jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Genshen Chu | Yang Li | Runchu Zhao | Shuai Ren | Wen Yang | Xinfu He | Chungjun Hu | Jue Wang
Source: arXiv (Cornell University) (preprint, 2021-07-16)
Field: Materials Science — Materials Chemistry

MD Simulation of Hundred-Billion-Metal-Atom Cascade Collision on Sunway Taihulight Radiation damage to the steel material of reactor pressure vessels is a major threat to the nuclear reactor safety. It is caused by the metal atom cascade collision, initialized when the atoms are struck by a high-energy neutron. The paper presents MISA-MD, a new implementation of molecular dynamics, to simulate such cascade collision with EAM potential. MISA-MD realizes (1) a hash-based data structure to efficiently store an atom and find its neighbors, and (2) several acceleration and optimization strategies based on SW26010 processor of Sunway Taihulight supercomputer, including an efficient potential table storage and interpolation method, a coloring method to avoid write conflicts, and double-buffer and data reuse strategies. The experimental results demonstrated that MISA-MD has good accuracy and scalability, and obtains a parallel efficiency of over 79% in an 655-billion-atom system. Compared with a state-of-the-art MD program LAMMPS, MISA-MD requires less memory usage and achieves better computational performance. Cascade ; Atom (system on chip) ; Supercomputer ; Scalability ; Molecular dynamics ; Chemistry ; Collision ; Parallel computing ; Computer science ; Metal ; Computational science ; Operating system ; Computational chemistry Nuclear Materials and Properties ; Fusion materials and technologies ; Nuclear reactor physics and engineering
Authors: L. Klochko
Source: theses.fr (ABES) (preprint, 2021-01-21)
Field: Chemistry — Spectroscopy

Propriétés viscoélastiques et corrélations dynamiques de la contrainte mécanique dans des systèmes modèles de polymères et colloïdes vitrifiables Dans le cadre de cette thèse, nous avons étudié et analysé comment les propriétés viscoélastiques et la gamme des corrélations structurelles et dynamiques dans les systèmes oligomères tridimensionnels et liquides simples bidimensionnels formant le verre changent au fur et à mesure qu'ils se vitrifient avec une température décroissante en utilisant des simulations de dynamique moléculaire (MD). Pour le système liquide polydispersé bidimensionnel formant le verre, un certain nombre de caractéristiques intéressantes pour l'état vitreux sont découvertes. Pour le régime liquide (bien au-dessus de Tg), nous avons constaté que la relation entre la compressibilité et le facteur de structure statique S(q) est fortement violée et que la capacité thermique cv(t) dépendante du temps implique une queue de loi de puissance de longue durée. En outre, pour des vecteurs d'ondes faibles q, le facteur de structure dynamique S(q,t) montre une relaxation en deux étapes bien au-dessus de la température de vitrification. Pour étudier plus directement la gamme spatiale des corrélations de contraintes pour ce système, nous avons analysé la fonction de corrélation du tenseur de contraintes à différents vecteurs d'onde en utilisant des simulations de dynamique moléculaire (MD). Viscoelasticity ; Materials science ; Stress (linguistics) ; Colloid ; Polymer ; Composite material ; Chemical engineering ; Engineering ; Philosophy Adsorption, diffusion, and thermodynamic properties of materials ; Structural Analysis of Composite Materials ; Advanced Theoretical and Applied Studies in Material Sciences and Geometry
Authors: Javier Díaz | Marco Pinna | A. V. Zvelindovsky | Ignacio Pagonabarraga
Source: Macromolecular Theory and Simulations (article, 2021-07-01)
Field: Materials Science — Materials Chemistry

Parallel Hybrid Simulations of Block Copolymer Nanocomposites using Coarray Fortran Computer simulations of experimentally comparable system sizes in Soft Matter often require considerable elapsed times. The use of many cores can reduce the needed time, ideally proportionally to the number of processors. In this paper a parallel computational method using Coarray Fortran is implemented and tested for large systems of purely block copolymer melts, as well as block copolymer nanocomposites. A satisfactory strong scaling is shown up to 512 cores while a weak scaling with a drop in performance is achieved up to 4096 cores. The scaling of the parallel cell dynamic simulations scheme displays no drawbacks over MPI and provides an example of the simplicity of the Coarray approach. The code has been tested on several architectures and compilers. The hybrid block copolymer/nanoparticle algorithm can achieve previously unavailable system sizes. Copolymer ; Fortran ; Nanocomposite ; Block (permutation group theory) ; Cover (algebra) ; Scale (ratio) ; Materials science ; Computer science ; Nanoparticle ; Polymer chemistry ; Parallel computing ; Computational science ; Nanotechnology ; Polymer ; Mathematics ; Physics ; Composite material ; Combinatorics ; Engineering ; Mechanical engineering Block Copolymer Self-Assembly ; Advanced Polymer Synthesis and Characterization ; Polymer Nanocomposites and Properties
Authors: Samuel Poncé | Francesco Macheda | Elena R. Margine | Nicola Marzari | Nicola Bonini | Feliciano Giustino
Source: Physical Review Research (preprint, 2021-10-08)
Field: Materials Science — Materials Chemistry

First-principles predictions of Hall and drift mobilities in semiconductors Carrier mobility is at the root of our understanding of electronic devices. We present a unified methodology for the parameter-free calculations of phonon-limited drift and Hall carrier mobilities in real materials within the framework of the Boltzmann transport equation. This approach enables accurate and parameter-free calculations of the intrinsic mobility and will find applications in the design of electronic devices under realistic conditions of strain and temperature. The methodology exploits a novel approach for incorporating the effect of long-range quadrupole fields in the electron-phonon scattering rates and capitalizes on a rigorous and efficient procedure for numerical convergence. The accuracy reached in this work allows us to assess the impact of common approximations employed in transport calculations, including the role of exchange and correlation functionals, spin-orbit coupling, pseudopotentials, Wannier interpolation, Brillouin-zone sampling, dipole and quadrupole corrections, and the relaxation-time approximation. We study diamond, silicon, GaAs, 3C-SiC, AlP, GaP, c-BN, AlAs, AlSb, and SrO, and find that our most accurate calculations predict Hall mobilities significantly larger than the experimental data in the case of SiC, AlAs, and GaP. We identify possible improvements to the theoretical and computational frameworks to reduce this discrepancy, and we argue that new experimental data are needed to perform a meaningful comparison, since almost all existing data are more than two decades old. By setting tight standards for reliability and reproducibility, the present work aims to facilitate validation and verification of data and software towards predictive calculations of transport phenomena in semiconductors. Semiconductor ; Statistical physics ; Condensed matter physics ; Boltzmann equation ; Brillouin zone ; Phonon ; Physics ; Materials science ; Computational physics ; Quantum mechanics Machine Learning in Materials Science ; Surface and Thin Film Phenomena ; Advancements in Semiconductor Devices and Circuit Design
Authors: Zachary Smith | Pratyush Tiwary
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-06-29)
Field: Materials Science — Materials Chemistry

Making high-dimensional molecular distribution functions tractable through Belief Propagation on Factor Graphs Molecular dynamics (MD) simulations provide a wealth of high-dimensional data at all-atom and femtosecond resolution but deciphering mechanistic information from this data is an ongoing challenge in physical chemistry and biophysics. Theoretically speaking, joint probabilities of the equilibrium distribution contain all thermodynamic information, but they prove increasingly difficult to compute and interpret as the dimensionality increases. Here, inspired by tools in probabilistic graphical modeling, we develop a factor graph trained through belief propagation that helps factorize the joint probability into an approximate tractable form that can be easily visualized and used. We validate the study through the analysis of the conformational dynamics of two small peptides with 5 and 9 residues. Our validations include testing the conditional dependency predictions through an intervention scheme inspired by Judea Pearl. Secondly we directly use the belief propagation based approximate probability distribution as a high-dimensional static bias for enhanced sampling, where we achieve spontaneous back-and-forth motion between metastable states that is up to 350 times faster than unbiased MD. We believe this work opens up useful ways to thinking about and dealing with high-dimensional molecular simulations. Factor graph ; Computer science ; Joint probability distribution ; Belief propagation ; Graphical model ; Probabilistic logic ; Curse of dimensionality ; Molecular dynamics ; Statistical physics ; Probability distribution ; Conditional probability distribution ; Conditional probability ; Theoretical computer science ; Algorithm ; Artificial intelligence ; Mathematics ; Chemistry ; Computational chemistry ; Physics ; Decoding methods Machine Learning in Materials Science ; Protein Structure and Dynamics ; Computational Drug Discovery Methods
Authors: Martin van Horn | Trond Saue | Nanna Holmgaard List
Source:  (preprint, 2021-10-27)
Field: Chemistry — Spectroscopy

Probing Chirality across the Electromagnetic Spectrum with the Full Semi-classical Light--Matter Interaction We present a formulation and implementation of anisotropic and isotropic electronic circular dichroism (ECD) using the full semi-classical light--matter interaction operator within a four-component relativistic framework. The account of both beyond-first-order light--matter interactions and relativistic effects allows us to investigate the ECD response across the electromagnetic spectrum from optical to X-ray wavelengths where relativistic selection rules and spatial field variations gain increasing importance. We consider the isotropic and oriented ECD across the valence, sulfur L- and K-edge transitions in the simplest disulfides, H2S2 and (CH3S)2, and evaluate the influence of the full interaction by comparing to a traditional truncated formulation in the Coulomb gauge (velocity representation). Additionally, we demonstrate that in the relativistic formalism it is possible to work in the velocity representation, hence keeping order-by-order gauge-origin invariance, contrary to multipolar gauge, yet being able to distinguish electric and magnetic multipole contributions. Going beyond a first-order treatment in the wave vector is mandatory in the higher-energy end of the soft X-ray region where the consequent intensity redistribution becomes significant. While the sulfur K-edge absorption spectrum is essentially unaffected by this redistribution, the signed differential counterpart is not: at least third-order contributions are required to describe the differential absorption profile that is otherwise overestimated by a factor of about two. Physics ; Multipole expansion ; Isotropy ; Coulomb ; Anisotropy ; Quantum electrodynamics ; Quantum mechanics ; Classical mechanics ; Computational physics ; Electron Molecular spectroscopy and chirality ; Spectroscopy and Quantum Chemical Studies ; Strong Light-Matter Interactions
Authors: Martin van Horn | Trond Saue | Nanna Holmgaard List
Source: ChemRxiv (preprint, 2021-10-24)
Field: Chemistry — Spectroscopy

Probing Chirality across the Electromagnetic Spectrum with the Full Semi-classical Light--Matter Interaction We present a formulation and implementation of anisotropic and isotropic electronic circular dichroism (ECD) using the full semi-classical light--matter interaction operator within a four-component relativistic framework. The account of both beyond-first-order light--matter interactions and relativistic effects allows us to investigate the ECD response across the electromagnetic spectrum from optical to X-ray wavelengths where relativistic selection rules and spatial field variations gain increasing importance. We consider the isotropic and oriented ECD across the valence, sulfur L- and K-edge transitions in the simplest disulfides, H2S2 and (CH3S)2, and evaluate the influence of the full interaction by comparing to a traditional truncated formulation in the Coulomb gauge (velocity representation). Additionally, we demonstrate that in the relativistic formalism it is possible to work in the velocity representation, hence keeping order-by-order gauge-origin invariance, contrary to multipolar gauge, yet being able to distinguish electric and magnetic multipole contributions. Going beyond a first-order treatment in the wave vector is mandatory in the higher-energy end of the soft X-ray region where the consequent intensity redistribution becomes significant. While the sulfur K-edge absorption spectrum is essentially unaffected by this redistribution, the signed differential counterpart is not: at least third-order contributions are required to describe the differential absorption profile that is otherwise overestimated by a factor of about two. Physics ; Isotropy ; Multipole expansion ; Coulomb ; Anisotropy ; Quantum electrodynamics ; Electromagnetic field ; Quantum mechanics ; Classical mechanics ; Computational physics ; Electron Molecular spectroscopy and chirality ; Spectroscopy and Quantum Chemical Studies ; Strong Light-Matter Interactions
Authors: Aswin Mohan | Shanitha Shaji | P. Sunitha | Shahanas Naisam | Nidhin Sreeku
Source: Research Square (preprint, 2021-04-22)
Field: Materials Science — Biomaterials

The Potentials of Calotropis procera against Filarial Elephantiasis: An in- silico approach Abstract Lymphatic filariasis is one of the major diseases that belong to the category of neglected tropical illness. Filarial nematodes are the cause of the disease and are transmitted to humans via blood-feeding arthropod vectors. Drugs such as Albendazole, Ivermectin and diethylcarbamazine are administered either individually or in combination to overcome the progress of the lymphatic filariasis. However, these drugs have some disadvantages like temporary hair loss, dizziness, nausea etc. The filarial parasites have multifunctional proteins including the Glutathione-s-transferase (GST) enzyme which plays a major role in detoxification of endogenous electrophilic compounds. This study aims at the identification of a natural molecule that has the potential to bind with the GST enzyme and thus interrupt the detoxification process within the filarial parasite, Brugia malayi. A medicinal plant Calotropis procera , owing to its anthelmintic properties was searched for the presence of potential phytocompounds. The phytocompounds were docked against the homology modeled GST enzyme using the MOE software. The results were screened and analyzed based on the Lipinski rule of 5. N-octanoate was the phytocompound obtained based on molecular docking, subjected to molecular dynamics. These results require further in vitro and in vivo validation to consider n-octanoate as a potential drug candidate for lymphatic filariasis treatment. Calotropis procera ; Elephantiasis ; In silico ; Filariasis ; Biology ; Procera ; Computational biology ; Medicine ; Immunology ; Traditional medicine ; Zoology ; Helminths ; Genetics Phytochemistry and Bioactive Compounds ; Phytochemistry and Bioactivity Studies ; Cynara cardunculus studies
Authors: Atsushi Ishikawa
Source:  (preprint, 2021-10-25)
Field: Materials Science — Materials Chemistry

Combining Generative Adversarial Network and First-Principles Based Microkinetics for Heterogeneous Catalyst Design Microkinetic analysis based on density functional theory (DFT) was combined with a generative adversarial network (GAN) to enable artificial proposal of heterogeneous catalysts based on the DFT-calculated dataset. The approach was applied to the NH3 formation reaction on Ru-Rh alloy surfaces as an example. The NH3 formation turnover frequency (TOF) was calculated by DFT-based microkinetics. Specifically, six elementary reactions (N2 dissociation, H2 dissociation, NHx (x = 1–3) formation, and NH3 desorption) were explicitly considered, and their reaction energies were evaluated by DFT. On the basis of TOF values and atomic compositions, new alloy surfaces were generated using the GAN. This approach successfully generated the surfaces not included in the initial dataset but have higher TOF values. The N2 dissociation reaction was more exothermic for the generated surfaces, leading to higher TOF. The present study shows that automatic improvement of catalyst materials is possible by using the iterative steps of DFT calculation and sample generation by GAN. Dissociation (chemistry) ; Density functional theory ; Catalysis ; Exothermic reaction ; Computer science ; Generative grammar ; Desorption ; Adsorption ; Chemistry ; Generative adversarial network ; Materials science ; Computational chemistry ; Physical chemistry ; Artificial intelligence ; Organic chemistry ; Deep learning Machine Learning in Materials Science ; Ammonia Synthesis and Nitrogen Reduction ; Hydrogen Storage and Materials
Authors: Kisoo Kwon | Jung‐Hyun Park | Kuhwan Jeong | Sunjae Lee | Hoshik Lee
Source:  (article, 2021-05-04)
Field: Materials Science — Materials Chemistry

LATENT OPTIMIZATION VARIATIONAL AUTOENCODER FOR CONDITIONAL MOLECULAR GENERATION Variational autoencoder (VAE) is a generation algorithm, consisting of an encoder and a decoder, and the latent variable from the encoder is used as the input of the decoder. VAE is widely used for image, audio and text generation tasks. In general, the training of VAE is at risk of posterior collapsing especially for long sequential data. To alleviate this, modified evidence lower bounds (ELBOs) were proposed. However, these approaches heuristically control training loss using a hyper-parameter, and it is not way to solve the fundamental problem of vanilla VAE. In this paper, we propose a method to insert an optimization step of the latent variable and alternately update the encoder and decoder of conditional VAE for maximizing ELBOs. In experiments, we applied the latent optimization VAE (LOVAE) on ZINC database, consisting of string representation of molecules, for the inverse molecular design. We showed that the proposed LOVAE achieves better performance than vanilla VAE in terms of ELBOs and molecular generation performance. In addition, the proposed method showed better performance in property satisfaction and property maximization tasks compared to existing works. Autoencoder ; Computer science ; Latent variable ; Encoder ; Encoding (memory) ; Representation (politics) ; Optimization problem ; Algorithm ; Artificial intelligence ; Set (abstract data type) ; Maximization ; String (physics) ; Pattern recognition (psychology) ; Mathematical optimization ; Mathematics ; Artificial neural network Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Advanced Chemical Sensor Technologies
Authors: Yoshihiro Osakabe | Akinori Asahara
Source: National Conference on Artificial Intelligence (article, 2021-01-01)
Field: Materials Science — Materials Chemistry

MatVAE: Independently Trained Nested Variational Autoencoder for Generating Chemical Structural Formula. Autoencoder ; Computer science ; Artificial intelligence ; Algorithm ; Mathematics ; Applied mathematics ; Pattern recognition (psychology) ; Artificial neural network Machine Learning in Materials Science ; Computational Drug Discovery Methods ; X-ray Diffraction in Crystallography
Authors: Sara Romeo Atance | Juan Viguera Diez
Source:  (article, 2021-01-01)
Field: Materials Science — Materials Chemistry

Towards molecular design with desired property profiles and 3D conformer generation using Deep Generative Models Generative grammar ; Property (philosophy) ; Conformational isomerism ; Computer science ; Artificial intelligence ; Chemistry ; Philosophy ; Epistemology ; Molecule Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Various Chemistry Research Topics
Authors: Christopher M. Bottoms | Tanguy Terlier | Gila E. Stein | Manolis Doxastakis
Source: Bulletin of the American Physical Society (article, 2021-03-18)
Field: Materials Science — Materials Chemistry

Probing ion diffusion in chemically amplified resists through experiments and atomistic simulations Catalyst diffusion is a critical component of the pattern formation process in chemically amplified resists (CARs). In this study, we used a concerted experimental and modeling effort to examine diffusion of an inert catalyst analogue (sodium triflate) in a hydroxystyrene-based ESCAP terpolymer resin. First, atomistic simulations at high temperatures reveal an order-of-magnitude enhancement of the Fickian diffusivity in the protected reactant versus the fully deprotected product, while time-of-flight secondary ion mass spectrometry (TOF-SIMS) measurements at temperatures near the glass transition show no appreciable differences. The data from simulations and experiments conform to a unified curve, enabling estimates of the Fickian diffusivity at relevant post-exposure bake (PEB) temperatures through extrapolation. Second, acid-catalyzed reaction kinetics were measured with Fourier-transform infrared spectroscopy and compared with reaction-diffusion models based on the estimated Fickian diffusivities. The initial kinetics in experiments is orders-of-magnitude faster than predictions, demonstrating that models of catalyst transport should capture effects beyond Fickian diffusion. Finally, the simulations examined ion-ion and polymer-ion interactions at the atomistic level, features that are difficult to probe by experimental investigations. These data show that ion pair clustering in the protected and deprotected materials is similar as temperature is reduced, and ion pair dynamics in both materials is dominated by interactions with hydroxystyrene repeat units. These trends explain the experimental observations that ion diffusion is similar in the protected and deprotected polymers. Fick's laws of diffusion ; Diffusion ; Thermal diffusivity ; Ion ; Chemical physics ; Chemistry ; Diffusion process ; Materials science ; Analytical Chemistry (journal) ; Thermodynamics ; Organic chemistry Block Copolymer Self-Assembly ; Advancements in Photolithography Techniques ; Ion-surface interactions and analysis
Authors: Manal F. Abou Taleb | Faten Ismail Abou El Fadl | Hanan A. Albalwi | Mohamed M. Ibrahim
Source: Research Square (preprint, 2021-03-22)
Field: Chemistry — Organic Chemistry

Radiation Induced Silver Nanoparticles in Ionically Crosslinked Alginate Beads for Efficient Catalytic Degradation of Basic Dye Degradation (telecommunications) ; Catalysis ; Nanoparticle ; Silver nanoparticle ; Chemical engineering ; Radiation ; Materials science ; Chemistry ; Nanotechnology ; Organic chemistry ; Optics ; Computer science Nanomaterials for catalytic reactions ; Advanced Nanomaterials in Catalysis