cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.24435/materialscloud:x9-bz
title: Generalized stacking fault energy surfaces for eight face-centered cubic transition metals

description: Density functional theory calculations were used to obtain the generalized stacking fault energy surfaces in eight FCC metals: Ag, Au, Cu, Ir, Ni, Pd, Pt, and Rh. Among them, ferromagnetism was considered only in Ni. Results based on non-magnetic Ni are denoted as Ni-NM.
DOI: 10.24435/materialscloud:vv-y6
title: Large magnetic exchange coupling in rhombus-shaped nanographenes with zigzag periphery

description: In this record we provide data to support our recent findings for the magnetic properties of rhombus-shaped nanographenes. Nanographenes with zigzag edges are predicted to manifest non-trivial π-magnetism resulting from the interplay of concurrent electronic effects, such as hybridization of localized frontier states and Coulomb repulsion between valence electrons. This provides a chemically tunable platform to explore quantum magnetism at the nanoscale and opens avenues towards organic spintronics. The magnetic stability in nanographenes is thus far greatly limited by the weak magnetic exchange coupling, which remains below the room-temperature thermal energy. In our work, we report the synthesis of large rhombus-shaped nanographenes with zigzag peripheries on gold and copper surfaces. Single-molecule scanning probe measurements show an emergent magnetic spin singlet ground state with increasing nanographene size. The magnetic exchange coupling in the largest nanographene (C70H22, containing five benzenoid rings along each edge), determined by inelastic electron tunnelling spectroscopy, exceeds 100 meV or 1,160 K, which outclasses most inorganic nanomaterials and survives on a metal electrode.
DOI: 10.24435/materialscloud:2018.0021/v1
title: Few layer 2D pnictogens catalyze the alkylation of soft nucleophiles with esters.

description: Group 15 elements in zero oxidation state (P, As, Sb and Bi), also called pnictogens, are rarely used in catalysis due to the difficulties associated in preparing well–structured and stable materials. Here, we report on the synthesis of highly exfoliated, few layer 2D phosphorene and antimonene in zero oxidation state, suspended in an ionic liquid, with the native atoms ready to interact with external reagents while avoiding aerobic or aqueous decomposition pathways, and on their use as efficient catalysts for the alkylation of nucleophiles with esters. The few layer pnictogen material circumvents the extremely harsh reaction conditions associated to previous superacid–catalyzed alkylations, by enabling an alternative mechanism on surface, protected from the water and air by the ionic liquid. These 2D catalysts allow the alkylation of a variety of acid–sensitive organic molecules and giving synthetic relevancy to the use of simple esters as alkylating agents.
DOI: 10.24435/materialscloud:sq-ra
title: Large magnetic exchange coupling in rhombus-shaped nanographenes with zigzag periphery

description: In this record we provide data to support our recent findings for the magnetic properties of rhombus-shaped nanographenes. Nanographenes with zigzag edges are predicted to manifest non-trivial π-magnetism resulting from the interplay of concurrent electronic effects, such as hybridization of localized frontier states and Coulomb repulsion between valence electrons. This provides a chemically tunable platform to explore quantum magnetism at the nanoscale and opens avenues towards organic spintronics. The magnetic stability in nanographenes is thus far greatly limited by the weak magnetic exchange coupling, which remains below the room-temperature thermal energy. In our work, we report the synthesis of large rhombus-shaped nanographenes with zigzag peripheries on gold and copper surfaces. Single-molecule scanning probe measurements show an emergent magnetic spin singlet ground state with increasing nanographene size. The magnetic exchange coupling in the largest nanographene (C70H22, containing five benzenoid rings along each edge), determined by inelastic electron tunnelling spectroscopy, exceeds 100 meV or 1,160 K, which outclasses most inorganic nanomaterials and survives on a metal electrode.
DOI: 10.24435/materialscloud:2019.0029/v1
title: MD trajectories of semiconductor-water interfaces and relaxed atomic structures of semiconductor surfaces

description: This entry includes the MD trajectories of several semiconductor-water interfaces generated with ab initio molecular dynamics using the rVV10 density functional at the temperature of 350 K. Eight semiconductor surfaces are considered, namely GaAs(110), GaP(110), GaN(10-10), CdS(10-10), ZnO(10-10), SnO2(110), rutile TiO2(110) and anatase TiO2(101). For GaAs, GaP and anatase TiO2, the trajectories for the interfaces with both the molecular and the dissociative adsorption mode of water are provided. In addition, the relaxed atomic structures of the semiconductor surfaces used to calculate the ionization potential (IP) reported in [Chem. Mater. 2018, 30, 94−111] are added.
DOI: 10.24435/materialscloud:2019.0023/v1
title: Chemical Shifts in Molecular Solids by Machine Learning Datasets

description: We present a database of energy and NMR chemical shifts DFT calculations of 2500 crystal organic solids. The structures contain only H/C/N/O atoms and were subject to all-atoms geometry optimisation. Calculations were carried out using Quantum Espresso and GIPAW.
DOI: 10.24435/materialscloud:2q-0p
title: MD trajectories of semiconductor-water interfaces and relaxed atomic structures of semiconductor surfaces

description: This entry includes the MD trajectories of several semiconductor-water interfaces generated with ab initio molecular dynamics using the rVV10 density functional at the temperature of 350 K. Eight semiconductor surfaces are considered, namely GaAs(110), GaP(110), GaN(10-10), CdS(10-10), ZnO(10-10), SnO2(110), rutile TiO2(110) and anatase TiO2(101). For GaAs, GaP and anatase TiO2, the trajectories for the interfaces with both the molecular and the dissociative adsorption mode of water are provided. In addition, the relaxed atomic structures of the semiconductor surfaces used to calculate the ionization potential (IP) reported in [Chem. Mater. 2018, 30, 94−111] are added.
DOI: 10.24435/materialscloud:8n-50
title: Learning the exciton properties of azo-dyes

description: The ab initio determination of the character and properties of electronic excited states (ES) is the cornerstone of modern theoretical photochemistry. Yet, traditional ES methods become readily impractical when applied to fairly large molecules, or when used on thousands of different systems. In contrast, Machine Learning (ML) techniques have demonstrated their accuracy at retrieving ES properties of large molecular databases at a reduced computational cost. Especially for excited states applications, non-linear algorithms tend to be specialized and to target only individual properties. Learning fundamental quantum chemical objects potentially represents a more efficient, yet complex, alternative as a large number of molecular properties could be then extracted through post-processing. Herein, we report the general framework able to learn three fundamental objects of an ES: the hole and particle densities, as well as the transition density. We demonstrate the advantages of targeting those outputs of an ES computation, and address the additional complexity of learning 3-dimensional scalar fields. We apply our predictions to obtain a list of derived properties, including the state character and the topological descriptors of the exciton, for the two bands (nπ* and ππ*) of a collection of 3432 azoheteroarene photoswitches. In doing so, we prove that the proposed approach offers a way to access ES information of different kinds, bypassing the need of traditional electronic structure computations, while retaining ab initio accuracy.
DOI: 10.24435/materialscloud:j8-wr
title: Learning the exciton properties of azo-dyes

description: The ab initio determination of the character and properties of electronic excited states (ES) is the cornerstone of modern theoretical photochemistry. Yet, traditional ES methods become readily impractical when applied to fairly large molecules, or when used on thousands of different systems. In contrast, Machine Learning (ML) techniques have demonstrated their accuracy at retrieving ES properties of large molecular databases at a reduced computational cost. Especially for excited states applications, non-linear algorithms tend to be specialized and to target only individual properties. Learning fundamental quantum chemical objects potentially represents a more efficient, yet complex, alternative as a large number of molecular properties could be then extracted through post-processing. Herein, we report the general framework able to learn three fundamental objects of an ES: the hole and particle densities, as well as the transition density. We demonstrate the advantages of targeting those outputs of an ES computation, and address the additional complexity of learning 3-dimensional scalar fields. We apply our predictions to obtain a list of derived properties, including the state character and the topological descriptors of the exciton, for the two bands (nπ* and ππ*) of a collection of 3432 azoheteroarene photoswitches. In doing so, we prove that the proposed approach offers a way to access ES information of different kinds, bypassing the need of traditional electronic structure computations, while retaining ab initio accuracy.
DOI: 10.24435/materialscloud:2018.0021/v2
title: Few layer 2D pnictogens catalyze the alkylation of soft nucleophiles with esters.

description: Group 15 elements in zero oxidation state (P, As, Sb and Bi), also called pnictogens, are rarely used in catalysis due to the difficulties associated in preparing well–structured and stable materials. Here, we report on the synthesis of highly exfoliated, few layer 2D phosphorene and antimonene in zero oxidation state, suspended in an ionic liquid, with the native atoms ready to interact with external reagents while avoiding aerobic or aqueous decomposition pathways, and on their use as efficient catalysts for the alkylation of nucleophiles with esters. The few layer pnictogen material circumvents the extremely harsh reaction conditions associated to previous superacid–catalyzed alkylations, by enabling an alternative mechanism on surface, protected from the water and air by the ionic liquid. These 2D catalysts allow the alkylation of a variety of acid–sensitive organic molecules and giving synthetic relevancy to the use of simple esters as alkylating agents.
DOI: 10.24435/materialscloud:sd-j6
title: Ranking the synthesizability of hypothetical zeolites with the sorting hat

description: Zeolites are nanoporous alumino-silicate frameworks widely used as catalysts and adsorbents. Even though millions of siliceous networks can be generated by computer-aided searches, no new hypothetical framework has yet been synthesized. The needle-in-a-haystack problem of finding promising candidates among large databases of predicted structures has intrigued materials scientists for decades; yet, most work to date on the zeolite problem has been limited to intuitive structural descriptors. Here, we tackle this problem through a rigorous data science scheme—the "zeolite sorting hat"—that exploits interatomic correlations to discriminate between real and hypothetical zeolites and to partition real zeolites into compositional classes that guide synthetic strategies for a given hypothetical framework. We find that, regardless of the structural descriptor used by the zeolite sorting hat, there remain hypothetical frameworks that are incorrectly classified as real ones, suggesting that they might be good candidates for synthesis. We seek to minimize the number of such misclassified frameworks by using as complete a structural descriptor as possible, thus focusing on truly viable synthetic targets, while discovering structural features that distinguish real and hypothetical frameworks as an output of the zeolite sorting hat. Further ranking of the candidates can be achieved based on thermodynamic stability and/or their suitability for the desired applications. Based on this workflow, we propose three hypothetical frameworks differing in their molar volume range as the top targets for synthesis, each with a composition suggested by the zeolite sorting hat. Finally, we analyze the behavior of the zeolite sorting hat with a hierarchy of structural descriptors including intuitive descriptors reported in previous studies, finding that intuitive descriptors produce significantly more misclassified hypothetical frameworks, and that more rigorous interatomic correlations point to second-neighbor Si-O distances around 3.2–3.4 Å as the key discriminatory factor.
DOI: 10.24435/materialscloud:yz-k4
title: Few layer 2D pnictogens catalyze the alkylation of soft nucleophiles with esters.

description: Group 15 elements in zero oxidation state (P, As, Sb and Bi), also called pnictogens, are rarely used in catalysis due to the difficulties associated in preparing well–structured and stable materials. Here, we report on the synthesis of highly exfoliated, few layer 2D phosphorene and antimonene in zero oxidation state, suspended in an ionic liquid, with the native atoms ready to interact with external reagents while avoiding aerobic or aqueous decomposition pathways, and on their use as efficient catalysts for the alkylation of nucleophiles with esters. The few layer pnictogen material circumvents the extremely harsh reaction conditions associated to previous superacid–catalyzed alkylations, by enabling an alternative mechanism on surface, protected from the water and air by the ionic liquid. These 2D catalysts allow the alkylation of a variety of acid–sensitive organic molecules and giving synthetic relevancy to the use of simple esters as alkylating agents.
DOI: 10.24435/materialscloud:2020.0047/v1
title: Moiré Flat Bands in Twisted Double Bilayer Graphene

description: We investigate twisted double bilayer graphene (TDBG), a four-layer system composed of two AB-stacked graphene bilayers rotated with respect to each other by a small angle. Our ab-initio band structure calculations reveal a considerable energy gap at the charge point neutrality that we assign to the intrinsic symmetric polarization (ISP). We then introduce the ISP effect into the tight-binding parameterization and perform calculations on TDBG models that include lattice relaxation effects down to very small twist angles. We identify a narrow region around the magic angle θ*= 1.3° characterized by a manifold of remarkably flat bands gapped out from other states even without external electric fields. To understand the fundamental origin of the magic angle in TDBG, we construct a continuum model that points to a hidden mathematical link to the twisted bilayer graphene (TBG) model, thus indicating that the band flattening is a fundamental feature of TDBG, and is not a result of external fields.
DOI: 10.24435/materialscloud:tt-y4
title: Moiré Flat Bands in Twisted Double Bilayer Graphene

description: We investigate twisted double bilayer graphene (TDBG), a four-layer system composed of two AB-stacked graphene bilayers rotated with respect to each other by a small angle. Our ab-initio band structure calculations reveal a considerable energy gap at the charge point neutrality that we assign to the intrinsic symmetric polarization (ISP). We then introduce the ISP effect into the tight-binding parameterization and perform calculations on TDBG models that include lattice relaxation effects down to very small twist angles. We identify a narrow region around the magic angle θ*= 1.3° characterized by a manifold of remarkably flat bands gapped out from other states even without external electric fields. To understand the fundamental origin of the magic angle in TDBG, we construct a continuum model that points to a hidden mathematical link to the twisted bilayer graphene (TBG) model, thus indicating that the band flattening is a fundamental feature of TDBG, and is not a result of external fields.
DOI: 10.24435/materialscloud:2019.0023/v2
title: Chemical Shifts in Molecular Solids by Machine Learning Datasets

description: We present a database of energy and NMR chemical shifts DFT calculations of 4150 crystal organic solids. The structures contain only H/C/N/O/S atoms and were subject to all-atoms geometry optimisation. Calculations were carried out using Quantum Espresso and GIPAW.
DOI: 10.24435/materialscloud:2020.0040/v1
title: Bright Electroluminescence from Single Graphene Nanoribbon Junctions

description: This record refers to a study on the electroluminescence of individual GNRs suspended between the tip of a scanning tunneling microscope (STM) and a Au(111) substrate. Emission spectra of such GNR junctions reveal a bright and narrow band emission of red light, whose energy can be tuned with the bias voltage applied to the junction, but always lying below the gap of infinite GNRs. Comparison with ab initio calculations indicates that the emission involves electronic states localized at the GNR termini. The results shed light on unpredicted optical transitions in GNRs.

The record includes the computational data that allows to reproduce the published results.
DOI: 10.24435/materialscloud:ca-t7
title: Chemical Shifts in Molecular Solids by Machine Learning Datasets

description: We present a database of energy and NMR chemical shifts DFT calculations of 4150 crystal organic solids. The structures contain only H/C/N/O/S atoms and were subject to all-atoms geometry optimisation. Calculations were carried out using Quantum Espresso and GIPAW.
DOI: 10.24435/materialscloud:qf-xx
title: Bright Electroluminescence from Single Graphene Nanoribbon Junctions

description: This record refers to a study on the electroluminescence of individual GNRs suspended between the tip of a scanning tunneling microscope (STM) and a Au(111) substrate. Emission spectra of such GNR junctions reveal a bright and narrow band emission of red light, whose energy can be tuned with the bias voltage applied to the junction, but always lying below the gap of infinite GNRs. Comparison with ab initio calculations indicates that the emission involves electronic states localized at the GNR termini. The results shed light on unpredicted optical transitions in GNRs.

The record includes the computational data that allows to reproduce the published results.
DOI: 10.24435/materialscloud:2019.0025/v1
title: Determining interface structures in vertically aligned nanocomposite films

description: Vertically aligned nanocomposites (VANs) films have self-assembled pillar-matrix nanostructures. Owing to their large area-to-volume ratios,  interfaces in VAN films are expected to play key roles in inducing functional properties, but our understanding is hindered by limited knowledge about their structures. Motivated by the lack of definitive explanation for the experimentally-found enhanced ionic conductivity in Sm-doped-CeO2/SrTiO3 VAN films, we determine the structure at vertical interfaces using random structure searching and explore how it can affect ionic conduction. This record contains the candidate structures and provenance of the DFT validation calculations. Previously unknown interface structures are found, with lower energy than that of an optimized hand-built model. We find a strongly distorted oxygen sub-lattice which gives a complex landscape of vacancy energies. The cation lattice remains similar to the bulk phase but has a localized strain field. The excess energy of the interface is similar to that of high angle grain boundaries in SrTiO3.
DOI: 10.24435/materialscloud:2019.0024/v3
title: Applicability of tail-corrections in the molecular simulations of porous materials

description: Molecular simulations with periodic boundary conditions require to define a certain cutoff distance   beyond which pairwise dispersion interactions are neglected. For the simulation of homogeneous phases it is well-established to use tail-corrections, that can remedy this truncation of the potential. These corrections are built under the assumption that beyond  the cutoff the radial distribution function is equal to one. In this work we shed some light on the discussion whether or not tail corrections should be used in the  modelling of heterogeneous systems. We show that for the adsorption of gasses in a diverse set  nanoporous crystalline materials (zeolites, Covalent Organic Frameworks (COFs), and Metal Organic Frameworks (MOFs)), tail-corrections are an appropriate choice with which the results are much less sensitive to the details of the truncation.
DOI: 10.24435/materialscloud:ff-0p
title: Determining interface structures in vertically aligned nanocomposite films

description: Vertically aligned nanocomposites (VANs) films have self-assembled pillar-matrix nanostructures. Owing to their large area-to-volume ratios,  interfaces in VAN films are expected to play key roles in inducing functional properties, but our understanding is hindered by limited knowledge about their structures. Motivated by the lack of definitive explanation for the experimentally-found enhanced ionic conductivity in Sm-doped-CeO2/SrTiO3 VAN films, we determine the structure at vertical interfaces using random structure searching and explore how it can affect ionic conduction. This record contains the candidate structures and provenance of the DFT validation calculations. Previously unknown interface structures are found, with lower energy than that of an optimized hand-built model. We find a strongly distorted oxygen sub-lattice which gives a complex landscape of vacancy energies. The cation lattice remains similar to the bulk phase but has a localized strain field. The excess energy of the interface is similar to that of high angle grain boundaries in SrTiO3.
DOI: 10.24435/materialscloud:2019.0024/v1
title: Applicability of tail-corrections in the molecular simulations of porous materials

description: Molecular simulations with periodic boundary conditions require to define a certain cutoff distance   beyond which pairwise dispersion interactions are neglected. For the simulation of homogeneous phases it is well-established to use tail-corrections, that can remedy this truncation of the potential. These corrections are built under the assumption that beyond  the cutoff the radial distribution function is equal to one. In this work we shed some light on the discussion whether or not tail corrections should be used in the  modelling of heterogeneous systems. We show that for the adsorption of gasses in a diverse set  nanoporous crystalline materials (zeolites, Covalent Organic Frameworks (COFs), and Metal Organic Frameworks (MOFs)), tail-corrections are an appropriate choice with which the results are much less sensitive to the details of the truncation.
DOI: 10.24435/materialscloud:2019.0024/v2
title: Applicability of tail-corrections in the molecular simulations of porous materials

description: Molecular simulations with periodic boundary conditions require to define a certain cutoff distance   beyond which pairwise dispersion interactions are neglected. For the simulation of homogeneous phases it is well-established to use tail-corrections, that can remedy this truncation of the potential. These corrections are built under the assumption that beyond  the cutoff the radial distribution function is equal to one. In this work we shed some light on the discussion whether or not tail corrections should be used in the  modelling of heterogeneous systems. We show that for the adsorption of gasses in a diverse set  nanoporous crystalline materials (zeolites, Covalent Organic Frameworks (COFs), and Metal Organic Frameworks (MOFs)), tail-corrections are an appropriate choice with which the results are much less sensitive to the details of the truncation.