jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Hui Peng | Pengfei Hou
Source: ACS Applied Materials & Interfaces (article, 2025-10-03)
Field: Materials Science — Materials Chemistry

Self-Powered Polarized Photodetection and Low-Voltage Modulated Bidirectional Visual Synapse of Ta<sub>2</sub>NiS<sub>5</sub>/MoS<sub>2</sub>/Gr Vertical Heterojunction with Asymmetric Interface Modulation Modern application scenarios increasingly demand multifunctional integrated photodetectors with high efficiency and low-power consumption. However, existing two-dimensional (2D) heterojunction-based devices face critical challenges. For instance, metal-semiconductor contacts can induce Schottky barriers and Fermi level pinning, which hinder carrier transport and degrade overall performance. To address these issues, this work proposes a vertical van der Waals heterojunction design, employing graphene (Gr) as the top electrode, tantalum nickel sulfide (Ta<sub>2</sub>NiS<sub>5</sub>) with a narrow-bandgap and anisotropy as the bottom electrodes, and molybdenum disulfide (MoS<sub>2</sub>) as the main light-absorbing layer. This architecture engineers reverse built-in electric fields at Ta<sub>2</sub>NiS<sub>5</sub>/MoS<sub>2</sub> and MoS<sub>2</sub>/Gr interfaces and replaces Schottky contacts with ohmic-like transport, leveraging Ta<sub>2</sub>NiS<sub>5</sub>'s anisotropy and interfacial asymmetry to integrate multiple functions. Under 660 nm light illumination (249.24 mW/cm<sup>2</sup>), it achieves a high photocurrent density of 171 mA/cm<sup>2</sup> and an on/off ratio of 3.7 × 10<sup>4</sup>. Under 808 nm light illumination, a self-powered anisotropy ratio of 6.03 is realized. It exhibits excitatory postsynaptic currents (EPSC) under 1064 nm light illumination with an ultralow energy consumption of 82 fJ, alongside bidirectional synaptic weight modulation via bias polarity and light pulse (duration, intensity, and number) control. This integrated design paves the way for advancing multifunctional optoelectronic devices in next-generation integrated systems and artificial intelligence applications. Photodetection ; Photocurrent ; Heterojunction ; Molybdenum disulfide ; Photodetector ; Schottky barrier ; Modulation (music) ; Plasmon ; Graphene 2D Materials and Applications ; Perovskite Materials and Applications ; Advanced Memory and Neural Computing
Authors: Mingming Yi | Yiou Qiu | Ping Wu | Guoliao Sun | Wenhui Zhu | Liancheng Wang
Source: Microelectronics Reliability (article, 2025-02-11)
Field: Materials Science — Materials Chemistry

Investigation on FCBGA package with vertical-aligned carbon fiber thermal pad as thermal interface material Materials science ; Ball grid array ; Interface (matter) ; Thermal ; Composite material ; Thermal grease ; Thermal conductivity ; Physics ; Thermodynamics Thermal properties of materials ; Heat Transfer and Optimization ; Electronic Packaging and Soldering Technologies
Authors: Alan Clavelland Ochioni | Ítalo Rennan Sousa Vieira | Carlos Adam Conte‐Júnior
Source: Journal of Drug Delivery Science and Technology (article, 2025-09-11)
Field: Materials Science — Biomaterials

Advances in stimuli-responsive nanoparticles for cancer therapy: Mechanisms, functional materials, and emerging technologies Nanomedicine ; Cancer ; Drug delivery ; Cancer treatment ; Cancer therapy ; Drug ; Clinical Practice ; Applications of nanotechnology Nanoparticle-Based Drug Delivery ; Nanoplatforms for cancer theranostics ; RNA Interference and Gene Delivery
Authors: Yamei Yu | Abdulnasser Mahmoud Karami | Lin Yuan | Lei Qin | Awad Nasser Albalwi | Jianqiang Liu | Irshad Ul Haq Bhat | Mohd. Muddassir
Source: Microchemical Journal (article, 2025-04-03)
Field: Materials Science — Materials Chemistry

MOF and COF platforms toward kidney-disease: Advanced nanovehicles for effective diagnosing and treatment Kidney disease ; Chemistry ; Nanotechnology ; Medicine ; Materials science ; Internal medicine Advanced Nanomaterials in Catalysis ; Metal-Organic Frameworks: Synthesis and Applications ; Nanoplatforms for cancer theranostics
Authors: Chao Tan | Cheng Tan | Maoxian Chen | Hui Chen | Zan Lin
Source: Microchemical Journal (article, 2025-02-17)
Field: Chemistry — Analytical Chemistry

Identification of sulfur-fumigated Shanyao by near-infrared spectroscopy combined with DD-SIMCA Sulfur ; Spectroscopy ; Chemistry ; Infrared spectroscopy ; Analytical Chemistry (journal) ; Near-infrared spectroscopy ; Identification (biology) ; Chromatography ; Physics ; Organic chemistry ; Optics Spectroscopy and Chemometric Analyses ; Ziziphus Jujuba Studies and Applications ; Insect Pest Control Strategies
Authors: Farzad Barzegar Marvasti | Seyed Hadi Razavi | Reza Salehian | Neda Akbari | Nima Esmaeili | Ali Amini Valashani
Source: Journal of Stored Products Research (article, 2025-10-18)
Field: Materials Science — Biomaterials

Novel insights into phage-based films and coatings: Innovative solutions for active food packaging systems Active packaging ; Food spoilage ; Food packaging ; Antimicrobial ; Bacteriophage ; Food industry ; Foodborne pathogen ; Food safety ; Pathogenic bacteria Nanocomposite Films for Food Packaging ; Biosensors and Analytical Detection ; Bacteriophages and microbial interactions
Authors: Xuanyu Zhu | Francesco Paesani
Source: Journal of Chemical Theory and Computation (article, 2025-07-05)
Field: Chemistry — Spectroscopy

Permutationally Invariant Fourier Series for Accurate and Robust Data-Driven Many-Body Potentials We present a robust solution to the long-standing challenge of eliminating unphysical energy predictions, or "holes," in machine-learned many-body potentials, which can destabilize simulations when encountering configurations beyond the training set. By leveraging permutationally invariant Fourier series (PIFSs) within the MB-nrg data-driven many-body formalism, we introduce a new approach that significantly enhances the numerical stability of MB-nrg potential energy functions (PEFs) while preserving accuracy and transferability. Unlike conventional strategies that attempt to "plug holes" by expanding training data sets, PIFSs provide a more fundamental and efficient means of ensuring physically meaningful extrapolation across diverse molecular configurations. Using water as a benchmark system, we demonstrate that the MB-pol(PIFS) PEF retains the high accuracy of MB-pol across gas and condensed phases while extending the PEF's stability to a much broader range of thermodynamic conditions. Our results suggest that the PIFS-based MB-nrg many-body formalism provides a general framework for constructing accurate and robust physics-based/machine-learned potentials applicable to a broad range of molecular systems. Computer science ; Series (stratigraphy) ; Fourier series ; Invariant (physics) ; Fourier transform ; Statistical physics ; Algorithm ; Physics ; Mathematics ; Mathematical analysis ; Quantum mechanics Advanced NMR Techniques and Applications ; Quantum, superfluid, helium dynamics ; Solid-state spectroscopy and crystallography
Authors: Fan Xie | Qiaoling Liu | Longhai Zhuo | Haitao Wei | Yu‐Xuan Shang | Tao Liu | Zhaoqing Lu
Source: Composite Structures (article, 2025-05-04)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Hierarchically engineered Sandwich-Structured h-MXene/ANF hybrid films with tunable electromagnetic interference shielding and exceptional environmental resilience Electromagnetic shielding ; Resilience (materials science) ; Electromagnetic interference ; Materials science ; Interference (communication) ; Composite material ; Optoelectronics ; Electronic engineering ; Engineering ; Electrical engineering Electromagnetic wave absorption materials ; MXene and MAX Phase Materials ; Advanced Antenna and Metasurface Technologies
Authors: Abid Hussain | Muhammad Usman
Source: Nanotechnology for Environmental Engineering (article, 2025-12-27)
Field: Materials Science — Materials Chemistry

Synergistic nanobioremediation: exploring nanoparticle–plant–microbe interactions for sustainable soil decontamination Bioremediation ; Phytoremediation ; Environmental remediation ; Soil contamination ; Arable land ; Bioaugmentation ; Sustainable agriculture Nanoparticles: synthesis and applications ; Arsenic contamination and mitigation ; Plant-Microbe Interactions and Immunity
Authors: Jisu Kim | Ashish Kumar | J.H. Kim | Hayoung Park | Suwan Lee | Rana Basit Ali | Hyungtak Seo
Source: Journal of Alloys and Compounds (article, 2025-08-25)
Field: Materials Science — Electronic, Optical and Magnetic Materials

High power operating neuromorphic transistor based on F-doped β-Ga2O3 channel on Si wafers Neuromorphic engineering ; Wafer ; Optoelectronics ; Materials science ; Transistor ; Doping ; Channel (broadcasting) ; Power (physics) ; Power semiconductor device ; Electrical engineering ; Nanotechnology ; Computer science ; Engineering ; Physics ; Artificial neural network ; Voltage Ga2O3 and related materials ; ZnO doping and properties ; Electronic and Structural Properties of Oxides
Authors: Yuxuan Ma | Taro Takemata | Fangsi Ren | S Nakaya | Mitsuhiro Tsue
Source: Proceedings of the Combustion Institute (article, 2025-01-01)
Field: Materials Science — General Materials Science

Bayesian MCMC estimation of the limiting oxygen concentrations for laboratory electrical wires in various gravity levels Scaling analysis offers a promising approach for predicting the flammability of electrical wires in manned space missions, yet determining the high-dimensional model parameter vector remains challenging, particularly when extrapolating to unknown gravities. This study introduces an effective method for predicting the limiting oxygen concentration (LOC) of electrical wires across different gravities, by integrating physical flame spread modeling with the data-driven technique and ground-based experimental data. A flame spread model for thin wires was developed based on the energy conservation law, and the LOC is determined by the existence of a stable-physical solution to the resulting nonlinear equation. Model parameters were estimated using a Bayesian approach, specifically the Markov Chain Monte Carlo (MCMC) method, trained on experimental LOC data under various hypergravity and opposed flow conditions. The results demonstrate the model’s capability to predict LOC curves accurately across gravity levels, providing fire safety margins based on uncertainties in model parameters and experimental measurements. The physics underlying the inferred parameter values was discussed, showing the important role of boundary layer effect and structure of the flame front. The interdependence of model parameters governing the blowoff or quenching branches allows for their values to be inferred via posterior distributions or inherent correlations. Interestingly, despite notable variations in quenching and blowoff branches, the predicted minimum LOC (MLOC) remains largely unchanged from 0 g to 4 g, thus it appears feasible to consider MLOC as a quasi-intrinsic property of the tested wire itself. Stable flame spread cannot be sustained in low-speed, low-gravity environments, even in oxygen-enriched atmospheres, due to the significant radiative heat loss. This “physics-informed data-driven” modelling approach bridges the gap between uncertainties in scaling analysis and practical flammability evaluations, thereby offering a more reliable methodology for screening spacecraft materials using ground-based facilities that support fire safety for space missions to Moon and Mars. Markov chain Monte Carlo ; Nonlinear system ; Monte Carlo method ; Scaling ; Bayesian inference ; Bayesian probability ; Limiting ; Quenching (fluorescence) ; Boundary layer ; Parameter space Engineering and Material Science Research ; Fire dynamics and safety research ; Wind and Air Flow Studies
Authors: Hans‐Jörg Schneider
Source: ACS Bio & Med Chem Au (review, 2025-04-11)
Field: Chemistry — Physical and Theoretical Chemistry

Problematic Attributions of Entropic and Hydrophobic Effects in Drug Interactions The ΔG affinity of drugs with biopolymers and the underling noncovalent interactions play an essential role in drug discovery. Supramolecular complexes can be designed for the identification and quantification of specific interactions, including their dependence on the medium; they also secure the additivity of ΔΔG increments. Such analyses have helped to clarify hydrophobic effects in intermolecular associations, which are barely measurable with small alkyl groups, but large in the presence of curved surfaces in which the replacement of hydrogen bond-deficient water molecules by a ligand leads to sizable enthalpy gain. Difficult to predict entropy contributions TΔS to ΔG vary between 5% and over 90%, particularly in drug associations, as is obvious from literature data. As illustrated with several drug complexes, many so-called hydrophobic effects involve in fact van der Waals or dispersive interactions. Measurements with supramolecular porphyrin complexes allowed us to derive dispersive binding contributions for many groups, which exhibit a correlation with polarizability. In consequence, heteroatoms or π-systems always lead to enhanced van der Waals contributions, while for hydrophobic effects the opposite is expected. Binding contributions from supramolecular complexes can in the future also help artificial intelligence approaches in drug discovery, by expansion of hybrid databases with potential ligands containing groups with desired binding contributions. Attribution ; Drug ; Psychology ; Chemistry ; Pharmacology ; Social psychology ; Medicine thermodynamics and calorimetric analyses ; Analytical Chemistry and Chromatography ; Lipid Membrane Structure and Behavior
Authors: Lunjie Huang | Xinyuan Zhao | Jianlong Wang | Qiang He | Bi Shi
Source: Trends in Food Science & Technology (article, 2025-04-09)
Field: Materials Science — Materials Chemistry

Enzyme-inspired nanosensing of food antioxidants: From targeted quantification to system-level analysis Computer science ; Chemistry Advanced Nanomaterials in Catalysis ; Electrochemical sensors and biosensors ; Nanoparticles: synthesis and applications
Authors: Sensen Meng | Gang Zhang | Zhipeng Tang | Qing Wang | Yang Yang | Kaiming Wu
Source: steel research international (review, 2025-07-06)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Critical Factors Influencing the Formation of Forsterite Film in Grain‐Oriented Electrical Steel: A Systematic Review Grain‐oriented electrical steel (GOES), a cornerstone of modern energy infrastructure, owes its superior performance to the well‐engineered forsterite (Mg 2 SiO 4 ) film formed during high‐temperature annealing. This interfacial layer is critical for GOES magnetic properties, insulation, and corrosion resistance. This review focuses on describing research into the influencing factors of forsterite film formation, including but not limited to key determinants such as surface oxide layer, magnesia (MgO) characteristics, additives, annealing process parameters, and coating methods. The article also summarizes current research challenges in the field, such as: precise regulation of oxide layer composition and structure; optimization bottlenecks in high‐ temperature annealing parameters; stability control of MgO performance; uniformity and defect suppression in coating processes; additive balance issues; and challenges in industrial‐scale production. Concurrently, this article presents future prospects for current research directions, proposing: deep integration of multiscale modeling and dynamic simulation; innovation in low‐temperature processes and inhibitor functional design; functional design and green synthesis technologies for MgO; intelligent process control and big data‐driven optimization; revealing interfacial dynamic mechanisms through advanced characterization techniques; and synergistic enhancement of environmental friendliness and cost‐effectiveness. This vision is expected to fully unleash the potential of GOES, enabling a more energy‐efficient and sustainable energy future. Forsterite ; Materials science ; Grain size ; Metallurgy ; Composite material ; Engineering physics ; Mineralogy ; Engineering ; Geology Magnetic Properties and Applications ; Microstructure and Mechanical Properties of Steels ; Electric Motor Design and Analysis
Authors: Lirong Liang | Longwei Li | Li Liu | Shuting Dong | Chunyu Du | Zhenqiang Ye | Guangming Chen
Source: Chemical Engineering Journal (article, 2025-06-21)
Field: Materials Science — Materials Chemistry

A compressible wave-like thermoelectric generator with excellent mechanical and humidity stability Materials science ; Humidity ; Thermoelectric effect ; Compressibility ; Generator (circuit theory) ; Thermoelectric generator ; Composite material ; Stability (learning theory) ; Mechanical engineering ; Mechanics ; Thermodynamics ; Engineering ; Physics ; Computer science Advanced Thermoelectric Materials and Devices ; Advanced Thermodynamics and Statistical Mechanics ; Thermal Radiation and Cooling Technologies
Authors: Jinchen Xie | Christian Linder
Source: Journal of the Mechanics and Physics of Solids (article, 2025-10-04)
Field: Materials Science — Materials Chemistry

Plane strain couple stress based contact mechanics of flexoelectric solids Contact mechanics ; Finite element method ; Multiphysics ; Plane stress ; Continuum mechanics ; Nanoindentation ; Contact force ; Eigenstrain ; Viscoelasticity ; Stress field Nonlocal and gradient elasticity in micro/nano structures ; Mechanical stress and fatigue analysis ; Force Microscopy Techniques and Applications
Authors: Matteo Becchi | Giovanni M. Pavan
Source: Machine Learning Science and Technology (article, 2025-12-16)
Field: Materials Science — Materials Chemistry

Maximum information extraction via clustering and minimization of Shannon entropy Abstract In the analysis of any type of system, granting maximum information extraction (MInE) from its data is non-trivial. Confidence in successful information extraction typically builds on prior knowledge of the studied system or on the user’s experience. However, a robust and objective criterion for ensuring MInE from data is difficult to define. Here, we introduce a data-driven approach that employs Shannon entropy as a transferable metric to assess and quantify MInE from data via their clustering into statistically-relevant micro-domains. The method is general and can be applied virtually to any type of data or system. We demonstrate its efficiency by analyzing, as a first example, time-series data extracted from molecular dynamics simulations of water and ice coexisting at the solid/liquid transition temperature. The method allows quantifying the information contained in the data distributions (time-independent component) and the additional information gain attainable by analyzing data as time-series (i.e. accounting for the information contained in data time-correlations). The different micro-domains that can be effectively resolved and classified in the system are characterized by own entropy, which are found consistent with experimentally known thermodynamic parameters. A second test case demonstrates how the MInE approach is also effective for high-dimensional datasets and clearly shows how including little informative, but noisy, extra components/features in high-dimensional analyses may be not only useless, but even detrimental to MInE. This provides a robust parameter-free approach and quantitative metrics for data-analysis, and for the study of any type of system from its data. Cluster analysis ; Entropy (arrow of time) ; Minification ; Information extraction ; Information theory ; Principle of maximum entropy ; Kullback–Leibler divergence ; Metric (unit) Machine Learning in Materials Science ; nanoparticles nucleation surface interactions ; Protein Structure and Dynamics
Authors: Chuandong Li | Xinhai Yu | Wei Yu | Bo Li | Shan‐Tung Tu
Source: International Journal of Hydrogen Energy (article, 2025-08-25)
Field: Materials Science — Materials Chemistry

Multiobjective optimization of 3D printed structured catalysts and reactors for high-efficiency vehicular methanol steam reforming Steam reforming ; Methanol ; Process engineering ; Catalysis ; Hydrogen production ; Chemical engineering ; Materials science ; Environmental science ; Waste management ; Chemistry ; Engineering ; Organic chemistry Catalytic Processes in Materials Science ; Catalysis and Hydrodesulfurization Studies ; Catalysts for Methane Reforming
Authors: Aswathy Jayasekher | Devendra Prajapati | Ajoy K. Palit | Francesco Maurelli | P. C. Panchariya
Source: Microchemical Journal (article, 2025-05-06)
Field: Chemistry — Analytical Chemistry

Multi-spectral sensor fusion methodology for the quality assessment of Cymbopogon citratus essential oil Cymbopogon citratus ; Essential oil ; Quality (philosophy) ; Chemistry ; Chromatography ; Physics Spectroscopy and Chemometric Analyses ; Essential Oils and Antimicrobial Activity ; Advanced Chemical Sensor Technologies
Authors: Mohammed Grabsi | Nacéra Zabat | Mohamed Djermane | Abdeltif Amrane
Source: Molecular Catalysis (article, 2025-03-14)
Field: Materials Science — Materials Chemistry

Environmentally friendly and recyclable Dawson-type polyoxometalate: A novel homogeneous catalytic system for degradation of dye pollutants Polyoxometalate ; Environmentally friendly ; Pollutant ; Catalysis ; Homogeneous ; Degradation (telecommunications) ; Chemistry ; Chemical engineering ; Organic chemistry ; Environmental chemistry ; Computer science ; Engineering ; Physics Polyoxometalates: Synthesis and Applications ; Nanomaterials for catalytic reactions ; Advanced oxidation water treatment
Authors: Yuxin He | Xinyu Gao | Jiaming Liu | Junxin Zhou | Jiayu Wang | Dan Li | Sha Zhao | Wei Feng
Source: Nanomaterials (review, 2025-07-28)
Field: Materials Science — Polymers and Plastics

Recent Advances in the Application of VO2 for Electrochemical Energy Storage Energy storage technology is crucial for addressing the intermittency of renewable energy sources and plays a key role in power systems and electronic devices. In the field of energy storage systems, multivalent vanadium-based oxides have attracted widespread attention. Among these, vanadium dioxide (VO<sub>2</sub>) is distinguished by its key advantages, including high theoretical capacity, low cost, and strong structural designability. The diverse crystalline structures and plentiful natural reserves of VO<sub>2</sub> offer a favorable foundation for facilitating charge transfer and regulating storage behavior during energy storage processes. This mini review provides an overview of the latest progress in VO<sub>2</sub>-based materials for energy storage applications, specifically highlighting their roles in lithium-ion batteries, zinc-ion batteries, photoassisted batteries, and supercapacitors. Particular attention is given to their electrochemical properties, structural integrity, and prospects for development. Additionally, it explores future development directions to offer theoretical insights and strategic guidance for ongoing research and industrial application of VO<sub>2</sub>. Energy storage ; Electrochemical energy storage ; Renewable energy ; Nanotechnology ; Supercapacitor ; Vanadium ; Lithium (medication) ; Materials science ; Process engineering ; Computer science ; Electrochemistry ; Power (physics) ; Engineering ; Electrical engineering ; Chemistry Transition Metal Oxide Nanomaterials ; Advanced battery technologies research ; Supercapacitor Materials and Fabrication