cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.24435/materialscloud:97-2x
title: Building a consistent and reproducible database for adsorption evaluation in Covalent-Organic Frameworks

description: 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)
DOI: 10.24435/materialscloud:2018.0020/v1
title: Ab initio thermodynamics of liquid and solid water: supplemental materials

description: 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.
DOI: 10.24435/materialscloud:zq-8b
title: Ab initio thermodynamics of liquid and solid water: supplemental materials

description: 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.
DOI: 10.24435/materialscloud:2019.0015/v1
title: High-throughput calculations of catalytic properties of bimetallic alloy surfaces

description: 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.
DOI: 10.24435/materialscloud:2h-g1
title: High-throughput calculations of catalytic properties of bimetallic alloy surfaces

description: 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.
DOI: 10.24435/materialscloud:kd-wj
title: Building a consistent and reproducible database for adsorption evaluation in Covalent-Organic Frameworks

description: 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
DOI: 10.24435/materialscloud:2019.0051/v1
title: Dopant discovery in cuprous iodide

description: 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.
DOI: 10.4121/924dc692-80e6-475f-8966-3bd672683f43.v2
title: Data underlying the MSc research project: Targeted Urban Stream Renewal: The Case of Bílá Nisa in Jablonec nad Nisou

description: This dataset contains qualitative and quantitative data on biodiversity, climate adaptation and quality of life. The data is normalized (values range from 0-1, indicating good-bad, high-low and otherwise specified). The data is selected with a 100 meter radius along the Bílá Nisa stream. This data is then organized on a grid of 100x100 meters, with a more detailed grid of 50x50 meters further overlayed in the inner city borders of Jablonec nad Nisou.The research project was conducted for a TU Delft Urbanism MSc elective course Applied Spatial Analytics for Sustainable Urban Development (course code ARFW0501). The course is based on the ReBioClim project, funded by the Interreg Central Europe Program, which focuses on revitalizing small urban streams in European cities to enhance biodiversity, mitigate climate change effects, and improve urban living conditions. Running from June 2024 to January 2027, the project addresses the challenges of urban stream restoration in four Central European cities: Dresden, Jablonec nad Nisou, Poznan and Senica. The case study of this dataset is Jablonec nad Nisou.
DOI: 10.24435/materialscloud:q2-8n
title: Dopant discovery in cuprous iodide

description: 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.
DOI: 10.4121/924dc692-80e6-475f-8966-3bd672683f43.v3
title: Data underlying the MSc research project: Targeted Urban Stream Renewal: The Case of Bílá Nisa in Jablonec nad Nisou

description: This dataset contains qualitative and quantitative data on biodiversity, climate adaptation and quality of life. The data is normalized (values range from 0-1, indicating good-bad, high-low and otherwise specified). The data is selected with a 100 meter radius along the Bílá Nisa stream. This data is then organized on a grid of 100x100 meters, with a more detailed grid of 50x50 meters further overlayed in the inner city borders of Jablonec nad Nisou.The research project was conducted for a TU Delft Urbanism MSc elective course Applied Spatial Analytics for Sustainable Urban Development (course code ARFW0501). The course is based on the ReBioClim project, funded by the Interreg Central Europe Program, which focuses on revitalizing small urban streams in European cities to enhance biodiversity, mitigate climate change effects, and improve urban living conditions. Running from June 2024 to January 2027, the project addresses the challenges of urban stream restoration in four Central European cities: Dresden, Jablonec nad Nisou, Poznan and Senica. The case study of this dataset is Jablonec nad Nisou.
DOI: 10.24435/materialscloud:2019.0052/v1
title: EAM potential for Hf-Nb-Ta-Zr high-entropy alloy

description: 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.
DOI: 10.24435/materialscloud:vt-dc
title: EAM potential for Hf-Nb-Ta-Zr high-entropy alloy

description: 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.
DOI: 10.24435/materialscloud:ef-4j
title: Predicting polymerization reactions via transfer learning using chemical language models

description: Polymers are candidate materials for a wide range of sustainability applications such as carbon capture and energy storage. However, computational polymer discovery lacks automated analysis of reaction pathways and stability assessment through retro-synthesis. Here, we report the first extension of transformer-based language models to polymerization reactions for both forward and retrosynthesis tasks. We curated a polymerization dataset for vinyl polymers covering reactions and retrosynthesis for representative homo-polymers and co-polymers. Overall, we report a forward model accuracy of 80% and a backward model accuracy of 60%. We further analyse the model performance on a set of case studies by providing polymerization and retro-synthesis examples and evaluating the model's predictions quality from a materials science perspective.
DOI: 10.24435/materialscloud:an-gg
title: Naphthalene crystal shape prediction from molecular dynamics simulations

description: We used molecular dynamics simulations to predict the steady state crystal shape of naphthalene grown from ethanol solution. The simulations were performed at constant supersaturation by utilizing a recently proposed algorithm [Perego et al., J. Chem. Phys., 2015, 142, 144113]. To bring the crystal growth within the timescale of a molecular dynamics simulation we applied well-tempered Metadynamics with a spatially constrained collective variable, which focuses the sampling on the growing layer. We estimated that the resulting steady state crystal shape corresponds to a rhombic prism, which is in line with experiments. Further, we observed that at the investigated supersaturations, the {00-1} face grows in a two step two dimensional nucleation mechanism while the considerably faster growing faces {1-10} and {20-1} grow new layers with a one step two dimensional nucleation mechanism.
DOI: 10.24435/materialscloud:k6-ve
title: Naphthalene crystal shape prediction from molecular dynamics simulations

description: We used molecular dynamics simulations to predict the steady state crystal shape of naphthalene grown from ethanol solution. The simulations were performed at constant supersaturation by utilizing a recently proposed algorithm [Perego et al., J. Chem. Phys., 2015, 142, 144113]. To bring the crystal growth within the timescale of a molecular dynamics simulation we applied well-tempered Metadynamics with a spatially constrained collective variable, which focuses the sampling on the growing layer. We estimated that the resulting steady state crystal shape corresponds to a rhombic prism, which is in line with experiments. Further, we observed that at the investigated supersaturations, the {00-1} face grows in a two step two dimensional nucleation mechanism while the considerably faster growing faces {1-10} and {20-1} grow new layers with a one step two dimensional nucleation mechanism.
DOI: 10.24435/materialscloud:jw-kq
title: On-surface synthesis of super-heptazethrene

description: 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).
DOI: 10.24435/materialscloud:cw-p5
title: On-surface synthesis of super-heptazethrene

description: 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).
DOI: 10.24435/materialscloud:dq-z3
title: Engineering  frustrated lewis pair active sites in porous organic scaffolds for catalytic CO₂ hydrogenation

description: 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.
DOI: 10.24435/materialscloud:cg-q0
title: Controlling the quantum spin Hall edge states in two-dimensional transition metal dichalcogenides

description: 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.
DOI: 10.24435/materialscloud:he-d6
title: Data for ferromagnetic resonance simulation in a microtube

description: Ferromagnetic resonance fields in a microtube with the various ratio of the inner and outer diameter of the tube β were studied using micromagnetic simulation. For β < 0.15 the resonance field agrees with the prediction of the Kittel equation for an infinite ferromagnetic cylinder for both parallel and perpendicular orientation of the applied field to its axis. For β > 0.15 the resonance field increases from the resonance field of the infinite cylinder and approaches the level of the film magnetized along the plane. This behavior was at odds both with the prediction that can be made using analytically calculated demagnetizing factor in ferromagnetic tube, and with the prediction that use the empirical dependence of the demagnetizing field on β, established from the magnetization curves. For β > 0.15 and transverse applied field a number of resonance peaks were observed.