jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Giacomo Saielli | Luca Fusaro | Nikolay Tumanov | Johan Wouters | Vieri Fusi | Riccardo Montis
Source: ChemRxiv (preprint, 2022-04-01)
Field: Materials Science — Materials Chemistry

Applying Molecular Dynamics for the Search of New Frank-Kasper Phases of 4-aminopyridinium Chloride. In a previous crystallographic study on 4-aminopyridinium chloride, Frank-Kasper (FK) phases were serendipitously produced for the first time in a small organic molecule, showing that a simple organic salt can crystallise as hydrate phases of extraordinary complexity. These results raised questions on the mechanisms of formation of such phases, for instance, whether they arise from a specific pre-organization in the liquid state, probably following a non-classical nucleation path and, most importantly, opened discussions on whether this family of structures can be extended. Here we report the results from a classical molecular dynamics investigation aimed to give more insights on this matter. In particular, we modelled the thermal behaviour of an arbitrary FK phase of 4-aminopyridinium chloride prior the melting and after cooling the molten phase, exploring the mechanisms of dehydration of these phases and nucleation from the melt. The results, also confirmed by experiments, suggest that the dehydration of these phases can occur without dramatic changes in the crystal packing. This is also confirmed by simulating a stable anhydrous FK phase of 4-aminopyridinium chloride. Most importantly, molecular dynamics simulated by cooling the melt of this anhydrous phase, showed the formation of mainly two types of aggregates identical to those observed in the experimental crystal structures. These results confirm that other unknown FK structures might be obtained for our system, either from the melt or by dehydration of the known phases. Moreover, they provide further evidence that their crystallisation follows a non-classical path with a probable formation of two types of highly symmetric clusters that assemble into the solid-state only when the relative ratio of these reaches a threshold. Nucleation ; Crystallization ; Anhydrous ; Molecular dynamics ; Phase (matter) ; Crystal (programming language) ; Hydrate ; Chloride ; Chemistry ; Crystallography ; Thermodynamics ; Dehydration ; Chemical physics ; Computational chemistry ; Organic chemistry ; Physics Crystallization and Solubility Studies ; Thermodynamic properties of mixtures ; Ionic liquids properties and applications
Authors: Helen V. Thorbjørnsrud | Luca Bressan | Tamjidmaa Khatanbaatar | Manuel Carrer | Kathrin Würth-Roderer | Gabriele Cordara | Peter Kast | Michele Cascella | Ute Krengel
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2022-11-08)
Field: Materials Science — Materials Chemistry

What drives chorismate mutase to top performance? Insights from a combined <i>in silico</i> and <i>in vitro</i> study ABSTRACT Unlike typical chorismate mutases, the enzyme from Mycobacterium tuberculosis (MtCM) has only low activity on its own. Remarkably, its catalytic efficiency k cat / K m can be boosted more than 100-fold by complex formation with a partner enzyme. Recently, an autonomously fully active MtCM variant was generated using directed evolution, and its structure solved by X-ray crystallography. However, key residues were involved in crystal contacts, challenging the functional interpretation of the structural changes. Here, we address these challenges by microsecond molecular dynamics simulations, followed up by additional kinetic and structural analyses of selected sets of specifically engineered enzyme variants. A comparison of wild-type MtCM with naturally and artificially activated MtCMs revealed the overall dynamic profiles of these enzymes as well as key interactions between the C-terminus and the active site loop. In the artificially evolved variant of this model enzyme, this loop is pre-organized and stabilized by Pro52 and Asp55, two highly conserved residues in typical, highly active chorismate mutases. Asp55 stretches across the active site and helps to appropriately position active site residues Arg18 and Arg46 for catalysis. The role of Asp55 can be taken over by another acidic residue, if introduced at position 88 close to the C-terminus of MtCM, as suggested by MD simulations and confirmed by kinetic investigations of engineered variants. Active site ; Chorismate mutase ; In silico ; Enzyme ; Chemistry ; Mutase ; Protein Data Bank (RCSB PDB) ; Stereochemistry ; Residue (chemistry) ; Biochemistry ; Biosynthesis Enzyme Structure and Function ; Biochemical and Molecular Research ; Carbohydrate Chemistry and Synthesis
Authors: Marvin P. Bernhardt
Source:  (preprint, 2022-07-07)
Field: Chemistry — Spectroscopy

DosCalc: a parallelized tool to compute degree of freedom-separated density of states We introduce DosCalc, a computational tool for calculating the degree of freedom separated vibrational density of states (DoS). The rotational contribution is obtained from the angular velocity in the lab frame, principal axis frame, or an auxiliary frame. Using the Eckart formalism, the rotational-vibrational coupling DoS and the Coriolis term can also be calculated. We use software to measure the periodic flipping of molecules due to the tennis racket effect in water and propane in gas, liquid, and critical phase. We find significant differences between the behavior of the two molecules, especially in proximity to the critical point where propane shows the effect to a higher degree than water. Propane ; Formalism (music) ; Measure (data warehouse) ; Frame (networking) ; Principal axis theorem ; Degree (music) ; Racket ; Angular velocity ; Physics ; Classical mechanics ; Mathematics ; Computer science ; Thermodynamics ; Geometry ; Acoustics ; Data mining Spectroscopy and Laser Applications ; Advanced Chemical Physics Studies ; Atmospheric Ozone and Climate
Authors: Aditya Sakti | Nila Tanyela
Source:  (article, 2022-01-01)
Field: Chemistry — Physical and Theoretical Chemistry

Efficient Computational Chemistry Protocol Implementations for Chemical Research in Pandemic Situation During the COVID-19 pandemic situation, accessing a chemical laboratory becomes problematic. The issues emerge not only for experimentalists but also for computational chemists who require additional access to the computer hardware for maintenance purposes. As a result, a predictive computational ch Computer science ; Implementation ; Protocol (science) ; Pandemic ; Coronavirus disease 2019 (COVID-19) ; Computational model ; Data science ; Software engineering ; Simulation ; Medicine Various Chemistry Research Topics
Authors: Anthuan Ferino-Pérez | Queiroz Portorreal | Juan José Gamboa‐Carballo | Babak Minofar | Sarra Gaspard | Ulises Jäuregui‐Haza
Source: Research Square (preprint, 2022-08-29)
Field: Chemistry — Spectroscopy

Competitive formation of molecular inclusion complexes of chlordecone and β- hexachlorocyclohexane with natural cyclodextrins: DFT and Molecular Dynamics study Abstract The chlordecone (CLD) and β-hexachlorocyclohexane (β-HCH) are chlorinated pesticides that coexist as persistent organic pollutants in the groundwater of several countries in the Caribbean, being an environmental issue. This work theoretically evaluates the competitive formation of host-guest complexes pesticides@cyclodextrines (CDs) as an alternative for water purification and selective separation of pesticides. Quantum mechanical calculations based on Density Functional Theory (DFT) and classical molecular dynamics (MD) simulations were used to achieve information on geometries, energies, structure, and dynamics of guest-host complexes in the gas phase, implicit solvent medium, and in aqueous solutions. DFT studies showed that interactions of both pesticides with CDs are mediated by steric factors and guided by maximization of the hydrophobic interactions either with the other pesticide or with the CD cavity’s inner atoms. MD results corroborate the formation of stable complexes of both pesticides with the studied CDs. α-CD exhibited a preference for the smaller β-HCH molecule over the CLD that could not perturb the formed complex. The simulation of competitive formation with γ-CD illustrated that this molecule could accommodate both pesticides inside its cavity. These results suggest that CDs with smaller cavity sizes such as α-CD could be used for selective separation of β-HCH from CLD in water bodies while γ-CD could be used for methods that aim to remove both pesticides at the same time. Chemistry ; Hexachlorocyclohexane ; Molecular dynamics ; Pesticide ; Molecule ; Aqueous solution ; Computational chemistry ; Chemical physics ; Density functional theory ; Steric effects ; Physical chemistry ; Organic chemistry Analytical Chemistry and Chromatography ; Spectroscopy and Quantum Chemical Studies ; Surfactants and Colloidal Systems
Authors: Raffaela Cabriolu | Bruno G. Pollet | P. Ballone
Source: ChemRxiv (preprint, 2022-11-14)
Field: Materials Science — Materials Chemistry

The effect of organic ions on the formation and collapse ofnanometric bubbles in ionic liquid/water solutions: A molecular dynamics study Molecular dynamics simulation is applied to investigate the effect of two ionic liquids (IL) on the nucleation and growth of (nano-)cavities in water under tension and on the cavities’ collapse following the release of tension. Simulations of the same phenomena in two pure water samples of different sizes are carried out for comparison. The first IL, i.e., tetra-ethyl ammonium mesylate ([Tea][Ms]), is relatively hydrophilic and its addition to water at 25 wt% concentration decreases its tendency to nucleate cavities. Apart from quantitative details, cavity formation and collapse are similar to those taking place in water, and qualitatively follow the Rayleigh-Plesset (RP) equation. The second IL, i.e., tetrabutyl phosphonium 2,4-dimethylbenzene sulfonate ([P4444 ][DMBS]), is amphiphilic, and forms nanostructured solutions with water. At 25 wt% concentrations, [P4444 ][DMBS] favours the nucleation of bubbles, that tend to form at the interface between water-rich and IL-rich domains. Cavity collapse in [P4444 ][DMBS]/water solutions are greatly hindered by a shell of ions decorating the interface between the solution and the vapour phase. A similar effect is observed for the equilibration of a population of bubbles of different sizes. The drastic slowing down of bubbles’ relaxation processes suggests ways to produce long-lived nanometric cavities in the liquid phase that could be useful for nanotechnology and drug delivery. Nucleation ; Molecular dynamics ; Phosphonium ; Chemical physics ; Chemistry ; Phase (matter) ; Surface tension ; Ion ; Relaxation (psychology) ; Ionic liquid ; Chemical engineering ; Ionic bonding ; Materials science ; Thermodynamics ; Computational chemistry ; Organic chemistry ; Physics Pickering emulsions and particle stabilization ; Innovative Microfluidic and Catalytic Techniques Innovation ; Minerals Flotation and Separation Techniques
Authors: Benjamin Helmich‐Paris
Source: The Journal of Chemical Physics (article, 2022-05-04)
Field: Chemistry — Organic Chemistry

A trust-region augmented Hessian implementation for state-specific and state-averaged CASSCF wave functions In this work, we present a one-step second-order converger for state-specific (SS) and state-averaged (SA) complete active space self-consistent field (CASSCF) wave functions. Robust convergence is achieved through step restrictions using a trust-region augmented Hessian (TRAH) algorithm. To avoid numerical instabilities, an exponential parameterization of variational configuration parameters is employed, which works with a nonredundant orthogonal complement basis. This is a common approach for SS-CASSCF and is extended to SA-CASSCF wave functions in this work. Our implementation is integral direct and based on intermediates that are formulated in either the sparse atomic-orbital or small active molecular-orbital basis. Thus, it benefits from a combination with efficient integral decomposition techniques, such as the resolution-of-the-identity or the chain-of-spheres for exchange approximations. This facilitates calculations on large molecules, such as a Ni(II) complex with 231 atoms and 5154 basis functions. The runtime performance of TRAH-CASSCF is competitive with the other state-of-the-art implementations of approximate and full second-order algorithms. In comparison with a sophisticated first-order converger, TRAH-CASSCF calculations usually take more iterations to reach convergence and, thus, have longer runtimes. However, TRAH-CASSCF calculations still converge reliably to a true minimum even if the first-order algorithm fails. Hessian matrix ; Wave function ; Complete active space ; Convergence (economics) ; Parametrization (atmospheric modeling) ; State (computer science) ; Basis (linear algebra) ; Field (mathematics) ; Computer science ; Algorithm ; Mathematics ; Applied mathematics ; Physics ; Quantum mechanics ; Molecular orbital ; Molecule ; Geometry ; Pure mathematics Synthesis and Properties of Aromatic Compounds ; Advanced Chemical Physics Studies ; Photoreceptor and optogenetics research
Authors: Matteo Vandelli | Josef Kaufmann | M El-Nabulsi | Viktor Harkov | A. I. Lichtenstein | Е. А. Степанов
Source: SciPost Physics (article, 2022-08-26)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Multi-band D-TRILEX approach to materials with strong electronic correlations We present the multi-band dual triply irreducible local expansion (D-TRILEX) approach to interacting electronic systems and discuss its numerical implementation. This method is designed for a self-consistent description of multi-orbital systems that can also have several atoms in the unit cell. The current implementation of the D-TRILEX approach is able to account for the frequency- and channel-dependent long-ranged electronic interactions. We show that our method is accurate when applied to small multi-band systems such as the Hubbard-Kanamori dimer. Calculations for the extended Hubbard, the two-orbital Hubbard-Kanamori, and the bilayer Hubbard models are also discussed. Hubbard model ; Physics ; Electronic structure ; Condensed matter physics ; Electronic systems ; Superconductivity ; Electronic engineering Organic and Molecular Conductors Research ; Physics of Superconductivity and Magnetism ; Inorganic Fluorides and Related Compounds
Authors: 敦之 石川 | Atsushi Ishikawa
Source: Institutional Repositories DataBase (IRDB) (article, 2022-07-01)
Field: Materials Science — Materials Chemistry

Heterogeneous catalyst design by generative adversarial network and first-principles based microkinetics Abstract Microkinetic analysis based on density functional theory (DFT) was combined with a generative adversarial network (GAN) to enable the artificial proposal of heterogeneous catalysts based on the DFT-calculated dataset. The approach was applied to the NH 3 formation reaction on Rh−Ru alloy surfaces as an example. The NH 3 formation turnover frequency (TOF) was calculated by DFT-based microkinetics. Six elementary reactions, namely, N 2 dissociation, H 2 dissociation, NH x ( x = 1–3) formation, and NH 3 desorption, were explicitly considered, and their reaction energies were evaluated by DFT calculations. Based on the TOF values and atomic compositions, new alloy surfaces were generated using the GAN. This approach successfully generated the surfaces that were not included in the initial dataset but exhibited higher TOF values. The N 2 dissociation reaction was more exothermic for the generated surfaces, leading to higher TOF. The present study demonstrates that the automatic improvement of catalyst materials is possible using DFT calculations and GAN sample generation. Exothermic reaction ; Density functional theory ; Catalysis ; Generative adversarial network ; Generative grammar ; Dissociation (chemistry) ; Adversarial system Machine Learning in Materials Science ; Catalysis and Oxidation Reactions ; Electrocatalysts for Energy Conversion
Authors: 陽介 松田 | Yosuke Matsuda | 真一 大川原 | Shinichi Ookawara | 知輝 保田 | Tomoki Yasuda | 史郎 吉川 | Shiro Yoshikawa | 秀行 松本 | Hideyuki Matsumoto
Source: Institutional Repositories DataBase (IRDB) (article, 2022-09-01)
Field: Materials Science — Materials Chemistry

Framework for discovering porous materials: Structural hybridization and Bayesian optimization of conditional generative adversarial network Generative grammar ; Adversarial system ; Bayesian probability ; Bayesian network ; Key (lock) ; Pattern recognition (psychology) ; Conditional probability Machine Learning in Materials Science ; Generative Adversarial Networks and Image Synthesis ; Topology Optimization in Engineering
Authors: M. Wróbel | A. Burbelko
Source: Archives of Foundry Engineering (article, 2022-09-19)
Field: Chemistry — Spectroscopy

Impact of Values of Diffusion Coefficient on Results of Diffusion Modelling Driven by Chemical Potential Gradient In the paper critical role of including the right material parameters, as input values for computer modelling, is stressed. The presented model of diffusion, based on chemical potential gradient, in order to perform calculations, requires a parameter called mobility, which can be calculated using the diffusion coefficient. When analysing the diffusion problem, it is a common practice to assume the diffusion coefficient to be a constant within the range of temperature and chemical composition considered. By doing so the calculations are considerably simplified at the cost of the accuracy of the results. In order to make a reasoned decision, whether this simplification is desirable for particular systems and conditions, its impact on the accuracy of calculations needs to be assessed. The paper presents such evaluation by comparing results of modelling with a constant value of diffusion coefficient to results where the dependency of Di on temperature, chemical composition or both are added. The results show how a given deviation of diffusivity is correlated with the change in the final results. Simulations were performed in a single dimension for the FCC phase in Fe-C, Fe-Si and Fe-Mn systems. Different initial compositions and temperature profiles were used. Diffusion ; Materials science ; Potential gradient ; Effective diffusion coefficient ; Concentration gradient ; Thermodynamics ; Mechanics ; Statistical physics ; Biochemical engineering ; Engineering Adsorption, diffusion, and thermodynamic properties of materials ; Coal and Coke Industries Research ; Catalysis and Oxidation Reactions
Authors: Costas Kiparissides | Athina Vasileiadou | Filippos F. Karageorgos
Source: SSRN Electronic Journal (article, 2022-01-01)
Field: Chemistry — Organic Chemistry

Model-Based Optimization of Drug Release Rate from a Size Distributed Population of Biodegradable Polymer Carriers Drug ; Polymer ; Population ; Drug carrier ; Biodegradable polymer ; Materials science ; Chemical engineering ; Pharmacology ; Medicine ; Composite material ; Engineering Advanced Polymer Synthesis and Characterization ; 3D Printing in Biomedical Research ; Innovative Microfluidic and Catalytic Techniques Innovation
Authors: Jiaxin Zhang | Sirui Bi | Victor S.C. Fung
Source: arXiv (Cornell University) (preprint, 2022-12-02)
Field: Materials Science — Materials Chemistry

Accelerating Inverse Learning via Intelligent Localization with Exploratory Sampling In the scope of "AI for Science", solving inverse problems is a longstanding challenge in materials and drug discovery, where the goal is to determine the hidden structures given a set of desirable properties. Deep generative models are recently proposed to solve inverse problems, but these currently use expensive forward operators and struggle in precisely localizing the exact solutions and fully exploring the parameter spaces without missing solutions. In this work, we propose a novel approach (called iPage) to accelerate the inverse learning process by leveraging probabilistic inference from deep invertible models and deterministic optimization via fast gradient descent. Given a target property, the learned invertible model provides a posterior over the parameter space; we identify these posterior samples as an intelligent prior initialization which enables us to narrow down the search space. We then perform gradient descent to calibrate the inverse solutions within a local region. Meanwhile, a space-filling sampling is imposed on the latent space to better explore and capture all possible solutions. We evaluate our approach on three benchmark tasks and two created datasets with real-world applications from quantum chemistry and additive manufacturing, and find our method achieves superior performance compared to several state-of-the-art baseline methods. The iPage code is available at https://github.com/jxzhangjhu/MatDesINNe. Computer science ; Gradient descent ; Initialization ; Benchmark (surveying) ; Inference ; Invertible matrix ; Bayesian optimization ; Inverse problem ; Inverse ; Sampling (signal processing) ; Artificial intelligence ; Mathematical optimization ; Algorithm ; Machine learning ; Theoretical computer science ; Artificial neural network ; Mathematics Machine Learning in Materials Science ; Generative Adversarial Networks and Image Synthesis ; Gaussian Processes and Bayesian Inference
Authors: Badreddine Hatimi | A. Loudiki | J. Mouldar | Houyem Hafdi | Meryem Bensemlali | Abdellatif Aarfane | Hamid Nasrellah | M.A. El Mhammedi | M. Bakasse
Source: SSRN Electronic Journal (article, 2022-01-01)
Field: Chemistry — Inorganic Chemistry

Pyrrhotite Ash Waste-Based Catechin-Iron Complex for Ry 145 Adsorption: Rsm Optimization, Isotherm and Kinetic Study Adsorption ; Catechin ; Response surface methodology ; Kinetic energy ; Chemistry ; Pyrrhotite ; Waste management ; Metallurgy ; Nuclear chemistry ; Materials science ; Chromatography ; Mineralogy ; Organic chemistry ; Polyphenol ; Engineering ; Pyrite ; Physics Pigment Synthesis and Properties ; Adsorption and biosorption for pollutant removal ; Minerals Flotation and Separation Techniques
Authors: Xiaomi Guo | Lincan Fang | Yong Xu | Wenhui Duan | Patrick Rinke | Milica Todorović | Xi Chen
Source: arXiv (Cornell University) (preprint, 2022-03-26)
Field: Materials Science — Materials Chemistry

Molecular conformer search with low-energy latent space Identifying low-energy conformers with quantum mechanical accuracy for molecules with many degrees of freedom is challenging. In this work, we use the molecular dihedral angles as features and explore the possibility of performing molecular conformer search in a latent space with a generative model named variational auto-encoder (VAE). We bias the VAE towards low-energy molecular configurations to generate more informative data. In this way, we can effectively build a reliable energy model for the low-energy potential energy surface. After the energy model has been built, we extract local-minimum conformations and refine them with structure optimization. We have tested and benchmarked our low-energy latent-space (LOLS) structure search method on organic molecules with $5-9$ searching dimensions. Our results agree with previous studies. Conformational isomerism ; Dihedral angle ; Space (punctuation) ; Energy (signal processing) ; Potential energy surface ; Energy minimization ; Computer science ; Degrees of freedom (physics and chemistry) ; Potential energy ; Quantum ; Statistical physics ; Molecule ; Biological system ; Physics ; Artificial intelligence ; Computational chemistry ; Chemistry ; Classical mechanics ; Quantum mechanics Machine Learning in Materials Science ; Protein Structure and Dynamics ; Mass Spectrometry Techniques and Applications