jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Nancy Mwikali Mwenze | Zephania Birech | Moses Juma | Karen J. Cloete | Annah M. Ondieki | Carolyne Jeptoo | Kenneth A. Kaduki | M.S. Dhlamini | M. Mâaza
Source: Research Square (preprint, 2023-08-01)
Field: Materials Science — Materials Chemistry

A combined experimental and computational analysis of dexamethasone-conjugated silver nanoparticles for improved surface-enhanced Raman substrate detection. Abstract Computations based on density functional theory (DFT) and experimental analysis on spectral vibrations have been performed on the dexamethasone molecule. The computer simulations have been analyzed using DFT-B3LYP functional at 6-311 + + G(d,p) basis. UV-Vis and Raman spectra have been recorded and reported. High-purity silver granules (99.99%) were immersed in 5 ml of distilled water in a 25 ml glass beaker. A Q-Switched Nd: YAG laser (1064 nm, max energy of 250 mJ, 8 ns) was focused on the silver sample target by a convex lens whose focal length was 30mm. The ablation time varied from 2 to 8 hours leading to the formation of yellow to dark brown AgNPs colloids. Raman spectroscopy, UV-Vis spectroscopy, and Scanning Electron Microscopy techniques were used for the sample characterization. At 8 hours, the synthesized AgNPs were most chemically stable and had spherical colloids with a diameter of 6.3 nm. Conjugating dexamethasone with AgNPs led to the enhancement of the Raman signals by a factor of 1.4. A position shift in the plasmon resonance peak attributed to the newly formed complex with unique optical characteristics was noted. The findings support the possibility of enhancing the functionality of dexamethasone by developing new-drug-like candidates after conjugation with AgNPs. Raman spectroscopy ; Silver nanoparticle ; Density functional theory ; Scanning electron microscope ; Surface plasmon resonance ; Materials science ; Spectroscopy ; Nanoparticle ; Laser ; Analytical Chemistry (journal) ; Chemistry ; Nanotechnology ; Optics ; Chromatography Quantum Dots Synthesis And Properties ; Gold and Silver Nanoparticles Synthesis and Applications ; Laser-Ablation Synthesis of Nanoparticles
Authors: Namkyeong Lee | Heewoong Noh | Sungwon Kim | Dongmin Hyun | Gyoung S. Na | Chanyoung Park
Source: arXiv (Cornell University) (preprint, 2023-03-13)
Field: Materials Science — Materials Chemistry

Predicting Density of States via Multi-modal Transformer The density of states (DOS) is a spectral property of materials, which provides fundamental insights on various characteristics of materials. In this paper, we propose a model to predict the DOS by reflecting the nature of DOS: DOS determines the general distribution of states as a function of energy. Specifically, we integrate the heterogeneous information obtained from the crystal structure and the energies via multi-modal transformer, thereby modeling the complex relationships between the atoms in the crystal structure, and various energy levels. Extensive experiments on two types of DOS, i.e., Phonon DOS and Electron DOS, with various real-world scenarios demonstrate the superiority of DOSTransformer. The source code for DOSTransformer is available at https://github.com/HeewoongNoh/DOSTransformer. Modal ; Computer science ; Statistical physics ; Density of states ; Transformer ; Source code ; Phonon ; Computational physics ; Algorithm ; Physics ; Theoretical computer science ; Materials science ; Quantum mechanics ; Voltage Machine Learning in Materials Science ; Solid-state spectroscopy and crystallography ; X-ray Diffraction in Crystallography
Authors: Haoxiang Lin | Xi Zhu
Source: Digital Discovery (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

Atomic fragment approximation from a tensor network We propose atomic-fragment approximation (AFA), which uses the tensor network (TN) as a platform to estimate the molecular properties through “adding up” fragment properties. Fragment (logic) ; Tensor (intrinsic definition) ; Physics ; Computer science ; Algorithm ; Mathematics ; Geometry Machine Learning in Materials Science ; Mass Spectrometry Techniques and Applications ; Protein Structure and Dynamics
Authors: Ameen Abbas | Mashhud-Ul-Hasan Abid | Hafza Mahnoor | Malaika Bukhari | Rameen Malik | Muhammad Jaon Haider | Rabish Rafique | Mishaal Fatima | Taiba Shoaib
Source: FRONTIERS IN CHEMICAL SCIENCES (article, 2023-12-31)
Field: Chemistry — Spectroscopy

Quantum Biochemistry: Unveiling the Quantum Coherence in Enzyme Catalysis Objective: This study investigates the influence of quantum coherence in enzyme catalysis, aiming to elucidate its role in biochemical processes. The primary objective is to unravel quantum effects within various enzymes (A-F) involved in crucial biochemical pathways. Methodology: Employing a multidisciplinary approach, advanced experimental techniques and computational methods were utilized. Quantum tunneling rates were measured through Reaction Progress Kinetic Analysis (RPKA) with High-Performance Liquid Chromatography (HPLC). Femtosecond-resolved spectroscopy captured quantum coherence times, while Two-Dimensional Infrared Spectroscopy (2D IR) probed vibrational coupling. Ultrafast Laser Spectroscopy provided insights into enzyme dynamics. Density Functional Theory (DFT) calculations and Ab Initio Simulations complemented experimental findings. Results: The results reveal distinct quantum signatures across all enzymes. Notably, Enzyme A demonstrates a quantum tunneling rate of 3.2 x 10^-2 s^-1. Quantum coherence times in Enzyme B showcase unprecedented femtosecond scales, while other enzymes exhibit diverse behaviors. DFT calculations for Enzyme E predict a 30% reduction in energy barriers. Ab Initio Simulations of Enzyme F unveil persistent entanglement states. Conclusion: The observed quantum phenomena suggest a profound interplay between quantum coherence and enzyme catalysis, emphasizing the enzyme-specific nature of quantum effects. The implications of energy barrier reduction and entanglement states provide insights into potential quantum-assisted catalytic mechanisms. Coherence (philosophical gambling strategy) ; Quantum ; Enzyme ; Physics ; Chemistry ; Quantum mechanics ; Biochemistry Molecular spectroscopy and chirality ; Photosynthetic Processes and Mechanisms
Authors: Teresa de los Arcos | Peter Awakowicz | Marc Böke | Nils Boysen | Ralf Peter Brinkmann | Rainer Dahlmann | Anjana Devi | Denis Eremin | Jonas Franke | Tobias Gergs | Jonathan Jenderny | Efe Ke­man­eci | Thomas D. Kühne | Simon Kusmierz | Thomas Mussenbrock | Jens Rubner | Jan Trieschmann | Matthias Weßling | Xiaofan Xie | David Zanders | Frederik Zysk | Guido Grundmeier
Source: arXiv (Cornell University) (preprint, 2023-06-26)
Field: Materials Science — Surfaces, Coatings and Films

PECVD and PEALD on polymer substrates (Part II): Understanding and tuning of barrier and membrane properties of thin films This feature article presents insights concerning the correlation of PECVD and PEALD thin film structures with their barrier or membrane properties. While in principle similar precursor gases and processes can be applied, the adjustment of deposition parameters for different polymer substrates can lead to either an effective diffusion barrier or selective permeabilities. In both cases the understanding of the film growth and the analysis of the pore size distribution and the pore surface chemistry is of utmost importance for the understanding of the related transport properties of small molecules. In this regard the article presents both concepts of thin film engineering and analytical as well as theoretical approaches leading to a comprehensive description of the state of the art in this field. Moreover, based on the presented correlation of film structure and molecular transport properties perspectives of future relevant research in this area is presented. Thin film ; Materials science ; Polymer ; Chemical physics ; Plasma-enhanced chemical vapor deposition ; Nanotechnology ; Membrane ; Diffusion ; Deposition (geology) ; Diffusion barrier ; Computer science ; Chemistry ; Physics ; Thermodynamics ; Composite material Electron and X-Ray Spectroscopy Techniques ; Block Copolymer Self-Assembly ; Corrosion Behavior and Inhibition
Authors: O. A. Elhefnawy | Amira A. Elabd
Source: Research Square (preprint, 2023-04-03)
Field: Chemistry — Inorganic Chemistry

Modified Activated carbon by in-situ co-precipitation process of tetra metal oxide magnetic nanocomposite for adsorption of Th(IV) from aqueous media Adsorption ; Endothermic process ; Aqueous solution ; Metal ions in aqueous solution ; Langmuir adsorption model ; Activated carbon ; Oxide ; Nanocomposite ; Inorganic chemistry ; Precipitation ; Materials science ; Fourier transform infrared spectroscopy ; Metal ; Chemistry ; Nuclear chemistry ; Chemical engineering ; Physical chemistry ; Nanotechnology ; Metallurgy Radioactive element chemistry and processing ; Chemical Synthesis and Characterization ; Adsorption and biosorption for pollutant removal
Authors: Wenjie Tan | Jiarui Zhang | Fukun Ma | Min Jing | Ningning Xing
Source: Coatings (article, 2023-08-14)
Field: Materials Science — Materials Chemistry

Thermoelectric Performance of Ca2Si Synthesized by High-Temperature Melting Ca2Si was successfully synthesized via a high-temperature melting furnace and a spark plasma sintering process, allowing its thermoelectric properties to be studied. High-temperature melting furnaces were utilized to inhibit the volatilization of Ca elements during the preparation stage, ensuring the production of high-purity Ca2Si. The resistivity of Ca2Si increased gradually with rising temperature and reached 12 mΩ·cm at 873 K, demonstrating semi-metallic characteristics. In the temperature range of 323 K–873 K, Ca2Si displayed relatively low total thermal conductivity, from 1.1 to 1.7 W·m−1·K−1. Nevertheless, Ca2Si attained a maximum thermoelectric figure of merit (ZT) of 0.1 due to the atypical behavior and electrical properties of semiconductors. In contrast, Mg2Si achieved a ZT value of 0.32 at 873 K, owing to its exceptional Seebeck coefficient. Spark plasma sintering ; Thermoelectric effect ; Materials science ; Seebeck coefficient ; Electrical resistivity and conductivity ; Thermal conductivity ; Atmospheric temperature range ; Thermoelectric materials ; Sintering ; Analytical Chemistry (journal) ; Semiconductor ; Metallurgy ; Optoelectronics ; Composite material ; Thermodynamics ; Chemistry ; Electrical engineering Advanced Thermoelectric Materials and Devices ; Semiconductor materials and interfaces ; Chalcogenide Semiconductor Thin Films
Authors: Florian Dietrich | Xavier R. Advincula | Gianpaolo Gobbo | Michael A. Bellucci | Matteo Salvalaglio
Source: ChemRxiv (preprint, 2023-10-04)
Field: Materials Science — Materials Chemistry

Machine Learning Nucleation Collective Variables with Graph Neural Networks The efficient calculation of nucleation collective variables (CVs) is one of the main limitations to the application of enhanced sampling methods to the investigation of nucleation processes in realistic environments. Here we discuss the development of a graph-based model for the approximation of nucleation CVs, which enables orders-of-magnitude gains in computational efficiency in the on-the-fly evaluation of nucleation CVs. By performing simulations on a nucleating colloidal system mimicking a multistep nucleation process from solution, we assess the model's efficiency in both postprocessing and on-the-fly biasing of nucleation trajectories with pulling, umbrella sampling and metadynamics simulations. Moreover, we probe and discuss the transferability of graph-based models of nucleation CVs across systems by using the model of a CV based on sixth-order Steinhardt parameters trained on a colloidal system to drive the nucleation of crystalline copper from its melt. Our approach is general and potentially transferable to more complex systems as well as to different CVs. Nucleation ; Metadynamics ; Computer science ; Graph ; Statistical physics ; Process (computing) ; Biological system ; Artificial intelligence ; Materials science ; Chemistry ; Theoretical computer science ; Molecular dynamics ; Physics ; Computational chemistry ; Thermodynamics Machine Learning in Materials Science ; nanoparticles nucleation surface interactions ; Material Dynamics and Properties
Authors: Lvzhou Li | Lijun Wang | Xu Dong | Yaoyao Jiang | Jianning Ding | Ningyi Yuan
Source: ACS Omega (article, 2023-11-20)
Field: Materials Science — Materials Chemistry

New Nanofibrous Structured CsAg<sub>5</sub>Te<sub>3</sub> Exhibiting Ultralow Thermal Conductivity and High Figure of Merit Low-thermal-conductivity materials are ideal candidates for high-performance thermoelectric materials. CsAg<sub>5</sub>Te<sub>3</sub> is a new metal-rich chalcogenide with an inherent low-thermal conductivity. However, due to its complex crystal structure, obtaining high-purity CsAg<sub>5</sub>Te<sub>3</sub> poses a serious challenge. In addition, the high price of pure metals Cs, Ag, and Te leads to the high cost of traditional solid-state methods for preparing CsAg<sub>5</sub>Te<sub>3</sub>. To address these issues, the preparation of CsAg<sub>5</sub>Te<sub>3</sub> with a nanostructured fiber morphology was carried out using a low-energy-intensity scalable microwave method. The CsAg<sub>5</sub>Te<sub>3</sub> nanofibers were then assembled using spark plasma sintering technology to prepare CsAg<sub>5</sub>Te<sub>3</sub> bulk with a layered structure. The lattice thermal conductivity of the CsAg<sub>5</sub>Te<sub>3</sub> nanostructured material is 0.19 W m<sup>-1</sup> K<sup>-1</sup>, which is almost the lowest among the state-of-the-art thermoelectric materials. Finally, at 673 K, the maximum <i>zT</i> value of CsAg<sub>5</sub>Te<sub>3</sub> can reach ∼0.67. This study provides a feasible pathway for low-cost preparation of nanostructured thermoelectric materials. Spark plasma sintering ; Materials science ; Chalcogenide ; Thermal conductivity ; Thermoelectric materials ; Thermoelectric effect ; Figure of merit ; Optoelectronics ; Nanotechnology ; Sintering ; Composite material Advanced Thermoelectric Materials and Devices ; Heusler alloys: electronic and magnetic properties ; 2D Materials and Applications
Authors: Mauricio J. del Razo | Daan Crommelin | Peter G. Bolhuis
Source: arXiv (Cornell University) (preprint, 2023-06-30)
Field: Materials Science — Materials Chemistry

Data-driven dynamical coarse-graining for condensed matter systems Simulations of condensed matter systems often focus on the dynamics of a few distinguished components but require integrating the dynamics of the full system. A prime example is a molecular dynamics simulation of a (macro)molecule in solution, where both the molecules(s) and the solvent dynamics needs to be integrated. This renders the simulations computationally costly and often unfeasible for physically or biologically relevant time scales. Standard coarse graining approaches are capable of reproducing equilibrium distributions and structural features but do not properly include the dynamics. In this work, we develop a stochastic data-driven coarse-graining method inspired by the Mori-Zwanzig formalism. This formalism shows that macroscopic systems with a large number of degrees of freedom can in principle be well described by a small number of relevant variables plus additional noise and memory terms. Our coarse-graining method consists of numerical integrators for the distinguished components of the system, where the noise and interaction terms with other system components are substituted by a random variable sampled from a data-driven model. Applying our methodology on three different systems -- a distinguished particle under a harmonic potential and under a bistable potential; and a dimer with two metastable configurations -- we show that the resulting coarse-grained models are not only capable of reproducing the correct equilibrium distributions but also the dynamic behavior due to temporal correlations and memory effects. Our coarse-graining method requires data from full-scale simulations to be parametrized, and can in principle be extended to different types of models beyond Langevin dynamics. Granularity ; Statistical physics ; Bistability ; Integrator ; Computer science ; Metastability ; Physics ; Quantum mechanics Block Copolymer Self-Assembly ; Markov Chains and Monte Carlo Methods ; Theoretical and Computational Physics
Authors: Sinan Mithat Muhammet
Source: Gazi University Journal of Science Part A Engineering and Innovation (article, 2023-03-08)
Field: Chemistry — Organic Chemistry

Design, DFT Calculations and Antimicrobial Activity of New Synthesized Piperazine Derivative The title compound (2,2'-(piperazine-1,4-diyl)bis(N'-((E)-5-chloro-2-hydroxybenzylidene) acetohydrazide) (5-ClPAH) was synthesized by reacting 1,4-Piperazinediacetic acid, 1,4-dihydrazide and 5 -Chloro-2-hydroxybenzaldehyde. Mass spectrometry, 1H, 13C-NMR, IR results of the synthesized compound were examined. Many information about physical and chemical properties of 5-ClPAH can be obtained by theoretical calculations. Density functional theory (DFT) is widely used theoretical method for predicting of chemical structures. The structure was optimized using DFT/6311G method with GAUSSIAN09. Frontier Molecular Orbitls (HOMO and LUMO) energies were calculated. Global reactivity descriptors and also electrophilic and nucleophilic regions were defined by molecular electrostatic potential surface. Antibacterial and fungal activity were evaluated. Piperazine ; Density functional theory ; HOMO/LUMO ; Chemistry ; Electrophile ; Nucleophile ; Reactivity (psychology) ; Derivative (finance) ; Computational chemistry ; Carbon-13 NMR ; Chemical shift ; Antibacterial activity ; Combinatorial chemistry ; Molecule ; Physical chemistry ; Stereochemistry ; Organic chemistry ; Catalysis Synthesis and biological activity ; Bioactive Compounds and Antitumor Agents ; Structural and Chemical Analysis of Organic and Inorganic Compounds
Authors: Alec Glisman | Sriteja Mantha | Decai Yu | Eric Wasserman | Scott A. Backer | Zhen‐Gang Wang
Source: arXiv (Cornell University) (preprint, 2023-11-17)
Field: Chemistry — Physical and Theoretical Chemistry

Multi-valent Ion Mediated Polyelectrolyte Association and Structure Polyelectrolytes are commonly used to chelate multi-valent ions in aqueous solutions, playing a critical role in water softening and the prevention of mineralization. At sufficient ionic strength, ion-mediated polyelectrolyte--polyelectrolyte interactions can precipitate polyelectrolyte--ion complexes, a phenomenon known as "like-charge attraction". While the significant influence of small ions on polyelectrolyte solution phase behavior is recognized, the precise molecular mechanisms driving the counterintuitive phenomenon remain largely elusive. In this study, we employ all-atom molecular dynamics simulations to investigate the molecular mechanism of like-charge attraction between two poly(acrylic acid) (PAA) chains in solution. We find that moderate quantities of Ca$^{2+}$ ions induce attraction between PAA chains, facilitated by the formation of PAA--Ca$^{2+}$--PAA bridges and a significant increase in the coordination of Ca$^{2+}$ ions by the PAA chains. At high Ca$^{2+}$ number densities, ion bridges are disfavored due to electrostatic screening, yet the chains are still attracted to each other due to solvent-mediated interactions between the chains and their chelated ions. The insights gleaned from this study not only enrich our understanding of the intricate mechanism of like-charge attraction between polyanions in solution but also illuminate the influence of multi-valent ions on polyelectrolyte interactions. Polyelectrolyte ; Ion ; Chemical physics ; Electrostatics ; Chemistry ; Aqueous solution ; Molecular dynamics ; Polymer ; Computational chemistry ; Physical chemistry ; Organic chemistry Electrostatics and Colloid Interactions ; Surfactants and Colloidal Systems ; Environmental Chemistry and Analysis
Authors: Luca Artiglia | Xiansheng Li | Xing Wang | Arik Beck | Mikalai A. Artsiusheuski | Qianyu Liu | Qiang Liu | Frank Krumeich | Ulrich Aschauer | Jeroen A. van Bokhoven
Source: Research Square (preprint, 2023-06-28)
Field: Materials Science — Materials Chemistry

Quantifying electronic structure and geometric effects on the activity of Pt/CeO2 catalysts for the water-gas shift reaction Catalysis ; X-ray photoelectron spectroscopy ; Platinum nanoparticles ; Platinum ; Electronic structure ; Nanoparticle ; Chemical physics ; Materials science ; Atom (system on chip) ; Water-gas shift reaction ; Kinetic energy ; Spectroscopy ; Chemistry ; Nanotechnology ; Chemical engineering ; Computational chemistry ; Computer science ; Physics ; Organic chemistry Catalytic Processes in Materials Science ; Nanomaterials for catalytic reactions ; Electrocatalysts for Energy Conversion
Authors: Jan P. Unsleber
Source: ChemRxiv (preprint, 2023-04-19)
Field: Materials Science — Materials Chemistry

Accelerating Reaction Network Explorations with Automated Reaction Template Extraction and Application Autonomously exploring chemical reaction networks with first-principles methods can generate vast data. Especially autonomous explorations without tight constraints risk getting trapped in regions of reaction networks that are not of interest. In many cases, these regions of the networks are only exited once fully searched. Consequently, the required human time for analysis and computer time for data generation can make these investigations unfeasible. Here, we show how simple reaction templates can facilitate the transfer of chemical knowledge from expert input or existing data into new explorations. This process significantly accelerates reaction network explorations and improves cost-effectiveness. We discuss the definition of the reaction templates and their generation based on molecular graphs. The resulting, simple filtering mechanism for autonomous reaction network investigations is exemplified with a polymerization reaction. Computer science ; Template ; Simple (philosophy) ; Process (computing) ; Programming language Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Bioinformatics and Genomic Networks