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: Synthesis of Metal-Organic Frameworks: capturing chemical intuition

machine-learning

display_name: machine-learning

metal-organic-frameworks

display_name: metal-organic-frameworks

optimisation

display_name: optimisation

synthesis

display_name: synthesis


$oid: OBSOLETE

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.

materialscloud

approval_status: approved

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

political_level: other

state: active

type: organization

psi

capacity: public

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

type: dataset

key: guid

key: uri

value: DCAT Harvester Materials Cloud

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

flexibility

display_name: flexibility

nanoporous-materials

display_name: nanoporous-materials

xekr-separations

display_name: xekr-separations


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. 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


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: 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

data-mining

display_name: data-mining

goldschmidt

display_name: goldschmidt

perovskites

display_name: perovskites

structure-predictions

display_name: structure-predictions


the-geometric-blueprint-of-perovskites

title_for_slug: the-geometric-blueprint-of-perovskites


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.

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

mean-square-deviation

display_name: mean-square-deviation


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

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

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

metalorganic-frameworks

display_name: metalorganic-frameworks

molecular-simulation

display_name: molecular-simulation

monte-carlo

display_name: monte-carlo

product-distribution

display_name: product-distribution

propene-dimerization

display_name: propene-dimerization

zeolites

display_name: zeolites


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:
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 post-combustion flue gases. We apply the workflow 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 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 (empirical interaction potential) and, finally,
(5) assessing the CO2 parasitic energy via process modelling.

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 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 COFs with optimized geometry and high quality DFT-derived point charges is available for further investigations of gas adsorption properties. We plan to update the database as new COFs are being reported.

en: Materials Cloud

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

marvel

display_name: marvel

reproducibility

display_name: reproducibility

workflows

display_name: workflows


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

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

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

envi

en: Environment

charge-equilibration-methods

display_name: charge-equilibration-methods

partial-charges

display_name: partial-charges

qeq

display_name: qeq


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

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

nanoporous-materials

display_name: nanoporous-materials

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


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:
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 paper published until the 1st September 2019)
- Migration to AiiDA-v1.0.0
- Using the publicly available plugin aiida-lsmo

aiida

display_name: aiida

covalent-organic-framework

display_name: covalent-organic-framework

marvel

display_name: marvel

reproducibility

display_name: reproducibility

workflows

display_name: workflows


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.

materialscloud

en: Materials Cloud

chirality

display_name: chirality

many-body-dispersion

display_name: many-body-dispersion

pdga

display_name: pdga


en: Hidden Beneath the Surface: Origin of the Observed Enantioselective Adsorption on PdGa(111)


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


envi

en: Environment


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)

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


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

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

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


marvel

display_name: marvel


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

aiida

display_name: aiida

covalent-organic-framework

display_name: covalent-organic-framework

reproducibility

display_name: reproducibility

workflows

display_name: workflows


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


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: 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

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


materialscloud

en: Materials Cloud

marvel

display_name: marvel


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)

aiida

display_name: aiida

covalent-organic-framework

display_name: covalent-organic-framework

erc

display_name: erc

marvelosp

display_name: marvelosp

reproducibility

display_name: reproducibility

workflows

display_name: workflows


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


envi

en: Environment


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


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

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


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

cui

display_name: cui

defects

display_name: defects

dopants

display_name: dopants

supercell

display_name: supercell

transparent-conductors

display_name: transparent-conductors


dopant-discovery-in-cuprous-iodide

title_for_slug: dopant-discovery-in-cuprous-iodide


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

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


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:
Frustrated Lewis pairs (FLPs), featuring reactive combinations of Lewis acids and Lewis bases, have been utilized for myriad metal-free homogeneous catalytic processes. Immobilizing the active Lewis sites to a solid support, especially to porous scaffolds, has shown great potential to ameliorate FLP catalysis by circumventing some of its inherent drawbacks, such as product separation and catalyst recyclability. Nevertheless, designing immobilized Lewis pair active sites (LPASs) is challenging due to the requirement of placing the donor and acceptor centers in appropriate geometric arrangements while maintaining the necessary chemical environment to perform catalysis, and clear design rules have not yet been established. In this work, we formulate simple guidelines to build highly active LPASs for direct catalytic hydrogenation of CO₂ through a large-scale screening of a diverse library of 25,000 immobilized FLPs.
The library is built by introducing boron-containing acidic sites in the vicinity of the existing basic nitrogen sites of the organic linkers of metal-organic frameworks collected in a "top-down" fashion from an experimental database. The chemical and geometrical appropriateness of these LPASs for CO₂ hydrogenation is determined by evaluating a series of simple descriptors representing the intrinsic strength (acidity and basicity) of the components and their spatial arrangement in the active sites. Analysis of the leading candidates enables the formulation of pragmatic and experimentally-relevant design principles and they constitute the starting point for further exploration of FLP-based catalysts for the reduction of CO₂.

en: Engineering  frustrated lewis pair active sites in porous organic scaffolds for catalytic CO₂ hydrogenation

catalysis

display_name: catalysis

epfl

display_name: epfl

frustrated-lewis-pairs

display_name: frustrated-lewis-pairs

metal-organic-frameworks

display_name: metal-organic-frameworks

molecular-catalysts

display_name: molecular-catalysts

volcano-plot

display_name: volcano-plot


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.

materialscloud

en: Materials Cloud

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

edge-states

display_name: edge-states

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


envi

en: Environment


en: We propose a general method to calculate the average misfit volumes of atoms in any random alloy via DFT calculations. The method is validated with an example of a 6-component equi-composition high entropy alloy. The special quasi-random structures (SQSs) used in our work are reported here.

en: Special quasi-random structures for the 6-component high entropy alloys

high-entropy-alloys

display_name: high-entropy-alloys

misfit-volumes

display_name: misfit-volumes

random-alloys

display_name: random-alloys

special-quasi-random-structures-sqss

display_name: special-quasi-random-structures-sqss


en: Metal-Organic Frameworks (MOFs) are highly versatile materials owing to their vast structural and chemical tunability. These hybrid inorganic-organic crystalline materials offer an ideal platform to incorporate light-harvesting and catalytic centers and thus, exhibit a great potential to be exploited in solar-driven photocatalytic processes such as H2 production and CO2 reduction. To be photocatalytically active, UV-visible optical absorption and appropriate band alignment with respect to the target redox potential is required. Despite fulfilling these criteria, the photocatalytic performance of MOFs is still limited by their ability to produce long-lived electron-hole pairs and long-range charge transport. In this work, we present a computational strategy to address these two descriptors in MOF structures and translate them into charge transfer numbers and effective mass values. We apply our approach to 15 MOF structures from the literature that encompass the main strategies used in the design of efficient photocatalysts including different metals, ligands, and topologies. Our results capture the main characteristics previously reported for these MOFs and enable us to identify promising candidates. In the quest of novel photocatalytic systems, high-throughput screening based on charge separation and charge mobility features is envisioned to be applied in large databases of both experimentally and in silico generated MOFs.

en: Charge separation and charge carrier mobility in photocatalytic metal-organic frameworks

charge-transfer

display_name: charge-transfer

erc

display_name: erc

mof

display_name: mof

photocatalysis

display_name: photocatalysis


epfl

display_name: epfl

snsf

display_name: snsf


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)

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

marvelosp

display_name: marvelosp

reproducibility

display_name: reproducibility

workflows

display_name: workflows


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

maximally-localised-wannier-functions

display_name: maximally-localised-wannier-functions

scdm

display_name: scdm


en: The leucine-lysine amphiphilic peptide LKα14 has been used to study fundamental driving forces in processes such as peptide-surface binding and biomineralization. Here, we employ molecular dynamics (MD) simulations in tandem with replica exchange metadynamics to probe the binding mechanism and thermodynamics of LKα14 on silica. We also investigate the effect that the nature of the silica surface – crystalline vs. amorphous, has on the binding properties and peptide-surface conformations. We find that water adsorbs differently on both surfaces; it forms a denser interfacial layer on the crystalline surface, compared to the amorphous surface. This causes the peptide to bind more strongly on the amorphous surface than the crystalline surface. Cluster analysis shows that the peptide adopts a helical conformation at both surfaces, with a greater distribution of states on the crystalline surface. Peptide binding is primarily through lysine interactions, in line with prior experimental results.

en: Amphiphilic Peptide Binding on Crystalline vs. Amorphous Silica from Molecular Dynamics Simulations

enhanced-sampling

display_name: enhanced-sampling

molecular-dynamics-simulations

display_name: molecular-dynamics-simulations

peptide-surface-interactions

display_name: peptide-surface-interactions


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

erc

display_name: erc

long-range-interactions

display_name: long-range-interactions

machine-learning

display_name: machine-learning


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:
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.

aiida

display_name: aiida


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


materialscloud

en: Materials Cloud


en:
Frustrated Lewis pairs (FLPs), featuring reactive combinations of Lewis acids and Lewis bases, have been utilized for myriad metal-free homogeneous catalytic processes. Immobilizing the active Lewis sites to a solid support, especially to porous scaffolds, has shown great potential to ameliorate FLP catalysis by circumventing some of its inherent drawbacks, such as product separation and catalyst recyclability. Nevertheless, designing immobilized Lewis pair active sites (LPASs) is challenging due to the requirement of placing the donor and acceptor centers in appropriate geometric arrangements while maintaining the necessary chemical environment to perform catalysis, and clear design rules have not yet been established. In this work, we formulate simple guidelines to build highly active LPASs for direct catalytic hydrogenation of CO₂ through a large-scale screening of a diverse library of 25,000 immobilized FLPs.
The library is built by introducing boron-containing acidic sites in the vicinity of the existing basic nitrogen sites of the organic linkers of metal-organic frameworks collected in a "top-down" fashion from an experimental database. The chemical and geometrical appropriateness of these LPASs for CO₂ hydrogenation is determined by evaluating a series of simple descriptors representing the intrinsic strength (acidity and basicity) of the components and their spatial arrangement in the active sites. Analysis of the leading candidates enables the formulation of pragmatic and experimentally-relevant design principles and they constitute the starting point for further exploration of FLP-based catalysts for the reduction of CO₂.

en: Engineering  frustrated lewis pair active sites in porous organic scaffolds for catalytic CO₂ hydrogenation

envi

en: Environment

catalysis

display_name: catalysis

epfl

display_name: epfl

frustrated-lewis-pairs

display_name: frustrated-lewis-pairs

metal-organic-frameworks

display_name: metal-organic-frameworks

molecular-catalysts

display_name: molecular-catalysts

volcano-plot

display_name: volcano-plot


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.

covalent-organic-framework

display_name: covalent-organic-framework

marvelosp

display_name: marvelosp

reproducibility

display_name: reproducibility

workflows

display_name: workflows


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- thoughput (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. Finally, we provide here a downloadable virtual machine that allows to reproduce the results of this paper, including all first-principles and atomistic simulations as well as 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

maximally-localised-wannier-functions

display_name: maximally-localised-wannier-functions

scdm

display_name: scdm


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

marvel

display_name: marvel

wanniertools

display_name: wanniertools


en: We investigate the solvation effect of water on the overpotentials of the oxygen evolution reaction on rutile TiO2 by applying the thermodynamic integration method on atomistic model interfaces with and without the water molecules. We compare the results at the vacuum interface with the commonly used computational hydrogen electrode method, finding overall good agreement. The effect of the solvent is found to be twofold. First, the explicit treatment of the solvent can lead to equilibrium configurations differing from the relaxed structures without solvent. Second, the overpotentials can be affected by up to 0.5 eV. The energetics are subject to electrostatic effects at the interface rather than to modifications in the hydrogen bond network. These results provide a promising perspective for treating the solvent with implicit models.

en: Effect of the Solvent on the Oxygen Evolution Reaction at the TiO2-Water Interface

explicit-solvent

display_name: explicit-solvent

oxygen-evolution-reaction

display_name: oxygen-evolution-reaction

rutile

display_name: rutile

solvation-effect

display_name: solvation-effect

water

display_name: water


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- thoughput (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

marvelosp

display_name: marvelosp


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.

automated-wannierisation

display_name: automated-wannierisation

band-structure-interpolation

display_name: band-structure-interpolation


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


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:
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.

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:
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.

materialscloud

en: Materials Cloud


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


envi

en: Environment


en: We investigate the synergy occurring in photocatalytic water splitting between the metal-organic framework MIL-125-NH2 and two co-catalysts, namely NiO and Ni2P, by calculating their band edge alignment with respect to the redox levels of liquid water. For the NiO/H2O and Ni2P/H2O interfaces, we employ an explicit atomistic description of water and perform molecular dynamics simulations considering both molecular and dissociated water adsorbed at the co-catalyst surface. For the MIL-125-NH2/NiO and MIL-125-NH2/Ni2P interfaces, we rely on the concept of charge neutrality and use a scheme combining the electron affinities and the charge neutrality levels of the interface components. We provide a description of the underlying fundamental processes that is consistent with photoluminescence and intrinsic activity experiments and that supports NiO and Ni2P as suitable co-catalysts for MIL-125-NH2 as far as the hydrogen evolution reaction is concerned.

en: Unraveling the synergy between metal-organic frameworks and co-catalysts in photocatalytic water splitting

co-catalyst

display_name: co-catalyst

density-functional-calculations

display_name: density-functional-calculations

first-principles-calculations

display_name: first-principles-calculations

hydrogen-evolution

display_name: hydrogen-evolution

metal-organic-frameworks

display_name: metal-organic-frameworks

molecular-dynamics

display_name: molecular-dynamics

photocatalysis

display_name: photocatalysis

water-splitting

display_name: water-splitting