive way to assess how compression packing affects covalent bonding in organic solids.

en: DORI reveals the influence of non-covalent interactions on covalent bonding patterns in molecular crystals under pressure

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

high-pressure

display_name: high-pressure

molecular-scalar-fields

display_name: molecular-scalar-fields

organic-crystals

display_name: organic-crystals

topology

display_name: topology


en: Ice nucleation is a process of great relevance in physics, chemistry, technology, and environmental sciences; much theoretical effort has been devoted to its understanding, but it still remains a topic of intense research. We shed light on this phenomenon by performing atomistic based simulations. Using metadynamics and a carefully designed set of collective variables, reversible transitions between water and ice are able to be simulated. We find that water freezes into a stacking disordered structure with the all-atom transferable intermolecular potential with 4 points/ice (TIP4P/ice) model, and the features of the critical nucleus of nucleation at the microscopic level are revealed. We have also estimated the ice nucleation rates along with other nucleation parameters at different undercoolings. Our results are in agreement with recent experimental and other theoretical works, and they confirm that nucleation is preceded by a large increase in tetrahedrally coordinated water molecules.

en: Temperature Dependence of Homogeneous Nucleation in Ice

envi

en: Environment

enhanced-sampling

display_name: enhanced-sampling

erc

display_name: erc

homegenous-nucleation

display_name: homegenous-nucleation

ice

display_name: ice

metadynamics

display_name: metadynamics

molecular-dynamics

display_name: molecular-dynamics

plumed

display_name: plumed


en: We describe a double helical conformation in the densely charged aromatic polyamide poly(2,2'- disulfonyl-4,4'-benzidine terephthalamide) or PBDT. This double helix macromolecule represents one of the most rigid simple molecular structures known, exhibiting an extremely high axial persistence length (~ 1 micrometer).

en: Double helix PBDT polymer - Submitted manuscript, simulations and other source data

ionic

display_name: ionic

nematic

display_name: nematic

nmr

display_name: nmr

polymer

display_name: polymer

simulations

display_name: simulations

x-ray

display_name: x-ray


en: We present a derivation of the exact expression for Pulay forces in density-functional theory calculations augmented with extended Hubbard functionals, and arising from the use of orthogonalized atomic orbitals as projectors for the Hubbard manifold. The derivative of the inverse square root of the orbital overlap matrix is obtained as a closed-form solution of the associated Lyapunov (Sylvester) equation. The expression for the resulting contribution to the forces is presented in the framework of ultrasoft pseudopotentials and the projector-augmented-wave method, and using a plane wave basis set. We have benchmarked the present implementation with respect to finite differences of total energies for the case of NiO, finding excellent agreement. Owing to the accuracy of Hubbard-corrected density-functional theory calculations - provided the Hubbard parameters are computed for the manifold under consideration - the present work paves the way for systematic studies of solid-state and molecular transition-metal and rare-earth compounds.

en: Pulay forces in density-functional theory with extended Hubbard functionals: from nonorthogonalized to orthogonalized manifolds

cscs

display_name: cscs

density-functional-theory

display_name: density-functional-theory

dftu

display_name: dftu

dftuv

display_name: dftuv

hubbard-corrections

display_name: hubbard-corrections

hubbard-forces

display_name: hubbard-forces

hubbard-manifold

display_name: hubbard-manifold

hubbard-parameters

display_name: hubbard-parameters

lowdin-orthogonalization-method

display_name: lowdin-orthogonalization-method

lyapunov-equation

display_name: lyapunov-equation

marvel

display_name: marvel

orbital-overlap-matrix

display_name: orbital-overlap-matrix

pulay-forces

display_name: pulay-forces

self-interaction-corrections

display_name: self-interaction-corrections

sylvester-equation

display_name: sylvester-equation


en:
Thermodynamic properties of liquid water as well as hexagonal (Ih) and cubic (Ic) ice are predicted based on density functional theory at the hybrid-functional level, rigorously taking into account quantum nuclear motion, anharmonic fluctuations and proton disorder. This is made possible by combining advanced free energy methods and state-of-the-art machine learning techniques. The ab initio description leads to structural properties in excellent agreement with experiments, and reliable estimates of the melting points of light and heavy water. We observe that nuclear quantum effects contribute a crucial 0.2 meV/H2O to the stability of ice Ih, making it more stable than ice Ic. Our computational approach is general and transferable, providing a comprehensive framework for quantitative predictions of ab initio thermodynamic properties using machine learning potentials as an intermediate step.

In this set of supplemental materials, we have included the neural network potential for bulk water, including its training set in two different formats. We have also included the input files for running free energy calculations.

en: Ab initio thermodynamics of liquid and solid water: supplemental materials

free-energy-calculation-input-files

display_name: free-energy-calculation-input-files

machine-learning-potential

display_name: machine-learning-potential

machine-learning-potential-training-set

display_name: machine-learning-potential-training-set


en: We present a large dataset of adsorption of H, C, N, O and S onto more than 2,000 metallic and bimetallic alloy surfaces, consisting of approximately 90,000 DFT calculations performed in Quantum Espresso. The alloys are constructed from all possible combinations of 37 metals into AB and A3B stoichiometries, in the L1_0 and L1_2 structures respectively, where the 37 metals in the A1 structure are included as well. Slabs are cleaved along the 111 facet for A1 and L1_2 and along the 101 facet for L1_0, and all possible adsorption sites are sampled. In addition to the monoatomic adsorbates, adsorption of CH, CH2, CH3, NH, NH2, OH, H2O and SH  is sampled for a smaller subset of alloys.

en: High-throughput calculations of catalytic properties of bimetallic alloy surfaces

chemisorption

display_name: chemisorption

dft

display_name: dft

heterogeneous-catalysis

display_name: heterogeneous-catalysis

surfaces

display_name: surfaces


dopant-discovery-in-cuprous-iodide

en: Computational data to support an extensive study of prospective dopants in the zinc blende (gamma) phase of cuprous iodide. This phase of CuI holds the current record hole conductivity for intrinsic transparent p-type semiconductors. In the corresponding scientific article, a high-throughput approach was employed to systematically explore strategies for enhancing CuI further by impurity incorporation. Our objectives were to identify a practical approach for increasing hole conductivity in CuI thin films and to explore the possibility for ambivalent doping. A total of 64 chemical elements was investigated. This materials cloud record contains all optimized defective structures for Cu and I substitutional sites, calculation settings and some of the output (LOCPOT files, required for electrostatic correction calculations are not included due to their large size).  Chalcogen elements were found to display acceptor character when substituting iodine. Further eight impurities suitable for n-type doping were also discovered. Unfortunately, our work further revealed that donor doping is hindered by compensating native defects.

en: Dopant discovery in cuprous iodide

title_for_slug: dopant-discovery-in-cuprous-iodide

cui

display_name: cui

defects

display_name: defects

dopants

display_name: dopants

supercell

display_name: supercell

transparent-conductors

display_name: transparent-conductors


en: This is a LAMMPS readable EAM type potential file for Hf-Nb-Ta-Zr based high-entropy alloys (HEAs). In this potential file the elements are sequenced as Hf, Nb, Ta and Zr, respectively. This potential was previously used to model the HEA for the local lattice distortions due to short-range order clustering found in the alloy after long-term annealing at high-temperature. The input to build this potential is based on the physical properties of pure elements such as the lattice parameter, cohesive energy, elastic constants etc and the details are discussed in the associated reference. Units used are in eV/atom for energy and Angstrom for distance.

en: EAM potential for Hf-Nb-Ta-Zr high-entropy alloy

eam-potential

display_name: eam-potential

high-entropy-alloys

display_name: high-entropy-alloys

lammps

display_name: lammps

refractory-elements

display_name: refractory-elements


en: Zethrenes are model diradicaloids with potential applications in spintronics and optoelectronics. Despite a rich chemistry in solution, on-surface synthesis of zethrenes has never been demonstrated. This record contains data to support our recent publication where we report the on-surface synthesis of super-heptazethrene on Au(111). Scanning tunneling spectroscopy investigations reveal that super-heptazethrene exhibits an exceedingly low HOMO–LUMO gap of 230 meV and, in contrast to its open-shell singlet ground state in the solution phase and in the solid-state, likely adopts a closed-shell ground state on Au(111).

en: On-surface synthesis of super-heptazethrene

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).

ab-initio

display_name: ab-initio

cscs

display_name: cscs

diradicaloid

display_name: diradicaloid

erc

display_name: erc

on-surface-synthesis

display_name: on-surface-synthesis

snsf

display_name: snsf


en: Two-dimensional transition metal dichalcogenides (TMDs) of Mo and W in their 1T′ crystalline phase host the quantum spin Hall (QSH) insulator phase. We address the electronic properties of the QSH edge states by means of first-principles calculations performed on realistic models of edge terminations of different stoichiometries. The QSH edge states show a tendency to have complex band dispersions and coexist with topologically trivial edge states. We nevertheless identify two stable edge terminations that allow isolation of a pair of helical edge states within the band gap of TMDs, with monolayer 1T′-WSe2 being the most promising material. We also characterize the finite-size effects in the electronic structure of 1T′-WSe2 nanoribbons. Our results provide guidance to the experimental studies and possible practical applications of QSH edge states in monolayer 1T′-TMDs.

en: Controlling the quantum spin Hall edge states in two-dimensional transition metal dichalcogenides

materialscloud

en: Materials Cloud

edge-states

display_name: edge-states

epfl

display_name: epfl

marvel

display_name: marvel

quantum-spin-hall-effect

display_name: quantum-spin-hall-effect

topological-insulators

display_name: topological-insulators

transition-metal-dichalcogenides

display_name: transition-metal-dichalcogenides


en: The most successful and popular machine learning models of atomic-scale properties derive their transferability from a locality ansatz. The properties of a large molecule or a bulk material are written as a sum over contributions that depend on the configurations within finite atom-centered environments. The obvious downside of this approach is that it cannot capture nonlocal, nonadditive effects such as those arising due to long-range electrostatics or quantum interference. We propose a solution to this problem by introducing nonlocal representations of the system, which are remapped as feature vectors that are defined locally and are equivariant in O(3). We consider, in particular, one form that has the same asymptotic behavior as the electrostatic potential. We demonstrate that this framework can capture nonlocal, long-range physics by building a model for the electrostatic energy of randomly distributed point-charges, for the unrelaxed binding curves of charged organic molecular dimers, and for the electronic dielectric response of liquid water. By combining a representation of the system that is sensitive to long-range correlations with the transferability of an atom-centered additive model, this method outperforms current state-of-the-art machine-learning schemes and provides a conceptual framework to incorporate nonlocal physics into atomistic machine learning.

en: Incorporating long-range physics in atomic-scale machine learning

envi

en: Environment

long-range-interactions

display_name: long-range-interactions

machine-learning

display_name: machine-learning


en: We investigate formation energies of C, Si, and Ge defects in β-Ga2O3 through hybrid functional calculations. We find that the interstitial defects of these elements generally occur at higher energies than their substitutional counterparts, while they are more stable at low Fermi energies in Ga-rich conditions. In n-type and Ga-rich conditions, interstitials of Si and Ge show significantly higher formation energies than their substitutional form, but this difference is less pronounced for C. Charge transition levels of interstitial defects lie in the upper part of the band-gap, and account for several measured levels in unintentionally doped and Ge-doped samples of β-Ga2O3.

en: Defect Formation Energies of Interstitial C, Si, and Ge Impurities in β-Ga2O3

defects

display_name: defects

hybrid-functional

display_name: hybrid-functional


en: In this work, we investigate the transverse magnetoresistance of materials by combining the Fermi surfaces calculated from first principles with the Boltzmann transport theory approach relying on the semiclassical model and the relaxation time approximation. We first consider a series of simple model Fermi surfaces to provide a didactic introduction into the charge-carrier compensation and open-orbit mechanisms leading to nonsaturating magnetoresistance. We then address in detail magnetotransport in three representative materials: (i) copper,  (ii) bismuth,  and (iii) tungsten diphosphide. Furthermore, the calculations allow for a full interpretation of the observed features in terms of the Fermi surface topology. Our study thus establishes guidelines to clarifying the physical mechanisms underlying the magnetotransport properties in a broad range of materials.

en: Magnetoresistance from Fermi surface topology

boltzmann-transport-theory

display_name: boltzmann-transport-theory

fermi-surface

display_name: fermi-surface

first-principles

display_name: first-principles

magnetoresistance

display_name: magnetoresistance

wanniertools

display_name: wanniertools


en: Maximally-localised Wannier functions (MLWFs) are routinely used to compute from first-principles advanced materials properties that require very dense Brillouin zone integration and to build accurate tight-binding models for scale-bridging simulations. At the same time, high-throughput (HT) computational materials design is an emergent field that promises to accelerate the reliable and cost-effective design and optimisation of new materials with target properties. The use of MLWFs in HT workflows has been hampered by the fact that generating MLWFs automatically and robustly without any user intervention and for arbitrary materials is, in general, very challenging. We address this problem directly by proposing a procedure for automatically generating MLWFs for HT frameworks. Our approach is based on the selected columns of the density matrix method (SCDM) and we present the details of its implementation in an AiiDA workflow. We apply our approach to a dataset of 200 bulk crystalline materials that span a wide structural and chemical space. We assess the quality of our MLWFs in terms of the accuracy of the band-structure interpolation that they provide as compared to the band-structure obtained via full first-principles calculations. We provide here an AiiDA export file with the full provenance of all simulations run in the project. Moreover, we provide a downloadable virtual machine that allows to reproduce the results of this paper and also to run new calculations for different materials, including all first-principles and atomistic simulations and the computational workflows.

aiida-workflow

display_name: aiida-workflow

automated-wannierisation

display_name: automated-wannierisation

band-structure-interpolation

display_name: band-structure-interpolation

high-throughput-simulations

display_name: high-throughput-simulations

marvelosp

display_name: marvelosp

maximally-localised-wannier-functions

display_name: maximally-localised-wannier-functions

scdm

display_name: scdm


en: Nonbenzenoid carbocyclic rings are postulated to serve as important structural elements toward tuning the chemical and electronic properties of extended polycyclic aromatic hydrocarbons (PAHs, or namely nanographenes), necessitating a rational and atomically precise synthetic approach toward their fabrication. This record contains data supporting a recent work where, using a combined bottom-up in-solution and on-surface synthetic approach, we report the synthesis of nonbenzenoid open-shell nanographenes containing two pairs of embedded pentagonal and heptagonal rings.

en: Open-shell Non-benzenoid Nanographenes Containing Two Pairs of Pentagonal and Heptagonal Rings

ab-initio

display_name: ab-initio

nanographene

display_name: nanographene

on-surface-synthesis

display_name: on-surface-synthesis

polycyclic-aromatic-hydrocarbons

display_name: polycyclic-aromatic-hydrocarbons

scanning-tunneling-microscopy

display_name: scanning-tunneling-microscopy


en:
We present a workflow that traces the path from the bulk structure of a crystalline material to assessing its performance in carbon capture from coal's postcombustion flue gases. This workflow is applied to a database of 324 covalent−organic frameworks (COFs) reported in the literature, to characterize their CO2 adsorption properties using the following steps:
(1) optimization of the crystal structure (atomic positions and unit cell) using density functional theory,
(2) fitting atomic point charges based on the electron density,
(3) characterizing the pore geometry of the structures before and after optimization,
(4) computing carbon dioxide and nitrogen isotherms using grand canonical Monte Carlo simulations with an empirical interaction potential, and finally,
(5) assessing the CO2 parasitic energy via process modeling.

The full workflow has been encoded in the Automated Interactive Infrastructure and Database for Computational Science (AiiDA). Both the workflow and the automatically generated provenance graph of our calculations are made available on the Materials Cloud, allowing peers to inspect every input parameter and result along the workflow, download structures and files at intermediate stages, and start their research right from where this work has left off. In particular, our set of CURATED (Clean, Uniform, and Refined with Automatic Tracking from Experimental Database) COFs, having optimized geometry and high-quality DFT-derived point charges, are available for further investigations of gas adsorption properties. We plan to update the database as new COFs are being reported.

*** UPDATE December 2019 ***
 - Database extended to  include 417 COFs (from papers published until September 1st 2019)
- Migration to AiiDA-v1.0.0
- Using the publicly available plugin aiida-lsmo

*** UPDATE February 2020 ***
 - Database extended to  include 505 COFs (from papers published until February 1st 2020)
 - Including AiiDA Groups for quick interactive visualization

*** UPDATE June 2020 ***
 - Database extended to include 574 COFs (from papers published until June 1st 2020)

*** UPDATE September 2020 ***
 - Include other applications than CCS, considering the same set of 574 COFs

*** UPDATE October 2020 ***
 - Database extended to include 626 COFs (from papers published until October 1st 2020)

*** UPDATE February 2021 ***
 - Database extended to include 632 COFs (from papers published until February 1st 2021). We added a total of 61 new structures but we discarded 55: see CURATED-COFs GitHub for more details.

*** UPDATE June 2021 ***
 - Database extended to include 648 valid COFs (from papers published until June 1st 2021) plus 80 discarded: see CURATED-COFs GitHub for more details.

*** UPDATE July 2022 ***
 - Database extended to include 871 valid COFs (from papers published until July 1st 2022) plus 110 discarded: see CURATED-COFs GitHub for more details.

en: Building a consistent and reproducible database for adsorption evaluation in Covalent-Organic Frameworks

aiida

display_name: aiida

covalent-organic-framework

display_name: covalent-organic-framework

erc

display_name: erc

reproducibility

display_name: reproducibility

workflows

display_name: workflows


en: Oxygen vacancies are a common source of excess electrons in complex oxides. In Mott insulators, these additional electrons can induce a metal-insulator transition (MIT), fundamentally altering the electronic properties of the  system. Here we study the effect of oxygen vacancies in LaTiO3, a prototypical Mott insulator close to the MIT. We show that the introduction of oxygen vacancies creates a vacancy-related band immediately below the partially filled Ti-t 2g bands. We study the effect of this additional band on the Mott MIT  using a combination of density functional theory and dynamical mean-field theory (DFT+DMFT), employing a minimal correlated subspace consisting of effective Ti-t 2g orbitals plus an additional Wannier function centered on the vacancy site. We find that the Mott insulating state in LaTiO3 is robust to the presence of the vacancy band, which remains fully occupied even in the presence of a local Coulomb repulsion, and therefore does not cause a doping of the Mott insulator

en: DFT+DMFT study of oxygen vacancies in a Mott insulator

defects

display_name: defects

dftdmft

display_name: dftdmft

electronic-structure

display_name: electronic-structure

mott-insulators

display_name: mott-insulators

oxygen-vacancies

display_name: oxygen-vacancies