cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccr2zyq
title: CCDC 688074: Experimental Crystal Structure Determination

description: Related Article: B.-M.Kukovec, P.D.Vaz, Z.Popovic, M.J.Calhorda, K.Furic, G.Pavlovic, M.R.Linaric|2008|Cryst.Growth Des.|8|3465|doi:10.1021/cg800512k
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccr5r6v
title: CCDC 690717: Experimental Crystal Structure Determination

description: Related Article: J.Beckmann, R.Ruttinger, T.Schwich|2008|Cryst.Growth Des.|8|3271|doi:10.1021/cg8000569
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccr2s7t
title: CCDC 687866: Experimental Crystal Structure Determination

description: Related Article: M.Wiecko, C.Eidamshaus, R.Koppe, P.W.Roesky|2008|Dalton Trans.||4837|doi:10.1039/b811436f
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccr74gk
title: CCDC 692058: Experimental Crystal Structure Determination

description: Related Article: A.M.Corrente, T.Chivers|2008|Dalton Trans.||4840|doi:10.1039/b810319d
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.15468/dl.zuth55
title: Occurrence Download

description: A dataset containing 29376220 species occurrences available in GBIF matching the query:
(Query is too complex. Can be viewed on the landing page)

 The dataset includes 29376220 records from 5353 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016043-210819072339941/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.24435/materialscloud:cs-2a
title: Designing crystallization to tune the performance of phase-change memory: rules of hierarchical melt and coordinate bond

description: While alloy design has practically shown an efficient strategy to mediate two seemingly conflicted performances of writing speed and data retention in phase-change memory, the detailed kinetic pathway of alloy-tuned crystallization is still unclear. Here, we propose hierarchical melt and coordinate bond strategies to solve them, where the former stabilizes a medium-range crystal-like region and the latter provides a rule to stabilize amorphous. The Er0.52Sb2Te3 compound we designed achieves writing speed of 3.2 ns and ten-year data retention of 161 °C. We provide a direct atomic-level evidence that two neighbor Er atoms stabilize a medium-range crystal-like region, acting as a precursor to accelerate crystallization; meanwhile, the essential reason of stabilization originates from the formation of coordinate bonds by sharing lone-pair electrons of chalcogenide atoms with the empty 5d orbitals of Er atoms. The two rules pave the way for the development of storage-class memory with excellent comprehensive performance to achieve next revolutionary technology node.
DOI: 10.24435/materialscloud:6n-fe
title: Designing crystallization to tune the performance of phase-change memory: rules of hierarchical melt and coordinate bond

description: While alloy design has practically shown an efficient strategy to mediate two seemingly conflicted performances of writing speed and data retention in phase-change memory, the detailed kinetic pathway of alloy-tuned crystallization is still unclear. Here, we propose hierarchical melt and coordinate bond strategies to solve them, where the former stabilizes a medium-range crystal-like region and the latter provides a rule to stabilize amorphous. The Er0.52Sb2Te3 compound we designed achieves writing speed of 3.2 ns and ten-year data retention of 161 °C. We provide a direct atomic-level evidence that two neighbor Er atoms stabilize a medium-range crystal-like region, acting as a precursor to accelerate crystallization; meanwhile, the essential reason of stabilization originates from the formation of coordinate bonds by sharing lone-pair electrons of chalcogenide atoms with the empty 5d orbitals of Er atoms. The two rules pave the way for the development of storage-class memory with excellent comprehensive performance to achieve next revolutionary technology node.
DOI: 10.24435/materialscloud:jc-ky
title: A microscopic picture of paraelectric perovskites from structural prototypes

description: This work details how to determine structural prototypes for the cubic perovskite structure that are used to study the B-site displacements in the cubic, paraelectric phase. Car-Parrinello MD simulations of cubic barium titanate (BaTiO3) show the titanium displacements from the undistorted cubic structure. Using a systematic symmetry analysis we construct microscopic templates, i.e. representative structural models in the form of supercells that satisfy a desired point symmetry but are built from the combination of lower-symmetry primitive cells. Density functional theory calculations, using the microscopic templates as starting structures for a relaxation, are carried out to find structural prototypes of BaTiO3 with local polar distortions but with cubic point symmetry. The stability of these structures is studied as a function of volume and with respect to the zone-boundary phonons of pristine cubic BaTiO3. The stable distortions patterns for BaTiO3 are investigated for other titanates and for a handful of niobates and zirconates.
DOI: 10.24435/materialscloud:y1-zd
title: Effects of the density and composition on the properties of amorphous alumina: a high dimensional neural network potential study

description: Amorphous alumina (a-AlOx), which plays important roles in several technological fields, shows wide variation of the density and composition. However, their influences on the properties of a-AlOx have rarely been investigated from a theoretical perspective. In this study, high dimensional neural network (NN) potentials were constructed to generate a series of atomic structures of a-AlOx with different densities (2.6–3.3 g/cm3) and O/Al ratios (1.0–1.75). The structural, vibrational, mechanical, and thermal properties of the a-AlOx models were investigated, as well as the Li and Cu diffusion behaviour in the models. The results showed that the density and composition had different degrees of effects on the different properties. The structural and vibrational properties were strongly affected by the composition, whereas the mechanical properties were mainly determined by the density. The thermal conductivity was affected by both the density and composition of a-AlOx. However, the effects on the Li and Cu diffusion behaviour were relatively unclear.
DOI: 10.24435/materialscloud:jj-m3
title: Effects of the density and composition on the properties of amorphous alumina: a high dimensional neural network potential study

description: Amorphous alumina (a-AlOx), which plays important roles in several technological fields, shows wide variation of the density and composition. However, their influences on the properties of a-AlOx have rarely been investigated from a theoretical perspective. In this study, high dimensional neural network (NN) potentials were constructed to generate a series of atomic structures of a-AlOx with different densities (2.6–3.3 g/cm3) and O/Al ratios (1.0–1.75). The structural, vibrational, mechanical, and thermal properties of the a-AlOx models were investigated, as well as the Li and Cu diffusion behaviour in the models. The results showed that the density and composition had different degrees of effects on the different properties. The structural and vibrational properties were strongly affected by the composition, whereas the mechanical properties were mainly determined by the density. The thermal conductivity was affected by both the density and composition of a-AlOx. However, the effects on the Li and Cu diffusion behaviour were relatively unclear.
DOI: 10.24435/materialscloud:66-ec
title: Accurate and scalable multi-element graph neural network force field and molecular dynamics with direct force architecture

description: Data includes the the ab initio molecular dynamic simulation of Li7P3S11 that was used to measure the performance of the GNNFF. The data is divided into training and testing sets.

Brief descirption of the work: Recently, machine learning (ML) has been used to address the computational cost that has been limiting ab initio molecular dynamics (AIMD). Here, we present GNNFF, a graph neural network framework to directly predict atomic forces from automatically extracted features of the local atomic environment that are translationally-invariant, but rotationally-covariant to the coordinate of the atoms. We demonstrate that GNNFF not only achieves high performance in terms of force prediction accuracy and computational speed on various materials systems, but also accurately predicts the forces of a large MD system after being trained on forces obtained from a smaller system. Finally, we use our framework to perform an MD simulation of Li7P3S11, a superionic conductor, and show that resulting Li diffusion coefficient is within 14% of that obtained directly from AIMD. The high performance exhibited by GNNFF can be easily generalized to study atomistic level dynamics of other material systems.
DOI: 10.24435/materialscloud:az-2c
title: Accurate and scalable multi-element graph neural network force field and molecular dynamics with direct force architecture

description: Data includes the the ab initio molecular dynamic simulation of Li7P3S11 that was used to measure the performance of the GNNFF. The data is divided into training and testing sets.

Brief descirption of the work: Recently, machine learning (ML) has been used to address the computational cost that has been limiting ab initio molecular dynamics (AIMD). Here, we present GNNFF, a graph neural network framework to directly predict atomic forces from automatically extracted features of the local atomic environment that are translationally-invariant, but rotationally-covariant to the coordinate of the atoms. We demonstrate that GNNFF not only achieves high performance in terms of force prediction accuracy and computational speed on various materials systems, but also accurately predicts the forces of a large MD system after being trained on forces obtained from a smaller system. Finally, we use our framework to perform an MD simulation of Li7P3S11, a superionic conductor, and show that resulting Li diffusion coefficient is within 14% of that obtained directly from AIMD. The high performance exhibited by GNNFF can be easily generalized to study atomistic level dynamics of other material systems.
DOI: 10.24435/materialscloud:pg-50
title: A microscopic picture of paraelectric perovskites from structural prototypes

description: This work details how to determine structural prototypes for the cubic perovskite structure that are used to study the B-site displacements in the cubic, paraelectric phase. Car-Parrinello MD simulations of cubic barium titanate (BaTiO3) show the titanium displacements from the undistorted cubic structure. Using a systematic symmetry analysis we construct microscopic templates, i.e. representative structural models in the form of supercells that satisfy a desired point symmetry but are built from the combination of lower-symmetry primitive cells. Density functional theory calculations, using the microscopic templates as starting structures for a relaxation, are carried out to find structural prototypes of BaTiO3 with local polar distortions but with cubic point symmetry. The stability of these structures is studied as a function of volume and with respect to the zone-boundary phonons of pristine cubic BaTiO3. The stable distortions patterns for BaTiO3 are investigated for other titanates and for a handful of niobates and zirconates.
DOI: 10.24435/materialscloud:cc-j6
title: A data-driven perspective on the colours of metal-organic frameworks

description: Colour is at the core of chemistry and has been fascinating humans since ancient times. It is also a key descriptor of optoelectronic properties of materials and is used to assess the success of a synthesis. 
However, predicting the colour of a material based on its structure is challenging.
In this work, we leverage subjective and categorical human assignments of colours to build a model that can predict the colour of compounds on a continuous scale, using chemically meaningful reasoning.
In the process of developing the model, we also uncover inadequacies in current reporting mechanisms. 
For example, we show that the majority of colour assignments are subject to perceptive spread that would not comply with common printing standards. 
To remedy this, we suggest and implement an alternative way of reporting colour that is more suitable for a data-driven approach to materials science.
DOI: 10.24435/materialscloud:k6-vp
title: A microscopic picture of paraelectric perovskites from structural prototypes

description: This work details how to determine structural prototypes for the cubic perovskite structure that are used to study the B-site displacements in the cubic, paraelectric phase. Car-Parrinello MD simulations of cubic barium titanate (BaTiO3) show the titanium displacements from the undistorted cubic structure. Using a systematic symmetry analysis we construct microscopic templates, i.e. representative structural models in the form of supercells that satisfy a desired point symmetry but are built from the combination of lower-symmetry primitive cells. Density functional theory calculations, using the microscopic templates as starting structures for a relaxation, are carried out to find structural prototypes of BaTiO3 with local polar distortions but with cubic point symmetry. The stability of these structures is studied as a function of volume and with respect to the zone-boundary phonons of pristine cubic BaTiO3. The stable distortions patterns for BaTiO3 are investigated for other titanates and for a handful of niobates and zirconates.
DOI: 10.24435/materialscloud:eb-a4
title: A data-driven perspective on the colours of metal-organic frameworks

description: Colour is at the core of chemistry and has been fascinating humans since ancient times. It is also a key descriptor of optoelectronic properties of materials and is used to assess the success of a synthesis. 
However, predicting the colour of a material based on its structure is challenging.
In this work, we leverage subjective and categorical human assignments of colours to build a model that can predict the colour of compounds on a continuous scale, using chemically meaningful reasoning.
In the process of developing the model, we also uncover inadequacies in current reporting mechanisms. 
For example, we show that the majority of colour assignments are subject to perceptive spread that would not comply with common printing standards. 
To remedy this, we suggest and implement an alternative way of reporting colour that is more suitable for a data-driven approach to materials science.
DOI: 10.24435/materialscloud:vh-mk
title: Bloch's theorem in orbital-density-dependent functionals: Band structures from Koopmans spectral functionals

description: Koopmans-compliant functionals provide an orbital-density-dependent framework for an accurate evaluation of spectral properties; they are obtained by imposing a generalized piecewise-linearity condition on the total energy of the system with respect to the occupation of any orbital. In crystalline materials, due to the orbital-density-dependent nature of the functionals, minimization of the total energy to a ground state provides a set of minimizing variational orbitals that are localized and thus break the periodicity of the underlying lattice. Despite this, we show that Bloch symmetry can be preserved and it is possible to describe the electronic states with a band-structure picture, thanks to the Wannier-like character of the variational orbitals. We also present a method to unfold and interpolate the electronic bands from supercell (Γ-point) calculations, which enables us to calculate full band structures with Koopmans-compliant functionals. The results obtained for a set of benchmark semiconductors and insulators show very good agreement with state-of-the-art many-body perturbation theory and experiments, underscoring the reliability of these spectral functionals in predicting band structures.
DOI: 10.24435/materialscloud:xj-9d
title: Identifying the trade-off between intramolecular singlet fission requirements in donor-acceptor copolymers

description: Intramolecular singlet fission (iSF) has shown potential to improve the power conversion efficiency in photovoltaic devices by promoting the splitting of a photon-absorbing singlet exciton into two triplet excitons within a single molecule. Among different possibilities, the donor-acceptor modular strategy of copolymers has shown great promise in its ability to undergo iSF under certain conditions. However, the number of iSF donor-acceptor copolymers reported in the literature remains remarkably narrow and clear trends for the molecular design of better candidates have not yet been established. In this work, we identify the trade-off between the main iSF requirements of the donor-acceptor strategy and formulate design rules that allow them to be tuned simultaneously in a fragment-based approach. Based on a library of 2944 donor-acceptor copolymers, we establish simple guidelines to build promising novel materials for iSF. These consist in (1st) selecting an acceptor core with high intrinsic singlet-triplet splitting, (2nd) locating a donor with a larger monomer frontier molecular orbital (FMO) gap than that of the acceptor, and (3rd) tuning the relative energy of donor and/or acceptor FMOs through functionalization to promote photoinduced charge transfer in the resulting polymer. Remarkably, systems containing benzothiadiazole and thiophene-1,1-dioxide acceptors, which have been shown to undergo iSF, fulfill all criteria simultaneously when paired with appropriate donors. This is due to their particular electronic features, which make them highly promising candidates in the quest for iSF materials.
DOI: 10.24435/materialscloud:n5-pt
title: Identifying the trade-off between intramolecular singlet fission requirements in donor-acceptor copolymers

description: Intramolecular singlet fission (iSF) has shown potential to improve the power conversion efficiency in photovoltaic devices by promoting the splitting of a photon-absorbing singlet exciton into two triplet excitons within a single molecule. Among different possibilities, the donor-acceptor modular strategy of copolymers has shown great promise in its ability to undergo iSF under certain conditions. However, the number of iSF donor-acceptor copolymers reported in the literature remains remarkably narrow and clear trends for the molecular design of better candidates have not yet been established. In this work, we identify the trade-off between the main iSF requirements of the donor-acceptor strategy and formulate design rules that allow them to be tuned simultaneously in a fragment-based approach. Based on a library of 2944 donor-acceptor copolymers, we establish simple guidelines to build promising novel materials for iSF. These consist in (1st) selecting an acceptor core with high intrinsic singlet-triplet splitting, (2nd) locating a donor with a larger monomer frontier molecular orbital (FMO) gap than that of the acceptor, and (3rd) tuning the relative energy of donor and/or acceptor FMOs through functionalization to promote photoinduced charge transfer in the resulting polymer. Remarkably, systems containing benzothiadiazole and thiophene-1,1-dioxide acceptors, which have been shown to undergo iSF, fulfill all criteria simultaneously when paired with appropriate donors. This is due to their particular electronic features, which make them highly promising candidates in the quest for iSF materials.
DOI: 10.24435/materialscloud:w8-k3
title: Thermodynamics of order and randomness in dopant distributions inferred from atomically resolved images

description: Exploration of structure-property relationships as a function of dopant concentration is commonly based on mean field theories for solid solutions. However, such theories that work well for semiconductors tend to fail in materials with strong correlations, either in electronic behavior or chemical segregation. In these cases, the details of atomic arrangements are generally not explored and analyzed. The knowledge of the generative physics and chemistry of the material can obviate this problem, since defect configuration libraries as stochastic representation of atomic level structures can be generated, or parameters of mesoscopic thermodynamic models can be derived. To obtain such information for improved predictions, we use data from atomically resolved microscopic images that visualize complex structural correlations within the system and translate them into statistical mechanical models of structure formation. Given the significant uncertainties about the microscopic aspects of the material's processing history along with the limited number of available images, we combine model optimization techniques with the principles of statistical hypothesis testing. We demonstrate the approach on data from a series of atomically-resolved scanning transmission electron microscopy images of MoxRe1−xS2 at varying ratios of Mo/Re stoichiometries, for which we propose an effective interaction model that is then used to generate atomic configurations and make testable predictions at a range of concentrations and formation temperatures.

This dataset includes STEM image data files and associated python code to perform statistical analysis of the images and simulations.