2026-11-04T09:20:00Z https://archive.materialscloud.org/oai2d

oai:materialscloud.org:2191 2024-05-23T09:59:05Z openaire_data community-mcarchive

Fiorentino, Alfredo Drigo, Enrico Baroni, Stefano Pegolo, Paolo Fiorentino, Alfredo Drigo, Enrico Baroni, Stefano Pegolo, Paolo 2024-05-23 The time-honored Allen-Feldman theory of heat transport in glasses is generally assumed to predict a finite value for the thermal conductivity, even if it neglects the anharmonic broadening of vibrational normal modes. We demonstrate that the harmonic approximation predicts that the bulk lattice thermal conductivity of harmonic solids inevitably diverges at any temperature, irrespective of configurational disorder, and that its ability to represent the heat-transport properties observed experimentally in most glasses is implicitly due to finite-size effects. Our theoretical analysis is thoroughly benchmarked against careful numerical simulations. Our findings thus reveal that a proper account of anharmonic effects is indispensable to predict a finite value for the bulk thermal conductivity in any solid material, be it crystalline or glassy. This record contains data and scripts to support the findings of the manuscript and ensure their reproducibility. text/markdown application/zip application/zip application/zip application/zip application/zip text/markdown https://doi.org/10.24435/materialscloud:wc-yf oai:materialscloud.org:2191 mcid:2024.77 eng Materials Cloud https://doi.org/10.48550/arXiv.2307.09370 https://archive.materialscloud.org/communities/mcarchive/ https://doi.org/10.24435/materialscloud:a8-p8 info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode MaX thermal transport amorphous solids glass Unearthing the foundational role of anharmonicity in heat transport in glasses info:eu-repo/semantics/other

oai:materialscloud.org:2061 2024-05-27T10:10:43Z openaire_data community-mcarchive

Bonnet, Nicephore Marzari, Nicola Bonnet, Nicephore Marzari, Nicola 2024-05-27 In this paper, we propose an extension to the approach of [Xi, C; et al. J. Chem. Theory Comput. 2022, 18, 6878] to calculate ion solvation free energies from first-principles (FP) molecular dynamics (MD) simulations of a hybrid solvation model. The approach is first re-expressed within the quasi-chemical theory of solvation. Then, to allow for longer simulation times than the original first-principles molecular dynamics approach and thus improve the convergence of statistical averages at a fraction of the original computational cost, a machine-learned (ML) energy function is trained on FP energies and forces and used in the MD simulations. The ML workflow and MD simulation times (≈200 ps) are adjusted to converge the predicted solvation energies within a chemical accuracy of 0.04 eV. The extension is successfully benchmarked on the same set of alkaline and alkaline-earth ions. The record includes all molecular-dynamics trajectories, energies and forces used to obtain the solvation energies of alkaline and alkaline-earth ions in water, as reported in Table 2 of referenced paper. application/zip text/plain text/markdown https://doi.org/10.24435/materialscloud:a0-jh oai:materialscloud.org:2061 mcid:2024.80 eng Materials Cloud https://doi.org/10.1021/acs.jctc.4c00116 https://archive.materialscloud.org/communities/mcarchive/ https://doi.org/10.24435/materialscloud:66-sv info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode solvation machine learning molecular dynamics Solvation free energies from machine learning molecular dynamics info:eu-repo/semantics/other

oai:materialscloud.org:rdm6f-8qp56 2026-01-23T13:47:08Z openaire_data community-mcarchive

Partos, Alma Partos, Alma Di Marco, Igor Sharma, Shivalika 2026-01-23 <p>The study of magnetism in transition metals is a cornerstone in understanding complex electronic and magnetic interactions in condensed matter systems. Among transition metal elements, body-centered cubic (bcc) chromium stands out because of its spin-density wave (SDW) ground state, posing a long-standing challenge for density functional theory (DFT). Conventional functionals, such as the generalized-gradient approximation (GGA) and the local-density approximation (LDA), fail to predict this experimentally observed incommensurate SDW as the ground state. In this study, we present a comprehensive DFT analysis of bcc Cr employing GGA and a variety of meta-GGA functionals. We evaluated total energies, structural parameters, and magnetic properties across a wide range of SDW wave vectors. Our results show that all meta-GGA functionals overestimate the local magnetic moments and enhance the nodal magnetic frustration, destabilizing the SDW state relative to the commensurate antiferromagnetic (AF) configuration. Tao-Perdew-Staroverov-Scuseria (TPSS) yields results closest to those of the GGA, thus providing the most adequate description of bcc Cr among the meta-GGA functionals. These results emphasize the need for the further development of non-local or hybrid functionals tailored for complex magnetic systems.</p> application/zip text/plain https://doi.org/10.24435/materialscloud:sq-hq oai:materialscloud.org:rdm6f-8qp56 mcid:2026.23 eng Materials Cloud https://doi.org/10.1016/j.jmmm.2026.173847 https://archive.materialscloud.org/communities/mcarchive/ https://doi.org/10.24435/materialscloud:sv-fm info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode magnetism DFT chromium spin-density waves A first-principles study of bcc chromium beyond the generalized gradient approximation (GGA) info:eu-repo/semantics/other

oai:materialscloud.org:1200 2022-01-21T17:10:08Z openaire_data community-mcarchive

Hu, Yi Curtin, William Hu, Yi Curtin, William 2022-01-21 Strengthening by needle-shaped β′′ precipitates is critical in Al–Mg–Si alloys. Here, the strengthening is studied computationally at the peak-aged condition where precipitate shearing and Orowan looping are usually considered to have equal strengths. Pseudo-random precipitate microstructures are constructed based on experimental precipitate dimensions and volume fractions at peak aging. A Discrete Dislocation Dynamics method is then adapted to compute the Critical Resolved Shear Stress (CRSS) for Orowan looping of dislocations moving through the non-shearable precipitate field. The CRSS for Orowan looping is determined by a typical in-situ precipitate spacing that is smaller than the average spacing and by the dislocation core energy within a radius of ≈5b, a factor rarely considered. The matrix misfit stresses, volume fraction, and precipitate shape have small effects on the CRSS. With microstructure and property details introduced as faithfully as possible, the CRSS for Orowan looping using atomistically-calibrated core energies at room temperature is nonetheless ≈33% higher than experiments. This suggests that precipitate shearing controls strength, and analyses of (i) forces acting on the precipitates, (ii) misfit stresses inside the precipitates, (iii) first-principles results for the relevant precipitate fault energies, and (iv) simulations that mimic precipitate shearing indicate a shearing CRSS closer to experiments. Thus, Orowan looping only sets an upper bound for the CRSS even at peak aging, and further quantitative progress requires detailed modeling of precipitate shearing. text/markdown text/plain application/x-xz application/x-xz application/x-xz https://doi.org/10.24435/materialscloud:2c-7c oai:materialscloud.org:1200 mcid:2022.10 eng Materials Cloud https://doi.org/10.1016/j.jmps.2021.104378 https://www.sciencedirect.com/science/article/pii/S002250962100065X?via%3Dihub https://archive.materialscloud.org/communities/mcarchive/ https://doi.org/10.24435/materialscloud:rs-12 info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode Aluminum Metallurgy Discrete Dislocation Dynamics Precipitation strengthening Orowan Mechanism MARVEL/DD2 Modeling peak-aged precipitate strengthening in Al-Mg-Si alloys info:eu-repo/semantics/other

oai:materialscloud.org:1997 2023-11-30T10:13:06Z openaire_data community-mcarchive

Liu, Xin Liu, Xin Curtin, William 2023-11-30 A theory for strengthening for multicomponent non-dilute alloys possessing short-range order (SRO) has recently been developed. The theory predicts that, in addition to a well-known athermal strengthening, there is a notable effect of SRO on the solute–dislocation interactions that can decrease or increase the strength relative to a random alloy. Here, carefully designed atomistic simulations in a model binary NbW alloy are used to demonstrate that alloy strength due to solute–dislocation interactions can be increased or decreased, depending on the SRO and consistent with theoretical predictions. Specifically, SRO is introduced using fictitious solute– solute interactions in an alloy system with very small true solute–solute interactions, and the Nudged Elastic Band (NEB) method is then used to compute the energy barriers for edge dislocation motion for various levels of SRO. Energy barriers, and hence alloy strengths, can be decreased when the Warren-Cowley SRO parameters are negative (attraction of unlike solutes). The theoretical predictions for the same system are in reasonable quantitative agreement with the simulation results. These findings demonstrate the unexpected possibility of reduced strength due to SRO and also further validate the analytical theory as a tool to guide alloy design. text/markdown application/zip https://doi.org/10.24435/materialscloud:kz-b7 oai:materialscloud.org:1997 mcid:2023.184 eng Materials Cloud https://doi.org/10.1016/j.actamat.2023.119471 https://archive.materialscloud.org/communities/mcarchive/ https://doi.org/10.24435/materialscloud:g9-y6 info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode Alloys Yield strength Short-range order Theory Simulation MARVEL Atomistic simulations reveal strength reductions due to short-range order in alloys info:eu-repo/semantics/other

oai:materialscloud.org:1223 2022-01-21T09:32:03Z openaire_data community-mcarchive

Corminboeuf, Clemence Laplaza, Ruben Gallarati, Simone Corminboeuf, Clemence 2022-01-21 We present the NaviCatGA package, a versatile genetic algorithm capable of optimizing molecular catalyst structures using well-suited fitness functions to achieve a set of targeted properties. The flexibility and generality of this tool are demonstrated with two examples: i) Ligand optimization and exploration for Ni-catalyzed aryl-ether cleavage manipulating SMILES and using a fitness function derived from molecular volcano plots, ii) multiobjective (i.e., activity/selectivity) optimization of bipyridine N.N'-dioxide Lewis basic organocatalysts for the asymmetric propargylation of benzaldehyde from 3D molecular fragments. We show that evolutionary optimization, enabled by NaviCatGA, is an efficient way of accelerating catalyst discovery that bypasses combinatorial scaling issues and incorporates compelling chemical constraints. application/zip application/zip text/markdown text/plain https://doi.org/10.24435/materialscloud:fz-sw oai:materialscloud.org:1223 mcid:2022.9 eng Materials Cloud https://doi.org/10.1002/cmtd.202100107 https://doi.org/10.5281/zenodo.5786559 https://zenodo.org/record/5786559#.Yebj5vso9hE https://archive.materialscloud.org/communities/mcarchive/ https://doi.org/10.24435/materialscloud:65-wa info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode homogeneous catalysis volcano plot catalysis optimization organocatalysis Genetic optimization of homogeneous catalysts info:eu-repo/semantics/other

oai:materialscloud.org:1778 2023-05-30T13:37:42Z openaire_data community-mcarchive

Bonfà, Pietro Onuorah, Ifeanyi John Bonfà, Pietro Onuorah, Ifeanyi John Lang, Franz Timrov, Iurii Monacelli, Lorenzo Wang, Chennan Sun, Xiao Petracic, Oleg Pizzi, Giovanni Marzari, Nicola Blundell, Stephen John De Renzi, Roberto 2023-05-30 Magnetostriction drives a rhombohedral distortion in the cubic rock salt antiferromagnet MnO at the Nèel temperature T<sub>N</sub>=118 K. As an unexpected consequence we show that this distortion acts to localize the site of an implanted muon due to the accompanying redistribution of electron density. This lifts the degeneracy between equivalent sites, resulting in a single observed muon precession frequency. Above T<sub>N</sub>, the muon instead becomes delocalized around a network of equivalent sites. Our first-principles simulations based on Hubbard-corrected density-functional theory and molecular dynamics are consistent with our experimental data and help to resolve a long-standing puzzle regarding muon data on MnO, as well as having wider applicability to other magnetic oxides. application/gzip text/markdown text/plain https://doi.org/10.24435/materialscloud:8s-qh oai:materialscloud.org:1778 mcid:2023.82 eng Materials Cloud https://doi.org/10.1103/PhysRevLett.132.046701 https://doi.org/10.48550/arXiv.2305.12237 https://archive.materialscloud.org/communities/mcarchive/ https://doi.org/10.24435/materialscloud:jr-m3 info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode Muon Spin Rotation, Relaxation and Resonance DFT+U+V Experimental molecular dynamics simulation MARVEL Magnetostriction-driven muon localisation in an antiferromagnetic oxide info:eu-repo/semantics/other

oai:materialscloud.org:1467 2022-09-14T16:02:13Z openaire_data community-mcarchive

Lei, Ting Li, Peiyun Shi, Junwei Huang, Zhen Lei, Yuqiu Lei, Ting 2022-09-14 High-performance n-type organic electrochemical transistors (OECTs) are essential for logic circuits and sensors. However, the performances of n-type OECTs lag far behind that of p-type ones. Conventional wisdom posits that the LUMO energy level dictates the n-type performance. Herein, we show that engineering the doped state is more critical for n-type OECT polymers. By balancing more charges to the donor moiety, we could effectively switch a p-type polymer to high-performance n-type material. Based on this concept, the polymer, P(gTDPP2FT), exhibits a record high n-type OECT performance with μC* of 54.8 F cm⁻¹ V⁻¹ s⁻¹, mobility of 0.35 cm² V⁻¹ s⁻¹, and response speed of τon/τoff = 1.75/0.15 ms. Calculations and comparison studies show that the conversion is primarily due to the more uniform charges, stabilized negative polaron, enhanced conformation, and backbone planarity at negatively charged states. Our work highlights the critical role of understanding and engineering polymers' doped states. application/zip application/zip application/zip application/zip application/zip text/markdown https://doi.org/10.24435/materialscloud:vs-79 oai:materialscloud.org:1467 mcid:2022.113 eng Materials Cloud https://doi.org/10.1038/s41467-022-33553-w https://www.ncbi.nlm.nih.gov/pubmed/36216813 https://doi.org/10.21203/rs.3.rs-1631706/v1 https://archive.materialscloud.org/communities/mcarchive/ https://doi.org/10.24435/materialscloud:ch-6s info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode n-type organic electrochemical transistor doped state engineering Switching p-type to high-performance n-type organic electrochemical transistors via doped state engineering info:eu-repo/semantics/other

oai:materialscloud.org:2723 2025-06-16T09:42:17Z openaire_data community-mcarchive

Fabbri, Emiliana Falqueto, Juliana Bruneli Panunzi, Anna Paola Duranti, Leonardo Di Bartolomeo, Elisabetta Huang, Jinzhen Borca, Camelia N. Huthwelker, Thomas Baster, Dominika El Kazzi, Mario Marelli, Marcello Fabbri, Emiliana Falqueto, Juliana Bruneli 2025-06-16 The use of perovskite oxides as bifunctional catalysts for oxygen electrocatalysis is a promising strategy for developing high-performance unified regenerative fuel cells (URFCs), thanks to their highly tunable structure. This work explores the exsolution of well-dispersed nanoparticles containing reduced Pt species from La<sub>0.6</sub>Sr<sub>0.4</sub>Fe<sub>0.95</sub>Pt<sub>0.05</sub>O<sub>3-δ</sub> (LSFPt) as an effective approach to design bifunctional catalysts for oxygen electrocatalysis. A 10 h reduction treatment at 500 °C in 5% H2/Ar promotes the exsolution of ~1.2 nm Pt-containing nanoparticles on the surface, increasing oxygen deficiency without compromising the perovskite structure. The resulting catalyst exhibits significantly improved activity for oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) in alkaline media, with over 2.5-fold performance improvement compared to the as-prepared LSFPt. Electrochemical impedance spectroscopy (EIS), combined with distribution of relaxation times (DRT) deconvolution analysis, revealed a notable decrease in medium-frequency resistance, indicating enhanced charge transfer at the electrode surface for OER and ORR. Post-mortem O K-edge spectra obtained by soft X-ray absorption spectroscopy in total electron yield mode further suggest an increased surface restructuring in the reduced LSFPt, attributed to the synergistic presence of surface defects and exsolved nanoparticles containing reduced Pt species. This one-step reduction protocol offers a promising strategy for designing efficient bifunctional electrocatalysts. application/zip text/markdown https://doi.org/10.24435/materialscloud:rj-dx oai:materialscloud.org:2723 mcid:2025.93 eng Materials Cloud https://archive.materialscloud.org/communities/mcarchive/ https://doi.org/10.24435/materialscloud:90-n1 info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode Pt exsolution unified regenerative fuel cells bifunctional electrocatalyst distribution of relaxation times DRT perovskite oxygen evolution reaction OER oxygen reduction reaction ORR Harnessing bifunctional oxygen electrocatalysis: Exsolved Pt nanoparticles from La_0.6Sr_0.4Fe_0.95Pt_0.05O_3-δ info:eu-repo/semantics/other

oai:materialscloud.org:2279 2026-01-26T22:01:21Z openaire_data community-mcarchive

Bonnet, Nicephore Marzari, Nicola Bonnet, Nicephore Marzari, Nicola 2025-05-26 A first-principles approach for calculating ion separation in solution through 2D membranes is proposed. Ionic energy profiles across the membrane are obtained first, where solvation effects are explicitly simulated by machine-learning molecular dynamics, electrostatic corrections are applied to remove finite-size capacitive effects, and a mean-field treatment of the electrochemical double layer charging is used. Entropic contributions are assessed analytically and through a thermodynamic integration scheme. Ionic separations are then inferred through a microkinetic model of the filtration process, accounting for steady-state charge separation effects across the membrane. The approach is applied to Li+, Na+, K+ sieving through a crown-ether functionalized graphene membrane, with a case study of the mechanisms for a highly selective and efficient extraction of lithium from aqueous solutions. This record contains the MD trajectories used to generate the energy and free energy profiles of Fig. 4. application/zip text/markdown https://doi.org/10.24435/materialscloud:mg-wh oai:materialscloud.org:2279 mcid:2025.85 eng Materials Cloud https://archive.materialscloud.org/communities/mcarchive/ https://doi.org/10.24435/materialscloud:zx-x4 info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode 2D membrane Ion sieving Machine learning Molecular dynamics Ion sieving in 2D membranes from first principles info:eu-repo/semantics/other .eJwlzN1qgzAYANB3-a6lJLFZ0bsFG2Gw2drus3pTgok_JFZRW4XSd9-g5wHOEyZjNIRkQ_huywj1-Ycf-IwH1INB1QZC5oFd1FhPED6hM7PSalaH0VTtCiH0qr3qEl4eTOXYO3dt_zeQsbvnbKVFjFXOgruOcatlQHXmbHSRtLh88WPGbdohyVktpBNdIkVurKMYz9HvuUHlhM26oTnb_edbQpa0OGaIlYrkKZXy8X0bFo0Of1izljcU8PoDTnFCkg.aur4wA.WFohJyfkxbsMOfRKizHWyRA2ZHE