jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Pierre Illien
Source: arXiv (Cornell University) (preprint, 2024-11-20)
Field: Chemistry — Physical and Theoretical Chemistry

The Dean-Kawasaki equation and stochastic density functional theory The Dean-Kawasaki (DK) equation, which is at the basis of stochastic density functional theory (SDFT), was proposed in the mid-nineties to describe the evolution of the density of interacting Brownian particles, which can represent a large number of systems such as colloidal suspensions, supercooled liquids, polymer melts, biological molecules, active or chemotactic particles, or ions in solution. This theoretical framework, which can be summarized as a mathematical reformulation of the coupled overdamped Langevin equations that govern the dynamics of the particles, has attracted a significant amount of attention during the past thirty years. In this review, I present the context in which this framework was introduced, and I recall the main assumptions and calculation techniques that are employed to derive the DK equation. Then, in the broader context of statistical mechanics, I show how SDFT is connected to other theories, such fluctuating hydrodynamics, macroscopic fluctuation theory, or mode-coupling theory. The mathematical questions that are raised by the DK equation are presented in a non-specialist language. In the last parts of the review, I show how the original result was extended in several directions, I present the different strategies and approximations that have been employed to solve the DK equation, both analytically and numerically. I finally list the different situations where SDFT was employed to describe the fluctuations of Brownian suspensions, from the physics of active matter to the description of charged particles and electrolytes. Mathematics ; Mathematical economics History and advancements in chemistry
Authors: Samuel Aldana | Cara‐Lena Nies | Michael Nolan
Source: arXiv (Cornell University) (preprint, 2024-10-08)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Control of Cu morphology on TaN barrier and combined Ru-TaN barrier/liner substrates for nanoscale interconnects from atomistic kinetic Monte Carlo simulations The miniaturization of electronic devices brings severe challenges in the deposition of metal interconnects in back end of line processing due to a continually decreasing volume available for metal deposition in the interconnect via. Cu is currently used as the interconnect metal and requires barrier and liner layers to prevent diffusion into silicon and promote deposition of smooth conducting metal films, respectively. However, these take up a significant volume in the interconnect vias, which are already extremely narrow due to the high aspect ratio required. Designing combined barrier/liner materials provides opportunities to promote deposition of smooth films and avoid islanding and frees up precious volume to deposit the required amount of interconnect metal. We present here the first atomistic kinetic Monte Carlo (kMC) investigation of the potential of Ru-modified TaN as a dual-function barrier/line material to promote 2D morphology of deposited Cu enabling optimization of the limited available interconnect volume. The kMC simulations use Density Functional Theory (DFT) activation barriers to predict the role of the combined barrier/liner material on the morphology of deposited Cu and give, for the first time, a tool to predict metal deposition on technologically important substrates. We study Cu deposition at different partial pressures on a series of substrates, including unmodified TaN and TaN with 25% or 50% surface Ru incorporation, at deposition temperatures of 300 K, 500 K and 800 K. The deposition simulations predict Cu film roughness, island size and number, substrate exposure area (as a measure of 2D vs. 3D morphology), layer occupation rate, compactness (as a measure of film quality) and the impact of annealing. As-deposited Cu on unmodified TaN exhibits significantly higher roughness and substrate exposure areas, demonstrating island formation... Kinetic Monte Carlo ; Nanoscopic scale ; Monte Carlo method ; Materials science ; Kinetic energy ; Morphology (biology) ; Chemical physics ; Statistical physics ; Nanotechnology ; Physics ; Geology ; Mathematics ; Classical mechanics Copper Interconnects and Reliability ; Semiconductor materials and devices ; Metal and Thin Film Mechanics
Authors: Mohammed Salim Jumaah | Lekaa  Mahdi | Maysam  Rasheed
Source: Al Rafidain Journal of Engineering Sciences (review, 2024-01-24)
Field: Materials Science — Biomaterials

Zeolite Mineral Importance for Soil and Agricultural engineering – A Review Zeolite is a stone that was discovered in 1756 by Baron Axel Frederick Cronstedt- Swedish scientist. He identified the existence of natural Zeolite in samples of copper mines in Sabavari, Lampmarke County, Sweden. Baron Axel called this stone "boil" (zen) and "stone" (lithos), (Greek name) i.e. boiling metal because when the metal is heated, water comes out of it and it appears as if it is boiling. It is a type of sedimentary, volcanic mineral rock, it is considered a crystalline aluminosilicate in the form of a three-dimensional network, and spread especially common in tuffaceous rocks. Our objective is to establish the significance of zeolites and elucidate their role in agricultural engineering, particularly in fostering sustainability, through an examination of key attributes of this mineral. To begin, we introduce the mineral zeolite, providing insights into its inherent nature. We investigate into its classification, physical and chemical characteristics, subsequently exploring transformations that the zeolite mineral undergoes. Further, we cast a spotlight on diverse agricultural applications of zeolites, including their utilization as fertilizers or soil enhancers, outlining their contributions to agricultural productivity. The paramount features of zeolites are closely tied to their primary applications across a range of fields, prominently within the agricultural domain. Agriculture ; Mineral ; Environmental science ; Zeolite ; Earth science ; Agricultural engineering ; Agroforestry ; Geology ; Natural resource economics ; Engineering ; Geography ; Materials science ; Chemistry ; Archaeology ; Economics ; Metallurgy Clay minerals and soil interactions
Authors: Muzhen Cai | Sendong Zhao | Haochun Wang | Yanrui Du | Zewen Qiang | Bing Qin | Ting Liu
Source: arXiv (Cornell University) (preprint, 2024-06-26)
Field: Materials Science — Materials Chemistry

MolFusion: Multimodal Fusion Learning for Molecular Representations via Multi-granularity Views Artificial Intelligence predicts drug properties by encoding drug molecules, aiding in the rapid screening of candidates. Different molecular representations, such as SMILES and molecule graphs, contain complementary information for molecular encoding. Thus exploiting complementary information from different molecular representations is one of the research priorities in molecular encoding. Most existing methods for combining molecular multi-modalities only use molecular-level information, making it hard to encode intra-molecular alignment information between different modalities. To address this issue, we propose a multi-granularity fusion method that is MolFusion. The proposed MolFusion consists of two key components: (1) MolSim, a molecular-level encoding component that achieves molecular-level alignment between different molecular representations. and (2) AtomAlign, an atomic-level encoding component that achieves atomic-level alignment between different molecular representations. Experimental results show that MolFusion effectively utilizes complementary multimodal information, leading to significant improvements in performance across various classification and regression tasks. Granularity ; Fusion ; Computer science ; Artificial intelligence ; Philosophy ; Linguistics Machine Learning in Materials Science
Authors: Ziwen Zhao | Nikolaos Kostopoulos | Sagar Ganguli | Paul L. Bergstrom | Alina Sekretareva
Source: ChemRxiv (preprint, 2024-02-06)
Field: Chemistry — Electrochemistry

Single-Entity Protein Electrochemistry of Diffusion-Limited Enzymes Single-entity electrochemistry has recently emerged as a promising method for label-free exploration of the catalytic functions of individual enzymes. However, skepticism within the scientific community regarding the applicability of the method for single enzyme measurements has arisen due to issues in the experimental data presented in the literature and limited theoretical modeling of such data. Here, we address these concerns through a thorough experimental investigation of two diffusion-limited enzymes, catalase and superoxide dismutase, employing a combination of protein film voltammetry and single-entity protein electrochemistry measurements. We then introduce a novel theoretical model for simulating the current responses, generated by the reduction of the product of the enzymatic reaction of single enzyme molecules at the electrode. This model is based on a combination of finite element simulations using COMSOL Multiphysics and random walk simulations. It incorporates the diffusion-limited enzymatic kinetics of the investigated enzymes and introduces a geometry that mimics the substrate diffusion channel of the enzyme. Our work demonstrates that the experimentally detected current signals align with the simulated current signals, affirming that they can be attributed to the catalytic activity of single enzymes detected via the product of the enzymatic reaction. Electrochemistry ; Enzyme ; Diffusion ; Chemistry ; Biochemistry ; Computer science ; Computational biology ; Biology ; Physics ; Thermodynamics ; Physical chemistry ; Electrode Electrochemical Analysis and Applications ; Biotin and Related Studies ; Molecular Junctions and Nanostructures
Authors: Zhenzhong Wang | Zehui Lin | Wanyu Lin | Ming Yang | Minggang Zeng | Kay Chen Tan
Source: arXiv (Cornell University) (preprint, 2024-05-25)
Field: Materials Science — Materials Chemistry

Explainable Molecular Property Prediction: Aligning Chemical Concepts with Predictions via Language Models Providing explainable molecular property predictions is critical for many scientific domains, such as drug discovery and material science. Though transformer-based language models have shown great potential in accurate molecular property prediction, they neither provide chemically meaningful explanations nor faithfully reveal the molecular structure-property relationships. In this work, we develop a framework for explainable molecular property prediction based on language models, dubbed as Lamole, which can provide chemical concepts-aligned explanations. We take a string-based molecular representation -- Group SELFIES -- as input tokens to pretrain and fine-tune our Lamole, as it provides chemically meaningful semantics. By disentangling the information flows of Lamole, we propose combining self-attention weights and gradients for better quantification of each chemically meaningful substructure's impact on the model's output. To make the explanations more faithfully respect the structure-property relationship, we then carefully craft a marginal loss to explicitly optimize the explanations to be able to align with the chemists' annotations. We bridge the manifold hypothesis with the elaborated marginal loss to prove that the loss can align the explanations with the tangent space of the data manifold, leading to concept-aligned explanations. Experimental results over six mutagenicity datasets and one hepatotoxicity dataset demonstrate Lamole can achieve comparable classification accuracy and boost the explanation accuracy by up to 14.3%, being the state-of-the-art in explainable molecular property prediction. Property (philosophy) ; Computer science ; Natural language processing ; Artificial intelligence ; Epistemology ; Philosophy Machine Learning in Materials Science ; Computational Drug Discovery Methods
Source: Biointerface Research in Applied Chemistry (article, 2024-08-15)
Field: Materials Science — Materials Chemistry

Synthesis and Ultrasonic Investigation of Graphene Oxide and Reduced Graphene Oxide Nanosuspension with Ethylene Glycol The Original Hummer’s Method was used to produce Graphene Oxide. Hydrazine monohydrate was used to produce Reduced Graphene Oxide by the Graphene Oxide sample. The processed Reduced Graphene Oxide was confirmed by numerous characterization methodologies: RAMAN, X-ray diffraction, Field emission scanning electron microscopy, Energy-dispersive X-ray spectroscopy, and Fourier transform infrared. The numerous characterization methodologies verified the manufacture of Graphene Oxide and the transformation of Reduced Graphene Oxide from Graphene Oxide. The ultrasonication process of double distilled water was used for 24 hours to produce reduced graphene oxide nanosuspension. Further existence of reduced graphene oxide was confirmed by the ultraviolet-visible spectroscopy operating procedure in the nanosuspension. The dimension of reduced graphene oxide fragments was verified by an Ethylene Glycol solution's dynamic light scattering technique. Viscosity, density, and ultrasonic velocity for every concentration were calculated. Other parameters, such as acoustical impedance, intermolecular length, and adiabatic compressibility, are also calculated from investigated data. Graphene ; Materials science ; Oxide ; Graphene oxide paper ; Raman spectroscopy ; Ethylene glycol ; Dynamic light scattering ; Chemical engineering ; Analytical Chemistry (journal) ; Nanotechnology ; Organic chemistry ; Chemistry ; Optics ; Nanoparticle Graphene research and applications ; Graphene and Nanomaterials Applications ; Supercapacitor Materials and Fabrication
Authors: Sri Sugiarti | Idayu Safitri | Noviyan Darmawan
Source: JURNAL PIJAR MIPA (article, 2024-03-25)
Field: Materials Science — Materials Chemistry

Comparing Three Methods for Producing Carbon Dots from Mangosteen Peel Carbon dots are fluorescent nanoparticles that are around 10 nm in size. Carbon dots can be formed via pyrolysis, hydrothermal, and solvothermal procedures from raw materials such as mangosteen peels. Because it contains cyanidin and xanthone, which improve the intensity of carbon dot fluorescence, mangosteen peel waste can be utilized to make carbon dots. The presence of a urea passivation agent is expected to boost carbon dot luminescence intensity. The study aimed to develop carbon dots from mangosteen peel using three different methods: pyrolysis, hydrothermal, and solvothermal, and to assess their ability to produce luminous hues. Carbon dot yield was 21% by the solvothermal method, 5% by the hydrothermal method, and 2% by pyrolysis. All three methods produced blue carbon dot luminescence. The solvothermal method, hydrothermal procedure, and pyrolysis had the highest luminescence intensity. Adding urea as a passivation agent increased the luminescence of carbon dots. The solvothermal approach produced the highest carbon dot production and fluorescence intensity. The hydrothermal and solvothermal carbon dots made emissions at wavelengths of 413 nm and 454 nm, respectively, both corresponding to blue luminescence. Carbon fibers ; Business ; Pulp and paper industry ; Materials science ; Composite material ; Engineering ; Composite number Carbon and Quantum Dots Applications ; Electromagnetic wave absorption materials ; Advanced Cellulose Research Studies
Authors: Haidy Metwally | Jian Yu | R J Thériault | Jennifer Kolwich | Randy E. Ellis | Avena C. Ross | Richard D. Oleschuk
Source: Rapid Communications in Mass Spectrometry (article, 2024-08-19)
Field: Chemistry — Spectroscopy

Crown ether dopant to reduce ion suppression and improve detection in the liquid microjunction surface sampling probe Our approach can be implemented in natural product discovery using LMJ-SSP to allow fast and accurate detection of interesting/novel compounds. Chemistry ; Contamination ; Chromatography ; Ion suppression in liquid chromatography–mass spectrometry ; Sample preparation ; Potassium ; Crown ether ; Disperser ; Shewanella oneidensis ; Ion ; Analytical Chemistry (journal) ; Mass spectrometry ; Bacteria ; Liquid chromatography–mass spectrometry ; Chemical engineering ; Organic chemistry Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Microfluidic and Capillary Electrophoresis Applications
Authors: Jing Li | Tan Shi | Chen Zhang | Ping Zhang | Shehu Adam Ibrahim | Zhipeng Sun | Yuanming Li | Chuanbao Tang | Qing Peng | Chenyang Lu
Source: Materials (article, 2024-07-23)
Field: Materials Science — Materials Chemistry

A Comparative Study on Force-Fields for Interstitial Diffusion in α-Zr and Zr Alloys Interstitial diffusion is important for radiation defect evolution in zirconium alloys. This study employed molecular dynamics simulations to investigate interstitial diffusion in α-Zr and its alloys with 1.0 at.% Nb and 1.0 at.% Sn using a variety of interatomic potentials. Pronounced differences in diffusion anisotropy were observed in pure Zr among the employed potentials. This was attributed to the considerable differences in migration barriers among the various interstitial configurations. The introduction of small concentrations of Nb and Sn solute atoms was found to significantly influence diffusion anisotropy by either directly participating in the diffusion process or altering the chemical environment around the diffusing species. Based on the moderate agreement of interstitial energetics in pure Zr, accurately describing interstitial diffusion in Zr alloys is expected to be more complex. This work underscores the importance of the careful validation and selection of interatomic potentials and highlights the need to understand the effects of solute atoms on interstitial diffusion. Diffusion ; Materials science ; Anisotropy ; Molecular dynamics ; Chemical physics ; Zirconium ; Anisotropic diffusion ; Interstitial defect ; Energetics ; Diffusion process ; Thermodynamics ; Metallurgy ; Computational chemistry ; Chemistry ; Physics Nuclear Materials and Properties ; Fusion materials and technologies ; Nuclear reactor physics and engineering
Authors: Uday Kumar P | S Dharani | Puthanveedu Divya | T Mounika
Source: Journal of Pharma Insights and Research. (article, 2024-10-04)
Field: Chemistry — Spectroscopy

Advancements in Rapid Detection Technologies for Club Drugs in Beverages The rising incidence of drug-facilitated crimes, particularly sexual assaults, has heightened the need for efficient and accessible detection methods for club drugs in beverages. This review article discusses about the recent developments in sensor-based technologies designed to identify common date rape drugs, including benzodiazepines, gamma-hydroxybutyric acid (GHB), ketamine, and their analogs. We discuss the evolution from traditional analytical methods to more portable and user-friendly solutions, focusing on microfluidic paper-based analytical devices (μPADs), electrochemical sensors, and colorimetric assays. The integration of these technologies with smartphone applications and machine learning algorithms has significantly enhanced their practicality for real-time, on-site detection. We evaluate the sensitivity, specificity, and ease of use of various detection methods, highlighting their potential for widespread implementation in social settings. Additionally, we address the challenges associated with detecting multiple drugs simultaneously and the ongoing efforts to minimize false positives. The review also considers the legal and ethical implications of using such devices in public spaces. Finally, we outline future research directions, including the development of wearable sensors and the application of nanotechnology to further improve detection capabilities. This review aims to inform researchers, healthcare professionals, and policymakers about the current state and future potential of club drug detection technologies in combating drug-facilitated crimes Club ; Computer science ; Business ; Medicine Analytical Chemistry and Chromatography ; Advanced Chemical Sensor Technologies ; Various Chemistry Research Topics
Authors: Camille Bacon | Patrice Simon | Mathieu Salanne | Alessandra Serva
Source: ChemRxiv (preprint, 2024-02-19)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Simulating the charging mechanism of a realistic nanoporous carbon-based supercapacitor using a fully polarizable model Nanoporous carbon-based supercapacitors are established energy storage devices, that complement Li-ion batteries in high-power applications. So far, their study through simulations required drastic simplification of the electrolyte and/or of the electrode. In this work, we use state-of-the-art constant potential classical molecular dynamics simulations, where both the electrode and the electrolyte are polarizable, to study complex carbide-derived carbons with 1-ethyl-3-methylimidazolium bis(trifluoromethane)sulfonyl imide ionic liquid electrolyte. We show that using this set-up allows to obtain integral capacitances (i.e. the main property to characterize supercapacitors) in quantitative agreement with experiments. The simulations, performed in a range of applied potentials of 1V to 4V, then provide microscopic details on the charging mechanism, revealing that it is not symmetrical between the positive and negative electrodes. A pure exchange of ions is observed on the positive electrode, while an ion exchange combined with cation adsorption takes place on the negative one. Our work shows that accounting for the coupling of electrode and electrolyte polarization improves the accuracy of the results, opening the way toward a more quantitative comparison with experiments. Electrolyte ; Supercapacitor ; Polarizability ; Ionic liquid ; Nanoporous ; Materials science ; Electrode ; Chemical physics ; Ion ; Molecular dynamics ; Nanotechnology ; Electrochemistry ; Chemistry ; Computational chemistry ; Physical chemistry ; Molecule ; Organic chemistry Supercapacitor Materials and Fabrication ; Advancements in Battery Materials ; Electrocatalysts for Energy Conversion
Authors: Shankar Bhattarai | Vinay Shankar Tiwari | Benjamin Tam | A. Rozen | Adam Soffer | Samuel Durbah | Sarah Adi Eisdorfer | Angeliki Giannoulis | Daniella Goldfarb | Barak Akabayov
Source: NAR Molecular Medicine (article, 2024-12-28)
Field: Chemistry — Organic Chemistry

Indole-containing inhibitors with improved efficacy targeting the gyrase of <i>Mycobacterium tuberculosis</i> Tuberculosis is a major cause of mortality worldwide, with drug-resistant strains complicating its treatment. We report the discovery of small-molecule inhibitors targeting the gyrase of <i>Mycobacterium tuberculosis</i>, the bacterium responsible for tuberculosis. Gyrase, a type II topoisomerase, consists of two subunits: GyrA, which breaks and rejoins DNA, and GyrB, which contains the ATPase domain responsible for ATP binding and hydrolysis. An indole scaffold identified by nuclear magnetic resonance fragment screening was grown into drug-sized candidates through computational optimization, chemical synthesis and functional selection. Several indole-containing gyrase inhibitors were found to be specific for the GyrB subunit of <i>M. tuberculosis</i>. Structural studies using double electron-electron resonance spectroscopy between the Mn(II) ion in the catalytic site of GyrB and a nitroxide-labeled inhibitor provided insights into the potential docking sites of the protein target. Key chemical descriptors essential for gyrase binding were identified for the small-molecule inhibitors using data-driven algorithms. Our results demonstrate the effectiveness of fragment screening and computational optimization in drug discovery. The inhibitors presented in this study are promising candidates for further pharmacological studies <i>in vivo</i>. DNA gyrase ; Mycobacterium tuberculosis ; Microbiology ; Indole test ; Tuberculosis ; Bacterial protein ; Mycobacterium ; Medicine ; Virology ; Biology ; Bacteria ; Escherichia coli ; Biochemistry ; Gene ; Genetics Synthesis and biological activity ; Cancer therapeutics and mechanisms ; Tuberculosis Research and Epidemiology