jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: José Manuel Terrés | Javier Monreal-Trigo | Andy Hernández‐Montoto | Javier Ibáñez Civera | Rafael Masot | Ramón Martínez‐Máñez
Source: Bioengineering (article, 2023-02-09)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Finite Element Models of Gold Nanoparticles and Their Suspensions for Photothermal Effect Calculation (1) Background: The ability of metal nanoparticles to carry other molecules and their electromagnetic interactions can be used for localized drug release or to heat malignant tissue, as in the case of photothermal treatments. Plasmonics can be used to calculate their absorption and electric field enhancement, which can be further used to predict the outcome of photothermal experiments. In this study, we model the nanoparticle geometry in a Finite Element Model calculus environment to calculate the effects that occur as a response to placing it in an optical, electromagnetic field, and also a model of the experimental procedure to measure the temperature rise while irradiating a suspension of nanoparticles. (2) Methods: Finite Element Method numerical models using the COMSOL interface for geometry and mesh generation and iterative solving discretized Maxwell's equations; (3) Results: Absorption and scattering cross-section spectrums were obtained for NanoRods and NanoStars, also varying their geometry as a parameter, along with electric field enhancement in their surroundings; temperature curves were calculated and measured as an outcome of the irradiation of different concentration suspensions; (4) Conclusions: The results obtained are comparable with the bibliography and experimental measurements. Finite element method ; Photothermal therapy ; Materials science ; Nanoparticle ; Nanorod ; Absorption (acoustics) ; Electric field ; Electromagnetic field ; Discretization ; Plasmon ; Suspension (topology) ; Plasmonic nanoparticles ; Nanotechnology ; Mechanics ; Physics ; Optoelectronics ; Composite material ; Mathematical analysis ; Thermodynamics ; Mathematics Gold and Silver Nanoparticles Synthesis and Applications ; Plasmonic and Surface Plasmon Research ; Nanoparticles: synthesis and applications
Authors: Jiali Yu | Uğur Uzuner | Bin Long | Zachary Wang | Joshua S. Yuan | Susie Y. Dai
Source: iScience (article, 2023-02-27)
Field: Chemistry — Spectroscopy

Artificial intelligence-based HDX (AI-HDX) prediction reveals fundamental characteristics to protein dynamics: Mechanisms on SARS-CoV-2 immune escape Three-dimensional structure and dynamics are essential for protein function. Advancements in hydrogen-deuterium exchange (HDX) techniques enable probing protein dynamic information in physiologically relevant conditions. HDX-coupled mass spectrometry (HDX-MS) has been broadly applied in pharmaceutical industries. However, it is challenging to obtain dynamics information at the single amino acid resolution and time consuming to perform the experiments and process the data. Here, we demonstrate the first deep learning model, artificial intelligence-based HDX (AI-HDX), that predicts intrinsic protein dynamics based on the protein sequence. It uncovers the protein structural dynamics by combining deep learning, experimental HDX, sequence alignment, and protein structure prediction. AI-HDX can be broadly applied to drug discovery, protein engineering, and biomedical studies. As a demonstration, we elucidated receptor-binding domain structural dynamics as a potential mechanism of anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody efficacy and immune escape. AI-HDX fundamentally differs from the current AI tools for protein analysis and may transform protein design for various applications. Protein dynamics ; Protein structure ; Computer science ; Hydrogen–deuterium exchange ; Artificial intelligence ; Computational biology ; Chemistry ; Biology ; Mass spectrometry Mass Spectrometry Techniques and Applications ; Analytical Chemistry and Chromatography ; RNA and protein synthesis mechanisms
Authors: Tiernan Baucom | Samir Budhathoki | Janice A. Steckel
Source: The Journal of Physical Chemistry C (article, 2023-08-29)
Field: Chemistry — Inorganic Chemistry

Effect of Flexibility in Molecular Simulations of Carbon Dioxide Adsorption and Diffusion in a Cuprous Triazolate Framework Using fixed atom force fields to model gas adsorption in flexible metal–organic frameworks (MOFs) is known to pose difficulties in accurately reproducing and predicting experimental results. This paper studies the difference in accuracy between flexible and fixed atom force fields in reproducing CO2 adsorption measurements in MAF-2 ([Cu(etz)]∞ (MAF-2, Hetz) 3,5-diethyl-1,2,4-triazole), an NbO-type triazolate scaffold with a bcu cavity system and attached ethyl groups. The flexible force field used to run the hybrid molecular dynamics, and grand canonical Monte Carlo calculations were generated using QuickFF software incorporating van der Waals parameters from the universal force field (UFF) and density derived electrostatic and chemical (DDEC) charges. The fixed atom force field used was composed of UFF van der Waals parameters together with DDEC charges. The calculations were run at 298 K and pressures of 0.1, 0.3, 0.5, 0.8, and 1 bar. It was observed that for this MOF the rigid force field overpredicted gas adsorption, whereas the flexible force field values closely matched experimental data. In the flexible structure, the freely moving ethyl groups of MAF-2 hindered adsorption, reducing the interaction energy between CO2 and the N atoms of the triazolate framework as well as reducing the size of the largest cavity diameter. The combination of these factors led to improved prediction of adsorption values with the flexible force field as compared to the rigid force field, demonstrating the need for modeling MOFs in a way more indicative of their behavior. van der Waals force ; Force field (fiction) ; Adsorption ; Chemistry ; Molecular dynamics ; Natural bond orbital ; Atom (system on chip) ; Computational chemistry ; Partial charge ; Density functional theory ; Chemical physics ; Thermodynamics ; Molecule ; Physical chemistry ; Physics ; Organic chemistry ; Quantum mechanics Metal-Organic Frameworks: Synthesis and Applications ; Crystallography and molecular interactions ; Machine Learning in Materials Science
Authors: Chiayee Salih Ajaj | Diyar Sadiq
Source: Nanomaterials and Nanotechnology (article, 2023-09-20)
Field: Materials Science — Materials Chemistry

Mulberry Juice-Derived Carbon Quantum Dots as a Cu2+ Ion Sensor: Investigating the Influence of Fruit Ripeness on the Optical Properties This study synthesized carbon quantum dots (CQDs) with green photoluminescence through a hydrothermal method that utilized mulberry juice as the carbon source. The influence of fruit ripeness on the physical and chemical properties, focusing on the fluorescence spectra, has been explored. Fourier-transform infrared spectroscopy (FT-IR) and energy dispersive X-ray analysis (EDX) showed that there were oxygen-containing groups, and X-ray diffraction (XRD) showed that the carbon quantum dots (CQDs) were graphitic. The results revealed that the CQDs had an average size of around 7.4 nm and 9.7 nm for unripe and ripe mulberry juice, respectively. These CQDs emitted green light at 500 nm and 510 nm in unripe and ripe mulberry juice, respectively, when excited at a wavelength of 400 nm. The prepared CQDs exhibited excitation-dependent photoluminescence (PL) emission behavior, demonstrating their dependence on the excitation light. The impact of fruit ripeness on optical properties was explored by examining fluorescent spectra from different fruits (including tomato and blackberry), demonstrating comparable behaviors observed in mulberry fruit. In addition, the prepared CQDs were utilized as a fluorescent sensor with high specificity to detect Cu2+ ions. The detection limit (DL) for this sensor was determined to be 0.2687 µM, and the limit of qualification (LOQ) is 0.814 µM. The linear range for detection lies between 0.1 and 1 µM. The selectivity of the CQDs towards Cu2+ ions was confirmed by recording the PL response for Cu2+ ions compared to the weak response of other metal ions. According to these results, the CQDs can be applied in various cellular imaging and biology applications, bio-sensing, optoelectronics, and sensors. Ripeness ; Photoluminescence ; Fluorescence ; Ion ; Detection limit ; Materials science ; Analytical Chemistry (journal) ; Fourier transform infrared spectroscopy ; Excited state ; Carbon fibers ; Spectroscopy ; Chemistry ; Optoelectronics ; Optics ; Food science ; Chromatography ; Atomic physics ; Organic chemistry ; Physics Carbon and Quantum Dots Applications ; Electrochemical sensors and biosensors ; Quantum Dots Synthesis And Properties
Authors: Boyu Yan | Ying Yang | Yinyun Xie | Jinzhao Li | Kun Li
Source: Chemistry (article, 2023-05-23)
Field: Materials Science — Materials Chemistry

Fe Doping Enhances the Peroxidase-Like Activity of CuO for Ascorbic Acid Sensing Although significant advances have been witnessed in the application of nanozymes in recent years, exploring new strategies to enhance the enzyme-like activity of nanozymes is of urgent importance. Herein, we investigate the feasibility of accelerating the peroxidase-like reaction rate of CuO nanostructures through Fe doping. The coprecipitation method was used to synthesize Fe-doped CuO (Fe-CuO) nanozymes, and the results indicate that the diversified valence of Fe benefits the redox reaction driven by CuO-based nanozymes. With the improved peroxidase-like activity, the Fe-CuO nanozyme enables the significant chromogenic oxidation reaction of 3,3′,5,5′-tetramethylbenzidine (TMB), facilitating the construction of a visual sensing platform for the sensitive and selective determination of ascorbic acid. Under optimal conditions, the absorbance at 652 nm decreases linearly with the concentration of ascorbic acid in the range of 5–50 μM, with a limit of detection as low as 4.66 μM. This work exemplifies the activity enhancement for peroxidase-mimicking nanozymes with a metal-doping strategy and provides a broad prospect for the design of more high-performance nanozymes for biosensing applications. Ascorbic acid ; Chemistry ; Doping ; Coprecipitation ; Detection limit ; Absorbance ; Peroxidase ; Biosensor ; Nanotechnology ; Redox ; Chromogenic ; Chemiluminescence ; Catalysis ; Combinatorial chemistry ; Inorganic chemistry ; Chemical engineering ; Materials science ; Enzyme ; Optoelectronics ; Physical chemistry ; Chromatography ; Organic chemistry Advanced Nanomaterials in Catalysis ; Advanced biosensing and bioanalysis techniques ; Electrochemical sensors and biosensors
Authors: Manoj Kumar Mahawar | Ashok Kumar Bharimalla | A. Arputharaj | Jagdish Palkar | Jyoti Dhakane‐Lad | Kirti Jalgaonkar | N. Vigneshwaran
Source: Scientific Reports (article, 2023-11-24)
Field: Materials Science — Biomaterials

Response surface optimization of process parameters for preparation of cellulose nanocrystal stabilized nanosulphur suspension This study employed response surface methodology (RSM) to optimize various parameters involved in the synthesis of nanosulphur (NS) stabilized by cellulose nanocrystals (CNCs). The elemental sulphur (ES) mixed with CNCs was processed in a high-pressure homogenizer to make a stable formulation of CNC-stabilized NS (CNC-NS). RSM was adopted to formulate the experiments using Box-Behnken design (BBD) by considering three independent variables i.e., ES (5, 10, 15 g), CNCs (25, 50, 75 ml), and the number of passes (NP) in the high-pressure homogenizer (1, 2, 3). For the prepared suspensions (CNC-NS), the range of the responses viz. settling time (0.84-20.60 min), particle size (500.41-1432.62 nm), viscosity (29.20-420.60 cP), and surface tension (60.35-73.61 N/m) were observed. The numerical optimization technique was followed by keeping the independent and dependent factors in the range yielded in the optimized solution viz. 46 ml (CNCs), 8 g (ES), and 2 (NP). It was interpreted from the findings that the stability of the suspension had a positive correlation with the amount of CNC while the increasing proportion of ES resulted in reduced stability. The quadratic model was fitted adequately to all the responses as justified with the higher coefficient of determination (R<sup>2</sup> ≥ 0.88). The characterization performed by X-ray diffraction (XRD), zeta potential, Raman spectroscopy, and Fourier transform infrared spectroscopy (FTIR) revealed better-stabilizing properties of the optimized CNCs-ES suspension. The study confirmed that CNCs have the potential to be utilized as a stabilizing agent in synthesizing stable nanosulphur formulation by high-pressure homogenization. Homogenizer ; Response surface methodology ; Materials science ; Zeta potential ; Fourier transform infrared spectroscopy ; Cellulose ; Particle size ; Suspension (topology) ; Chemical engineering ; Box–Behnken design ; Viscosity ; Central composite design ; Analytical Chemistry (journal) ; Chromatography ; Nanotechnology ; Chemistry ; Nanoparticle ; Composite material ; Mathematics Advanced Cellulose Research Studies ; Lignin and Wood Chemistry ; Nanocomposite Films for Food Packaging
Authors: Sherief A. Al Kiey | E. A. Abd El Meguid | S.S. Abd El Rehim
Source: Journal of Materials Engineering and Performance (article, 2023-04-03)
Field: Materials Science — Metals and Alloys

Electrochemical Investigations on the Corrosion Behavior of 904L Stainless Steel in LiBr Solutions Abstract The pitting corrosion susceptibility of 904L stainless steel in aerated LiBr solutions was investigated. The influence of various experimental variables, including electrolyte concentrations, pH, scan rate, temperatures, and constant potential has been studied using electrochemical measurements, such as cyclic potentiodynamic polarization, potentiostatic techniques, and electrochemical impedance spectroscopy (EIS). The surface morphology of 904L stainless steel was examined by scanning electron microscope (SEM). The rate of uniform corrosion and susceptibility toward pitting corrosion increases with an increase in LiBr concentrations and temperature. Increasing the pH of the solution decreases the rate of both uniform and pitting corrosion. An increase in the scan rate enhances the uniform corrosion, but suppresses the pitting corrosion. EIS diagrams displayed a depressed semicircles with the center under the real axis. Bode plots support the result that the uniform corrosion resistance of the alloy in LiBr solutions decreases with increasing Br − anion concentration. The observations suggest that this one time constant may actually be the overlap of two-time constants. Materials science ; Corrosion ; Dielectric spectroscopy ; Scanning electron microscope ; Pitting corrosion ; Metallurgy ; Alloy ; Polarization (electrochemistry) ; Electrolyte ; Electrochemistry ; Horizontal scan rate ; Composite material ; Cyclic voltammetry ; Electrode ; Chemistry Hydrogen embrittlement and corrosion behaviors in metals ; Corrosion Behavior and Inhibition ; Concrete Corrosion and Durability
Authors: Evan Angelo Quimada Mondarte | Yuchen Shi | Xue Qi Koh | Feng Xue-yu | Dan Daniel | Xin‐Xing Zhang | Jing Yu
Source: Macromolecules (article, 2023-06-23)
Field: Materials Science — Surfaces, Coatings and Films

Unveiling the Layered Structure of Sulfobetaine Polymer Brushes through Bimodal Atomic Force Microscopy Many zwitterionic polymer brushes exhibit highly stimuli-responsive properties stemming from the strong dipole and electrostatic interaction of their building blocks. Here, we showed how a combination of two atomic force microscopy (AFM) modes can reveal the layered structure of poly(sulfobetaine methacrylate) brushes synthesized by surface-initiated atom-transfer radical polymerization. Due to polydispersity and anti-polyelectrolyte effect, a diffused layer emerges on top of a condensed layer of the brush as a function of salt concentration. The amplitude-modulation mode of the AFM, owing to the tip’s dynamic motion, can only probe the more stable condensed layer near the substrate, whereas the force-spectroscopic mode with its high sensitivity can accurately detect the diffused layer and hence determine the total brush thickness. Infrared spectroscopy and quartz crystal microbalance monitoring revealed the strong ion-screening effect and higher brush hydration propensity of multivalent ions. Different cation valencies also showed subtle effects on the dimensionality of the layered structure. Our results highlight the usefulness of AFM in revealing various contextual phenomena that arise from the unique properties of zwitterionic polymers. Quartz crystal microbalance ; Polyelectrolyte ; Polymer ; Dispersity ; Polymer brush ; Mica ; Atom-transfer radical-polymerization ; Force spectroscopy ; Chemical physics ; Chemistry ; Methacrylate ; Polymer chemistry ; Monolayer ; Layer by layer ; Chemical engineering ; Materials science ; Layer (electronics) ; Atomic force microscopy ; Polymerization ; Nanotechnology ; Organic chemistry ; Composite material ; Adsorption Polymer Surface Interaction Studies ; Force Microscopy Techniques and Applications ; Analytical Chemistry and Sensors
Authors: Sandeep Kumar | Hossein Tahmasbi | Kushal Ramakrishna | Mani Lokamani | Svetoslav Nikolov | Julien Tranchida | Mitchell Wood | Attila Cangi
Source: Physical Review Research (article, 2023-09-06)
Field: Materials Science — Materials Chemistry

Transferable interatomic potential for aluminum from ambient conditions to warm dense matter We present a study on the transport and material properties of aluminum spanning from ambient to warm dense matter conditions using a machine-learned interatomic potential (ML-IAP). Prior research has utilized ML-IAPs to simulate phenomena in warm dense matter, but these potentials have often been calibrated for a narrow range of temperatures and pressures. In contrast, we train a single ML-IAP over a wide range of temperatures, using density functional theory molecular dynamics (DFT-MD) data. Our approach overcomes the computational limitations of DFT-MD simulations, enabling us to study the transport and material properties of matter at higher temperatures and longer time scales. We demonstrate the ML-IAP transferability across a wide range of temperatures using molecular dynamics by examining the ionic part of thermal conductivity, shear viscosity, self-diffusion coefficient, sound velocity, and structure factor of aluminum up to about 60000 K, where we find good agreement with previous theoretical data. Warm dense matter ; Molecular dynamics ; Density functional theory ; Transferability ; Diffusion ; Range (aeronautics) ; Thermal conductivity ; Aluminium ; Materials science ; Viscosity ; Interatomic potential ; Ionic bonding ; Chemistry ; Thermodynamics ; Chemical physics ; Physics ; Computational chemistry ; Plasma ; Ion ; Composite material ; Computer science ; Nuclear physics Machine Learning in Materials Science ; High-pressure geophysics and materials ; Material Dynamics and Properties
Authors: Dan Li | Tuocen Fan | Xifan Mei
Source: Nanoscale (review, 2023-01-01)
Field: Materials Science — Materials Chemistry

A comprehensive exploration of the latest innovations for advancements in enhancing selectivity of nanozymes for theranostic nanoplatforms Nanozymes have captured significant attention as a versatile and promising alternative to natural enzymes in catalytic applications, with wide-ranging implications for both diagnosis and therapy. However, the limited selectivity exhibited by many nanozymes presents challenges to their efficacy in diagnosis and raises concerns regarding their impact on the progression of disease treatments. In this article, we explore the latest innovations aimed at enhancing the selectivity of nanozymes, thereby expanding their applications in theranostic nanoplatforms. We place paramount importance on the critical development of highly selective nanozymes and present innovative strategies that have yielded remarkable outcomes in augmenting selectivities. The strategies encompass enhancements in analyte selectivity by incorporating recognition units, refining activity selectivity through the meticulous control of structural and elemental composition, integrating synergistic materials, fabricating selective nanomaterials, and comprehensively fine-tuning selectivity <i>via</i> approaches such as surface modification, cascade nanozyme systems, and manipulation of external stimuli. Additionally, we propose optimized approaches to propel the further advancement of these tailored nanozymes while considering the limitations associated with existing techniques. Our ultimate objective is to present a comprehensive solution that effectively addresses the limitations attributed to non-selective nanozymes, thus unlocking the full potential of these catalytic systems in the realm of theranostics. Nanotechnology ; Selectivity ; Materials science ; Chemistry Advanced Nanomaterials in Catalysis ; Nanocluster Synthesis and Applications ; Advanced biosensing and bioanalysis techniques
Authors: Yuanqing Wang | John D. Chodera
Source: arXiv (Cornell University) (preprint, 2023-01-21)
Field: Materials Science — Materials Chemistry

Spatial Attention Kinetic Networks with E(n)-Equivariance Neural networks that are equivariant to rotations, translations, reflections, and permutations on n-dimensional geometric space have shown promise in physical modeling for tasks such as accurately but inexpensively modeling complex potential energy surfaces to guiding the sampling of complex dynamical systems or forecasting their time evolution. Current state-of-the-art methods employ spherical harmonics to encode higher-order interactions among particles, which are computationally expensive. In this paper, we propose a simple alternative functional form that uses neurally parametrized linear combinations of edge vectors to achieve equivariance while still universally approximating node environments. Incorporating this insight, we design spatial attention kinetic networks with E(n)-equivariance, or SAKE, which are competitive in many-body system modeling tasks while being significantly faster. Equivariant map ; Computer science ; Spherical harmonics ; Formalism (music) ; Node (physics) ; Simple (philosophy) ; Artificial neural network ; Kinetic energy ; Theoretical computer science ; Sampling (signal processing) ; Topology (electrical circuits) ; Algorithm ; Mathematics ; Artificial intelligence ; Pure mathematics ; Physics ; Combinatorics ; Mathematical analysis ; Classical mechanics Machine Learning in Materials Science ; Neural Networks and Applications ; Gaussian Processes and Bayesian Inference