jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Daniel Massey | Christopher D. Williams | Junju Mu | Andrew J. Masters | Ryuhei Motokawa | Noboru Aoyagi | Yuki Ueda | Mark R. Antonio
Source: The Journal of Physical Chemistry B (article, 2023-02-23)
Field: Chemistry — Inorganic Chemistry

Hierarchical Aggregation in a Complex Fluid─The Role of Isomeric Interconversion There is an ever-increasing body of evidence that metallic complexes involving amphiliphic ligands do not form normal solutions in organic solvents. Instead, they form complex fluids with intricate structures. For example, the metallic complexes may aggregate into clusters, and these clusters themselves may aggregate into superclusters. To gain a deeper insight into the mechanisms at play, we have used an improved force field to conduct extensive molecular dynamics simulations of a system composed of zirconium nitrate, water, nitric acid, tri-<i>n</i>-butyl phosphate, and <i>n</i>-octane. The important new finding is that a dynamic equilibrium between the cis and trans isomers of the metal complex is likely to play a key role in the aggregation behavior. The isolated cis and trans isomers have similar energies, but simulation indicates that the clusters consist predominantly of cis isomers. With increasing metal concentration, we hypothesize that more clustering occurs and the chemical equilibrium shifts toward the cis isomer. It is possible that such isomeric effects play a role in the liquid-liquid extraction of other species and the inclusion of such effects in flow sheet modeling may lead to a better description of the process. Chemistry ; Molecular dynamics ; Metal ; Cis–trans isomerism ; Octane ; Chemical physics ; Aggregate (composite) ; Computational chemistry ; Stereochemistry ; Organic chemistry ; Nanotechnology ; Materials science Radioactive element chemistry and processing ; Chemical and Physical Properties in Aqueous Solutions ; Spectroscopy and Quantum Chemical Studies
Authors: Meenakshi Rana | Pooja Yadav | Shradha Lakhera | Papia Chowdhury
Source: Research Square (preprint, 2023-01-16)
Field: Chemistry — Organic Chemistry

Ivermectin and Doxycycline Combination as a Promising Anti-Viral Drug Candidate: An in-silico and DFT Study Abstract In the present study, we have described how by using molecular docking and molecular dynamic (MD) simulation studies the combination drug of Ivermectin and Doxycycline can be used as an anti-viral agent. Various possibilities for individual and combination drugs have been explored by medical practitioners/scientists for the remedial purpose of viral infections. 3CL pro is the main protease of the virus which plays an essential role in mediating viral replication in the human body. 3CL pro protein can serve as an attractive drug target. In this work, we have studied drug: 3CL pro interactions by in silico molecular docking and MD simulation approaches. Density functional theory was used to establish the chemical reactivity of the drugs individually and in combination. Molecular electrostatic potential (MEP) surfaces and Mulliken charge distribution were used to identify the electrophilic and nucleophilic moieties within the drugs. Common and easily available antiviral drugs Ivermectin, Doxycycline, and their combination have proved their valid candidature to be used as potential drug candidates against infections caused by 3CL pro . In silico ; Doxycycline ; Ivermectin ; Drug ; Computational biology ; Docking (animal) ; Pharmacology ; Chemistry ; Biology ; Medicine ; Genetics ; Antibiotics ; Gene ; Veterinary medicine Synthesis and Biological Evaluation
Authors: Massimiliano Aschi | Laura Palombi | Andrea Amadei
Source: Molecules (article, 2023-04-20)
Field: Chemistry — Spectroscopy

Theoretical–Computational Modeling of CD Spectra of Aqueous Monosaccharides by Means of Molecular Dynamics Simulations and Perturbed Matrix Method The electronic circular dichroism (ECD) spectra of aqueous d-glucose and d-galactose were modeled using a theoretical-computational approach combining molecular dynamics (MD) simulations and perturbed matrix method (PMM) calculations, hereafter termed MD-PMM. The experimental spectra were reproduced with a satisfactory accuracy, confirming the good performances of MD-PMM in modeling different spectral features in complex atomic-molecular systems, as already reported in previous studies. The underlying strategy of the method was to perform a preliminary long timescale MD simulation of the chromophore followed by the extraction of the relevant conformations through essential dynamics analysis. On this (limited) number of relevant conformations, the ECD spectrum was calculated via the PMM approach. This study showed that MD-PMM was able to reproduce the essential features of the ECD spectrum (i.e., the position, the intensity, and the shape of the bands) of d-glucose and d-galactose while avoiding the rather computationally expensive aspects, which were demonstrated to be important for the final outcome, such as (i) the use of a large number of chromophore conformations; (ii) the inclusion of quantum vibronic coupling; and (iii) the inclusion of explicit solvent molecules interacting with the chromophore atoms within the chromophore itself (e.g., via hydrogen bonds). Chromophore ; Molecular dynamics ; Chemistry ; Aqueous solution ; Computational chemistry ; Molecule ; Spectral line ; Hydrogen bond ; Matrix (chemical analysis) ; Chemical physics ; Physical chemistry ; Physics ; Quantum mechanics ; Photochemistry ; Organic chemistry Molecular spectroscopy and chirality ; Spectroscopy and Quantum Chemical Studies ; Photoreceptor and optogenetics research
Authors: Süleyman Selim Çınaroğlu | Philip C. Biggin
Source: Journal of Chemical Information and Modeling (article, 2023-09-28)
Field: Chemistry — Physical and Theoretical Chemistry

Computed Protein–Protein Enthalpy Signatures as a Tool for Identifying Conformation Sampling Problems Understanding the thermodynamic signature of protein-peptide binding events is a major challenge in computational chemistry. The complexity generated by both components possessing many degrees of freedom poses a significant issue for methods that attempt to directly compute the enthalpic contribution to binding. Indeed, the prevailing assumption has been that the errors associated with such approaches would be too large for them to be meaningful. Nevertheless, we currently have no indication of how well the present methods would perform in terms of predicting the enthalpy of binding for protein-peptide complexes. To that end, we carefully assembled and curated a set of 11 protein-peptide complexes where there is structural and isothermal titration calorimetry data available and then computed the absolute enthalpy of binding. The initial "out of the box" calculations were, as expected, very modest in terms of agreement with the experiment. However, careful inspection of the outliers allows for the identification of key sampling problems such as distinct conformations of peptide termini not being sampled or suboptimal cofactor parameters. Additional simulations guided by these aspects can lead to a respectable correlation with isothermal titration calorimetry (ITC) experiments (<i>R</i><sup>2</sup> of 0.88 and an RMSE of 1.48 kcal/mol overall). Although one cannot know prospectively whether computed ITC values will be correct or not, this work shows that if experimental ITC data are available, then this in conjunction with computed ITC, can be used as a tool to know if the ensemble being simulated is representative of the true ensemble or not. That is important for allowing the correct interpretation of the detailed dynamics of the system with respect to the measured enthalpy. The results also suggest that computational calorimetry is becoming increasingly feasible. We provide the data set as a resource for the community, which could be used as a benchmark to help further progress in this area. Isothermal titration calorimetry ; Enthalpy ; Chemistry ; Outlier ; Calorimetry ; Peptide ; Molecular dynamics ; Biological system ; Thermodynamics ; Computational chemistry ; Computer science ; Physics ; Artificial intelligence ; Physical chemistry ; Biochemistry thermodynamics and calorimetric analyses ; Protein Structure and Dynamics ; Computational Drug Discovery Methods
Authors: Wei Xu | Jiajun Shen | Han Chen | Ruifeng He | Xinlong Song | Zeming Xia | Lan Ma | Jingyao Song
Source: SID Symposium Digest of Technical Papers (article, 2023-06-01)
Field: Materials Science — Materials Chemistry

P‐104: Graph‐Based AI Workflow for OLED Materials Discovery Artificial Intelligence (AI) is becoming an emerging technique in scientific research including novel materials discovery. In this work, we present a novel graph‐based AI workflow for discovering Organic Light‐Emitting Diode (OLED) materials. This workflow contains two graph‐based AI models: a molecular structure generative model and a molecular property predictive model. The target materials here are Red‐Prime (RP) materials, which are widely used to pair with the red light emitters in OLED devices. Based on the desired properties required by our OLED devices, we apply the AI‐based workflow to perform high‐ throughput screening for RP materials. Several novel and potential RP molecules are discovered preliminarily. Workflow ; OLED ; Computer science ; Graph ; Artificial intelligence ; Materials science ; Nanotechnology ; Theoretical computer science ; Database Machine Learning in Materials Science ; Advanced Biosensing Techniques and Applications ; Computational Drug Discovery Methods
Authors: Jayant Iyer | Lucy M. Morgan | Pamela Harrison | Adrian Davis | Andrew Ray | Stefan Mitsche | Ferdinand Hofer | Isha Saraf | Amrit Paudel
Source: Journal of Pharmaceutical Sciences (article, 2023-04-07)
Field: Materials Science — Materials Chemistry

Applying Material Science Principles to Chemical Stability: Modelling Solid State Autoxidation in Mifepristone Containing Different Degrees of Crystal Disorder Ball-milling and harsh manufacturing processes often generate crystal disorder which have practical implications on the physical and chemical stabilities of solid drugs during subsequent storage, transport, and handling. The impact of the physical state of solid drugs, containing different degrees/levels of crystal disorder, on their autoxidative stability under storage has not been widely investigated. This study investigates the impact of differing degrees of crystal disorder on the autoxidation of Mifepristone (MFP) to develop a predictive (semi-empirical) stability model. Crystalline MFP was subjected to different durations of ambient ball milling, and the resulting disorder/ amorphous content was quantified using a partial least square (PLS) regression model based on Raman spectroscopy data. Samples of MFP milled to generate varying levels of disorder were subjected to a range of (accelerated) stability conditions, and periodically sampled to examine their recrystallization and degradation extents. Crystallinity was monitored by Raman spectroscopy, and the degradation was evaluated by liquid chromatography. The analyses of milled samples demonstrated a competition between recrystallization and degradation via autoxidation of MFP, to different extents depending on stability conditions/exposure time. The degradation kinetics were analyzed by accounting for the preceding amorphous content, and fitted with a diffusion model. An extended Arrhenius equation was used to predict the degradation of stored samples under long-term (25°C/60% RH) and accelerated (40°C/75% RH, 50°C/75% RH) stability conditions. This study highlights the utility of such a predictive stability model for identifying the autoxidative instability in non-crystalline/partially crystalline MFP, owing to the degradation of the amorphous phases. This study is particularly useful for identifying drug-product instability by leveraging the concept of material sciences. Raman spectroscopy ; Amorphous solid ; Recrystallization (geology) ; Autoxidation ; Crystallinity ; Arrhenius equation ; Chemical stability ; Chemistry ; Chemical engineering ; Materials science ; Physical chemistry ; Organic chemistry ; Crystallography ; Activation energy Crystallization and Solubility Studies ; Thermal and Kinetic Analysis ; Drug Solubulity and Delivery Systems
Authors: Nehal Abd ElRahman | Maha A. Marzouk | Asmaa M. Elbakry | Rania El-Hosary
Source: Azhar International Journal of Pharmaceutical and Medical Sciences/Azhar International Journal of Pharmaceutical and Medical Sciences  (article, 2023-03-16)
Field: Materials Science — Polymers and Plastics

Polymeric Nanoparticles Based Transdermal Hydrogel of Terbutaline Sulphate: Formulation and Evaluation Asthma is classified as chronic disease causing inflammation of the airways. Terbutaline sulphate is a synthetic β2-adrenoceptor stimulant used mainly in respiratory medicine. It has short half-life 3.4 hours so the study was done to evaluate the possibility of application of terbutaline sulphate loaded polymeric nanoparticles as transdermal drug delivery systems to give a sustained release dosage form. The technique that was chosen for the preparation of different formulae was ionic gelation method using tripolyphosphate and chitosan polymers and these formulae were evaluated for their polydespersity index and particle size. The most suitable formula (F5) was evaluated by entrapment efficiency and zeta potential. The nanoparticle suspension was incorporated in hydroxypropyl methylcellulose gel base and evaluated for visual appearance, pH, rheological properties and in-vitro release. The hydrogel was then evaluated for ex-vivo skin permeation. The chosen formula showed particle size 160.1 nm, entrapment efficiency 70.1, polydespersity index 0.336 and zeta potential 20.1 mv. The hydrogel showed good homogeneity with slightly whitish colour with pH 6.4 and the gel exhibited Higuchi diffusion model. In vitro test showed sustained release profile within 24 hours and the ex vivo test showed high permeation rate within 3 hours. Transdermal ; Terbutaline ; Nanoparticle ; Chemistry ; Self-healing hydrogels ; Chemical engineering ; Materials science ; Chromatography ; Nanotechnology ; Pharmacology ; Organic chemistry ; Medicine ; Asthma ; Engineering Synthesis and properties of polymers ; Electrochemical sensors and biosensors
Authors: Aparna Swain | Nimmi Das Anthuparambil | Victoria García Sakai | J. K. Basu
Source: Soft Matter (article, 2023-01-01)
Field: Materials Science — Polymers and Plastics

Microscopic temperature-dependent structural dynamics in polymer nanocomposites: role of the graft–matrix chain interfacial entropic effect We present a systematic study of the structural dynamics in bulk entropic polymer nanocomposites (PNCs) with deuterated-polymer-grafted nanoparticles (DPGNPs) using quasi-elastic neutron scattering (QENS). We observe that the wave-vector-dependent relaxation dynamics depend on the entropic parameter <i>f</i> as well as the length scale being probed. The entropic parameter can be defined in terms of the grafted-to-matrix polymer molecular weight ratio and controls the extent of matrix chain penetration into the graft. Dynamical cross-over from Gaussian to non-Gaussian behavior at the wave vector <i>Q</i><sub>c</sub>, which depends on temperature and <i>f</i>, was observed. Further insight into the underlying microscopic mechanism responsible for the observed behavior revealed that when interpreted using a jump-diffusion model, in addition to the speeding-up in local chain dynamics, the elementary distance over which sections of the chain hop is strongly dependent on <i>f</i>. Interestingly, we also observe dynamic heterogeneity (DH) in the studied systems, characterized by the non-Gaussian parameter <i>α</i><sub>2</sub>, which reduces for a high-<i>f</i> (<i>f</i> = 0.225) sample compared with the pristine host polymer, indicating reduced dynamical heterogeneity, while it is mostly unchanged for the low-<i>f</i> sample. The results highlight that, unlike enthalpic PNCs, entropic PNCs with DPGNPs can modify the host polymer dynamics due to the subtle balance of interactions that occur at different length scales in the matrix. Polymer ; Materials science ; Nanocomposite ; Dynamics (music) ; Chemical physics ; Molecular dynamics ; Matrix (chemical analysis) ; Polymer nanocomposite ; Chain (unit) ; Thermodynamics ; Nanotechnology ; Chemistry ; Composite material ; Computational chemistry ; Physics Polymer Nanocomposites and Properties ; Material Dynamics and Properties ; Polymer crystallization and properties
Authors: Kisoo Kwon | Kuhwan Jeong | Junghyun Park | Hwidong Na | Jinwoo Shin
Source:  (article, 2023-05-05)
Field: Materials Science — Materials Chemistry

String-Based Molecule Generation Via Multi-Decoder VAE In this study, we investigate the problem of string-based molecular generation via variational autoencoders (VAEs) that have served a popular generative approach for various tasks in artificial intelligence. Our main idea is to maintain multiple decoders while sharing a single encoder, i.e., it is a type of ensemble techniques. Here, we first found that training each decoder independently may not be effective as the bias of the ensemble decoder increases severely under its auto-regressive inference. To alleviate this issue, our proposed technique is two-fold: (a) a different latent variable is sampled for each decoder (from estimated mean and variance offered by the shared encoder) to encourage diverse characteristics of decoders and (b) a collaborative loss is used during training to control the aggregated quality of decoders using different latent variables. In our experiments, the proposed VAE model particularly performs well for generating a sample from out-of-domain distribution. Computer science ; String (physics) ; Latent variable ; Inference ; Decoding methods ; Encoder ; Generative grammar ; Generative model ; Artificial intelligence ; Variance (accounting) ; Algorithm ; Pattern recognition (psychology) ; Mathematics Machine Learning in Materials Science ; Mass Spectrometry Techniques and Applications ; Microfluidic and Capillary Electrophoresis Applications
Authors: Tatsuya Kikuchi | Yukinobu Kawakita | Kenji Nakajima | Seiko Ohira‐Kawamura | Yasuhiro Inamura
Source: Journal of Molecular Liquids (article, 2023-04-19)
Field: Materials Science — Materials Chemistry

Overall picture and details of diffusion dynamics for liquid benzene by quasielastic neutron scattering and mode distribution analysis Diffusion ; Quasielastic neutron scattering ; Jump diffusion ; Molecular dynamics ; Relaxation (psychology) ; Neutron scattering ; Rotational diffusion ; Chemistry ; Chemical physics ; Molecular diffusion ; Benzene ; Quasielastic scattering ; Liquid crystal ; Molecular physics ; Scattering ; Molecule ; Physics ; Jump ; Condensed matter physics ; Inelastic neutron scattering ; Computational chemistry ; Thermodynamics ; Optics Material Dynamics and Properties ; Advanced NMR Techniques and Applications ; Thermodynamic properties of mixtures
Authors: Mehmet Fazıl Kapçı | Burak Bal
Source: GAZI UNIVERSITY JOURNAL OF SCIENCE (article, 2023-03-12)
Field: Materials Science — Metals and Alloys

Investigation of Hydrogen Diffusion Profile of Different Metallic Materials for a Better Understanding of Hydrogen Embrittlement In this study, hydrogen diffusion profiles of different metallic materials were investigated. To model hydrogen diffusion, 1D and 2D mass diffusion models were prepared in MATLAB. Iron, nickel and titanium were selected as a material of choice to represent body-centered cubic, face-centered cubic, and hexagonal closed paced crystal structures, respectively. In addition, hydrogen back diffusion profiles were also modeled after certain baking times. Current results reveal that hydrogen diffusion depth depends on the microstructure, energy barrier model, temperature, and charging time. In addition, baking can help for back diffusion of hydrogen and can be utilized as hydrogen embrittlement prevention method. Since hydrogen diffusion is very crucial step to understand and evaluate hydrogen embrittlement, current set of results constitutes an important guideline for hydrogen diffusion calculations and ideal baking time for hydrogen back diffusion for different materials. Furthermore, these results can be used to evaluate hydrogen content inside the material over expensive and hard to find experimental facilities such as, thermal desorption spectroscopy. Hydrogen ; Hydrogen embrittlement ; Diffusion ; Materials science ; Embrittlement ; Chemical physics ; Metallurgy ; Thermodynamics ; Chemistry ; Corrosion ; Physics Hydrogen embrittlement and corrosion behaviors in metals ; Nuclear Materials and Properties ; Corrosion Behavior and Inhibition
Authors: Shih-Chi Wang | M. van Kampen | T.W. Morgan
Source: ACS Applied Materials & Interfaces (article, 2023-11-22)
Field: Materials Science — Materials Chemistry

Promotion of Plasma-Induced Deuterium Uptake in Ruthenium Films by Monolayer-Thick Tin Layers Surface impurities can have a significant influence on hydrogen uptake of materials. Examples such as the hydrogen spillover effect demonstrate that even very small surface impurity quantities can lead to order-of-magnitude changes in the total amount of hydrogen taken up by a material. In this work, we report the first experimental demonstration of promoted deuterium uptake in Ru thin films by Sn. Deuterium plasma exposures were carried out for Ru-capped targets covered by Sn up to a few atoms in thickness. After the exposure, the residual Sn content and the deuterium retention were measured to quantify the Sn etching and the deuterium uptake, respectively. By increasing the amount of Sn from zero to one atomic layer on Ru, we found after the exposure that the Sn content stays unchanged while the deuterium uptake rate severely increases with the Sn content by 2-3 orders of magnitude. These results can be understood by simulations using a reaction-diffusion model with multiple surface species and the lateral surface migration of deuterium. By contrast, as the as-deposited Sn content goes above one atomic layer, Sn removal takes place, and the deuterium uptake rate decreases with the as-deposited Sn content. Possible explanations are proposed by considering the interplay between Sn etching and deuterium uptake. In all, this work provides insights into interactions between multiple surface species in relation to plasma-induced hydrogen uptake. By further development, this could eventually lead to a potential mitigation method to circumvent the promoted hydrogen uptake in Ru-capped films. Deuterium ; Materials science ; Hydrogen ; Impurity ; Tin ; Diffusion ; Nuclear reaction analysis ; Etching (microfabrication) ; Analytical Chemistry (journal) ; Layer (electronics) ; Nanotechnology ; Chemistry ; Atomic physics ; Metallurgy ; Organic chemistry ; Thermodynamics Hydrogen Storage and Materials ; Ammonia Synthesis and Nitrogen Reduction ; Fusion materials and technologies
Authors: Jin-Woo Kim | Su-Jong Yoon | Tae-Sic Yoo | Eung Soo Kim
Source: International Journal of Heat and Mass Transfer (article, 2023-02-16)
Field: Materials Science — Materials Chemistry

Modelling and analysis of salt-convection effect on oxide reduction process for uranium oxides using smoothed particle hydrodynamics Molten salt ; Molten salt reactor ; Materials science ; Oxide ; Diffusion ; Convection ; Chemical engineering ; Mechanics ; Thermodynamics ; Metallurgy ; Physics Nuclear Materials and Properties ; Fluid Dynamics Simulations and Interactions ; Radioactive element chemistry and processing