jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Alexey S. Kotykhov | Max Hodapp | Christian Tantardini | Konstantin Kravtsov | Ivan A. Kruglov | Alexander V. Shapeev | Ivan S. Novikov
Source: arXiv (Cornell University) (preprint, 2024-12-28)
Field: Materials Science — Materials Chemistry

Actively-trained magnetic Moment Tensor Potentials for mechanical, dynamical, and thermal properties of paramagnetic CrN We present a protocol for automated fitting of magnetic Moment Tensor Potential explicitly including magnetic moments in its functional form. For the fitting of this potential we use energies, forces, stresses, and magnetic forces (negative derivatives of energies with respect to magnetic moments) of configurations selected with an active learning algorithm. These selected configurations are computed using constrained density functional theory, which enables calculating energies and their derivatives for both equilibrium and non-equilibrium (excited) magnetic states. We test our protocol on the system of B1-CrN and demonstrate that the automatically trained magnetic Moment Tensor Potential reproduces mechanical, dynamical, and thermal properties, of B1-CrN in the paramagnetic state with respect to density functional theory and experiments. Paramagnetism ; Moment tensor ; Tensor (intrinsic definition) ; Magnetic moment ; Moment (physics) ; Condensed matter physics ; Thermal ; Physics ; Materials science ; Statistical physics ; Classical mechanics ; Mathematics ; Thermodynamics ; Geometry ; Magnitude (astronomy) Boron and Carbon Nanomaterials Research ; Metal and Thin Film Mechanics ; Diamond and Carbon-based Materials Research
Authors: D. V. Tsygankov | Alena V. Polozova | A.O. Tyrtov | D.D. Kretsheva | I.G. Leonenko
Source:  (article, 2024-12-12)
Field: Chemistry — Analytical Chemistry

PROSPECTS FOR THE USE OF ALCOHOL FUELS AT THE PRESENT STAGE Stage (stratigraphy) ; Alcohol ; Computer science ; Process engineering ; Environmental science ; Waste management ; Engineering ; Chemistry ; Geology ; Organic chemistry Petroleum Processing and Analysis ; Biodiesel Production and Applications ; Coal Combustion and Slurry Processing
Authors: Rashmi. N.G
Source: African Journal of Biomedical Research (article, 2024-12-31)
Field: Chemistry — Spectroscopy

Advancing Antidepressant Therapy:The RoleOfChirality,Single-Enantiomer Formulations, AndPersonalized MedicineInEnhancing EfficacyAndSafetyA Review Chirality plays a significant role in the pharmacology, safety, and efficacy of antidepressants like duloxetine and paroxetine. The development of single-enantiomer formulations of these drugs offers the potential for enhanced therapeutic effects by targeting the most active enantiomer while minimizing adverse effects associated with the less potent counterpart. This approach optimizes the benefit-risk ratio and improves the long-term management of depression and anxiety. To ensure drug quality and safety, spectroscopic methods and pharmacological profiling are essential. Spectroscopy confirms the purity and structural integrity of drugs, preventing contaminants and ensuring batch consistency. Pharmacological profiling helps identify the optimal therapeutic effects, detect potential side effects, and improve safety, thus aiding in the development of more effective antidepressants. Ongoing research into chiral antidepressants is crucial for advancing psychopharmacology, offering more personalized and targeted treatments for mood disorders. Innovations in drug design, synthesis, and profiling will allow for antidepressants that are better tailored to individual patient needs, leading to fewer side effects and improved long-term outcomes. As personalized medicine becomes the standard, chiral antidepressants will play a central role in delivering more precise, effective treatments worldwide. Continued research in this field is essential to unlocking the full potential of these medications, addressing the diverse needs of patients with depression and anxiety, and advancing the overall effectiveness of antidepressant therapy. Medicine ; Antidepressant ; Adverse effect ; Duloxetine ; Anxiety ; Drug ; Paroxetine ; Pharmacology ; Mood ; Intensive care medicine ; Psychiatry ; Alternative medicine Analytical Chemistry and Chromatography ; Innovative Microfluidic and Catalytic Techniques Innovation ; Computational Drug Discovery Methods
Authors: William Freitas | B De Abreu | S. A. Vitiello
Source: arXiv (Cornell University) (preprint, 2024-11-04)
Field: Materials Science — Materials Chemistry

Neural network-based nodal structures optimization for interacting fermionic systems Simulating strongly correlated fermionic systems remains a fundamental challenge in quantum physics, largely due to the sign problem in quantum Monte Carlo (QMC) methods. We present a neural network-based variational Monte Carlo (NN-VMC) approach, leveraging a flexible neural network ansatz to represent the many-body wavefunction. Focusing on quantum dots with up to 30 electrons, we demonstrate that NN-VMC significantly reduces variational bias and achieves ground-state energies surpassing those of fixed-node diffusion Monte Carlo (DMC). A key feature is that the neural network adaptively learns and optimizes nodal structures during energy minimization. We provide qualitative insights into the nodal structure of fermionic wavefunctions by comparing the nodal structures generated by NN-VMC with those obtained from traditional trial functions. Additionally, we reveal spin-resolved radial distributions and electron density profiles, highlighting the versatility and accuracy of NN-VMC. This work underscores the potential of machine learning to advance quantum simulations and deepen our understanding of strongly correlated systems. NODAL ; Fermion ; Computer science ; Physics ; Particle physics ; Biology ; Anatomy Machine Learning in Materials Science ; Surface and Thin Film Phenomena ; Quantum and electron transport phenomena
Authors: Tapas Kumar Mohapatra | Priyanka Behera | Pranav Arvindkumar Patel | Rajesh Pothal
Source: International Journal of Pharmaceutical Research and Applications (article, 2024-05-01)
Field: Materials Science — Biomaterials

Nano based drug delivery systems: Emerging trends and future prospects Drug delivery systems based on nanotechnology have enormous potential to transform medicine by improving therapeutic efficacy, lowering side effects, and facilitating precision medicine. Liposomes, solid lipid nanoparticles, polymeric nanoparticles, and dendrimers are examples of nanocarriers that have shown notable benefits in terms of drug solubility, bioavailability, sitespecific and controlled delivery to diseased cells. By providing controlled and sustained release mechanisms, these systems minimise systemic toxicity and enable optimal dosing schedules. Through ligand functionalisation, responsive release to environmental stimuli (such as pH or temperature), and integration with diagnostic imaging for theragnostic applications, future developments seek to enhance targeted delivery. Biocompatibility, decreased immunogenicity, and scalability for broad clinical application are other emerging trends. The opportunities and challenges of nanomedicines in delivering drugs from natural or synthetic sources to clinical use. In the field of nanotechnology, there are numerous drug delivery systems based on nanotechnology. Additionally, gene therapy, cancer treatment, and overcoming multidrug resistance are being investigated using nanocarriers, which could lead to a shift towards more individualised and efficient treatments for a variety of illnesses. In the field of nanotechnology, there are numerous drug delivery systems based on nanotechnology. Because of its exceptional ability to get around the restrictions and disadvantages of conventional drug delivery, the pharmaceutical and biotechnology industries might focus research on nanotechnology applications in drug delivery. Nanocarriers ; Drug delivery ; Nanotechnology ; Solid lipid nanoparticle ; Nanomedicine ; Drug ; Pharmacology ; Medicine ; Materials science ; Nanoparticle Nanoparticle-Based Drug Delivery ; RNA Interference and Gene Delivery ; Computational Drug Discovery Methods
Authors: Chanbum Park | Soumya Ghosh | Harald Forbert | Dominik Marx
Source: Research Square (preprint, 2024-12-04)
Field: Chemistry — Electrochemistry

Distinct solvation patterns of OH– versus H3O+ charge defects atelectrified gold/water interfaces govern their properties Solvation ; Chemistry ; Aqueous solution ; Charge density ; Adsorption ; Electrochemistry ; Molecule ; Chemical physics ; Crystallography ; Inorganic chemistry ; Analytical Chemistry (journal) ; Physical chemistry ; Electrode ; Physics Electrochemical Analysis and Applications ; Electrocatalysts for Energy Conversion ; Machine Learning and ELM
Authors: José Luís Velázquez‐Libera | Rodrigo Recabarren | David Adrian Saez | Carlos Fernández‐del Castillo | J. Javier Ruiz‐Pernía | Iñaki Tuñón | Esteban Vöhringer‐Martinez
Source: ChemRxiv (preprint, 2024-12-12)
Field: Chemistry — Inorganic Chemistry

Adapted DFTB3 repulsive potentials reach DFT accuracy for hydride transfer reactions in enzymes Enzymatic hydride transfer reactions play a crucial role in numerous metabolic pathways, yet their accurate computational modeling remains challenging due to the trade-off between accuracy and computational efficiency. Ideally, molecular dynamics simulations should sample all enzyme configurations along the reaction path using post Hartree-Fock or DFT QM/MM electrostatic embedding methods, but these are computationally expensive. Here, we introduce a simple approach to improve the third-order density functional tight binding (DFTB3) semi-empirical method to model hydride transfer reactions in enzymes. We identified deficiencies in DFTB3's description of the potential energy surface for the hydride transfer step in Crotonyl-CoA Carboxylase/Reductase (Ccr) and developed a systematic methodology to address these limitations. Our approach involves modifying DFTB3's repulsive potential functions using linear combinations of harmonic functions, guided by analysis of C-H and C-C distance distributions along the reaction path. The optimized DFTB3 Hamiltonian significantly improved the description of the hydride transfer reaction in Ccr, reproducing the reference DFT activation barrier within 0.1 kcal/mol. We also addressed the transferability of our method by applying it to another hydride transfer reaction bearing the 1,4-dihydropyridine motif but exhibiting distinct structural features of the reactant and the hydride transfer reaction in Dihydrofolate Reductase (DHFR). In both cases our adapted DFTB3 Hamiltonian correctly reproduced the experimentally observed activation barrier. The low computational cost and transferability of our method will enable more accurate and efficient QM/MM molecular dynamics simulations of hydride transfer reactions, potentially accelerating research in enzyme engineering and drug design. Hydride ; Chemistry ; Computational chemistry ; Hamiltonian (control theory) ; Transferability ; Molecular dynamics ; Density functional theory ; Reaction coordinate ; Computer science ; Hydrogen ; Mathematics Metal-Catalyzed Oxygenation Mechanisms ; Protein Structure and Dynamics ; CO2 Reduction Techniques and Catalysts
Authors: Cameron A. Gorsak | Henry J. Bowman | Katie R. Gann | Buontempo, Joshua T. | Kathleen T. Smith | Tripathi, Pushpanshu | Jacob Steele | Debdeep Jena | Darrell G. Schlom | Xing, Huili Grace | Michael O. Thompson | Hari P. Nair
Source: arXiv (Cornell University) (preprint, 2024-08-02)
Field: Materials Science — Electronic, Optical and Magnetic Materials

In situ etching of \b{eta}-Ga2O3 using tert-butyl chloride in an MOCVD system In this study, we investigate in situ etching of \b{eta}-Ga2O3 in a metal-organic chemical vapor deposition (MOCVD) system using tert-Butyl chloride (TBCl). We report the successful etching of both heteroepitaxial (-201)-oriented and homoepitaxial (010)-oriented \b{eta}-Ga2O3 films over a wide range of substrate temperature, TBCl molar flows, and reactor pressures. We identify that the likely etchant is HCl (g) formed by the pyrolysis of TBCl in the hydrodynamic boundary layer above the substrate. The temperature dependence of the etch rate reveals two distinct regimes characterized by markedly different apparent activation energies. The extracted apparent activation energies suggest that at temperatures below ~800 °C the etch rate is likely limited by desorption of etch products. The relative etch rates of heteroepitaxial (-201) and homoepitaxial (010) \b{eta}-Ga2O3 were observed to scale by the ratio of the surface energies indicating an anisotropic etch. For (010) homoepitaxial films, relatively smooth post-etch surface morphology was achieved by tuning the etching parameters. Metalorganic vapour phase epitaxy ; In situ ; Chloride ; Etching (microfabrication) ; Materials science ; Optoelectronics ; Chemistry ; Nanotechnology ; Metallurgy ; Organic chemistry ; Epitaxy Ga2O3 and related materials ; Semiconductor materials and devices ; Advanced Photocatalysis Techniques
Authors: Alexis-Raja Brachet | Pierre-Yves Richard | Céline Hudelot
Source: arXiv (Cornell University) (preprint, 2024-05-22)
Field: Materials Science — Materials Chemistry

Bond Graphs for multi-physics informed Neural Networks for multi-variate time series In the trend of hybrid Artificial Intelligence techniques, Physical-Informed Machine Learning has seen a growing interest. It operates mainly by imposing data, learning, or architecture bias with simulation data, Partial Differential Equations, or equivariance and invariance properties. While it has shown great success on tasks involving one physical domain, such as fluid dynamics, existing methods are not adapted to tasks with complex multi-physical and multi-domain phenomena. In addition, it is mainly formulated as an end-to-end learning scheme. To address these challenges, we propose to leverage Bond Graphs, a multi-physics modeling approach, together with Message Passing Graph Neural Networks. We propose a Neural Bond graph Encoder (NBgE) producing multi-physics-informed representations that can be fed into any task-specific model. It provides a unified way to integrate both data and architecture biases in deep learning. Our experiments on two challenging multi-domain physical systems - a Direct Current Motor and the Respiratory System - demonstrate the effectiveness of our approach on a multivariate time-series forecasting task. Series (stratigraphy) ; Bond ; Random variate ; Statistical physics ; Artificial neural network ; Computer science ; Artificial intelligence ; Mathematics ; Physics ; Economics ; Geology ; Statistics ; Finance ; Paleontology ; Random variable Machine Learning in Materials Science ; Model Reduction and Neural Networks ; Neural Networks and Applications
Authors: Md Faizul Islam | Gamage Isuri P. Wijesekera | Anmon J. Sindt | Mark D Smith | Linda S. Shimizu
Source: Scholar Commons (University of South Carolina) (article, 2024-10-03)
Field: Materials Science — Materials Chemistry

Examination of Photoinduced Radicals in Two Crystal Forms of Triphenylamine Bis-Urea Macrocycles This study probes two solvates of triphenylamine (TPA) bis-urea macrocycle 1 and their activated structures to evaluate their maximum photoinduced radicals (PIRs), the subsequent decay of the radicals, and their regeneration. The hierarchical assembly of TPAs shows promise in stabilizing less substituted derivatives, potentially expanding the utility of TPAs that lack stabilizing para-substituents. Single crystal structure analysis reveals that host 1 adopts a planar conformation with the two ureas pointing in opposite directions when dimethoxyethane (DME) is encapsulated within the channel. Whereas previously, 1 adopted a bowl-shaped conformation with the two ureas pointing in the same direction (syn) with dimethylsulfoxide (DMSO) bound within the channels. Removal of the guests gives identical activated structures. The bulk materials of 1 are characterized by powder X-ray diffraction (PXRD), thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC). Finally, the process of radical generation under UV-irradiation, decay, and regeneration of radicals was monitored by electron paramagnetic resonance (EPR) spectroscopy. While macrocycle conformation and extended structure are important, the presence of guests was most significant for PIR percentages. Radical ; Electron paramagnetic resonance ; Triphenylamine ; Thermogravimetric analysis ; Crystal (programming language) ; Differential scanning calorimetry Photochromic and Fluorescence Chemistry ; Photopolymerization techniques and applications ; Advanced Polymer Synthesis and Characterization
Authors: Olivera Kosic | Milentije Luković | M. Spasojević | A. Maričić | Miroslav Spasojević
Source: Science of Sintering (article, 2024-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Influence of grinding and pressing of the powder 50.0 wt% Fe, 47.0 wt% BaTiO3 and 3.0 wt% TiO2 on morphology, microstructure and magnetic properties Mixing the powders Fe (50.0 wt%), BaTiO3 (47.0 wt%) and TiO2 (3.0wt%) provides a mixture consisting of a matrix of smaller particles BaTiO3 in which larger particles Fe and TiO2 were embedded. The powder grinding results in the crystal grains cracking, increase in both dislocations and internal microstrains, aggregates formation, decrease in the content of crystalline phases due to formation of amorphous and oxidation of Fe in its oxides. Crushing of Fe crystalline grains with increasing grinding time up to 110 min causes an increase in magnetization. With further increase in the grinding time up to 170 min, the magnetization decreases due to lowering of the Fe content, resulting from FeO formation. From 170 min to 220 min, the oxidation of FeO to Fe3O4 and Fe2O3 causes an increase in the magnetization. Annealing the pressed sample ground for 110 minutes from 270 to 400 ?C results in the structural relaxation and thus, the increase in magnetization of the cooled sample. In the temperature range of 400 to 620 ?C, by increasing the annealing temperature up to 440 ?C the magnetization of the cooled sample increases, reaches its maximum and hereafter decreases. This magnetization change is mainly due to sudden increase in the size of Fe crystal grains and oxidation of Fe to FeO. Materials science ; Magnetization ; Grinding ; Amorphous solid ; Microstructure ; Annealing (glass) ; Metallurgy ; Crystal (programming language) ; Analytical Chemistry (journal) ; Crystallography ; Chemistry ; Magnetic field Magnetic Properties of Alloys ; Powder Metallurgy Techniques and Materials ; Metallic Glasses and Amorphous Alloys
Authors: Hayriye Hale Aygün
Source: Journal of Nanotechnology (article, 2024-01-01)
Field: Materials Science — Biomaterials

Tailoring the Morphological Properties of PVA Nanofibrous Mats by Manipulating Working Planes Despite the process, solution, and ambient parameters of the electrospinning technique have been intensely studied, the effects of different setup orientations have not been thoroughly investigated. In many research studies, the attempts on electrospinning of polyvinyl alcohol have been performed with a horizontal electrospinning or researchers have not even mentioned the setup orientation. This paper examines the morphological properties of polyvinyl alcohol‐based fibrous mats electrospun with the same apparatus and identical process and solution parameters but with different working planes, namely, (x)‐axis, (+y) axis, and (−y) axis. From the test results, it is concluded that the (−y) axis is the most versatile working plane because fibrous mats have the finest nanofiber diameters with the lowest diameter variation, the medium‐level pore area with the smallest pore sizes. Besides, the highest packing density and highly deposited structure with the longest fibers with a high aspect ratio are constructed in this setup orientation. (−y) axis electrospinning is more favorable than that of other working planes for polyvinyl alcohol‐based permeable membranes and biostructures. Materials science ; Composite material ; Nanofiber ; Nanotechnology Electrospun Nanofibers in Biomedical Applications ; Advanced Sensor and Energy Harvesting Materials ; Tissue Engineering and Regenerative Medicine
Authors: Marcus Schwarting | Nathan A. Seifert | Michael J. Davis | Ben Blaiszik | Ian Foster | Kirill Prozument
Source: arXiv (Cornell University) (preprint, 2024-04-05)
Field: Chemistry — Spectroscopy

Twins in rotational spectroscopy: Does a rotational spectrum uniquely identify a molecule? Rotational spectroscopy is the most accurate method for determining structures of molecules in the gas phase. It is often assumed that a rotational spectrum is a unique "fingerprint" of a molecule. The availability of large molecular databases and the development of artificial intelligence methods for spectroscopy makes the testing of this assumption timely. In this paper, we pose the determination of molecular structures from rotational spectra as an inverse problem. Within this framework, we adopt a funnel-based approach to search for molecular twins, which are two or more molecules, which have similar rotational spectra but distinctly different molecular structures. We demonstrate that there are twins within standard levels of computational accuracy by generating rotational constants for many molecules from several large molecular databases, indicating the inverse problem is ill-posed. However, some twins can be distinguished by increasing the accuracy of the theoretical methods or by performing additional experiments. Rotational spectrum ; Spectroscopy ; Rotational–vibrational spectroscopy ; Rotational spectroscopy ; Rotational partition function ; Molecule ; Rotational transition ; Physics ; Rotational dynamics ; Nuclear magnetic resonance ; Molecular physics ; Classical mechanics ; Quantum mechanics ; Angular momentum Molecular Spectroscopy and Structure ; Atmospheric Ozone and Climate ; Cold Atom Physics and Bose-Einstein Condensates