cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.24435/materialscloud:4f-r5
title: Depth-dependent time reversal symmetry breaking response in the charge-ordered kagome material RbV₃Sb₅

description: The AV₃Sb₅ kagome superconductors series are of intense interest due to their diverse and intricate properties. The breaking of time-reversal symmetry (TRS) in the normal state of these superconductors stands as a significant feature, yet the extent to which this effect can be tuned remains uncertain. Here, we employ a unique low-energy muon spin rotation technique combined with local field numerical analysis to study the TRS breaking response as a function of depth from the surface in single crystals of RbV₃Sb₅ with charge order and Cs(V0.86Ta0.14)₃Sb₅ without charge order. In the bulk (specifically above 30 nm from the sur face) of RbV₃Sb₅, we have detected a notable increase in the internal field width experienced by the muon ensemble. This increase occurs within the charge ordered state. Intriguingly, the muon spin relaxation rate is significantly enhanced near the surface of RbV₃Sb₅ (specifically within a depth range of 30-40 nm from the surface), and this effect commences at temperatures significantly higher than the onset of charge order. Conversely, in Cs(V0.86Ta0.14)₃Sb₅, which lacks charge order, we do not observe a similar enhancement in the internal field width, neither in the bulk nor at the surface. These observations indicate a strong connection between charge order and TRS breaking on one hand, and on the other hand, suggest that TRS breaking can be manipulated to occur prior to long-range charge order. This research offers compelling evidence for depth-dependent magnetism in AV₃Sb₅ superconductors in the presence of charge order. Such findings are likely to illuminate the intricate microscopic mechanisms that underpin the TRS breaking phenomena in these materials.
DOI: 10.24435/materialscloud:ge-4q
title: Depth-dependent time reversal symmetry breaking response in the charge-ordered kagome material RbV₃Sb₅

description: The AV₃Sb₅ kagome superconductors series are of intense interest due to their diverse and intricate properties. The breaking of time-reversal symmetry (TRS) in the normal state of these superconductors stands as a significant feature, yet the extent to which this effect can be tuned remains uncertain. Here, we employ a unique low-energy muon spin rotation technique combined with local field numerical analysis to study the TRS breaking response as a function of depth from the surface in single crystals of RbV₃Sb₅ with charge order and Cs(V0.86Ta0.14)₃Sb₅ without charge order. In the bulk (specifically above 30 nm from the sur face) of RbV₃Sb₅, we have detected a notable increase in the internal field width experienced by the muon ensemble. This increase occurs within the charge ordered state. Intriguingly, the muon spin relaxation rate is significantly enhanced near the surface of RbV₃Sb₅ (specifically within a depth range of 30-40 nm from the surface), and this effect commences at temperatures significantly higher than the onset of charge order. Conversely, in Cs(V0.86Ta0.14)₃Sb₅, which lacks charge order, we do not observe a similar enhancement in the internal field width, neither in the bulk nor at the surface. These observations indicate a strong connection between charge order and TRS breaking on one hand, and on the other hand, suggest that TRS breaking can be manipulated to occur prior to long-range charge order. This research offers compelling evidence for depth-dependent magnetism in AV₃Sb₅ superconductors in the presence of charge order. Such findings are likely to illuminate the intricate microscopic mechanisms that underpin the TRS breaking phenomena in these materials.
DOI: 10.24435/materialscloud:gg-1s
title: Optimizing the thermodynamics and kinetics of the triplet-pair dissociation in donor-acceptor copolymers for intramolecular singlet fission

description: Singlet fission (SF) is a two-step process in which a singlet splits into two triplets throughout the so-called correlated triplet-pair (1TT) state. Intramolecular SF (iSF) materials in particular, have attracted growing interest as they can be easily implemented in single junction solar cells and boost their power conversion efficiency. Still, the potential of iSF materials such as polymers and oligomers for photovoltaic applications has been partially hindered by their ability to go beyond the 1TT intermediate and generate free triplets, which mechanism remains poorly understood. In this work, the main aspects governing the 1TT dissociation in donor-acceptor copolymers and the key features that optimize this process are exposed. First, we show that both thermodynamics and kinetics play a crucial role in the intramolecular triplet-pair separation and second, we uncover the inherent flexibility of the donor unit as the fundamental ingredient to optimize them simultaneously. Overall, these results provide a better understanding of the intramolecular 1TT dissociation process and establish a new paradigm for the development of novel iSF active materials.
DOI: 10.24435/materialscloud:ma-ge
title: High-quality data enabling universality of band-gap descriptor and discovery of photovoltaic perovskites

description: Extensive machine-learning assisted research has been dedicated to predicting band gaps for perovskites, driven by their immense potential in photovoltaics. Yet, the effectiveness is often hampered by the lack of high-quality band-gap datasets, particularly for perovskites involving d orbitals. In this work, we consistently calculate a large dataset of band gaps with a high level of accuracy, which is rigorously validated by experimental and state-of-the-art GW band gaps. Leveraging this achievement, our machine-learning derived descriptor exhibits exceptional universality and robustness, proving effectiveness not only for single and double, halide and oxide perovskites regardless of the underlying atomic structures, but also for hybrid organic-inorganic perovskites. With this approach, we comprehensively explore up to 15,659 materials, unveiling 14 unreported lead-free perovskites with suitable band gaps for photovoltaics. Notably, MASnBr₃, FA₂SnGeBr₆, MA₂AuAuBr₆, FA₂AuAuBr₆, FA₂InBiCl₆, FA₂InBiBr₆, and Ba₂InBiO₆ stand out with direct band gaps, small effective masses, low exciton binding energies, and high stabilities.
DOI: 10.24435/materialscloud:z1-qk
title: Optimizing the thermodynamics and kinetics of the triplet-pair dissociation in donor-acceptor copolymers for intramolecular singlet fission

description: Singlet fission (SF) is a two-step process in which a singlet splits into two triplets throughout the so-called correlated triplet-pair (1TT) state. Intramolecular SF (iSF) materials in particular, have attracted growing interest as they can be easily implemented in single junction solar cells and boost their power conversion efficiency. Still, the potential of iSF materials such as polymers and oligomers for photovoltaic applications has been partially hindered by their ability to go beyond the 1TT intermediate and generate free triplets, which mechanism remains poorly understood. In this work, the main aspects governing the 1TT dissociation in donor-acceptor copolymers and the key features that optimize this process are exposed. First, we show that both thermodynamics and kinetics play a crucial role in the intramolecular triplet-pair separation and second, we uncover the inherent flexibility of the donor unit as the fundamental ingredient to optimize them simultaneously. Overall, these results provide a better understanding of the intramolecular 1TT dissociation process and establish a new paradigm for the development of novel iSF active materials.
DOI: 10.24435/materialscloud:9k-e9
title: High-quality data enabling universality of band-gap descriptor and discovery of photovoltaic perovskites

description: Extensive machine-learning assisted research has been dedicated to predicting band gaps for perovskites, driven by their immense potential in photovoltaics. Yet, the effectiveness is often hampered by the lack of high-quality band-gap datasets, particularly for perovskites involving d orbitals. In this work, we consistently calculate a large dataset of band gaps with a high level of accuracy, which is rigorously validated by experimental and state-of-the-art GW band gaps. Leveraging this achievement, our machine-learning derived descriptor exhibits exceptional universality and robustness, proving effectiveness not only for single and double, halide and oxide perovskites regardless of the underlying atomic structures, but also for hybrid organic-inorganic perovskites. With this approach, we comprehensively explore up to 15,659 materials, unveiling 14 unreported lead-free perovskites with suitable band gaps for photovoltaics. Notably, MASnBr₃, FA₂SnGeBr₆, MA₂AuAuBr₆, FA₂AuAuBr₆, FA₂InBiCl₆, FA₂InBiBr₆, and Ba₂InBiO₆ stand out with direct band gaps, small effective masses, low exciton binding energies, and high stabilities.
DOI: 10.24435/materialscloud:b8-yj
title: Locating guest molecules inside metal-organic framework pores with a multiscale computational approach

description: Molecular docking has traditionally mostly been employed in the field of protein-ligand binding. In the publication associated with this data, we extend this method, in combination with DFT-level geometry optimizations, to locate guest molecules inside the pores of metal-organic frameworks. Additional information on the adsorption strength in the studied host-guest systems emerges from the computed interaction energies. This record contains inputs and outputs of the molecular docking and the DFT computations.
DOI: 10.24435/materialscloud:zq-3t
title: Locating guest molecules inside metal-organic framework pores with a multiscale computational approach

description: Molecular docking has traditionally mostly been employed in the field of protein-ligand binding. In the publication associated with this data, we extend this method, in combination with DFT-level geometry optimizations, to locate guest molecules inside the pores of metal-organic frameworks. Additional information on the adsorption strength in the studied host-guest systems emerges from the computed interaction energies. This record contains inputs and outputs of the molecular docking and the DFT computations.
DOI: 10.24435/materialscloud:46-wj
title: Infrared-active phonons in one-dimensional materials and their spectroscopic signatures

description: Dimensionality provides a clear fingerprint on the dispersion of infrared-active, polar-optical phonons. For these phonons, the local dipoles parametrized by the Born effective charges drive the LO-TO splitting of bulk materials; this splitting actually breaks down in two-dimensional materials. Here, we develop the theory for one-dimensional (1D) systems -nanowires, nanotubes, and atomic and polymeric chains. Combining an analytical model with the implementation of density-functional perturbation theory in 1D boundary conditions, we show that the dielectric splitting in the dispersion relations collapses as x²log(x) at the zone center. The dielectric properties and the radius of the 1D materials are linked by the present work to these red shifts, opening infrared and Raman characterization avenues.
DOI: 10.24435/materialscloud:er-6g
title: Infrared-active phonons in one-dimensional materials and their spectroscopic signatures

description: Dimensionality provides a clear fingerprint on the dispersion of infrared-active, polar-optical phonons. For these phonons, the local dipoles parametrized by the Born effective charges drive the LO-TO splitting of bulk materials; this splitting actually breaks down in two-dimensional materials. Here, we develop the theory for one-dimensional (1D) systems -nanowires, nanotubes, and atomic and polymeric chains. Combining an analytical model with the implementation of density-functional perturbation theory in 1D boundary conditions, we show that the dielectric splitting in the dispersion relations collapses as x²log(x) at the zone center. The dielectric properties and the radius of the 1D materials are linked by the present work to these red shifts, opening infrared and Raman characterization avenues.
DOI: 10.24435/materialscloud:k4-j5
title: Fully ab-initio electronic structure of Ca₂RuO₄

description: The reliable ab-initio description of strongly correlated materials is a long-sought capability in condensed matter physics. The GW+EDMFT method is a promising scheme, which provides a self-consistent description of correlations and screening, and does not require user-provided parameters. In order to test the reliability of this approach we apply it to the experimentally well characterized perovskite compound Ca₂RuO₄, in which a temperature-dependent structural deformation drives a paramagnetic metal-insulator transition. Our results demonstrate that the nonlocal polarization and self-energy components introduced by GW are essential for setting the correct balance between interactions and bandwidths, and that the GW+EDMFT scheme produces remarkably accurate predictions of the electronic properties of this strongly correlated material.
DOI: 10.24435/materialscloud:7q-ee
title: Fully ab-initio electronic structure of Ca₂RuO₄

description: The reliable ab-initio description of strongly correlated materials is a long-sought capability in condensed matter physics. The GW+EDMFT method is a promising scheme, which provides a self-consistent description of correlations and screening, and does not require user-provided parameters. In order to test the reliability of this approach we apply it to the experimentally well characterized perovskite compound Ca₂RuO₄, in which a temperature-dependent structural deformation drives a paramagnetic metal-insulator transition. Our results demonstrate that the nonlocal polarization and self-energy components introduced by GW are essential for setting the correct balance between interactions and bandwidths, and that the GW+EDMFT scheme produces remarkably accurate predictions of the electronic properties of this strongly correlated material.
DOI: 10.24435/materialscloud:4t-rb
title: Numerical study of neutral and charged microgel suspensions: from single-particle to collective behavior

description: We perform extensive molecular dynamics simulations of an ensemble of realistic microgel particles in swollen conditions in a wide range of packing fractions ζ. We compare neutral and charged microgels, where we consider charge distribution adherent to experimental conditions. Through a detailed analysis of singleparticle behavior, we are able to identify the different regimes occurring upon increasing concentration: from shrinking to deformation and interpenetration, always connecting our findings with available experimental observations. We then link these single-particle features with the collective behavior of the suspension, finding evidence of a structural reentrance that has no counterpart in the dynamics. Hence, while the maximum of the radial distribution function displays a nonmonotonic behavior with increasing ζ, the dynamics, quantified by the microgels' mean-squared displacement, always slows down. This behavior, at odds with the simple Hertzian model, can be described by a phenomenological multi-Hertzian model, which takes into account the enhanced internal stiffness of the core. However, also this model fails when deformation enters into play, whereby more realistic many-body models are required. Thanks to our analysis, we are able to unveil the key physical mechanisms, shrinking and deformation, giving rise to the structural reentrance that holds up to very large packing fractions. We further identify key similarities and differences between neutral and charged microgels, for which we detect at high enough ζ the fusion of charged shells, previously invoked to explain key experimental findings, and responsible for the structural reentrance. Overall, our study establishes a powerful framework to uncover the physics of microgel suspensions, paving the way to tackle different regimes, e.g., high temperature, and internal architectures, such as for hollow and ultralow-cross-linked microgels, where experimental evidence is still limited.
DOI: 10.24435/materialscloud:cb-xf
title: Predicting the influence of edge oxidation in parallel-plate rheometry

description: Melt post-condensation, thermal, and thermo-oxidative degradation of a cyclo-aliphatic polyamide were studied through time-resolved rheometry (TRR). The implemented TRR elucidates structural changes occurring during two concurrent phenomena, namely melt post-condensation and thermal/thermo-oxidative degradation, during the time sweep in a parallel plate rheometer. TRR measurements were conducted on neat polyamide under nitrogen (inert/non-oxidative) and air (oxidative) environment at 3 % strain amplitude and a range of frequencies between 0.1 and 100 rad/sec for two hours. At temperatures of 260, 270, and 275 °C, a dual-stage time-dependent growth in viscoelastic properties was observed under an oxidative environment. Thermo-oxidative degradation of polyamide melt 270 °C was shown to occur from the exposed sample edge, continuing inwards, effectively reducing the radius of the unoxidized polymer melt by 6.4 %. A modeling approach using MATLAB is presented to interpret and differentiate the rheological behavior of edge oxidized gel and bulk polymer within the volume of the sample melt. The code removes the effects of the strain limiter and the edge gelation from experimental measurements in predicting the material properties.
DOI: 10.24435/materialscloud:mt-pj
title: Numerical study of neutral and charged microgel suspensions: from single-particle to collective behavior

description: We perform extensive molecular dynamics simulations of an ensemble of realistic microgel particles in swollen conditions in a wide range of packing fractions ζ. We compare neutral and charged microgels, where we consider charge distribution adherent to experimental conditions. Through a detailed analysis of singleparticle behavior, we are able to identify the different regimes occurring upon increasing concentration: from shrinking to deformation and interpenetration, always connecting our findings with available experimental observations. We then link these single-particle features with the collective behavior of the suspension, finding evidence of a structural reentrance that has no counterpart in the dynamics. Hence, while the maximum of the radial distribution function displays a nonmonotonic behavior with increasing ζ, the dynamics, quantified by the microgels' mean-squared displacement, always slows down. This behavior, at odds with the simple Hertzian model, can be described by a phenomenological multi-Hertzian model, which takes into account the enhanced internal stiffness of the core. However, also this model fails when deformation enters into play, whereby more realistic many-body models are required. Thanks to our analysis, we are able to unveil the key physical mechanisms, shrinking and deformation, giving rise to the structural reentrance that holds up to very large packing fractions. We further identify key similarities and differences between neutral and charged microgels, for which we detect at high enough ζ the fusion of charged shells, previously invoked to explain key experimental findings, and responsible for the structural reentrance. Overall, our study establishes a powerful framework to uncover the physics of microgel suspensions, paving the way to tackle different regimes, e.g., high temperature, and internal architectures, such as for hollow and ultralow-cross-linked microgels, where experimental evidence is still limited.
DOI: 10.24435/materialscloud:yv-ss
title: Predicting the influence of edge oxidation in parallel-plate rheometry

description: Melt post-condensation, thermal, and thermo-oxidative degradation of a cyclo-aliphatic polyamide were studied through time-resolved rheometry (TRR). The implemented TRR elucidates structural changes occurring during two concurrent phenomena, namely melt post-condensation and thermal/thermo-oxidative degradation, during the time sweep in a parallel plate rheometer. TRR measurements were conducted on neat polyamide under nitrogen (inert/non-oxidative) and air (oxidative) environment at 3 % strain amplitude and a range of frequencies between 0.1 and 100 rad/sec for two hours. At temperatures of 260, 270, and 275 °C, a dual-stage time-dependent growth in viscoelastic properties was observed under an oxidative environment. Thermo-oxidative degradation of polyamide melt 270 °C was shown to occur from the exposed sample edge, continuing inwards, effectively reducing the radius of the unoxidized polymer melt by 6.4 %. A modeling approach using MATLAB is presented to interpret and differentiate the rheological behavior of edge oxidized gel and bulk polymer within the volume of the sample melt. The code removes the effects of the strain limiter and the edge gelation from experimental measurements in predicting the material properties.
DOI: 10.24435/materialscloud:es-a4
title: Spatiotemporal prediction of microstructure evolution with predictive recurrent neural network

description: Prediction of microstructure evolution during material processing is essential to control the material properties. Simulation tools for microstructure evolution prediction based on physical concepts are computationally expensive and time-consuming. Therefore, they are not practical when either there is an urgent need for microstructure morphology during the process, or there is a need to generate big microstructure datasets. Essentially, microstructure evolution prediction is a spatiotemporal sequence prediction problem, where the prediction of material microstructure is difficult due to different process histories and chemistry. We propose a Predictive Recurrent Neural Network (PredRNN) model for the microstructure prediction, which extends the inner-layer transition function of memory states in LSTMs to spatiotemporal memory flow. As a case study, we used a dataset from spinodal decomposition simulation of FeCrCo alloy created by the phase-field method for training and predicting future microstructures by previous observations. The results show that the trained network predicts quantitatively accurate microstructure morphologies while it is several orders of magnitude faster than the phase field method. 
The trained model aims to generate future material microstructures by learning from the historical microstructures, where the visual dynamics are believed to have modular structures that can be learned with compositional subsystems. A PredRNN (https://github.com/thuml/predrnn-pytorch) model was trained to predict Fe-Cr-Co microstructures evolution during the spinodal decomposition.