jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Joydip Sengupta | Arpita Adhikari | Chaudhery Mustansar Hussain
Source: Chemosensors (article, 2025-11-30)
Field: Materials Science — Polymers and Plastics

Organic Field-Effect Transistor Biosensors for Clinical Biomarkers: Materials, Architectures, and Translational Applications Organic field-effect transistor (OFET) biosensors have emerged as a transformative technology for clinical biomarker detection, offering unprecedented sensitivity, selectivity, and versatility in point-of-care (POC) diagnostics. This review examines the fundamental principles, materials innovations, device architectures, and clinical applications of OFET-based biosensing platforms. The unique properties of organic semiconductors, combined with advanced biorecognition strategies, enable the detection of clinically relevant biomarkers at low concentrations. Recent developments in organic semiconductor materials have significantly enhanced device performance and stability. The integration of novel device architectures such as electrolyte-gated OFETs (EGOFETs) and extended-gate configurations has expanded the operational capabilities of these sensors in aqueous environments. Clinical applications span a broad spectrum of biomarkers, demonstrating the versatility of OFET biosensors in disease diagnosis and monitoring. Despite remarkable progress, challenges remain in terms of long-term stability, standardization, and translation to clinical practice. The convergence of organic electronics, biotechnology, and clinical medicine positions OFET biosensors as a promising platform for next-generation personalized healthcare and precision medicine applications. Biosensor ; Organic field-effect transistor ; Transistor ; Precision medicine ; Field-effect transistor ; Personalized medicine Conducting polymers and applications ; Analytical Chemistry and Sensors ; Electrochemical sensors and biosensors
Authors: Nathália M. P. Rosa | Itamar Borges
Source: ChemRxiv (preprint, 2025-01-20)
Field: Materials Science — Polymers and Plastics

Review on the DFT Computation of Bulk Heterojunction and Dye-sensitized Organic Solar Cells Properties Organic solar cells (OSCs) represent a promising renewable energy technology due to their flexibility, low production cost, and environmental sustainability. To advance OSC efficiency and stability, Density Functional Theory (DFT) has emerged as a powerful computational tool, enabling the prediction and optimization of critical properties at the molecular and device levels. This review highlights the key properties of bulk heterojunction solar (BHJ) solar cells and dye-sensitized solar cells (DSSCs) that can be accurately computed using DFT, including electronic structure properties (HOMO-LUMO energy levels, bandgap energies, and exciton binding energies, which influence charge separation and transport); optical properties (absorption spectra and light-harvesting efficiency, essential for maximizing photon capture); charge transport properties (reorganization energies, electron, and hole mobilities, and charge transfer rates that govern carrier dynamics within devices); interfacial properties (energy alignment at donor-acceptor interfaces, contributing to efficient charge separation and minimizing recombination) and chemical reactivity descriptors (ionization potential, electron affinity, chemical hardness, and electrophilicity, which facilitate material screening for OSC applications). We show how to compute the power conversion efficiency (PCE) of OSCs from DFT. The review also discusses the importance of selecting appropriate exchange-correlation functionals and basis sets to ensure the accuracy of DFT predictions. By providing reliable computational insights, DFT accelerates the rational design of OSC materials, guiding experimental efforts and reducing resource demands. This work underscores DFT’s pivotal role in optimizing OSC performance, fostering the development of next-generation photovoltaic technologies. Heterojunction ; Computation ; Organic solar cell ; Materials science ; Dye-sensitized solar cell ; Optoelectronics ; Computer science ; Chemistry ; Composite material ; Physical chemistry ; Algorithm Conducting polymers and applications ; Organic Electronics and Photovoltaics
Authors: Hanifi Kebiroglu | Mücahit Yılmaz
Source: Journal of Physical Chemistry and Functional Materials (article, 2025-12-23)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Spectroscopic Characterization, Electronic Structure Analysis, and DFT Investigation of C₁₁H₁₄N₂O₄ In this study, the electronic properties of 2-(Tetrahydro-2H-pyran-4-ylmethoxy)-4-pyrimidinecarboxylic acid (THPMPCA, C₁₁H₁₄N₂O₄) were investigated using density functional theory (DFT) calculations with the LanL2MB basis set (0.625 eV). Spectroscopic methods including Ultraviolet-visible (UV-vis), Fourier Transform Infrared (FTIR), and Nuclear Magnetic Resonance (NMR) were employed to characterize the structural and electronic properties of THPMPCA. Detailed electronic structure analyses such as density of states (DOS), highest occupied molecular orbital (HOMO), and lowest unoccupied molecular orbital (LUMO) calculations were performed to elucidate the electronic transitions and stability of the molecule. The results revealed significant improvements in electronic properties, suggesting enhanced applicability of THPMPCA in electronic and medical fields. This comprehensive investigation provides insight into optimizing THPMPCA for future technological and pharmaceutical applications. Electronic structure ; Density functional theory ; Basis set ; Molecular orbital ; Infrared ; Resonance (particle physics) ; Atomic electron transition ; Molecular electronic transition Nonlinear Optical Materials Research ; Metal complexes synthesis and properties ; Advanced Physical and Chemical Molecular Interactions
Authors: Jon Otegi | Javier Carrasco | Hegoi Manzano
Source: Battery energy (article, 2025-11-11)
Field: Materials Science — Materials Chemistry

The Influence of the Electrolyte on Lithium Transport Through the DAAQ‐TFP‐COF Structure: A Molecular Dynamics Study ABSTRACT Covalent organic frameworks (COFs) have emerged as promising electrode materials for lithium‐ion batteries (LIBs) due to their tunable redox‐active properties and environmental benefits. However, the influence of electrolytes on COF‐based battery performance remains poorly understood at the molecular level. In this study, we employ molecular dynamics simulations to investigate the interaction between terephthalaldehyde and 1,3,5‐tris(4‐aminophenyl)benzene COF (DAAQ‐TFP‐COF) and two organic electrolytes: lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) in tetraethylene glycol dimethyl ether (TEGDME) and LiPF 6 in a mixture of ethylene carbonate and diethyl carbonate (EC/DEC). Our simulations reveal different lithium coordination environments: while LiTFSI in TEGDME shows better salt dissociation, LiPF 6 in EC/DEC exhibits higher lithium self‐diffusion coefficients, despite greater coordination to the COF structure. We identify that lithium transport is primarily mediated by the organic solvent, with COF coordination sites hindering mobility. These findings highlight the importance of electrolyte selection in optimizing COF‐based electrodes for LIBs and provide novel insights into the interplay between structural properties and ionic dynamics in porous frameworks. Electrolyte ; Lithium (medication) ; Ethylene carbonate ; Molecular dynamics ; Ionic bonding ; Dimethyl carbonate ; Battery (electricity) ; Electrode ; Covalent bond Covalent Organic Framework Applications ; Advanced battery technologies research ; Advanced Battery Materials and Technologies
Authors: E. Grajales-González | Adri C. T. van Duin | S. Mani Sarathy
Source: Physical Chemistry Chemical Physics (article, 2025-01-01)
Field: Chemistry — Inorganic Chemistry

Methanol-to-hydrocarbon initiation reactions over a zeolite catalyst: reactive molecular dynamics simulations Environmental concerns and energy security drive the need for renewable alternatives to fossil fuels. Methanol is an ideal candidate as it enables the synthesis of olefins and fuels from biomass using zeolite-catalyzed processes, which inspired the concept of "Methanol Economy" since it ideally implies an oil-independent scenario. Although MTH industrial units already exist, many fundamental aspects remain unknown. Therefore, in this contribution, we developed a ReaxFF reactive force field to study the dynamic features of the equilibration stage of the MTH process in an H-ZSM-5 zeolite. Simulations were run from 600 to 1200 K during 1000 ps, using a constant number of molecules, pressure, and temperature (NPT ensemble). Methanol conversion increases from 800 to 1000 K to form water and the crucial intermediate surface methoxy species (SMS), whose production diminishes at 1200 K because of the prevalence of undesired methane. Generally, temperatures above 1200 K can lead to questionable reactions due to entropy effects. Humidity at 800 K modifies the nature of the zeolite acidity from static to dynamic, embodied in hydronium ions, which enhances methanol conversion <i>via</i> hydrogen transfer reactions and framework activation, namely, water protonation leaves a negatively charged framework that eventually facilitates the dissociation of protonated methanol in water and an SMS. Cation diffusion was pervasive, and it is hypothesized that this relieves the entropic penalties of several relevant reactions. This phenomenon showcases a critical manifestation of dynamic effects that complements experimental and theoretical research mainly conducted by static density functional theory methods. Overall, dynamic effects involving diffusing cations and modification of the zeolite interior by water are complex and call for more extensive investigations. ReaxFF ; Molecular dynamics ; Methanol ; Hydronium ; Protonation ; Dissociation (chemistry) ; Density functional theory ; Hydrogen Zeolite Catalysis and Synthesis ; Microbial Metabolic Engineering and Bioproduction ; Catalysts for Methane Reforming
Authors: Xiaoguang Zhang | Wei Wang | Juan Zhang
Source: Nanomaterials (article, 2025-08-22)
Field: Materials Science — Materials Chemistry

Preparation of High-Strength and High-Rigidity Carbon Layer on Si/C Material Surface Using Solid–Liquid Coating Method The application of silicon-carbon (Si/C) composite materials in lithium-ion batteries faces problems regarding volume expansion and surface defects. Although coating is a popular modification scheme in the market, the influence of carbon layer quality on the electrochemical performance of Si/C still needs to be studied. By comparing the carbon layers produced by solid-phase and liquid-phase coating methods, an innovative solid-liquid coating technology was proposed to prepare high-strength and high-stiffness carbon layers, and the effects of different coating processes on the physical, mechanical, and electrochemical properties of the materials were systematically studied. Through physical properties and electrochemical testing, it was found that the solid-liquid coating method (Si/C@Pitch+RGFQ) can form a carbon layer with the least defects and the highest density. Compared with solid-phase coating and liquid-phase coating, its specific surface area (SSA) and carbon increment are the lowest, and the surface carbon content and oxygen content are significantly reduced after solid-liquid coating. Mechanical performance tests show that the Young's modulus of the carbon layer prepared by this method reaches 30.3 GPa, demonstrating excellent structural strength and elastic deformation ability. The first coulombic efficiency (ICE) of Si/C@Pitch+RGFQ reached 88.17%, the interface impedance (23.2 Ω) was the lowest, and the lithium-ion diffusion coefficient was significantly improved. At a rate of 0.1 C to 2 C, the capacity retention rate is excellent. After one hundred and a half-cell cycles, the remaining capacity is 1420.5 mAh/g, and the capacity retention rate reaches 92.4%. The full-cell test further proves that the material has a capacity retention rate of 82.3% and 81.3% after 1000 cycles at room temperature and high temperature (45 °C), respectively. At the same time, it has good rate performance and high-/low-temperature performance, demonstrating good commercial application potential. The research results provide a key basis for the optimized preparation of the surface carbon layer of Si/C composite materials and promote the practical application of high-performance silicon-based negative electrode materials. Materials science ; Coating ; Composite material ; Layer (electronics) ; Solid surface ; Rigidity (electromagnetism) ; Carbon fibers ; Surface layer ; Chemical engineering ; Chemistry ; Composite number Diamond and Carbon-based Materials Research ; Graphene research and applications ; ZnO doping and properties
Authors: Majid Vafaeezadeh | Fatemeh Rajabi | Xian Hua Qiu | Marco A. M. Tummeley | Paul Hausbrandt | Sven Schaefer | Alina Ouissa | Anna Demchenko | Johannes L’huillier | Volker Schünemann | Wolfgang Kleist | Werner R. Thiel
Source: Catalysts (article, 2025-12-01)
Field: Materials Science — Materials Chemistry

Synergy in Sonogashira Cross-Coupling Reactions with a Magnetic Janus-Type Catalyst This work describes the straightforward synthesis of a novel heterogeneous palladium catalyst immobilized on magnetic Janus-type silica particles coated with an amphiphilic ionic liquid (IL) layer. The material was prepared via a one-pot process wherein TEOS (tetraethoxysilane) and a bis(triethoxysilane) IL precursor are combined to form hollow shells. The IL motifs are selectively located on the outer surface of the hollow particles and serve as centers for the immobilization of palladium species on the material’s surface. The outer surface also hosts magnetic nanoparticles in close proximity to the palladium sites. Thanks to the uniform coverage of the surface with the amphiphilic IL functionality, the material exhibits a well-balanced wettability with reaction components of different polarities. The catalyst’s activity was tested in the Sonogashira cross-coupling reaction of terminal acetylenes and iodobenzene derivatives in water as the solvent. The results show that the mixed palladium–iron oxide catalyst exhibits higher activity than materials containing either immobilized palladium or iron oxide alone, suggesting a synergistic effect in this reaction. Additionally, the reaction proceeds well in the absence of expensive organic ligands and commonly employed additives such as copper co-catalysts or phase transfer catalysts. Furthermore, the material was also used in the oxidative Sonogashira coupling reaction of phenylboronic acid and phenylacetylene. The catalyst can be easily separated using an external magnet and can be reused several times. The feasibility of producing diphenylacetylene on a gram scale via the Sonogashira cross-coupling reaction was also investigated. Sonogashira coupling ; Iodobenzene ; Catalysis ; Palladium ; Diphenylacetylene ; Coupling reaction ; Alkyne ; Ionic liquid ; Heterogeneous catalysis Pickering emulsions and particle stabilization ; Catalytic Cross-Coupling Reactions ; Ionic liquids properties and applications
Authors: Ekta A Dixit | D.C. Joshi | Nalini S. Patil
Source: Journal of Mathematical Problems Equations and Statistics (article, 2025-01-01)
Field: Chemistry — Inorganic Chemistry

Nanotechnology-enhanced catalysts for sustainable chemical processes and their mathematical and computational approach Nanotechnology has emerged as a transformative approach to catalysis, enhancing reaction kinetics, efficiency, and sustainability in industrial chemical processes. Conventional catalytic systems face limitations, including high activation energy, catalyst deactivation, and excessive energy consumption, leading to inefficient reaction mechanisms. This study focuses on optimizing nanotechnology enhanced catalysts through mathematical modeling, computational simulations, and sustainability analysis. The catalytic activity is analyzed using the Langmuir-Hinshelwood and Michaelis-Menten kinetic models, which describe adsorption-desorption reaction mechanisms on nanostructured surfaces. To predict catalyst behavior at the atomic level, Density Functional Theory (DFT) simulations and Monte Carlo methods are employed, providing insights into reaction pathways, electronic structure modifications, and adsorption energetics. Computational Fluid Dynamics (CFD) simulations optimize nanocatalyst dispersion, improving mass transfer efficiency. Numerical results indicate a 35% reduction in activation energy for CO₂ hydrogenation using Pt-doped Ru nanoparticles on dendritic fibrous nanosilica (DFNS) compared to conventional catalysts. Additionally, graphene-supported electrocatalysts demonstrate a 42% enhancement in oxygen evolution reaction (OER) efficiency, optimizing their role in hydrogen production and fuel cells. A life cycle assessment (LCA) confirms a 50% reduction in toxic by-product generation, establishing nanocatalysts as a sustainable alternative. This research presents a computationally-driven strategy for designing nanocatalysts with tunable reactivity and enhanced durability, with implications for green synthesis, CO₂ reduction, and renewable energy applications. Nanotechnology ; Biochemical engineering ; Catalysis ; Materials science ; Management science ; Computer science ; Engineering ; Chemistry ; Organic chemistry Zeolite Catalysis and Synthesis ; Catalytic Processes in Materials Science ; Nanomaterials for catalytic reactions
Authors: Mostafa Bamdad | Mohammad Sadegh Eshaghi | Cosmin Anitescu | Navid Valizadeh | Timon Rabczuk
Source: ArXiv.org (preprint, 2025-12-04)
Field: Materials Science — Materials Chemistry

PENCO: A Physics-Energy-Numerics-Consistent Operator for 3D Phase Field Modeling Accurate and efficient solutions of spatiotemporal partial differential equations (PDEs), such as phase-field models, are fundamental for understanding interfacial dynamics and microstructural evolution in materials science and fluid mechanics. Neural operators (NOs) have recently emerged as powerful data-driven alternatives to traditional solvers; however, existing architectures often accumulate temporal errors, struggle to generalize over long temporal horizons, and require large training datasets. To overcome these limitations, we propose PENCO (Physics-Energy-Numerics-Consistent Operator), a hybrid operator-learning framework that integrates physical laws with data-driven neural operator methods, using either the Fourier Neural Operator (FNO-4D) or the Multi-Head Neural Operator (MHNO) architecture as the backbone. The formulation introduces an enhanced L^2 Gauss-Lobatto collocation residual around the temporal midpoint that robustly enforces the governing dynamics and significantly improves accuracy, a Fourier-space numerical consistency term that captures the balanced behavior of semi-implicit discretizations, and an energy-dissipation constraint that ensures thermodynamic consistency. Additional low-frequency spectral anchoring and teacher-consistency mechanisms further stabilize learning and suppress long-term error growth. This hybrid design enables PENCO to preserve governing physics while mitigating long-term error growth. Through extensive three-dimensional phase-field benchmarks on periodic cubic domains, covering phase ordering, crystallization, epitaxial growth, and complex pattern formation, PENCO demonstrates superior accuracy, stability, and data efficiency compared to state-of-the-art neural operators, including FNO-4D and MHNO, while maintaining physically consistent evolution. The associated dataset and implementation are available at github.com/MBamdad/PENCO. Operator (biology) ; Midpoint ; Artificial neural network ; Constraint (computer-aided design) ; Residual ; Fourier transform ; Phase (matter) ; Partial differential equation Solidification and crystal growth phenomena ; Model Reduction and Neural Networks ; Machine Learning in Materials Science
Authors: Taibao Zhao | Bidyut Baran Saha
Source: Proceedings of International Exchange and Innovation Conference on Engineering & Sciences (IEICES) (article, 2025-10-30)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Applications of Biomass-Derived Carbon in Supercapacitor Energy Storage: A Review Biomass-derived carbon materials have garnered significant attention as sustainable, low-cost electrode candidates for supercapacitors owing to their abundant availability and tunable properties.This review categorizes biomass sources into plant-based, animal-based, marine-based, and human waste-based, highlighting their structural diversity and electrochemical potential.Key structural factors, such as pore size distribution and surface functional groups, are discussed in relation to their impact on capacitance performance.Hierarchical porosity enhances ion transport and charge storage, whereas heteroatom doping and oxygen-containing groups contribute to pseudocapacitive behavior.By tailoring these features, biomass carbon materials can achieve a high specific capacitance, excellent rate capability, and cycling stability.Future research directions include precise structural control, exploration of novel biomass precursors, and the development of scalable green synthesis methods.This review aims to provide insights into the rational design of biomass-derived carbons for environmentally friendly and high-performance energy storage applications. Carbon fibers ; Supercapacitor ; Energy (signal processing) ; Process (computing) ; Carbon nanotube Supercapacitor Materials and Fabrication ; Catalysis for Biomass Conversion ; Aerogels and thermal insulation
Authors: Eveliina Korhonen | Mikko Laaksonen | S. -M. Niemi
Source: International Journal of Materials Science (article, 2025-07-01)
Field: Materials Science — General Materials Science

Advances in functional materials: Structural, mechanical, and electronic perspectives Functional materials have become central to technological innovation, offering tailored structural, mechanical, and electronic properties for next-generation applications. This paper explores recent advances in functional materials, focusing on their structural adaptability, mechanical performance under extreme conditions, and electronic versatility for energy and information technologies. Developments in nanostructured composites, high-entropy alloys, and two-dimensional materials have significantly expanded the design landscape, enabling unprecedented strength-to-weight ratios, tunable conductivity, and multifunctionality. The methodology integrates experimental characterization, first-principles simulations, and data-driven approaches to provide a comprehensive assessment of performance metrics. Results highlight the ability of advanced ceramics and hybrid materials to withstand high stress, the role of defect engineering in enhancing durability, and the electronic tunability of graphene derivatives and perovskite oxides for quantum devices and renewable energy applications. Comparative analyses demonstrate that emerging functional materials outperform traditional counterparts in durability, scalability, and efficiency. The discussion situates these findings within the broader context of material design, addressing opportunities in aerospace, biomedical, and energy storage systems. The study underscores the critical importance of integrating computational models with high-throughput experimental validation to accelerate discovery. It concludes by identifying future directions in sustainable synthesis, multiscale modeling, and smart material design, which will likely redefine the structural, mechanical, and electronic paradigms of modern industries. Context (archaeology) ; Smart material ; Electronics ; Electronic materials ; Renewable energy ; Emerging technologies Material Properties and Applications ; Material Science and Thermodynamics