jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Brett A. Smith | Somon Hakimov | David M. Jenkins | Konstantinos D. Vogiatzis
Source: Dalton Transactions (article, 2024-01-01)
Field: Chemistry — Organic Chemistry

Ligand engineering of tetra N-heterocyclic carbenes for boosting catalytic aziridination A comprehensive computational study on the underlying reactivity of iron tetra-NHC complexes for C<sub>2</sub> + N<sub>1</sub> aziridination catalysis is presented. A library of 18 unique iron tetra-NHC complexes was constructed, and a computational screening was performed on the reaction barriers associated with the rate-determining step (formation of an open chain radical intermediate). Thermodynamic barriers were computed along with a variety of steric and electronic properties, including the percentage of buried volume, orbital energies and ETS-NOCV analysis, which were used to identify key characteristics related to reactivity. The analysis performed in this study successfully identified key differences in tetracarbenes, such as linking groups (BMe<sub>2</sub> or CH<sub>2</sub>) and the identity of the NHC groups (imidazole, imidazoline or benzimidazole) in terms of sterics, electronics and thermodynamics. Additionally, we have proposed two reaction pathways based on electronic structure arguments for the formation of the key open-chain radical intermediate. The first reaction pathway proceeds through a σ-hole channel where the Fe(IV)-imide intermediate evolves into Fe(III)-imidyl radical through electron donation into the antibonding σ* orbital, while the second involves a Fe(III)-imidyl radical formed through a π-hole channel (donation into π*). These pathways are consistent with the isoelectronic iron(IV)-oxo species for hydrogen atom abstraction mechanisms and they can be used as descriptors of the rate-determining step of the aziridination reaction. Tetra ; Catalysis ; Ligand (biochemistry) ; Chemistry ; Boosting (machine learning) ; Combinatorial chemistry ; Medicinal chemistry ; Organic chemistry ; Computer science ; Receptor ; Biochemistry ; Artificial intelligence Synthesis and Catalytic Reactions ; N-Heterocyclic Carbenes in Organic and Inorganic Chemistry ; Asymmetric Hydrogenation and Catalysis
Authors: Kyunghoon Han | Ariadni Boziki | Alexandre Tkatchenko | Joshua T. Berryman
Source: ACS Omega (article, 2024-12-06)
Field: Chemistry — Analytical Chemistry

TIHI Toolkit: A Peak Finder and Analyzer for Spectroscopic Data Complex signal vectors, particularly spectra, are integral to many scientific domains. Interpreting these signals often involves decomposing them into contributions from independent components and subtraction or deconvolution of the channel and instrument noise. Despite the fundamental nature of this task, researchers frequently rely on costly commercial tools. To make such tools accessible to all, we present <i>Tihi</i>, interactive, open-source multiplatform software for interpolation, denoising, baseline correction, peak detection, and signal decomposition. <i>Tihi</i> provides a user-friendly graphical interface (GUI) that facilitates the analysis of spectroscopic data and more. It allows researchers to contribute to and freely distribute these tools, ensuring broad accessibility and fostering collaborative improvements. We present examples demonstrating the efficiency of the program using the spectra of different systems acquired by different spectroscopic techniques, including Raman (aspirin), IR (solid ammonia), XRD (anatase), and UV-vis (petal tip from the <i>Puya alpestris</i> flower). These examples showcase a variety of spectra that differ significantly, from signals with narrow profiles to signals with very broad profiles. This demonstrates the versatility of <i>Tihi</i> for peak identification in a wide range of spectroscopic techniques. Spectrum analyzer ; Computer science ; Computer graphics (images) ; Telecommunications Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Mass Spectrometry Techniques and Applications
Authors: Sihan Yan | Jingpeng Zhang | Jiahan Zhang | Songrui Wei | Shaohui Zhang | Shan Li | Chee‐Keong Tan | Mingming Jiang | Weihua Tang | Zeng Liu
Source: iScience (article, 2024-09-27)
Field: Materials Science — Materials Chemistry

Unveiling anharmonic scattering in van der Waals semiconductor GaPS4 through Raman spectroscopy and theoretical calculation The van der Waals thiophosphate GaPS<sub>4</sub> presents additional opportunities for gallium-based semiconductors, but limited research on phonon interactions has hindered optimization on thermal properties. This research undertakes a comprehensive investigation into the anharmonic phonon scattering within GaPS<sub>4</sub>. The findings reveal pronounced anharmonic scattering, with both cubic and quartic phonon scatterings significantly influencing phonon redshift and broadening. Notably, the scattering strength is markedly higher in Raman peaks with higher wavenumbers, where quartic phonon scattering leads to conspicuous nonlinear broadening. Furthermore, a large amount of cubic and quartic scattering events is found to be Umklapp process. Besides, the molecular dynamics calculation quantitatively confirms the extensive redshift and broadening and suggests stronger anharmonic scattering beyond the Brillouin zone center. This research not only elucidates the anharmonic phonon scattering in GaPS4 but also provides theoretical foundation for further application. Concurrently, it enhances the understanding of anharmonic scattering in semiconductors within the condensed matter physics. Anharmonicity ; van der Waals force ; Raman spectroscopy ; Raman scattering ; Semiconductor ; Spectroscopy ; Chemical physics ; Physics ; Chemistry ; Nanotechnology ; Materials science ; Condensed matter physics ; Quantum mechanics ; Molecule 2D Materials and Applications ; Chalcogenide Semiconductor Thin Films ; Nanowire Synthesis and Applications
Authors: Sriram Devata | Bhuvanesh Sridharan | Sarvesh Mehta | Yashaswi Pathak | Siddhartha Laghuvarapu | Girish Varma | Deva Priyakumar
Source: ChemRxiv (preprint, 2024-01-16)
Field: Chemistry — Analytical Chemistry

DeepSPInN - Deep reinforcement learning for molecular Structure Prediction from Infrared and 13C NMR spectra Molecular spectroscopy studies the interaction of molecules with electromagnetic radiation, and interpreting the resultant spectra is invaluable for deducing the molecular structures. However, predicting the molecular structure from spectroscopic data is a strenuous task that requires highly specific domain knowledge. DeepSPInN is a deep reinforcement learning method that predicts the molecular structure when given Infrared and 13C Nuclear magnetic resonance spectra by formulating the molecular structure prediction problem as a Markov decision process (MDP) and employs Monte-Carlo tree search to explore and choose the actions in the formulated MDP. On the QM9 dataset, DeepSPInN is able to predict the correct molecular structure for 91.5% of the input spectra in an average time of 77 seconds for molecules with less than 10 heavy atoms. This study is the first of its kind that uses only infrared and 13C nuclear magnetic resonance spectra for molecular structure prediction without referring to any pre-existing spectral databases or molecular fragment knowledge bases, and is a leap forward in automated molecular spectral analysis. Spectral line ; Molecule ; Infrared ; Infrared spectroscopy ; Molecular dynamics ; Chemistry ; Computer science ; Nuclear magnetic resonance ; Computational chemistry ; Physics ; Optics Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Asep Bayu Dani Nandiyanto | Risti Ragadhita | Meli Fiandini
Source: Indonesian Journal of Science and Technology (article, 2024-07-09)
Field: Chemistry — Physical and Theoretical Chemistry

How to Calculate and Determine Chemical Kinetics: Step-by-Step Interpretation of Experimental Data to Get Reaction Rate and Order Chemical kinetics is a fundamental field of study that focuses on the rates of chemical reactions and the factors influencing them. Determining the rate and order of the chemical reaction is an important aspect of understanding the reaction mechanism. This article presents a step-by-step guide to calculate and determine the rate and order of the reaction through a comprehensive analysis of experimental data. We discussed the concept of chemical kinetics, the integration of the kinetic order method, and the curve-fitting analysis technique. Several case studies are also included to provide practical applications of the theory outlined. This proposed guide aims to provide students, educators, researchers, and practitioners with a systematic approach to specify and verify prospective kinetic models, enabling them in decision-making, improving, and optimizing chemical reaction processes. Interpretation (philosophy) ; Kinetics ; Order of reaction ; Chemical kinetics ; Order (exchange) ; Chemistry ; Thermodynamics ; Biochemical engineering ; Biological system ; Computational chemistry ; Computer science ; Reaction rate constant ; Economics ; Engineering ; Physics ; Biology Various Chemistry Research Topics
Authors: Antoine Baron | Enrique H. Balaguera | Sébastien Pecqueur
Source: arXiv (Cornell University) (preprint, 2024-06-29)
Field: Materials Science — Polymers and Plastics

A Compact Electrochemical Model for a Conducting Polymer Dendrite Impedance Conducting Polymer Dendrites (CPD) are truly inspiring for unconventional electronics that shapes topological circuitries evolving upon an application. Driven by electrochemical processes, an electrochemical impedance rules signal propagation from one node to another. However, clear models dictating their behavior in an electroactive electrolyte have not been identified yet. In this study, we investigate on CPD in an aqueous electrolyte by impedance spectroscopy to unify their signal transport with an electrical model, aiming to define a circuit simulation block to integrate these objects in systems for in materio information processing. Dendrite (mathematics) ; Materials science ; Electrical impedance ; Electrochemistry ; Electrical engineering ; Engineering ; Physics ; Mathematics ; Geometry ; Electrode Conducting polymers and applications
Authors: Oisín Foley Doyle | Robert J. Forster
Source: Electrochemistry Communications (article, 2024-11-02)
Field: Chemistry — Electrochemistry

Wirefree Electrochemistry for Enhanced Detection and Treatment of Disease • Wireless electrochemistry enables the selective and sensitive detection of multiple biomarkers. • Continuous, non-invasive health monitoring and early disease detection • Smart, on demand drug delivery triggered by biomarkers to minimise side effects. • Electrostimulation of biological cells to drive proliferation, differentiation and interconnections. Wirefree, or bipolar electrochemistry, BPE, has the potential to transform patient outcomes through early diagnosis using ultrasensitive sensors for multiple biomarkers and personalised treatments such as enhanced cell growth, differentiation and destruction as well as local delivery of therapeutics. We highlight the emerging field of wirefree electroceuticals and show how BPE could enable precise modulation of neural circuits, non-pharmaceutical therapies for conditions like Parkinson’s disease and chronic pain management, as well as on-demand drug delivery with high spatial and temporal precision. Moreover, it explores the integration of advanced nanomaterials illustrating their pivotal role in enhancing electrode performance and biocompatibility, thereby maximising their potential diagnostic and therapeutic efficacy especially in vivo . Electrochemistry ; Nanotechnology ; Materials science ; Chemistry ; Electrode ; Physical chemistry Electrochemical Analysis and Applications ; Electrochemical sensors and biosensors ; Conducting polymers and applications
Authors: Yongle Wu | Yuzhen Zhao | Dong Wang
Source: Molecules (article, 2024-01-19)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Preparation of Progressive Driving Bilayer Polymer-Dispersed Liquid Crystals Possessing a PDLC-PVA-PDLC Structure In this paper, the bilayer polymer-dispersed liquid crystals possessing a PDLC-PVA-PDLC structure were prepared by integrating two monolayer PDLCs. The effect of the polymer mesh size on the electro-optical properties of a bilayer PDLC was investigated by comparing the micro-morphology and electro-optical curves under different polymerization conditions. In addition, the impact of doping MoO<sub>2</sub> nanoparticles with surface modification on the comprehensive performance of the bilayer PDLC was further researched. The contrast ratio of the bilayer PDLC prepared under the optimal conditions was improved by more than 90% and still maintained excellent progressive driving performance. Therefore, the development of a bilayer PDLC with optimal electro-optical properties will significantly enhance the technological prospects for the application of PDLC-based devices in smart windows, displays, and flexible devices. Bilayer ; Liquid crystal ; Materials science ; Polymer ; Chemical engineering ; Polymer chemistry ; Composite material ; Chemistry ; Optoelectronics ; Membrane Liquid Crystal Research Advancements ; Polydiacetylene-based materials and applications ; Synthesis and properties of polymers
Authors: Zhixiong Guo | Da Chen | T. K. Kwei | Yongquan Qu | Zhimin Tian
Source: Nano Research (article, 2024-12-16)
Field: Materials Science — Materials Chemistry

Ce-UiO-66 nanozymes with charge-regulated uricase-like activity for enzyme/reagent-free detection of uric acid Designing highly performed uricase-like nanozymes through enzymatic-like colorimetric analysis system is of vital significance for the quantitative detection of uric acid (UA). Herein, series of Ce-UiO-66 nanozymes with different surface charges through the ligand engineering strategy were rationally designed and synthesized as efficient uricase mimics with tailorable uricase-like activities to catalytically convert UA into allantoin and H<sub>2</sub>O<sub>2</sub>. Importantly, by tuning the functional groups of 1,4-benzoic acid ligands, we explored the relationships between the surface charges of Ce-UiO-66-X (X = H, NO<sub>2</sub>, Br, CH<sub>3</sub>, and OH) nanozymes and their uricase-like activity. Among them, Ce-UiO-66-CH<sub>3</sub> with the moderate surface charge exhibited optimal substrate adsorption and product desorption, displaying the highest uricase-like activity. Significantly, H<sub>2</sub>O<sub>2</sub>, as the product of UA oxidation, enabled Ce-UiO-66-CH<sub>3</sub> itself as a dose-dependent chromogenic substrate of H<sub>2</sub>O<sub>2</sub>, giving a white-to-orange color evolution due to the Ce-UiO-66-CH<sub>3</sub>-to-CeO<sub>2</sub> phase transition. Afterwards, a smartphone-assisted all-in-one enzyme/reagent-free biosensor based on Ce-UiO-66-CH<sub>3</sub> was established for the precise visual detection of UA analysis, which was featured by a wide detection range (31–4000 µM), a high sensitivity (limit of detection: 8.9 µM), a rapid response (~ 3 min), a high structural stability, and a high anti-interference ability. Uric acid ; Reagent ; Chemistry ; Enzyme ; Urate oxidase ; Biochemistry ; Organic chemistry Advanced Nanomaterials in Catalysis ; Electrochemical sensors and biosensors ; Advanced biosensing and bioanalysis techniques
Authors: Rakesh Kumar | Susheela K. Lenkennavar
Source: Prabha Materials Science Letters (article, 2024-12-27)
Field: Materials Science — Materials Chemistry

An Investigation into Empirical Equations for Predicting Density and Packing Density Parameters Across Diverse Chemical Compositions: A Theoretical Approach This work investigates an empirical equation for predicting the density and packing density parameter for different chemical combinations. The empirical equation suggested by Makishima and Mackenzie (1973) was employed to calculate the values of Vi, which indicates the packing density parameter and the equation proposed by Inaba and Fujino (2010) was utilized to calculate the density values. To determine the density values accurately, Vi is essential. This research focuses on revisiting the density model established by Inaba and Fujino (2010) to increase its accuracy. It is found that the ionic packing ratio is approximately constant and independent of the chemical composition. For different categories of glasses, including silicate, tellurite, and phosphate. The density has been meticulously calculated. These calculations rely on compositional parameters such as molecular weight, molecular fractions, and notably, the ionic radius of various metals. Density values are fundamental to the theoretical examination of radiation properties in the Phy-x/PSD software. Utilizing advanced tools and software allows for the prediction of glass physical parameters, which are indispensable in the fields of optical devices and electronic materials. This research establishes a connection between the composition of oxide glasses and their density. Consequently, it enhances our understanding of the properties and behaviour of these materials. Statistical physics ; Sphere packing ; Materials science ; Mathematics ; Physics ; Geometry Thermal and Kinetic Analysis ; X-ray Diffraction in Crystallography ; Adsorption, diffusion, and thermodynamic properties of materials
Authors: Xiaotong Zhang | T. B. Mitchell | Jason B. Benedict
Source: Crystal Growth & Design (article, 2024-07-23)
Field: Materials Science — Materials Chemistry

Crystal Structure Landscape of Diarylethene-Based Crystalline Solids: A Comprehensive CSD Analysis Diarylethenes (DAEs) are an exciting class of stimulus-responsive organic molecules that exhibit electrocyclization reactions upon exposure to light, heat, or other stimuli. The rational design of DAE-based crystalline materials is, however, complicated by the presence of DAE atropisomers, only one of which is photoactive. Data mining of the CSD produced 1349 unique molecular DAE structures that were subsequently analyzed according to selected chemical and geometric attributes. Additional analyses were performed on 1078 dithienylethene (DTE) structures-the largest subgroup within the ensemble. The crystal structure landscape, based upon <i>D</i>-<i>D</i> parameterization and analysis, revealed a vast array of molecular geometries, many of which may not correspond to energetic minima. The analyses link various chemical and geometric parameters to isomers observed in the lattice and their reactivity; however, potential biases intrinsic to this ensemble of structures complicate the determination of causal relationships. We believe that this retrospective comprehensive analysis of DAE structures represents an important step for understanding more broadly the crystal landscape of this class of materials. Diarylethene ; Molecule ; Photochromism ; Crystal structure ; Atropisomer ; Chemistry ; Crystal (programming language) ; Materials science ; Photochemistry ; Crystallography ; Stereochemistry ; Organic chemistry ; Computer science Photochromic and Fluorescence Chemistry ; Photoreceptor and optogenetics research ; Luminescence and Fluorescent Materials
Authors: Christopher D. Williams | Jas Kalayan | Neil A. Burton | Richard A. Bryce
Source: ChemRxiv (preprint, 2024-02-16)
Field: Materials Science — Materials Chemistry

Stable and Accurate Atomistic Simulations of Flexible Molecules using Conformationally Generalisable Machine Learned Potentials Computational simulation methods based on machine learned potentials (MLPs) promise to revolutionise shape prediction of flexible molecules in solution, but their widespread adoption has been limited by the way in which training data is generated. Here, we present an approach which allows the key conformational degrees of freedom to be properly represented in reference molecular datasets. MLPs trained on these datasets using a global descriptor scheme are generalisable in conformational space, providing quantum chemical accuracy for all conformers. These MLPs are capable of propagating long, stable molecular dynamics trajectories, an attribute that has remained a challenge for MLPs. We deploy the MLPs in obtaining converged conformational free energy surfaces for flexible molecules via well-tempered metadynamics simulations; this approach provides a hitherto inaccessible route to accurately computing the structural, dynamical and thermodynamical properties of a wide variety of flexible molecular systems. Metadynamics ; Molecular dynamics ; Computer science ; Degrees of freedom (physics and chemistry) ; Conformational ensembles ; Conformational isomerism ; Molecular machine ; Molecule ; Artificial intelligence ; Biological system ; Computational chemistry ; Nanotechnology ; Chemistry ; Materials science ; Physics ; Thermodynamics Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Protein Structure and Dynamics
Authors: Victor A. Kovtunenko
Source: Technologies (article, 2024-10-17)
Field: Materials Science — Materials Chemistry

Particle Size Distribution in Holby–Morgan Degradation Model of Platinum on Carbon Catalyst in Fuel Cell: Normal Distribution The influence of particle size distribution in platinum catalysts on the aging of PEM fuel cells described by Holby–Morgan electrochemical degradation model is under investigation. The non-diffusive model simulates mechanisms of particle drop by Pt dissolution and particle growth through Pt ion deposition. Without spatial dependence, the number of differential equations can be reduced using the first integral of the system. For an accelerated stress test, a non-symmetric square-wave potential profile is applied according to the European harmonized protocol. The normal particle size distribution determined by two probability parameters of the expectation and the standard deviation is represented within finite groups. Numerical solution of the nonlinear diffusion equation justifies dispersion for small and narrowing for large distribution means, decrease or increase in amplitude, and movement of Pt particle diameters towards small sizes, which is faster for small particles. Platinum ; Degradation (telecommunications) ; Catalysis ; Distribution (mathematics) ; Carbon fibers ; Fuel cells ; Particle (ecology) ; Chemical engineering ; Materials science ; Environmental science ; Chemistry ; Computer science ; Composite material ; Mathematics ; Engineering ; Organic chemistry ; Biology ; Mathematical analysis ; Ecology Catalytic Processes in Materials Science ; Recycling and Waste Management Techniques ; Electrocatalysts for Energy Conversion
Authors: Shiya Chen | Zepeng Wu | Zhen Zhang | Shunqing Wu | Kai‐Ming Ho | Vladimir Antropov | Yang Sun
Source: arXiv (Cornell University) (preprint, 2024-01-24)
Field: Materials Science — Materials Chemistry

High-throughput screening for boride superconductors A high-throughput screening using density functional calculations is performed to search for stable boride superconductors from the existing materials database. The workflow employs the fast frozen phonon method as the descriptor to evaluate the superconducting properties quickly. 23 stable candidates are identified from the screening. For almost all found binary compounds, the superconductivity was obtained earlier experimentally or computationally. For ternary borides, previous studies are very limited. Our extensive search among ternary systems confirmed superconductivity in known systems and found several new compounds. Among these discovered superconducting ternary borides, Ta(MoB)$_2$ shows the highest superconducting temperature of ~12K. Most predicted compounds were synthesized previously; therefore, our predictions can be examined experimentally. Our work also demonstrates that the boride systems can have diverse structural motifs that lead to superconductivity. Boride ; Superconductivity ; Ternary operation ; Materials science ; Workflow ; Binary number ; Condensed matter physics ; Throughput ; Computer science ; Physics ; Metallurgy ; Database ; Mathematics Machine Learning in Materials Science ; Iron-based superconductors research ; Inorganic Chemistry and Materials