jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Hongtai Li | Kehan Liu | Jing Wu | Yalin Wei | Jinzhu Tan
Source: Journal of Applied Polymer Science (article, 2025-12-31)
Field: Materials Science — Polymers and Plastics

Study on Mechanical and Tribological Properties of Nitrile Butadiene Rubber and Hydrogenated Nitrile Butadiene Rubber Blends Reinforced With Spherical Nano‐ <scp> Al <sub>2</sub> O <sub>3</sub> </scp> ABSTRACT Nitrile butadiene rubber (NBR) and hydrogenated nitrile butadiene rubber (HNBR) were blended at different weight ratios, with spherical nano‐alumina (nano‐Al 2 O 3 ) as the reinforcing filler. The vulcanization behavior, cross‐linking density, mechanical performance, wear resistance, and wear mechanisms of the NBR/HNBR composites filled with nano‐Al 2 O 3 were systematically characterized via vulcanization curve analysis, equilibrium swelling tests, tensile and compression tests, friction‐wear measurements, scanning electron microscopy (SEM) observations, and attenuated total reflection Fourier transform infrared spectroscopy (ATR‐FTIR). Results reveal that the torque difference and cross‐linking density of the composites exhibited nonlinear variations with increasing the ratio of NBR to HNBR. Notably, the composite with an NBR/HNBR weight ratio of 70:30 achieved superior mechanical properties and optimal wear resistance, accompanied by the lowest volume wear rate among all tested formulations. The key insight is that the NBR/HNBR ratio of 70:30 facilitated the formation of a synergistic interpenetrating cross‐link network. NBR contributed abundant cross‐link active unsaturated double bonds to densify the network, while the saturated main chain of HNBR imparted structural stability and inhibited crack propagation. This work provides a feasible strategy for optimizing rubber composites by regulating NBR/HNBR blending ratios, offering guidance for the design of high‐performance rubber materials for tribological applications. Vulcanization ; Nitrile rubber ; Natural rubber ; Nitrile ; Ultimate tensile strength ; Fourier transform infrared spectroscopy ; Composite number ; Tribology Polymer Nanocomposites and Properties ; Tribology and Wear Analysis ; Elasticity and Material Modeling
Authors: S. Chen | Huan Yang | Fangxu Shen | Anran Li | Shuangxing Wen | Shiping Gao | Yunyang Bai | Kai Li | Yuqing Lin
Source: Electroanalysis (article, 2025-12-01)
Field: Materials Science — Materials Chemistry

MXene‐Based Electrochemical Sensors: Design Strategies and Application Advances for the Detection of Biological Small Molecules Precise detection of biomolecules is crucial for disease diagnosis. Traditional detection methods suffer from limitations such as slow results and high costs, restricting their practical application. While electrochemical sensors offer advantages such as rapid detection, ease of operation, and low cost, they are fundamentally constrained by electrode materials. Among numerous candidates, MXene stands out due to its unique 2D structure, enormous specific surface area, excellent conductivity, and abundant surface functional groups (e.g., the electron transfer rate constant of Ti 3 C 2 Tx exceeds that of conventional materials by 2–3 orders of magnitude), making it one of the ideal materials for electrochemical sensor fabrication. This article comprehensively reviews the latest advances in MXene‐based electrochemical sensors for biomolecular detection. It systematically elucidates sensing principles, performance metrics, and material design strategies and for the first time distils a “design grammar” for MXene‐based sensors. This establishes universal design principles linking material characteristics (e.g., terminal functional groups and heterostructures) to detection performance (e.g., achieving a glucose detection limit at the aM level). Analysis indicates these rules can guide the construction of sensing interfaces that simultaneously achieve ultrahigh sensitivity, selectivity, and stability. This design framework not only points the way for developing high‐performance MXene sensors but also provides a critical theoretical framework and practical guide for rational optimization and novel sensing interface design in electroanalytical chemistry, advancing its practical applications in clinical diagnostics and personalized medicine. Rational design ; Biomolecule ; Biosensor ; Interface (matter) ; Design elements and principles ; Electrochemistry ; Ideal (ethics) MXene and MAX Phase Materials ; Advanced biosensing and bioanalysis techniques ; 2D Materials and Applications
Authors: Satwinder Singh | K. Singh
Source: Digital Discovery (article, 2025-01-01)
Field: Materials Science — Ceramics and Composites

An improved machine learning strategy using structural features to predict the glass transition temperature of oxide glasses We present a physics-informed machine learning approach to predict the glass transition temperature ( T g ) of sodium borosilicate glasses. Borosilicate glass ; Oxide ; Glass transition ; Active learning (machine learning) ; Sodium oxide Glass properties and applications ; Pigment Synthesis and Properties
Authors: Simão P. B. Teixeira | Rui L. Reis | Rui M. A. Domingues
Source: Regenerative Engineering and Translational Medicine (article, 2025-12-05)
Field: Chemistry — Analytical Chemistry

Epitope Imprinted Nanoparticles as Customized Synthetic Antibodies for Biorecognition in Theranostics Abstract As medicine advances towards an era of personalized and targeted therapies, the need for precise and reliable molecular recognition elements becomes increasingly critical. These elements are essential for directing therapeutic agents to specific cells or tissues, thereby maximizing efficacy while minimizing off-target effects. Among the emerging technologies, epitope-imprinted nanoparticles (EINPs) have demonstrated exceptional potential as “synthetic antibodies” for the recognition of biomarkers. These nanoparticles are designed to mimic the binding capabilities of natural antibodies but with enhanced stability, specificity, and ease of production. Unlike traditional antibodies, which can be costly, labile, and prone to significant side effects, EINPs offer a cost-effective, robust, and customizable platform for targeted sensing and therapeutic applications. This Perspective Review explores the design, synthesis, and application of epitope-imprinted nanoparticles, highlighting their advantages and potential to revolutionize the landscape of abiotic molecular recognition in disease detection and targeted therapies. Finally, we present perspectives on foreseeable breakthroughs and advances, offering insights into how molecular imprinting techniques can be expanded to new biomedical fields, such as tissue engineering. Lay Summary Personalized medicine requires precise tools to identify and target diseased cells while avoiding off target effects. Epitope-imprinted nanoparticles (EINPs) are emerging as synthetic alternatives to antibodies, designed to recognize disease markers with high stability, low cost, and fewer limitations than natural antibodies. By mimicking biological recognition, EINPs show promise in applications such as disease detection, drug delivery, and tissue engineering. This perspective review focus on how these nanoparticles are created and applied, and highlights their potential to transform regenerative medicine and targeted therapies through more reliable, customizable molecular recognition systems. Personalized medicine ; Precision medicine ; Nanomedicine ; Targeted drug delivery ; Molecular recognition ; Human disease ; Drug discovery ; Regenerative medicine Analytical chemistry methods development ; Innovative Microfluidic and Catalytic Techniques Innovation ; Advanced Biosensing Techniques and Applications
Authors: М.М. Pylypenko | О.V. Yefimov | A.О. Drobyshevska | Yu.O. Stupak
Source:  (article, 2025-04-03)
Field: Materials Science — Materials Chemistry

STRUCTURAL MATERIALS FOR ELEMENTS OF NUCLEAR REACTORS EQUIPMENT The paper presents the main results of research on the development of structural materials for equipment elements of existing and prospective nuclear power plants. The further development of nuclear energy largely depends on the development of advanced structural materials for new generation reactors and the improvement of materials for operating nuclear power plants. The results of research on the optimization the iron content of the zirconium alloy to increase corrosion resistance in the coolant and resistance to radiation growth are presented. Experimental determination of the laws of the behavior of impurities during the refining of chemically active and refractory metals made it possible to achieve a higher level of metals purity. It is shown that nickel alloys of the Hastelloy type, obtained from high-purity metal components, can be successfully used as a structural material of the MSRs. The high requirements for structural materials regarding the content of impurity elements can be met only when high-purity metals are used as initial components and new technologies for their production are used. Nuclear engineering ; Process engineering ; Materials science ; Engineering Nuclear Materials and Properties ; Graphite, nuclear technology, radiation studies ; Nuclear reactor physics and engineering
Authors: Miruna-Adriana Ioța | Laura-Mădălina Cursaru | Ioan Albert Tudor | Mariana Costea | Alexandru Cristian Matei | Dumitru Valentin Drăguț | Roxana Mioara Piticescu | Adriana-Gabriela Șchiopu
Source: Crystals (article, 2025-09-22)
Field: Materials Science — Materials Chemistry

The Influence of Pressure on Magnetite–Zinc Oxide Synthesis in Hydrothermal Conditions The combination of ZnO and Fe3O4 nanoparticles represents a synergistic strategy for the treatment of skin cancer, exploiting both oxidative stress-induced cytotoxicity and hyperthermic effects for improved anticancer activity. These nanoparticles also function as drug carriers, facilitating targeted delivery and reducing systemic toxicity. Furthermore, controlled-release systems activated by external stimuli, such as light, pH, temperature, or magnetic fields, optimize the accumulation of the drug in tumor tissues. In the present study, Fe3O4-ZnO composite powders were synthesized in aqueous solution through the hydrothermal method under high pressure and temperature. All synthesized powders were characterized by physicochemical and morpho-structural methods such as: FT-IR, XRD, SEM, DLS, and BET. The influence of the hydrothermal synthesis parameters (pressure and time) on the morpho-structural properties of the magnetite–zinc oxide nanocomposites was studied. Hydrothermal circulation ; Nanoparticle ; Aqueous solution ; Oxide ; Hydrothermal synthesis ; Nanocomposite ; Composite number ; Drug delivery Magnetic Properties and Synthesis of Ferrites ; Characterization and Applications of Magnetic Nanoparticles ; Minerals Flotation and Separation Techniques
Authors: Stephen E. Gant | Francesco Ricci | Guy Ohad | Ashwin Ramasubramaniam | Leeor Kronik | Jeffrey B. Neaton
Source: ArXiv.org (preprint, 2025-11-03)
Field: Materials Science — Materials Chemistry

Automated Workflow for Non-Empirical Wannier-Localized Optimal Tuning of Range-Separated Hybrid Functionals We introduce an automated workflow for generating non-empirical Wannier-localized optimally-tuned screened range-separated hybrid (WOT-SRSH) functionals. WOT-SRSH functionals have been shown to yield highly accurate fundamental band gaps, band structures, and optical spectra for bulk and 2D semiconductors and insulators. Our workflow automatically and efficiently determines the WOT-SRSH functional parameters for a given crystal structure and composition, approximately enforcing the correct screened long-range Coulomb interaction and an ionization potential ansatz. In contrast to previous manual tuning approaches, our tuning procedure relies on a new search algorithm that only requires a few hybrid functional calculations with minimal user input. We demonstrate our workflow on 23 previously studied semiconductors and insulators, reporting the same high level of accuracy. By automating the tuning process and improving its computational efficiency, the approach outlined here enables applications of the WOT-SRSH functional to compute spectroscopic and optoelectronic properties for a wide range of materials. Workflow ; Process (computing) ; Semiconductor ; Range (aeronautics) ; Hybrid functional ; Coulomb ; Density functional theory ; Yield (engineering) 2D Materials and Applications ; Machine Learning in Materials Science ; Electronic and Structural Properties of Oxides
Authors: Evyatar Shaulsky | Sabrina Marnoto | Anand Patel | Sara M. Hashmi
Source: ChemRxiv (preprint, 2025-07-01)
Field: Materials Science — Surfaces, Coatings and Films

Pushing the limits of Taylor’s theory: Using deformation in steady, pressure-driven fluidic flows to measure surface tension at high throughput Advances in fluidic droplet generation necessitate accessible, high throughput methods to optimize formulations by measuring surface tension. One fluidic approach involves creating extensional flow using constrictions. Transient relaxation of deformed droplets is then measured at the constriction exit. We propose an alternative, arguably simpler approach: we use steady deformation within a constriction to measure surface tension. We calculate surface tension using Taylor's small deformation theory, which describes the relationship between droplet deformation and the Capillary number, or ratio of applied viscous stress to restoring surface tension stress. Taylor originally developed his theory for unconfined droplets in pure shear or pure extension. We apply Taylor’s theory to droplets in pressure driven flows. We generate and flow emulsion droplets through a series of increasingly narrow constrictions and use steady deformation to measure surface tension. We investigate both water-in-oil and oil-in-water droplets, stabilized by three different surfactants over a range of concentrations. In a subset of experiments, we vary the viscosity ratio by adding polyethylene glycol diacrylate to water droplets. Validation using both the transient deformation fluidic approach and pendant drop measurements on individual droplets demonstrates the viability of Taylor’s theory in regimes beyond those originally proposed. Importantly, our results suggest steady state deformation in pressure driven flows can be used to measure surface tension even when droplets are slightly confined. This steady droplet deformation approach to surface tension measurements represents a readily-accessible option for those using fluidic droplet generators to perform biomedical or other assays, or to investigate or optimize emulsion formulations. Fluidics ; Measure (data warehouse) ; Surface tension ; Throughput ; Tension (geology) ; Mechanics ; Deformation (meteorology) ; Computer science ; Materials science ; Physics ; Engineering ; Classical mechanics ; Telecommunications ; Electrical engineering ; Thermodynamics ; Composite material ; Data mining Surface Modification and Superhydrophobicity ; Electrohydrodynamics and Fluid Dynamics
Authors: Dr. Koustava Kumar Panda
Source: Advances in Medical and Pharmaceutical Sciences (article, 2025-01-01)
Field: Materials Science — Biomaterials

Nanoparticle-Enabled Targeted Drug Delivery: Advancements in Controlled Release for Precision Therapeutics Nanoparticle-enabled targeted drug delivery has emerged as a transformative platform in modern precision therapeutics. By enabling controlled release, enhanced bioavailability, and site-specific accumulation, nanoparticles significantly improve treatment efficacy while reducing systemic toxicity. This research paper evaluates advancements in nanoparticle-based delivery systems, including polymeric nanoparticles, lipid nanocarriers, metallic nanoparticles, and stimuli-responsive smart materials. Furthermore, the paper examines controlled release mechanisms, biological interactions, pharmacokinetics, case studies, and stakeholder perceptions through structured questionnaires and data analysis. Findings indicate that novel nanoparticle formulations—when integrated with personalized medicine, AI-guided design, and multi-modal imaging—offer unprecedented potential for disease-specific therapeutics, particularly in oncology, neurology, and infectious diseases. Controlled release ; Targeted drug delivery ; Drug delivery ; Drug ; Precision medicine ; Delivery system Nanoparticle-Based Drug Delivery ; Advancements in Transdermal Drug Delivery ; Cancer Research and Treatment
Authors: Ali Hosseingholi Pourasl
Source: Journal of Materials Science (article, 2025-02-01)
Field: Materials Science — Materials Chemistry

Analytical modeling of NH3 gas sensing using zigzag graphene nanoscrolls: energy band structure and electrical properties Abstract Graphene nanoscrolls (GNSs), a unique nanostructure of graphene, have garnered considerable attention due to their distinctive properties such as a rolled-up papyrus-like structure, adjustable core geometry, increased inner wall area, and enhanced surface-to-volume ratio. These properties make GNS a promising candidate for various nanoelectronic applications, including gas sensing devices. Despite its potential, GNS has been relatively underexplored in the context of gas sensing applications. In this study, we present a series of analytical models to characterize the behavior of zigzag graphene nanoscrolls (ZGNS)-based gas sensors in the presence of NH 3 gas. The tight-binding technique, employing nearest neighbor approximation, is utilized to formulate the energy dispersion relation of GNS, incorporating the influence of gas molecule adsorption through parameters such as the hopping integral between GNS and gas and the on-site energy of adsorbed gas molecules. Furthermore, the derived energy equation is employed to establish the conductance relation and explore the impact of gas adsorption on the electrical conductance of GNS. Subsequently, the I-V characteristics of the GNS sensor are formulated, and the variations in current due to NH 3 gas exposure are analyzed. The gate voltage is modeled as a function of NH 3 concentration, and a sensing parameter is proposed based on current variations across different concentrations. Validation of the model is performed by comparing the obtained results with data extracted from previous studies. The findings demonstrate good agreement, underscoring the effectiveness of the proposed ZGNS-based sensor model for NH 3 detection under varying environmental conditions. Graphical abstract Zigzag ; Materials science ; Graphene ; Band gap ; Solid mechanics ; Electronic band structure ; Energy (signal processing) ; Nanotechnology ; Engineering physics ; Condensed matter physics ; Optoelectronics ; Composite material ; Physics ; Geometry ; Quantum mechanics Graphene research and applications ; Gas Sensing Nanomaterials and Sensors ; 2D Materials and Applications
Authors: J. P. Alvarinhas Batista | Matthieu J. Verstraete | Aloïs Castellano
Source: ArXiv.org (preprint, 2025-06-17)
Field: Materials Science — Materials Chemistry

Thermal Conductivity Of Monolayer Hexagonal Boron Nitride: Four-Phonon Scattering And Quantum Sampling Effects Monolayer hexagonal boron nitride is a prototypical planar 2-dimensional system material and has been the subject of many investigations of its exceptional vibrational, spectroscopic and transport properties. The lattice thermal conductivity remains quite uncertain, with theoretical and experimental reports varying between 218 and 1060 Wm-1K-1. It has a strong temperature evolution and is sensitive to strain effects and isotope concentrations. While the impact of isotope scattering has been widely studied and is well understood, nuclear quantum effects and 4-phonon scattering have so far been neglected. Monolayer hexagonal boron nitride is composed of light elements, and further has its 3-phonon scattering phase space restricted by mirror plane symmetry, so these effects may be of similar order as isotope scattering, and would lead to a completely different understanding of the fundamental processes limiting the lattice thermal conductivity for this system. In this work, we use both classical and path-integral molecular dynamics, in conjunction with the Temperature Dependent Effective Potential method, to compute temperature-dependent renormalized phonons including isotope scattering, 3-phonon scattering, 4-phonon scattering and nuclear quantum effects. We show the impact of the latter two on the lattice thermal conductivity for a large temperature range, as well as their impact on the phonon lifetimes. Overall, our work provides a robust framework for calculations of the lattice thermal conductivity in solids, providing quantitative improvements and physical understanding that help explain the variety of results found in the literature. Thermal conductivity ; Phonon ; Scattering ; Monolayer ; Phonon scattering ; Boron nitride ; Lattice (music) ; Kinetic isotope effect Thermal properties of materials ; Boron and Carbon Nanomaterials Research ; Graphene research and applications
Authors: Zhiyang Zhao | Takahide Ikeda
Source: Materials (article, 2025-11-15)
Field: Materials Science — Materials Chemistry

Characterization and Preparation of Nanostructured Al2Fe3Si3 Thermoelectric Materials A nanostructured Al<sub>2</sub>Fe<sub>3</sub>Si<sub>3</sub> composite has been synthesized by high-energy ball milling followed by spark plasma sintering. Formations of oxides and FeSi or Al<sub>2</sub>Fe<sub>3</sub>Si<sub>4</sub> phases in nanometer-size scales were observed in addition to the matrix Al<sub>2</sub>Fe<sub>3</sub>Si<sub>3</sub> phase. Because of enhanced phonon scattering, the materials show low lattice thermal conductivities such as ~5 W/mK at the minimum. Characterization (materials science) ; Thermoelectric effect ; Thermal conductivity ; Thermoelectric materials ; Ball mill ; Composite number ; Spark plasma sintering ; Nanostructure Advanced Thermoelectric Materials and Devices ; Intermetallics and Advanced Alloy Properties ; Semiconductor materials and interfaces
Authors: Fernando Tato | Hafsa Yasin
Source: Engineering and Technology Journal (article, 2025-04-05)
Field: Chemistry — Analytical Chemistry

Expanding the Horizons of Principal Component Analysis: Versatile Applications from Environmental Monitoring to Chemometrics Principal Component Analysis (PCA) is a popular statistical method for large dataset analysis and has established itself in many fields, ranging from environmental modeling to spectroscopy. In this work, we bring to light its use in monitoring NO2 air pollution from satellite data during the lockdown periods of COVID-19, incorporating the strengths of Weighted PCA and Rescaled PCA to achieve improved predictability. Additionally, PCA has been applied in resonant ultrasound spectroscopy to optimize measurement points, especially in samples with complex geometries, demonstrating its effectiveness in reducing data points of collection while maintaining accuracy. Further, PCA's application coupled with classification methods like LDA and SVM has effectively determined the geographic origin of Indonesian coconuts, demonstrating its effectiveness in enhancing classification accuracy and chemometric analysis. The versatility of PCA is also evidenced in its use in clustering high-dimensional data through Adaptive Local PCA, which employs a neural network-based approach with adaptive learning rates to enhance clustering quality in dynamic data environments. These examples show the flexibility and utility of PCA in big data analysis across different fields, and a greater application of PCA in gaseous pollutant analysis and other complex data issues is needed. Chemometrics ; Principal component analysis ; New horizons ; Environmental science ; Component (thermodynamics) ; Environmental chemistry ; Biochemical engineering ; Computer science ; Chemistry ; Engineering ; Artificial intelligence ; Aerospace engineering ; Machine learning ; Physics Spectroscopy and Chemometric Analyses ; Metabolomics and Mass Spectrometry Studies ; Computational Drug Discovery Methods