jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: S Sakthimurugan | S S Sukin | T. N. C. Anand
Source: INTERNATIONAL JOURNAL OF MECHANICAL ENGINEERING AND TECHNOLOGY (IJMET) (review, 2025-10-08)
Field: Materials Science — Materials Chemistry

A REVIEW ON SHOCK TUBE INNOVATIONS FOR MATERIAL IMPACT STRENGTH AND NEXT-GENERATION APPLICATIONS shock tube are powerful experimental tool that create controlled shock waves, allowing researchers to study how materials and gases behave under sudden high pressure and high temperature conditions.Once used mainly in aerodynamics and combustion research, their role has grown with the development of new design such as diaphragm les, valve driven, laser driven, and combustion driven system.These innovation have opened the door to applications in material testing, where metals, composites, ceramics, and polymers can be studied under extreme loading to better understand their strength and failure mechanisms.Modern diagnostics techniques, including schlieren imaging, interferometry, and laser based measurements, have further improved the precision of these studies.Advanced thermodynamic model, such as the NASG and Tait equation of state, now provide more accurate simulation of shock tube behavior, making them technology is evolving beyond the laboratory to support real world applications in aerospace, defense, energy, and biomedical engineering, while also pointing to future opportunities in compact high precision, and portable designs. Izod impact strength test ; Shock (circulatory) ; Tube (container) ; Strength of materials ; Impact energy ; Deformation (meteorology) High-Velocity Impact and Material Behavior ; Transportation Safety and Impact Analysis ; Structural Response to Dynamic Loads
Authors: Ziqi Guo | Xiulin Ruan | Guang Lin
Source: ArXiv.org (preprint, 2025-10-01)
Field: Materials Science — Materials Chemistry

FourPhonon_GPU: A GPU-accelerated framework for calculating phonon scattering rates and thermal conductivity Accurately predicting phonon scattering is crucial for understanding thermal transport properties. However, the computational cost of such calculations, especially for four-phonon scattering, can often be more prohibitive when large number of phonon branches and scattering processes are involved. In this work, we present FourPhonon_GPU, a GPU-accelerated framework for three-phonon and four-phonon scattering rate calculations based on the FourPhonon package. By leveraging OpenACC and adopting a heterogeneous CPU-GPU computing strategy, we efficiently offload massive, parallelizable tasks to the GPU while using the CPU for process enumeration and control-heavy operations. Our approach achieves over 25x acceleration for the scattering rate computation step and over 10x total runtime speedup without sacrificing accuracy. Benchmarking on various GPU architectures confirms the method's scalability and highlights the importance of aligning parallelization strategies with hardware capabilities. This work provides an efficient and accurate computational tool for phonon transport modeling and opens pathways for accelerated materials discovery. Speedup ; Scattering ; Computation ; Scalability ; Phonon ; Parallelizable manifold ; Process (computing) Thermal properties of materials ; Machine Learning in Materials Science
Authors: Junaid Jami | Rohit Pathak | N. Venkataramani | К. Г. Суреш | Amrita Bhattacharya
Source: ArXiv.org (preprint, 2025-07-02)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Tailoring hard magnetic properties of Fe2MnSn Heusler alloy via interstitial modification: A first-principles approach We employ first-principles calculations to explore interstitial engineering as a strategy to tailor the hard magnetic properties of Fe2MnSn Heusler alloy, establishing its potential as a rare-earth-free permanent magnet. By introducing light interstitial elements -- B, C, H, N, O, and F -- at varying concentrations (1.56-12.5 at%), we uncover significant enhancements in structural stability, magnetization, Curie temperature, and magnetocrystalline anisotropy. These dopants preferentially occupy octahedral interstitial sites in the hexagonal phase of Fe2MnSn, leading to localized lattice distortions that enhance its magnetic characteristics. Notably, at 12.5 at% doping, B, C, N, and O induce a critical transition from in-plane to out-of-plane magnetic anisotropy -- achieved without 5d or rare-earth elements -- highlighting a sustainable pathway to high-performance magnets. Among these, N-doped Fe2MnSn exhibits the highest uniaxial anisotropy (0.61 MJ/m^3), followed by the B-doped (0.44 MJ/m^3) alloy. The magnetization of the doped compounds surpasses that of conventional ferrites and gap magnets like MnAl and MnBi. The Curie temperature sees a substantial boost, reaching 1058 K for O-doped Fe2MnSn and 1000 K for the C-doped alloy. Although N-doping results in a modest increase in Tc (744 K vs. 729 K for the pristine alloy), it delivers superior hard magnetic properties, with the highest magnetic hardness (0.65) and an enhanced maximum energy product (0.36 MJ/m^3), making it a strong candidate for gap magnet applications. These findings highlight interstitial doping as a viable route to engineer rare-earth-free permanent magnets with optimized magnetic performance. Magnetocrystalline anisotropy ; Curie temperature ; Magnet ; Magnetization ; Magnetic anisotropy ; Alloy ; Dopant ; Doping ; Interstitial defect Heusler alloys: electronic and magnetic properties ; Magnetic Properties of Alloys ; Shape Memory Alloy Transformations
Authors: Senlau Sudarminto
Source: The Eurasia Proceedings of Science Technology Engineering and Mathematics (article, 2025-12-30)
Field: Materials Science — Materials Chemistry

Research Trends in the Heat Transfer Simulation of Al₂O₃/AlN Granular Composites for Thermal Interface Materials Heat transfer simulation in granular Al₂O₃/AlN composites has become an increasingly relevant topic in the development of thermal interface materials (TIMs) for high-performance electronic systems. This study conducted a bibliometric analysis of 1,169 articles from the Scopus database published between 2015 and 2025 to identify research trends, frequently occurring keywords, geographic contributions, author and institutional impacts, and to outline future research opportunities in the development of TIMs based on Al₂O₃/AlN. The analysis was performed using RStudio, VOSviewer, and Excel, identifying five main thematic clusters: (1) AI and Neuroimaging for Brain Diseases; (2) TIM Applications and Thermal Optimization; (3) Molecular Simulation and Interface Properties; (4) AI and Brain Functional Connectivity; (5) Numerical Simulation of Material Thermal Properties and (6) Materials &amp; Thermal Contact Resistance. The primary research focus includes numerical modeling of thermal conductivity, characterization of Al₂O₃ and AlN materials, and their initial applications in electronic cooling devices. While the scope remains limited at present, the annual growth in publications suggests that interest in this topic is likely to increase soon. This study provides an important initial overview of the research landscape. It opens up possibilities for future exploration, including the integration of multiscale approaches and enhanced experimental validation in heat transfer simulations involving granular composites. Thermal grease ; Interface (matter) ; Heat transfer ; Scope (computer science) ; Thermal ; Characterization (materials science) ; Thermal conductivity ; Focus (optics) Thermal properties of materials ; Advanced ceramic materials synthesis ; Advanced Thermoelectric Materials and Devices
Authors: Hafsa Ayaz | Abbas Khan | Numan Khan | Muhammad Hasnain | Suhaib Mesbah | Akhlaq Ahmad | Muhammad Rehan | Hasan Ayaz | Raheel Ahmed | Amrita Kumar Sana
Source: International Journal of Scientific Research and Modern Technology. (article, 2025-10-24)
Field: Materials Science — Biomaterials

Smart Drug Delivery Systems: Current Technologies, Clinical Applications, and Future Perspectives in Precision Therapeutics The pharmaceutical industry has come a long way with the introduction of smart drug delivery systems in terms of increasing control level over the therapeutic agents release and measurement of their effects. The recent achievements have demonstrated that these networks are useful in very specific pharmacotherapeutic treatment using high-technological equipment. Various types of diverse classes of delivery systems have been invented including nanoparticulate-based carriers, hydrogel-based matrices and implantable therapeutic systems that are associated with their own advantages in the clinical practice. In current investigations, several technologies has been developed in the controlled theraputic delivery and concomitant work in real time monitoring technology to measure delivery of therapeutic agents. Even though scientific evidence is uniform with regard to the potential of such systems to have a positive effect on therapy, challenges that hinder clinical translation which encompass system stability, biocompatibility determination, and complex regulatory compliance still exist. According to the literature, these limitations can be overcome by implementing artificial intelligence and new technologies in personalized medicine to offer more treatment choices to be administered by intelligent medication systems. It is possible that the evolving character of inventions they can have a significant positive effect on system efficacy and applicability in clinical settings. The available data is indicative of the existence of quantifiable possibilities to improve patient treatment and treatment outcome in various clinical applications. The paper has an extensive literature review on the existing information on smart drug delivery devices and their mechanisms, types of systems, and use in clinical practice. It evaluates the current findings and describes the colorful prospects of the way of further development of the therapeutic regimes and enhancement of the patient-centered healthcare services. Drug delivery ; Personalized medicine ; Smart system ; Precision medicine ; Context (archaeology) ; Relevance (law) Nanoparticle-Based Drug Delivery ; 3D Printing in Biomedical Research ; Graphene and Nanomaterials Applications
Authors: Jefferson Rafael de Carvalho Lira | Rogério Ferreira da Silva | Gilson Lima da Silva
Source: Geografia em Atos (Online) (article, 2025-10-10)
Field: Chemistry — Analytical Chemistry

Aplicação da fotocatálise heterogênea no tratamento de efluentes industriais An effluent loaded with chemicals, dyes, and surfactants has been a problem for the textile industry. An effective treatment is needed to degrade these compounds so that they can be disposed of as required by law. Heterogeneous photocatalysis is one of the promising treatments for this effluent. This study aimed to develop a systematic review using the PRISMA methodology to select articles from the Scopus and Web of Science platforms. 26 articles were selected that fit the research. With the help of the VOSviewer software, maps were created where the main co-authors, countries developing research, and the main keywords used could be identified. In these articles that were found, the various applications of heterogeneous photocatalysis in the treatment of these industrial effluents were observed. It was concluded that the correct disposal of effluent has been a worldwide concern, and from this perspective, new test studies are being developed. Effluent ; Scopus ; Textile ; Industrial effluent ; Waste treatment Dye analysis and toxicity ; Water Quality Monitoring and Analysis
Authors: Jack A. Logan | Jacob Sumner | Alex T. Grigas | Mark D. Shattuck | Corey S. O’Hern
Source: arXiv (Cornell University) (preprint, 2025-01-05)
Field: Materials Science — Biomaterials

The effect of stereochemical constraints on the structural properties of folded proteins Proteins are composed of chains of amino acids that fold into complex three-dimensional structures. Several key features, such as the radius of gyration, fraction of core amino acids $f_{\rm core}$, packing fraction $\langle ϕ\rangle$ of core amino acids, and structure factor $S(q)$ define the structure of folded proteins. It is well-known that folded proteins are compact with a radius of gyration $R_g(N) \sim N^ν$ that obeys power-law scaling with the number of amino acids $N$ and $ν\sim 1/3$, $f_{\rm core} \approx 0.09$, and $\langle ϕ\rangle \approx 0.55$. We also investigate the {\it internal} scaling of the radius of gyration $R_g(n)$ versus the chemical separation $n$ between amino acids for subchains of length $n$ and show that it does not obey simple power-law scaling with $ν\sim 1/3$. Instead, $R_g(n) \sim n^{ν_{1,2}}$ with a larger exponent $ν_1 &gt; 1/3$ for small $n$ and smaller exponent $ν_{2} &lt; 1/3$ for large $n$. To develop a minimal model for proteins that recapitulates these defining structural features, we carry out collapse simulations for a series of coarse-grained models with increasing complexity. We show that a model, which coarse-grains amino acids into a single spherical backbone bead and several variable-sized side-chain beads and enforces bend- and dihedral-angle constraints for the backbone, recapitulates $R_g(n)$, $f_{\rm core}$, $\langle ϕ\rangle$, and $S(q)$ for more than $2500$ x-ray crystal structures of proteins. Radius of gyration ; RADIUS ; Gyration ; Physics ; Computational chemistry ; Chemistry ; Materials science ; Crystallography ; Geometry ; Mathematics ; Polymer ; Computer science ; Nuclear magnetic resonance biodegradable polymer synthesis and properties ; Advanced Materials and Mechanics
Authors: Michael E. Zorn | Dean T. Tompkins | Ramsey Kropp | Walter A. Zeltner | Marc A. Anderson
Source: Catalysts (article, 2025-08-26)
Field: Materials Science — Materials Chemistry

Catalytic Oxidation of Ethanol for Treatment of Commercially Produced Carbon Dioxide Using Aqueous Sol–Gel-Derived Catalyst Materials The purpose of this study was to design a Pt/TiO2–ZrO2 catalytic-based treatment system to remove ethanol and oxygen (O2) from a gaseous feed stream. The ultimate target application was the conversion of ethanol and O2 to carbon dioxide (CO2) and water (H2O) from a feed stream of CO2 in a commercial beer brewing operation. Bench-scale reactions were performed at 250 °C and 300 °C, representing two temperatures under practical consideration for a full-scale catalytic reactor. The target gaseous feed stream would be expected to have a relatively low (near-stoichiometric) concentration of O2, so the effect of O2 concentration was also studied. On the bench scale, ethanol was completely converted to CO2 under low flow rate conditions, and the reactions proceeded through volatile and non-volatile reaction intermediates. Results from the bench-scale tests were used to make predictions for designing a pilot-scale catalytic reactor under conditions of high and low O2 concentration. A pilot-scale reactor was constructed and installed in a commercial brewing facility, and results from testing the pilot-scale reactor are also presented. The pilot-scale system reduced the feed stream ethanol concentrations by 99.9% while concomitantly reducing the O2 concentrations over the course of a six-day demonstration period without generating unacceptable levels of byproducts. Catalysis ; Carbon dioxide ; Aqueous solution ; Chemistry ; Ethanol ; Chemical engineering ; Materials science ; Organic chemistry Catalytic Processes in Materials Science ; Catalysis and Oxidation Reactions ; Mesoporous Materials and Catalysis
Authors: K.J. Rajimon | Renjith Thomas
Source: ES chemistry and sustainability. (article, 2025-01-01)
Field: Chemistry — Organic Chemistry

Antimicrobial Pharmacophore Screening of Imidazole[1,2-a] Pyrazine Derivatives: A Quantitative Structure-Activity Relationship Approach An extensive computational analysis examines 10 new compounds with possible pharmacological properties.Absorption, distribution, metabolism, and excretion (ADME) projections indicated that all drugs exhibited good gastrointestinal absorption, albeit with varying solubility profiles and permeability across the blood-brain barrier.Utilising bioavailability radar analysis, the ideal physicochemical characteristics of many substances were determined.The results of structural similarity investigations indicated that certain compounds may have potential anticancer, anticonvulsant, antibacterial, antiulcer, antiviral, and anti-inflammatory properties.In the context of antibacterial action, Quantitative structure-activity relationship (QSAR) modelling has identified compound 8 as the most highly promising option.Through pharmacophore modelling and target prediction, Staphylococcus aureus Pyruvate carboxylase (SaPC) was identified as the most likely molecular target for chemical 8.The molecular docking experimental investigations of compound 8 with SaPC revealed a binding energy of -6.9 kcal/mol, accompanied by promising stability indications in a biological setting.The Molecular Mechanics Generalized Born Surface Area energy analysis demonstrated the significance of hydrophobic interactions, van der Waals forces, and hydrogen bonding in the mechanism of interaction.The results of this study provide valuable insights for enhancing and advancing the optimization and development of these chemicals, specifically compound 8, in the field of antimicrobial drug discovery that targets Staphylococcus aureus. Pharmacophore ; Imidazole ; Antimicrobial ; Pyrazine ; Chemistry ; Combinatorial chemistry ; Stereochemistry ; Organic chemistry Synthesis and Biological Evaluation ; Synthesis and biological activity ; Click Chemistry and Applications
Authors: Steven A. Silber | Mikko Karttunen
Source: ArXiv.org (preprint, 2025-11-13)
Field: Materials Science — Materials Chemistry

Parallel and GPU accelerated code for phase-field and reaction-diffusion simulations We present SymPhas 2.0, a major update of the compile-time symbolic algebra simulation framework SymPhas for phase-field and reaction-diffusion models. This release introduces significant expansions and enhancements that enable the definition of a phase-field model directly from the free-energy functional via compile-time evaluated functional differentiation. It also introduces directional derivatives, symbolic summation, tensor-valued expressions, and compile-time derived finite difference stencils of arbitrary order and accuracy. Furthermore, the code has been parallelized for CPUs with MPI, and GPU computing has been added using CUDA (Compute Unified Device Architecture). For the latter, symbolic expressions are compiled into optimized CUDA kernels, allowing large-scale simulations to execute entirely on the GPU. For large systems ($32,768^2$ in 2D and $1,024^3$ in 3D with double precision), speedups up to $\sim \!\!1,000 \times$ were obtained compared to the first version of SymPhas using multi-threaded CPU execution on a single system. These developments establish SymPhas 2.0 as a flexible and scalable framework for efficient implementation of phase-field and reaction-diffusion models on GPU-based high-performance computing platforms. CUDA ; Scalability ; Code (set theory) ; General-purpose computing on graphics processing units ; Code generation ; Symbolic computation ; Symbolic execution ; Scheme (mathematics) Solidification and crystal growth phenomena ; Model Reduction and Neural Networks ; Block Copolymer Self-Assembly
Authors: Shengyin Sun | Wenhao Yu | Yuxiang Ren | Weitao Du | Liwei Liu | Xuecang Zhang | Ying Hu | Chen Ma
Source: ArXiv.org (preprint, 2025-01-14)
Field: Materials Science — Materials Chemistry

GDiffRetro: Retrosynthesis Prediction with Dual Graph Enhanced Molecular Representation and Diffusion Generation Retrosynthesis prediction focuses on identifying reactants capable of synthesizing a target product. Typically, the retrosynthesis prediction involves two phases: Reaction Center Identification and Reactant Generation. However, we argue that most existing methods suffer from two limitations in the two phases: (i) Existing models do not adequately capture the ``face'' information in molecular graphs for the reaction center identification. (ii) Current approaches for the reactant generation predominantly use sequence generation in a 2D space, which lacks versatility in generating reasonable distributions for completed reactive groups and overlooks molecules' inherent 3D properties. To overcome the above limitations, we propose GDiffRetro. For the reaction center identification, GDiffRetro uniquely integrates the original graph with its corresponding dual graph to represent molecular structures, which helps guide the model to focus more on the faces in the graph. For the reactant generation, GDiffRetro employs a conditional diffusion model in 3D to further transform the obtained synthon into a complete reactant. Our experimental findings reveal that GDiffRetro outperforms state-of-the-art semi-template models across various evaluative metrics. Dual (grammatical number) ; Retrosynthetic analysis ; Representation (politics) ; Graph ; Computer science ; Diffusion ; Dual graph ; Artificial intelligence ; Mathematics ; Theoretical computer science ; Chemistry ; Physics ; Political science ; Linguistics ; Line graph ; Stereochemistry Machine Learning in Materials Science ; Machine Learning in Bioinformatics ; Metabolomics and Mass Spectrometry Studies
Authors: Г. О. Рытиков | Fedor Doronin | A. G. Evdokimov | Mikhail Savel’ev | Yu.V. Rudyak | V. G. Nazarov
Source: Polymers (article, 2025-09-15)
Field: Materials Science — Surfaces, Coatings and Films

Biomimetic Functional Fluorinated Oxygen-Containing Coatings on 3D-Printing Composite Polymer Items We manufactured the 3D-printed prototypes with increased wear resistance using a combination of the following: biomimetic design (the shark skin was used as a natural object to follow), 3D-printing technological parameter regulation, rational choice of polymer matrix, dispersed filling ingredients and items' surface gas-phase modification technique. It was established that the bulk modification of the PETG filament with montmorillonite, graphite nano-plates, and other ingredients can reduce the 3D-printed prototypes' wear by up to eight times. The gas-phase fluorination of the product's surface provides a decrease in the rest friction coefficient and temperature in the "indentor-3D-printed disk" contact pair. We obtained the texture models and quantified the degree of similarity between the shark skin and the 3D-printed prototypes' surfaces. Polymer ; Graphite ; Composite number ; Surface modification ; Friction coefficient ; Wear resistance ; Response surface methodology ; Coefficient of friction Surface Modification and Superhydrophobicity ; Additive Manufacturing and 3D Printing Technologies ; Photopolymerization techniques and applications