AndreaBozzo/ceres-open-data-index huggingface dataset:
The Influence of Intrinsic Framework Flexibility on Adsorption in Nanoporous Materials (Data Download)

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.

Tags: flexibility, nanoporous-materials, xekr-separations
In Silico Design of 2D and 3D Covalent Organic Frameworks for Methane Storage Applications

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).

Tags: 2d, 3d, cof, covalent-organic-frameworks, database, dc, deliverable-capacities, gcmc, grand-canonical-monte-carlo, high-throughput, layered, marvel, methane-storage, nanoporous, three-dimensional, two-dimensional
The geometric blueprint of perovskites

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.

Tags: data-mining, goldschmidt, perovskites, structure-predictions
Approximation of Collective Variables by anncolvar

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.

Tags: artificial-neural-networks, collective-variable, metadynamics
The Influence of Intrinsic Framework Flexibility on Adsorption in Nanoporous Materials (Data Download)

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.

Tags: flexibility, nanoporous-materials, xekr-separations
Predicting Product Distribution of Propene Dimerization in Nanoporous Materials (Data Download)

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.

Tags: metalorganic-frameworks, molecular-simulation, monte-carlo, product-distribution, propene-dimerization, zeolites
Building a consistent and reproducible database for adsorption evaluation in Covalent-Organic Frameworks

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.

Tags: aiida, covalent-organic-framework, marvel, reproducibility, workflows
Evaluating charge equilibration methods to generate electrostatic fields in nanoporous materials

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.

Tags: charge-equilibration-methods, marvel, partial-charges, qeq
Accurate Characterization of the Pore Volume in Microporous Crystalline Materials (Data Download)

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.

Tags: marvel, nanoporous-materials, pore-volume, void-fraction
Generating carbon schwarzites via zeolite-templating

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.

Tags: carbon-materials, marvel, schwarzites, tpms, ztc
Machine learning meets volcano plots: Computational discovery of cross-coupling catalysts

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.

Tags: homogeneous-catalysis, machine-learning, transition-metal-complexes, volcano-plot
A Cannibalistic Approach to Grand Canonical Crystal Growth

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.

Tags: constant-chemical-potential-molecular-dynamics-simulations, crystal-nucleation-and-growth, crystallization-under-realistic-conditions, erc, marveldd1, solution-crystallization
Trins

Schlussresultate der regionalen Wahl "Trins", 14. Juni 2026, Graubünden - Grischun - Grigioni, aufgeschlüsselt nach Kandidaten und Gemeinden.

Tags: election, elecziun, elezione, plaun-regiunal-regionlabelgr, regional-regionlabelgr, regionale-regionlabelgr, wahl
Calculation and interpretation of classical turning surfaces in solids

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

Tags: density-functional-theory, dft, kohn-sham-potential, turning-surface
Building a consistent and reproducible database for adsorption evaluation in Covalent-Organic Frameworks

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

Tags: aiida, covalent-organic-framework, marvel, reproducibility, workflows