jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Evangelia Charvati | Huai Sun
Source: ChemRxiv (preprint, 2022-12-28)
Field: Chemistry — Physical and Theoretical Chemistry

Potential-Energy Surfaces Sampled in Cremer–Pople Coordinates and Represented by Common Force Field Functionals for Small-cyclic Molecules The complex conformations of the cyclic moieties impact the physical and chemical properties of the molecules. In this work, we chose 22 molecules of four-, five-, and six-membered rings and performed a thorough conformational sampling using Cremer-Pople coordinates. We sampled hundreds or thousand of conformational structures including all well-known and many less well-known conformers for each molecule. We tried to represent the potential energy surfaces (PESs) by fitting the data to common analytical force field functional forms. Although the general features of PESs can be described by the essential force field functional forms, the accuracy of representation can be improved remarkably by including the torsion-bond and torsion-angle coupling terms. The best fit yields R-squared (R2) values close to 1.0 and mean absolute errors (MAEs) in energy less than 0.3 kcal/mol. Force field (fiction) ; Conformational isomerism ; Molecule ; Dihedral angle ; Torsion (gastropod) ; Potential energy ; Chemistry ; Computational chemistry ; Chemical physics ; Physics ; Classical mechanics ; Quantum mechanics Crystallography and molecular interactions ; Chemical Thermodynamics and Molecular Structure ; Advanced Chemical Physics Studies
Authors: Felipe Bivort
Source:  (article, 2022-11-28)
Field: Chemistry — Spectroscopy

Towards a Machine Learning Prediction of Electronic Stopping Power The prediction of Electronic Stopping Power for general ions and targets is a problem that lacks a closed-form solution. While full approximate solutions from first principles exist for certain cases, the most general model in use is a pseudo-empirical model. This paper presents our advances towards creating predictive models that leverage state-of-the-art Machine Learning techniques. A key component of our approach is the training data selection. We show results that outperform or are on par with the current best pseudo-empirical Stopping Power model as quantified by the Mean Absolute Percentage Error metric. Leverage (statistics) ; Computer science ; Metric (unit) ; Stopping power ; Machine learning ; Artificial intelligence ; Early stopping ; Component (thermodynamics) ; Power (physics) ; Optimal stopping ; Key (lock) ; Selection (genetic algorithm) ; Mathematical optimization ; Artificial neural network ; Mathematics ; Engineering Mass Spectrometry Techniques and Applications
Authors: Michał Gocki | Agnieszka Jakubowska-Ciszek | Piotr Pruski
Source: Energies (article, 2022-12-27)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Comparative Analysis of a New Class of Symmetric and Asymmetric Supercapacitors Constructed on the Basis of ITO Collectors The paper presents the results of research on new electroconductive polymer materials, based on polypyrrole, for the different supercapacitor constructions, i.e., the symmetric and asymmetric constructions. All the supercapacitors considered contain ITO collectors. Measurements of the complex impedance frequency characteristics were performed for these elements using the electrochemical impedance spectroscopy (EIS) method. Selected fractional-order models, known from the literature, have been used to model the impedance of these elements. The Particle Swarm Optimization (PSO) algorithm was used to estimate the model parameters. Selected estimation results, their comparison, and conclusions are also presented in the paper. The type of active electrolyte component has the greatest impact on the shape of the impedance frequency characteristics. In most cases, the highest capacitance values and the smallest resistance values were obtained for asymmetric supercapacitors. Supercapacitor ; Capacitance ; Dielectric spectroscopy ; Electrical impedance ; Particle swarm optimization ; Electrolyte ; Polypyrrole ; Materials science ; Mathematics ; Mathematical optimization ; Electrochemistry ; Polymer ; Composite material ; Chemistry ; Electrode ; Electrical engineering ; Engineering Supercapacitor Materials and Fabrication ; Conducting polymers and applications ; Fuel Cells and Related Materials
Authors: Vladimir Kondratyev | Marian Dryzhakov | Timur Gimadiev | Dmitriy Slutskiy
Source: ChemRxiv (preprint, 2022-10-05)
Field: Materials Science — Materials Chemistry

Generative model based on junction tree variational autoencoder for HOMO value prediction and molecular optimisation In this work, we provide further development of the junction tree variational autoencoder (JT VAE) architecture in terms of implementation and application of the internal feature space of the model. Pretraining of JT VAE on a large dataset and further optimization with a regression model led to a latent space that can solve several tasks simultaneously: prediction, generation, and optimization. We use the ZINC database as a source of molecules for the JT VAE pretraining and the QM9 dataset with its HOMO values to show the application case. We evaluate our model on multiple tasks such as property (value) prediction, generation of new molecules with predefined properties, and structure modification toward the property. Across these tasks, our model shows improvements in generation and optimization tasks while preserving the precision of state-of-the-art models. Autoencoder ; Computer science ; Artificial intelligence ; Tree (set theory) ; Property (philosophy) ; Generative grammar ; Generative model ; Feature (linguistics) ; Machine learning ; Space (punctuation) ; Value (mathematics) ; Pattern recognition (psychology) ; Artificial neural network ; Mathematics Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Protein Structure and Dynamics
Authors: Mondal Santanu | Aher Ravindra D. | Bethi Venkati | Lin Yu-Ju | Taniguchi Tohru | Monde Kenji | Tanaka Fujie
Source: Institutional Repositories DataBase (IRDB) (article, 2022-02-28)
Field: Chemistry — Organic Chemistry

Control of Reactions of Pyruvates by Catalysts: Direct Enantioselective Mannich Reactions of Pyruvates Catalyzed by Amine-based Catalyst Systems Enantioselective Mannich reactions of pyruvates catalyzed by amine-based catalyst systems, in which pyruvates act as nucleophiles, are reported. The reactions of pyruvates and cyclic sulfonylimines afforded the desired Mannich products, including those bearing tetrasubstituted carbon centers, in high yields with high enantioselectivities in most cases. The selection of the acid used in the amine-based catalyst system was key for the formation of the Mannich products with high enantioselectivities. Catalysis ; Enantioselective synthesis ; Mannich reaction ; Reaction conditions ; Carbon fibers Asymmetric Synthesis and Catalysis ; Axial and Atropisomeric Chirality Synthesis ; N-Heterocyclic Carbenes in Organic and Inorganic Chemistry
Authors: L. Opeida | L. Volkova
Source: Visnyk of the Lviv University Series Chemistry (article, 2022-01-01)
Field: Chemistry — Organic Chemistry

On the limiting stage of oxidation of alkylarenes by potassium permanganate The first stage of hydrocarbon benzyl C–H bond oxidation with permanganate is considered. Using a thermochemical approach, three possible mechanisms of this stage are analyzed: electron transfer from hydrocarbon to oxidant, homolytic abstraction of H-atom from benzyl C–H bond, insertion of O-atom into benzyl C–H bond. The reaction enthalpies were used as a characteristic of the thermodynamic favorability of these reactions. The thermochemical characteristics of the species involved in oxidation reactions and the reaction enthalpies were calculated with the quantum chemical method PM7. It is the most accurate among the semi-empirical methods. The calculated reaction enthalpies of various oxidant species formed during the oxidation of the cumene with KMnO 4 showed that their reactivity increases in the series MnO 4 – &lt; HMnO 4 &lt; H 2 MnO 4 + &lt; MnO 3 + . It is established that the protonation of the oxidant species increases their reactivity both in homolytic reactions, where after the neutral H-atom abstraction free radical is formed, and in heterolytic ones, when electron or hydride ion transfer occurs. The obtained fact of increasing the reactivity of the species in oxidation reactions due to protonation explains the experimentally established significant effect of medium acidity on the rate of permanganate reactions with C–H bonds in hydrocarbon functionalization processes, and also provides understanding of the significant role of acidity in the oxidation of organic matter by permanganate. It should be noted that dehydration (removal of water molecule) of the oxidant species increases its reactivity in oxidation reactions. The results of the calculations of the enthalpies of the reactions show greater thermochemical favorability of hydride ion transfer reactions in comparison with reactions that proceed through homolysis of the C–H bond is shown. Keywords: potassium permanganate, oxidative functionalization, alkylarenes, PM7 method. Chemistry ; Reactivity (psychology) ; Homolysis ; Protonation ; Heterolysis ; Potassium permanganate ; Cumene ; Photochemistry ; Inorganic chemistry ; Permanganate ; Hydride ; Redox ; Organic chemistry ; Radical ; Benzene ; Catalysis ; Ion ; Metal Inorganic and Organometallic Chemistry ; Chemistry and Chemical Engineering ; Free Radicals and Antioxidants
Authors: Abhishek | Aniruddh Singh | Ashok Kumar | P.D. Sahare
Source: Journal of Atomic Molecular Condensed Matter and Nano Physics (article, 2022-06-30)
Field: Materials Science — Materials Chemistry

Effect of Nuclear Radiation Generated Thermal Spike on Degradation Reaction Kinetics of a Polymer SSNTD and Its Impact on Track Diameter It has been extensively studied that high polymer form an important group of materials used for solid state nuclear track detectors (SSNTD). The radiation induced damage not only leave tracks for microscopic examination but also change other physical properties of the material. One of them being the average molecular mass of the polymer. The change in this parameter which is induced by the radiation exposure can be studied and can give an estimate of the number of polymer chain scission, which has a direct influence on the track diameter and can give an estimate of the energy of radiation deposited inside the sample. From this the energy of the incoming particle flux can be calculated. In this paper a relationship between polymer degradation as given by the extent of the depolymerization reaction, the track diameter and energy of the incoming particle is sought. Polymer ; Radiation ; Depolymerization ; Materials science ; Nuclear track ; Chain scission ; Polymer degradation ; Particle (ecology) ; Track (disk drive) ; Degradation (telecommunications) ; Radiation damage ; Particle radiation ; Irradiation ; Nuclear physics ; Composite material ; Nuclear engineering ; Chemistry ; Polymer chemistry ; Optics ; Detector ; Physics ; Charged particle ; Organic chemistry Thermal and Kinetic Analysis ; Nuclear Physics and Applications ; Nuclear Materials and Properties
Authors: Yubo Liu | Xiaohong Chen | Yuhang Gao | Deng‐Guang Yu | Ping Liu
Source: Research Square (preprint, 2022-04-06)
Field: Materials Science — Biomaterials

Elaborate design of shell component for manipulating the sustained release behavior from core–shell nanofibres Abstract Background: The diversified combination of nanostructure and material has received considerable attention from researchers to exploit advanced functional materials. In drug delivery systems, the hydrophilicity and sustained–release drug properties are in opposition. Thus, difficulties remain in the simultaneous improve sustained–release drug properties and increase the hydrophilicity of materials. Methods: In this work, we proposed a modified triaxial electrospinning strategy to fabricate functional core–shell fibres, which could elaborate design of shell component for manipulating the sustained-release drug. Cellulose acetate (CA) was designed as the main polymeric matrix, whereas polyethylene glycol (PEG) was added as a hydrophilic material in the middle layer. Cur, as a model drug, was stored in the inner layer. Results: Scanning electron microscopy (SEM) results and transmission electron microscopy (TEM) demonstrated that the cylindrical F2–F4 fibres had a clear core–shell structure. The model drug Cur in fibres was verified in an amorphous form during the X-ray diffraction (XRD) patterns, and Fourier transformed infrared spectroscopy (FTIR) results indicated good compatibility with the CA matrix. The water contact angle test showed that functional F2–F4 fibres had a high hydrophilic property in 120 s and the control sample F1 needed over 0.5 h to obtain hydrophilic property. In the initial stage of moisture intrusion into fibres, the quickly dissolved PEG component guided the water molecules and rapidly eroded the internal structure of functional fibres. The good hydrophilicity of F2–F4 fibres brought relatively excellent swelling rate around 4600%. Blank outer layer of functional F2 fibres with 1% PEG created an exciting opportunity for providing a 96 h sustained-release drug profile, while F3 and F4 fibres with over 3% PEG provided a 12 h modified drug release profile to eliminate tailing–off effect. Conclusion: Here, the functional F2–F4 fibres had been successfully produced by using the advanced modified triaxial electrospinning nanotechnology with different polymer matrices. The simple strategy in this work has remarkable potential to manipulate hydrophilicity and sustained release of drug carriers, meantime it can also enrich the preparation approaches of functional nanomaterials. Materials science ; Fourier transform infrared spectroscopy ; Scanning electron microscope ; Polyethylene glycol ; Composite material ; Amorphous solid ; Chemical engineering ; Drug delivery ; Contact angle ; Transmission electron microscopy ; Swelling ; Nanotechnology ; Chemistry ; Organic chemistry Electrospun Nanofibers in Biomedical Applications ; Advanced Sensor and Energy Harvesting Materials ; Graphene and Nanomaterials Applications
Authors: Umit Volkan Ucak | Islambek Ashyrmamatov | Juyong Lee
Source: ChemRxiv (preprint, 2022-10-31)
Field: Materials Science — Materials Chemistry

Atom-in-SMILES tokenization Tokenization is an important preprocessing step in natural language processing that may have a significant influence on prediction quality. In this study we show that the conventional SMILES tokenization itself is at fault, resulting in tokens that fail to reflect the true nature of molecules. To address this we propose atom-in-SMILES approach, resolving the ambiguities in the genericness of SMILES tokens. Our findings in multiple translation tasks suggest that proper tokenization has a great impact on the prediction quality. Considering the prediction accuracy and token degeneration comparisons, atom-in-SMILES appears as an effective method to draw higher quality SMILES sequences out of AI-based chemical models than other tokenization schemes. We investigate the token degeneration, highlight its pernicious influence on prediction quality, quantify the token-level repetitions, and include generated examples for qualitative analysis. We believe that atom-in-SMILES tokenization can readily be utilized by the community at large, providing chemically accurate, tailor-made tokens for molecular prediction models. Lexical analysis ; Computer science ; Security token ; Natural language processing ; Preprocessor ; Artificial intelligence ; Quality (philosophy) ; Computer network ; Physics Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Machine Learning in Bioinformatics
Authors: Yenal Karaaslan
Source: Türk doğa ve fen dergisi :/Türk doğa ve fen dergisi (article, 2022-09-29)
Field: Materials Science — Materials Chemistry

Thermal Conductivity and Thermal Rectification in Various Sequences of Monolayer Hexagonal Boron Nitride/Aluminum Nitride Superlattice Nanoribbons In this study, the thermal transport properties for various geometries of monolayer h-BN/h-AlN superlattice nanoribbons are investigated using non-equilibrium molecular dynamics simulations. In this context, the lattice thermal conductivities of the superlattice nanoribbons are obtained for different period lengths, geometries, sample lengths, and temperatures. Results reveal that a decrease in the thermal conductivities of superlattice nanoribbons when compared with those of the pristine nanoribbons, the lattice thermal conductivities decrease with decreasing sample lengths and increasing temperatures, also the formation of the extremum points resulting from the competition between wave-like and particle-like phonon transport in the thermal conductivity of superlattice nanoribbons with the change of the period lengths. Moreover, superlattice nanoribbons with different geometries are created to connect the h-BN/h-AlN interface, and it is observed that there is a difference between the thermal conductivities calculated in the reverse directions. This difference leads to thermal rectification in the superlattice structures. As the asymmetry between thermal contact areas increases especially at low temperatures, it is found out the thermal rectification ratio increases. Superlattice ; Materials science ; Condensed matter physics ; Thermal conductivity ; Phonon ; Monolayer ; Graphene nanoribbons ; Rectification ; Boron nitride ; Nanotechnology ; Graphene ; Optoelectronics ; Composite material ; Thermodynamics ; Physics Thermal properties of materials ; Graphene research and applications ; Advanced Thermoelectric Materials and Devices
Authors: Emmanuel Ren | François‐Xavier Coudert
Source: ChemRxiv (preprint, 2022-12-12)
Field: Materials Science — Materials Chemistry

Rapid Adsorption Enthalpy Surface Sampling (RAESS) to Characterize Nanoporous Materials Molecular adsorption in nanoporous materials has many large-scale industrial applications ranging from separation to storage. To design the best materials, computational simulations are key in guiding the experimentation and engineering processes. Because nanoporous materials exist in a plethora of forms, we need to speed up the existing simulation tools to be able to screen databases of hundreds of thousands structures. Here, we describe a new algorithm that quickly calculates adsorption enthalpies by sampling the surface of the material instead of the whole porous space. This surface sampling has been tested on the CoRE MOF 2019 database and has been proven to be more than 2 orders of magnitude faster than the gold standard method (Widom insertion), with an acceptable level of error on the enthalpy value of 0.34 kJ/mol, and is therefore proposed as a valuable addition to the high-throughput screening toolbox. Nanoporous ; Adsorption ; Toolbox ; Sampling (signal processing) ; Enthalpy ; Porosity ; Materials science ; Computer science ; Surface (topology) ; Porous medium ; Nanotechnology ; Computational science ; Process engineering ; Thermodynamics ; Chemistry ; Physics ; Physical chemistry ; Mathematics ; Engineering ; Composite material Catalytic Processes in Materials Science ; Machine Learning in Materials Science ; Metal-Organic Frameworks: Synthesis and Applications
Authors: René Vernon
Source: ChemRxiv (preprint, 2022-11-15)
Field: Chemistry — Physical and Theoretical Chemistry

Hydrogen over helium: A philosophical position Hydrogen is troublesome in any periodic table classification. This being so it may as well be placed in a position that confers desirable attributes to the arrangement of the elements, while notionally recognising its lineage to the group 1 alkali metals and the group 17 halogens. Since the noble gases bridge the halogens and the alkali metals, and hydrogen encompasses the transition from the alkali metals to the halogens, there is more to the idea of hydrogen over helium. Halogen ; Alkali metal ; Hydrogen ; Helium ; Position (finance) ; Table (database) ; Inorganic chemistry ; Group (periodic table) ; Chemistry ; Materials science ; Organic chemistry ; Computer science ; Database History and advancements in chemistry
Authors: Jingru Lu | Irina Paci | David C. Leitch
Source: ChemRxiv (preprint, 2022-07-19)
Field: Chemistry — Organic Chemistry

A generally applicable quantitative reactivity model for nucleophilic aromatic substitution built from simple descriptors We report a multivariate linear regression model able to make accurate predictions for the rate and regioselectivity of nucleophilic aromatic substitution (SNAr) reactions based on the electrophile structure. This model uses a diverse training/test set from experimentally-determined relative SNAr rates between benzyl alcohol and 74 unique electrophiles, including heterocycles with multiple substitution patterns. There is a robust linear relationship between the experimental SNAr free energies of activation and three molecular descriptors that can be obtained computationally: the LUMO energy of the electrophile; the average molecular electrostatic potential (ESP) at the carbon undergoing substitution; and the sum of average ESP values for the ortho and para atoms relative to the reactive center. Despite using only simple descriptors calculated from ground state wavefunctions, this model demonstrates excellent correlation with previously measured SNAr reaction rates, and is able to accurately predict site selectivity for multihalogenated substrates: 91% prediction accuracy across 82 individual examples. The excellent agreement between predicted and experimental outcomes makes this easy-to-implement reactivity model a potentially powerful tool for synthetic planning. Nucleophilic aromatic substitution ; Chemistry ; Carbocation ; Regioselectivity ; Computational chemistry ; Electrophile ; Nucleophilic substitution ; Electrophilic aromatic substitution ; Organic chemistry Chemical Reaction Mechanisms ; Chemical Synthesis and Reactions ; Sulfur-Based Synthesis Techniques
Authors: Nafiseh Karimi | Jaber Jahanbin Sardroodi | Alireza Rastkar Ebrahimzadeh
Source: International Journal of Health Sciences (article, 2022-10-15)
Field: Materials Science — Materials Chemistry

Adsorption of SO2 air pollutant gas molecule on the pure and Al-doped graphene nano sheet: A DFT study The interaction of pure graphene nano sheet and Al-doped graphene nano sheet with SO2 pollutant gas molecules was examined by density functional theory (DFT). Adsorption energies and the transferred Mulliken charge were calculated. Doping Al on the graphene improved adsorption and electronic properties of graphene. Dos plots and HOMO-LUMO band gaps showed that pure graphene and Al-doped were semiconductor materials. The results revealed that sensitivity of graphene-based materials was enhanced by doping Al on the surface of pure graphene. Thus, Al-doped graphene was found to be a better detector of SO2 gas molecules. Graphene ; Materials science ; Adsorption ; Doping ; Density functional theory ; HOMO/LUMO ; Graphene nanoribbons ; Molecule ; Mulliken population analysis ; Semiconductor ; Bilayer graphene ; Nanotechnology ; Chemical physics ; Computational chemistry ; Physical chemistry ; Chemistry ; Organic chemistry ; Optoelectronics Graphene research and applications ; Gas Sensing Nanomaterials and Sensors ; 2D Materials and Applications