jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Rasha Atwi | Matthew Bliss | Maxim A. Makeev | Nav Nidhi Rajput
Source: Research Square (preprint, 2022-04-04)
Field: Materials Science — Materials Chemistry

MISPR: An automated infrastructure for high-throughput DFT and MD simulations Abstract Computational tools provide a unique opportunity to study and design optimal materials by enhancing our ability to comprehend the connections between their atomistic structure and functional properties. However, designing materials with tailored functionalities is complicated due to the necessity to integrate various computational-chemistry software (not necessarily compatible with one another), the heterogeneous nature of the generated data, and the need to explore vast chemical and parameter spaces. The latter is especially important to avoid bias in scattered data points-based models and derive statistical trends only accessible by systematic datasets. Here, we introduce a robust high-throughput multi-scale computational infrastructure coined MISPR (Materials Informatics for Structure-Property Relationships) that seamlessly integrates classical molecular dynamics (MD) simulations with density functional theory (DFT). By enabling high-performance data analytics and coupling between different methods and scales, MISPR addresses critical challenges arising from the needs of automated workflow management and data provenance recording. The major features of MISPR include automated DFT and MD simulations, error handling, derivation of molecular and ensemble properties, and creation of output databases that organize results from individual calculations to enable reproducibility and transparency. In this work, we describe fully automated DFT workflows implemented in MISPR to compute various properties such as nuclear magnetic resonance chemical shift, binding energy, bond dissociation energy, and redox potential with support for multiple methods such as electron transfer and proton-coupled electron transfer reactions. The infrastructure also enables the characterization of large-scale ensemble properties by providing MD workflows that calculate a wide range of structural and dynamical properties in liquid solutions. MISPR employs the methodologies of materials informatics to facilitate understanding and prediction of phenomenological structure-property relationships, which are crucial to designing novel optimal materials for numerous scientific applications and engineering technologies. Computer science ; Workflow ; Density functional theory ; Software ; Computational science ; Chemistry ; Database ; Computational chemistry Machine Learning in Materials Science ; Scientific Computing and Data Management ; Research Data Management Practices
Authors: Степан Петрович Михайлов | Валентин Юрьевич Долуда | Mikhail G. Sulman | Валентина Геннадьевна Матвеева
Source: Вестник Тверского государственного университета Серия Химия (article, 2022-04-05)
Field: Chemistry — Organic Chemistry

CURRENT STATES OF REGENERATIVE AMINATION Процесс восстановительного аминирования лежит в основе полученная различных ценных химических веществ. Одним из важных классов таких химикатов являются N-содержащие функциональные соединения, которые можно применять в качестве исходного материала или растворителя для синтеза фармацевтических препаратов и агрохимикатов. В последние годы было проведено множество исследований по поиску наиболее активного и селективного гетерогенного катализатора реакции восстановительного аминирования. Настоящая обзорная статья посвящена изучению каталитического поведения различных гетерогенных катализаторов при восстановительном аминировании левулиновой кислоты и ее производного. Было проведено сравнение выходов пирролидона при аналогичных условиях реакции. В обзоре также рассматривалось проведение исследуемой реакции как в реакторах периодического действия, так и в проточных реакторах непрерывного действия. The process of reductive amination underlies the production of various valuable chemicals. One important class of such chemicals are N-containing functional compounds that can be used as a starting material or solvent for the synthesis of pharmaceuticals and agrochemicals. In recent years, many studies have been carried out to find the most active and selective heterogeneous catalyst for the reductive amination reaction. This review article is devoted to the study of the catalytic behavior of various heterogeneous catalysts in the reductive amination of levulinic acid and its derivative. The yields of pyrrolidone were compared under similar reaction conditions. The review also considered the performance of the reaction under study both in batch reactors and in continuous flow reactors. Reductive amination ; Amination ; Levulinic acid ; Chemistry ; Catalysis ; Organic chemistry ; Combinatorial chemistry Chemical Synthesis and Reactions ; Asymmetric Hydrogenation and Catalysis ; Chemical Synthesis and Analysis
Authors: Seleznev Vyacheslav | Nikolay Chukov
Source:  (article, 2022-01-01)
Field: Materials Science — Materials Chemistry

Physical and mechanical characteristics of basalt plastic reinforcement The paper studies physical and mechanical characteristics of the basalt-composite plastic reinforcement with different anchorage layers and compares it with the glass composite reinforcement. The influence of long-term extension strain on the basalt-composite reinforcement characteristics has been found. The prospects of the composite-basalt plastic reinforcement usage have been determined. There is a brief overview of the present-day polymer composite reinforcement applications. The paper considered both advantages and disadvantages of the glass composite reinforcement and suggested using the basalt plastic reinforcement. Physico-mechanical characteristics of the basalt plastic reinforcement in comparison with other types of polymer composite reinforcement and their changes due to technological features of basalt plastic reinforcement manufacturing have been studied. The influence of technological features of basalt-composite reinforcement on its performance parameters has been found. The study revealed the action of long-term extension strain (180 days at 22oC) — comprising 20, 40, 50, 69 % of the tensile strength at stretching of the basalt-composite reinforcement — upon the strength and tensile modulus at stretching of the 12 mm diameter basalt-composite reinforcement with the sand coating and spiral winding. Reinforcement ; Composite number ; Composite material ; Basalt ; Basalt fiber ; Materials science ; Ultimate tensile strength ; Geology Structural mechanics and materials ; Advanced Energy Technologies and Civil Engineering Innovations
Authors: Fenglin Deng | Hongyu Wu | Ri He | Peijun Yang | Zhicheng Zhong
Source: arXiv (Cornell University) (preprint, 2022-09-12)
Field: Materials Science — Materials Chemistry

Large-scale atomistic simulation of dislocation core structure in face-centered cubic metal with Deep Potential method The core structure of dislocations is critical to their mobility, cross slip, and other plastic behaviors. Atomistic simulation of the core structure is limited by the size of first-principles density functional theory (DFT) calculation and the accuracy of classical molecular dynamics with empirical interatomic potentials. Here, we utilize a Deep Potential (DP) method learned from DFT calculations to investigate the dislocations of face-centered cubic copper on a large scale and obtain their core structures and energies. The validity of the DP description of the core structure and elastic strain from dislocation is confirmed by a fully discrete Peierls model. Moreover, the DP method can be further extended easily to dislocations with defects such as surface or vacancy, and our study will pave a way in the large-scale atomistic simulation of dislocation on the DFT level. Cubic crystal system ; Dislocation ; Interatomic potential ; Materials science ; Molecular dynamics ; Vacancy defect ; Core (optical fiber) ; Density functional theory ; Atomic units ; Condensed matter physics ; Statistical physics ; Crystallography ; Physics ; Computational chemistry ; Chemistry Microstructure and mechanical properties ; Ion-surface interactions and analysis ; Machine Learning in Materials Science
Authors: Zhen Liu | Tetiana Zubatiuk | Adrián E. Roitberg | Olexandr Isayev
Source: ChemRxiv (preprint, 2022-09-12)
Field: Materials Science — Materials Chemistry

Auto3D: Automatic Generation of the Low-energy 3D Structures with ANI Neural Network Potentials Computational programs accelerate the chemical discovery processes but often need proper 3-dimensional molecular information as part of the input. Getting optimal molecular structures is challenging because it requires enumerating and optimizing a huge space of stereoisomers and conformers. We developed the Python-based Auto3D package for generating the low-energy 3D structures using SMILES as the input. Auto3D is based on state-of-the-art algorithms and can automatize the isomer enumeration and duplicate filtering process, 3D building process, geometry optimization and ranking process. Tested on 50 molecules with multiple unspecified stereocenters, Auto3D is guaranteed to find the stereo-configuration that yields the lowest-energy conformer. With Auto3D we provide an extension of the ANI model. The new model, dubbed ANI-2xt, is trained on a tautomer-rich dataset. ANI-2xt is benchmarked with DFT methods on geometry optimization, electronic and Gibbs free energy calculations. Compared with ANI-2x, ANI-2xt provides a 42% error reduction for tautomeric reaction energy calculations when using the gold-standard coupled-cluster calculation as the reference. ANI-2xt can accurately predict the energies and is several orders of magnitude faster than DFT methods. Python (programming language) ; Computer science ; Energy minimization ; Conformational isomerism ; Algorithm ; Tautomer ; Computational science ; Molecule ; Chemistry ; Computational chemistry ; Physics ; Quantum mechanics ; Stereochemistry Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Catalysis and Oxidation Reactions
Authors: Adedibu C. Tella | Adetola C. Oladipo | Victoria T. Olayemi | Allen T. Gordon | Adeniyi S. Ogunlaja | Lukman O. Alimi | Stephen P. Argent | Robert Mokaya | Guy J. Clarkson | Richard I. Walton
Source: Research Square (preprint, 2022-01-27)
Field: Chemistry — Inorganic Chemistry

Calcium coordination compounds of dipicolinic and quinolinic acids: synthesis, characterization, crystal structures and DFT studies Abstract In the past two decades various N-heterocyclic carboxylate coordination compounds have been synthesized with intriguing architectures and potential applications as functional materials. In this regard, two novel calcium coordination compounds [Ca(2,6-Hpdc) 2 (H 2 O) 2 ] 1 and [Ca 2 (2,3-pdc) 2 (H 2 O) 6 ] n 2 (where 2,6-H 2 pdc = 2,6-pyridinedicarboxylic acid and 2,3-H 2 pdc = 2,3-pyridinedicarboxylic acid) were grown at room temperature. The compounds were characterized using elemental analysis, Fourier Transform infrared (FT-IR) spectroscopy, thermogravimetric analysis, powder X-ray diffraction and single crystal X-ray crystallographic analysis. Compounds 1 and 2 crystallize in orthorhombic space group Pccn and monoclinic space group Pc , respectively. The structures of both compounds are stabilized by a network of hydrogen bonds arising from coordinated water molecules and carboxylate groups. Computational analysis revealed that compound 1 has a large energy gap (9.221 eV) suggesting high excitation energies and chemical hardness making it a better electron acceptor while compound 2 displayed a smaller energy gap (5.156 eV) which is indicative of a softer molecule with better polarizability and reactivity. Dipicolinic acid ; Quinolinic acid ; Calcium ; Characterization (materials science) ; Chemistry ; Materials science ; Biochemistry ; Nanotechnology ; Organic chemistry ; Biology ; Amino acid ; Botany Crystal structures of chemical compounds ; Metal-Organic Frameworks: Synthesis and Applications ; Organometallic Compounds Synthesis and Characterization
Authors: Anupama Roy | Sushil Kumar | Arun Sharma
Source: International Journal of Health Sciences (article, 2022-06-13)
Field: Chemistry — Organic Chemistry

Synthesis, structural investigation and molecular docking studies of pyridinyl tetrahydroisoquinoline, morpholine and piperidine containing schiff's bases The present work was conducted to synthesize some Schiff's bases derived from pyridinyl tetrahydroisoquinoline, morpholine and piperidine moieties by the condensation reaction of aminobenzaldehyde with various aromatic amines in good to excellent yield. The structures of synthesized compounds were confirmed by 1H NMR, 13C NMR and mass spectra (ESI-MS) data. These compounds also evaluated for their in silico anti-microbial properties by molecular docking studies. Docking studies were carried out by using Argus Lab 4.0.1 software. Morpholine ; Piperidine ; Chemistry ; Docking (animal) ; Tetrahydroisoquinoline ; Schiff base ; Yield (engineering) ; Combinatorial chemistry ; Organic chemistry ; Stereochemistry ; Materials science Inorganic and Organometallic Chemistry
Authors: Sabrina Diehn | Helmut Schlaad | Janina Kneipp
Source: ChemRxiv (preprint, 2022-07-22)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Multivariate Imaging for Fast Evaluation of in Situ Dark Field Microscopy Hyperspectral Data Dark field scattering microscopy can create large hyperspectral data sets that contain a wealth of information on the properties and the molecular environment of noble metal nanoparticles. For a quick screening of samples of microscopic dimensions that contain many different types of plasmonic nanostructures, we propose a multivariate analysis of data sets of thousands to sever-al hundreds of thousands of scattering spectra. By using non-negative matrix factorization for decomposing the spectra, components are identified that represent individual plasmon reso-nances and relative contributions of these resonances to particular microscopic focal volumes in the mapping data sets. Using data from silver and gold nanoparticles in the presence of different molecules, including gold nanoparticle-protein agglomerates or silver nanoparticles forming aggregates in the presence of acrylamide, plasmonic properties are observed that differ from those of the original nanoparticles. For the case of acrylamide we show that the plasmon reso-nances of the silver nanoparticles are ideally suited to support surface enhanced Raman scatter-ing (SERS) and the two-photon excited process of surface enhanced hyper Raman scattering (SEHRS). Both vibrational tools give complementary information on the in situ formed poly-acrylamide and the molecular composition at the nanoparticle surface. Hyperspectral imaging ; Plasmon ; Nanoparticle ; Raman scattering ; Materials science ; Silver nanoparticle ; Raman spectroscopy ; Dark field microscopy ; Plasmonic nanoparticles ; Microscopy ; Surface plasmon ; Scattering ; Colloidal gold ; Nanotechnology ; Optics ; Physics ; Optoelectronics ; Computer science Gold and Silver Nanoparticles Synthesis and Applications ; Optical Imaging and Spectroscopy Techniques ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Haoyong Yang | Qihao Sun | Zhongquan Liao | Mike Hambsch | Zhecheng Guo | Daheng Wu | Birgit Jost | Yuejun Zhang | Stefan C. B. Mannsfeld | Xinliang Feng | Xiaojian Zhu | Tao Zhang
Source: Research Square (preprint, 2022-11-22)
Field: Chemistry — Organic Chemistry

Microwave-assisted High-Throughput Synthesis of Crystalline Porphyrin-based Two-dimensional Polymers for Neuromorphic Vision Sensor Abstract Emulating the biological visual adaptation in machine vision systems typically requires a neuromorphic vision sensor system that exhibits biomimetic light intensity-dependent photoadaptation. Inspired by the biological counterpart, porphyrin-based two-dimensional polymers (p2DPs) are of high interest for adaptative sensor due to their atomic thinness and adjustable charge transfer and trapping under light irradiations. However, the high-throughput synthesis of highly crystalline p2DPs thin films for the device application remains a great challenge because of the slow nucleation and crystallization process in classical interfacial synthesis. Here, we report a microwave-assisted interfacial methodology for the rapid synthesis (~3 mins) of p2DP thin films. The resultant film displays a long-range ordered molecular structure with a lateral size of ~23 cm2 and large crystal domains of ~4 µm as well as controllable thickness (2-40 nm). The p2DP film was then used to fabricate a vision sensor which exhibits a biomimetic light intensity-dependent photoadaptation and habituation behavior. Furthermore, a machine visual system consisting of a 4×8 p2DP-sensor array is developed to implement adaptive image recognition under bright and dim light stimuli, showing an accuracy of over 90%. Neuromorphic engineering ; Porphyrin ; Throughput ; Materials science ; Nanotechnology ; Microwave ; Computer science ; Artificial intelligence ; Photochemistry ; Chemistry ; Telecommunications ; Artificial neural network Polydiacetylene-based materials and applications ; Conducting polymers and applications ; Gas Sensing Nanomaterials and Sensors
Authors: Patrick Taylor | G. J. Conduit
Source: arXiv (Cornell University) (preprint, 2022-12-13)
Field: Materials Science — Materials Chemistry

Machine learning superalloy microchemistry and creep strength from physical descriptors We propose an element-agnostic set of descriptors to model superalloy properties with Gaussian process regression. Furthermore, we develop a correction method to deliver the best and most physical predictions for microchemistry in multi-phase alloys. The models' performance in predictions is confirmed for superalloy microchemistry, microstructure, and strength properties. When including new, unseen elements in the test data, the models still give good predictions; such extrapolations into new chemical-space would be impossible with component-based descriptors. Superalloy ; Microchemistry ; Creep ; Microstructure ; Materials science ; Component (thermodynamics) ; Process (computing) ; Computer science ; Biological system ; Thermodynamics ; Metallurgy ; Chemistry ; Physics ; Chromatography Machine Learning in Materials Science ; Petroleum Processing and Analysis ; Crystallization and Solubility Studies
Authors: Susannah L. Scott
Source:  (article, 2022-06-18)
Field: Materials Science — Materials Chemistry

2022 Catalysis GRC/GRS: Advancing Sustainable Technologies Through Catalysis ParticipantsThe Conference was well-attended with 172 participants.Scientists from academia represented 80% of the participants while attendees from government accounted for 8% and those from industry totaled 12%.The meeting also attracted a strong mix of young investigators and senior scientists.Students and post-docs accounted for 33% of all attendees.Approximately 20% of the participants at the 2022 meeting were women. Seminar ParticipantsThe Conference was well-attended with 48 participants.Students and post docs combined accounted for 92% of all attendees.Approximately 27% of the participants at the 2022 seminar were women. Conference ProgramThe long-standing basis for chemical manufacturing has been thermal conversion of fossil carbon to useful building blocks, eventually leading to functional and structural materials that have enhanced our standard of living tremendously at an enormous energy cost.As researchers in this area look to the future, we begin to imagine what chemical manufacturing will look like without fossil carbon as its origin.What types of new feedstocks will be Catalysis ; Computer science ; Chemistry ; Nanotechnology ; Materials science ; Organic chemistry Machine Learning in Materials Science
Authors: Ghodsi Mohammadi Ziarani | Mahdieh Khademi | Fatemeh Mohajer | Alireza Badiei | Rajender S. Varma
Source: Ecological Chemistry and Engineering S (article, 2022-12-01)
Field: Chemistry — Organic Chemistry

The Synthesis of 2,2-BIS(1-INDOL-3-YL)Acenaphthylene-1(2)-Ones Using Nanocatalysis: Fluorescent Sensing for Cu<sup>2+</sup> Ions Abstract 2,2-bis(1H-indol-3-yl)acenaphthylene-1(2H)-ones were synthesised by the reaction of acenaphthenequinone and 2 equivalents of indole using Fe 3 O 4 @SiO 2 @Si-Pr-NH-CH 2 CH 2 NH 2 as the basic magnetic nanocatalyst, assembled under greener and sustainable conditions in high purity and yields. Furthermore, the photoluminescence properties of 2,2-bis(2-methyl-1H-indol-3-yl)acenaphthylene-1(2H)-one were exploited for the sensing of copper ions in the mixed solvent systems comprising H 2 O and CH 3 CN in excitation wavelength at 410 nm with a detection limit of 9.5 ∙ 10 –6 M. Acenaphthylene ; Fluorescence ; Detection limit ; Ion ; Photoluminescence ; Copper ; Chemistry ; Solvent ; Materials science ; Nuclear chemistry ; Photochemistry ; Analytical Chemistry (journal) ; Organic chemistry ; Physics ; Naphthalene ; Optoelectronics ; Chromatography Multicomponent Synthesis of Heterocycles ; Synthesis of Indole Derivatives ; Synthesis and Biological Evaluation
Authors: Bjarne Kreitz | Patrick Lott | Jongyoon Bae | Katrín Blöndal | Sofia Angeli | Zachary W. Ulissi | Felix Studt | C. Franklin Goldsmith | Olaf Deutschmann
Source: ChemRxiv (preprint, 2022-07-13)
Field: Materials Science — Materials Chemistry

Detailed microkinetics for the oxidation of exhaust gas emissions through automated mechanism generation Emissions from vehicles contain a variety of pollutants that must be either oxidized or reduced efficiently in the catalytic converter. Improvements to the catalyst require knowledge of the microkinetics, but the complexity of the exhaust gas mixture makes it challenging to identify the reaction network. This complexity was tackled by using the "Reaction Mechanism Generator" (RMG) to automatically generate microkinetic models for the oxidation of combustion byproducts from stoichiometric gasoline direct injection engines on Pt(111). The possibilities and the limitations encountered during the generation procedure are discussed in detail. A combination of first-principles-based mechanism construction and top-down parameter refinement allows to describe experimental results obtained by kinetic testing of a Pt/Al2O3 monolith under stoichiometric conditions. The study can serve as a blueprint for the usage of RMG for other challenging heterogeneously catalyzed reactions. Gasoline ; Exhaust gas ; Stoichiometry ; Process engineering ; Catalysis ; Monolith ; Mechanism (biology) ; Combustion ; Blueprint ; Computer science ; Reaction mechanism ; Chemistry ; Environmental science ; Chemical engineering ; Mechanical engineering ; Engineering ; Organic chemistry ; Physics Catalytic Processes in Materials Science ; Electrocatalysts for Energy Conversion ; Catalysis and Oxidation Reactions