jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Andrea Ambrosino | Giovanni Bove | Marco Sorrentino | F. Postiglione
Source: Energies (article, 2025-09-10)
Field: Materials Science — Materials Chemistry

The Development of a Model-Based Methodology to Implement a Fused Health Indicator for a Solid Oxide Fuel Cell Hydrogen-based technologies are growing, thanks to recent advancements in systems such as fuel cells and electrolyzers. The present work aims to develop a methodology for the definition of a fused health indicator to monitor the operating and health conditions of a solid oxide fuel cell system. A suitable degradation model was built to yield four trendable output indicators, which were subsequently merged to create the fused health indicator. Subsequently, the assessment of off-design conditions and two realistic scenarios (leakage and constant excess of air working regime) was carried out. The health indicator has proved suitable for fault detection, prognostic applications, control strategy improvement, and health management. In particular, the methodology has underlined the necessity of making the control strategy adaptive with respect to degradation. Through this approach, it is observed that reducing the solid oxide fuel cell temperature difference by 10 °C can result in a 1.2% increase in lifetime. In contrast, the leakage simulation reveals a decrease of about 10.5% in the health state after 100 h, resulting in about a 21% lower end-of-life. Solid oxide fuel cell ; Fuel cells ; Work (physics) ; Leakage (economics) ; Yield (engineering) ; Oxide ; Condition monitoring Advancements in Solid Oxide Fuel Cells ; Fuel Cells and Related Materials ; Combustion and Detonation Processes
Authors: Özge Bağlayan | Cemal Parlak | Özgür Alver
Source: Gümüşhane Üniversitesi Fen Bilimleri Enstitüsü Dergisi (article, 2025-12-15)
Field: Chemistry — Organic Chemistry

Investigation of possible release mechanisms for flurbiprofen and ifosfamide drugs using multi-silicon decorated fullerene-C60: Computational insights Invention and production of new nano-based versatile materials make it possible to design new drug carriers and sensors. In the scope of this work, one of the famous members of fullerene family, C60, was taken as a reference structure and its multi-silicon modified form was investigated as possible drug delivery vehicles towards flurbiprofen and ifosfamide drug molecules. The results suggest that by replacing carbon atoms from the surface of fullerene-C60 with silicon dopants, it is possible to increase the numbers of loaded drugs over the surface of C60 with changing structural, electronic and vibrational properties. Calculations of desorption characteristics via the interpretation of recovery times also showed that the release of flurbiprofen tend to occur faster than that of the release of ifosfamide drug molecule making the selective drug delivery applications possible. Flurbiprofen ; Ifosfamide ; Drug ; Drug delivery ; Pharmacokinetics ; Drug interaction Fullerene Chemistry and Applications ; Boron and Carbon Nanomaterials Research ; Graphene and Nanomaterials Applications
Authors: Shahid Parapurath | Liya Jacob | Nader Vahdati | Ebru Günister
Source: Arabian Journal for Science and Engineering (article, 2025-04-15)
Field: Materials Science — Metals and Alloys

Influence of Microstructure Changes on the Stress Corrosion Properties of U-bend S275 Mild Steel Abstract Current research investigates the material degradation behavior of thermally processed S275 mild steel under continuous stress in chloride and sulfate media at different pH values (4, 7, and 10). The mild steel samples were quenched at 1000 °C, followed by tempering at 600 °C, followed by U-bending the samples and attaching a bolt and nut to develop continuous stress according to ASTM standards. A U-bend sample without heat treatment was used as a reference. The corrosion behavior of the samples was evaluated using linear polarization resistance and potentiodynamic polarization scans. Optical microscopy, scanning electron microscope, roughness measurements, and Raman spectroscopy have been used to examine the wear behavior of S275 samples. Quenching followed by tempering caused the quasi-polygonal ferrite and granular bainite to convert to martensite. This microstructural change impacted on the material’s mechanical properties and corrosion behavior. Tempering caused a 38% increase in ultimate tensile strength and a 103% increase in yield strength. It also caused a 7–27% increase in corrosion resistance in sulfate media. The pH of the electrolyte solution also influenced corrosion. The corrosion rate of the original and tempered U-bend samples in acidic sulfate media showed approximately a 700% increase in corrosion rate compared to media alkaline and neutral sulfate media samples. The prime reason for the exponential increase in the corrosion rate is the effect of the chemical reaction of highly oxidative species on stress-induced surface defects. Raman analysis confirmed a variety of ferrous oxides and hydroxide formations on the surface of S275 steel. Microstructure ; Materials science ; Corrosion ; Metallurgy ; Stress (linguistics) ; Composite material Hydrogen embrittlement and corrosion behaviors in metals ; Material Properties and Failure Mechanisms ; Fatigue and fracture mechanics
Authors: Yuheng Song | Jing Li | Xueyong Li | Hongmei Liu | Sha Zhou | Yiran Ge | Xin Chen | Zhengzhong Shao | Xiang Fei | Meifang Zhu
Source: Interdisciplinary materials (article, 2025-11-01)
Field: Materials Science — Biomaterials

Dual In Situ Integration for Braided Silk Fibers Enabling Multifunctional Bioactive Sutures ABSTRACT Developing surgical sutures with adjustable bioactivities is essential for diverse surgical interventions. However, adversely affecting their mechanical integrity, biocompatibility, and bioactivity poses a significant challenge. Herein, we present a silk‐based bioactive suture that incorporates silver nanoparticles (AgNPs) and curcumin (Cur) via a dual in situ integration strategy. This innovative approach leverages the unique reactive groups and molecular interactions inherent in silk to facilitate the in situ reduction of AgNPs and the conformal loading of Cur. Extensive in vitro and in vivo evaluations confirm the suture's multifunctionality. This suture excels in real‐time wound monitoring due to its sensitive colorimetric pH response. It is biocompatible and offers strong antibacterial and anti‐inflammatory benefits, essential for infection prevention and inflammation control postsurgery. Moreover, it actively aids wound healing by promoting angiogenesis and collagen deposition, vital for effective tissue repair. This approach provides a promising foundation for creating advanced smart sutures with on‐demand bioactivities and on‐site monitoring capabilities. In situ ; Biocompatible material ; Curcumin ; Fibrous joint ; In vivo ; Angiogenesis ; Wound healing ; SILK Silk-based biomaterials and applications ; Surgical Sutures and Adhesives ; Wound Healing and Treatments
Authors: Tamara Z. Fadhil | Ameer A. Kareim Al-Sahlawi
Source: Al-Iraqia Journal of Scientific Engineering Research (article, 2025-06-29)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Recent Developments in Active Metamaterials and their Practical Applications Mechanical metamaterials are specially designed materials that exhibit unconventional mechanical properties due to their precisely designed microarchitectures and inherent material characteristics. Recent developments have made it possible to create active, tunable, and reconfigurable metamaterials, which provide dynamic control over electromagnetic behavior and offer significant advantages over conventional static systems. In this paper, tuning mechanisms such as circuit-based, geometric, material-driven, and active control mechanisms are comprehensively discussed. It extends to their application in a number of devices, including antennas, filters, imaging devices, and sensors. Although these technologies have a great deal of promise, challenges exist, specifically with respect to fabrication complexity and limited tunability. Continuous breakthroughs in materials science and device engineering will be essential to developing these metamaterials from concepts in the lab to practical, real-world applications. The main contribution of this review is to give a systematic overview of the most recent tuning mechanisms for active metamaterials, while also highlighting the integration of artificial intelligence as a transformative approach for future design and optimization. Metamaterial ; Computer science ; Physics ; Optics Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: P. R. Kulkarni
Source: ChemRxiv (article, 2025-09-08)
Field: Chemistry — Spectroscopy

Predicting Supramolecular Stability: A Validated Framework Combining Orthogonal Topological and Electrostatic Descriptors The design of functional liquids like Deep Eutectic Solvents (DES) is hampered by an incomplete understanding of the link between molecular components and the physical properties of the resulting mixture. Traditional metrics like binding energy (ΔE)fail to explain why some strongly bound pairs form low-viscosity liquids while others form glassy solids. This work introduces a holistic, multi-scale computational framework, built upon a validated quantum chemical method, to deconstruct supramolecular stability into two distinct, orthogonal physical phenomena: local bonding quality and global electrostatic neutralization. We develop two novel descriptors: the topological Non-Covalent Interaction Score (SNCI), which quantifies localized interaction strength, and the electrostatic COSMO Dimer Interaction Score (SCDI), which measures the homogeneity of the complex's surface potential. By applying this framework to nearly 3,000 DES complexes, we construct a "Stability Phase Space" that classifies pairs into distinct archetypes, such as rigidly bound "Local Champions" and flexibly packed "Global Stabilisers." This classification provides a new, physically-grounded rationale for designing complex liquids and offers a powerful, scalable methodology for screening candidates. Supramolecular chemistry ; Homogeneity (statistics) ; Electrostatics ; Scalability ; Topology (electrical circuits) ; Dimer ; Stability (learning theory) ; Interaction energy ; Construct (python library) Analytical Chemistry and Chromatography ; Computational Drug Discovery Methods ; Machine Learning in Materials Science
Authors: Kevin V. Bigting | Shubhadeep Nag | Yaxin An
Source: arXiv (Cornell University) (preprint, 2025-11-14)
Field: Materials Science — Materials Chemistry

Martini Mapper: An Automated Fragment-Based Framework for Developing Coarse-Grained Models within the Martini 3 Framework Coarse-graining (CG) reduces molecular details to extend the time and length scales of molecular dynamics simulations to microseconds and micrometers. However, the CG approaches have long been limited by the difficulty of constructing both accurate and transferable models efficiently, considering the large diversity of chemical structures of materials. Among CG force fields, Martini is the most widely used, as it retains essential chemical features while offering substantial computational efficiency. Its most recent version, Martini 3, expands chemical resolution through a much broader bead set, particularly for small molecules. However, this flexibility also complicates the mapping of organic molecules because of context-dependent rules and the lack of standardized procedures. To address this issue, we present an automated framework that builds Martini 3 models directly from SMILES (Simplified Molecular Input Line Entry System) strings by combining a curated bead dictionary with a hierarchical, rule-based algorithm and molecule-specific bonded parameters. Our framework, Martini Mapper https://github.com/eliobaby/Martini_mapper, generated Martini 3 models for 6,280 molecules across six chemically diverse datasets, including 1,689 systems with bond/angle parameters and additional large systems mapped at the topological level. A curated subset of 1,075 mapped structures was benchmarked using transfer free energies in hydrated octanol, hexadecane, and chloroform from water against reference data wherever available. We further examined the benchmark with structural validation via SASA, yielding good agreement with experimental and atomistic reference data. The workflow can also map large molecules containing up to 172 heavy atoms, exceeding the capabilities of existing automated approaches. Our framework, therefore, enables Martini 3 structures for high-throughput simulations. Workflow ; Flexibility (engineering) ; Scalability ; Set (abstract data type) ; Resolution (logic) ; Chemical database ; Field (mathematics) ; Small molecule Machine Learning in Materials Science ; Block Copolymer Self-Assembly ; Protein Structure and Dynamics
Authors: Amira A. Alakhdar | Barnabás Póczos | Newell R. Washburn
Source: ArXiv.org (preprint, 2025-05-15)
Field: Chemistry — Organic Chemistry

Pharmacophore-Conditioned Diffusion Model for Ligand-Based De Novo Drug Design Developing bioactive molecules remains a central, time- and cost-heavy challenge in drug discovery, particularly for novel targets lacking structural or functional data. Pharmacophore modeling presents an alternative for capturing the key features required for molecular bioactivity against a biological target. In this work, we present PharmaDiff, a pharmacophore-conditioned diffusion model for 3D molecular generation. PharmaDiff employs a transformer-based architecture to integrate an atom-based representation of the 3D pharmacophore into the generative process, enabling the precise generation of 3D molecular graphs that align with predefined pharmacophore hypotheses. Through comprehensive testing, PharmaDiff demonstrates superior performance in matching 3D pharmacophore constraints compared to ligand-based drug design methods. Additionally, it achieves higher docking scores across a range of proteins in structure-based drug design, without the need for target protein structures. By integrating pharmacophore modeling with 3D generative techniques, PharmaDiff offers a powerful and flexible framework for rational drug design. Pharmacophore ; Drug design ; Generative model ; Drug ; Representation (politics) ; Drug discovery ; Generative grammar ; Key (lock) Synthesis and Biological Evaluation ; Computational Drug Discovery Methods ; Analytical Chemistry and Chromatography
Authors: Petrus Praditya Aswangga | Muhamad Akrom
Source: Journal of Applied Informatics and Computing (article, 2025-08-07)
Field: Materials Science — Materials Chemistry

Polynomial Integrated PLS Regression for Predicting Corrosion Inhibition Efficiency of Ionic Liquids Corrosion degrades and weakens metal surfaces, leading to structural failure and significant safety hazards across various sectors. Data driven machine learning offers a rapid, cost-effective alternative to the expensive and time consuming traditional experimental methods by predicting inhibitor performance computationally. This study addresses the challenge of accurately predicting corrosion inhibition efficiency (CIE) of ionic liquid compounds. Integration of a polynomial function, especially in higher degrees, inevitably grows the dimensionality and escalates multicollinearity, but it captures deeper nonlinear interactions that the original variables alone would miss. To counterbalance this curse of dimensionality, Partial Least Squares (PLS) Regression was applied after polynomial integration to project the high-dimensional variables into a smaller set of predictors. Besides PLS, Gradient Boosting Regressor (GBR) and Support Vector Regressor (SVR) models were also developed to establish baseline performance. Although these polynomial integrated models outperformed their baseline version, the Polynomial Integrated PLS outperformed their predictive performance, yielding R2, RMSE, and MAPE of 0.73, 4.730, and 3.73%, respectively. The result of this study highlights that the integration of a polynomial function can improve the predictive performance of PLS for corrosion inhibitors. Corrosion ; Polynomial ; Ionic liquid ; Regression ; Regression analysis ; Polynomial regression ; Biological system ; Mathematics ; Materials science ; Chemistry ; Metallurgy ; Statistics ; Organic chemistry ; Mathematical analysis ; Biology Corrosion Behavior and Inhibition ; Ionic liquids properties and applications ; Water Quality Monitoring and Analysis
Authors: Jaquelin Tovar‐Escobedo | José Guadalupe Rutiaga-Quiñones | Carleni Sarai Castellanos‐Henriquez | José Apolinar Cortés
Source: Environmental Progress & Sustainable Energy (article, 2025-11-30)
Field: Materials Science — Biomaterials

Production of high‐purity cellulosic pulps from mango endocarp residue using the green chemical process of peracetic acid Abstract Agro‐industrial wastes are considered a constant management challenge because they are generated in larger quantities than those the landfills are designed for, particularly, the mango pulping industries are facing a series of problems of regulatory compliance, as they generate organic wastes in quantities greater than those regulated in the applicable legislation, the present work has the objective of evaluating the technical feasibility of reincorporating mango endocarp in productive processes to obtain cellulose, using a “green” method that uses peracetic acid as a cooking liquor. The experimentation was carried out at laboratory and pilot scale, the results obtained showed that with the endocarp residues, it is possible to get high‐purity cellulosic fibers with a percentage of lignin lower than 1.35%, quantities higher than 90% of hemicellulose and cellulose, whose thick cell wall structure and poorly developed lumen can be used as a platform for absorbent materials. The yield of the extraction process was higher than 50%. In conclusion, it is possible to take advantage of mango endocarp residue by selective delignification with peracetic acid to obtain high‐quality cellulose. Peracetic acid ; Cellulosic ethanol ; Hemicellulose ; Lignin ; Residue (chemistry) ; Cellulose ; Pulp (tooth) Advanced Cellulose Research Studies ; Lignin and Wood Chemistry ; Natural Fiber Reinforced Composites
Authors: Khasanov Abdurashid Solievich
Source: The American Journal of Applied Sciences (article, 2025-03-01)
Field: Materials Science — Materials Chemistry

Aspects of modification and ccrystallization of0 high-alloy steels This article examines current approaches to modification and crystallization, as well as their practical applications in the field of materials science. An analysis of key modification tasks is provided, including the management of material structures, enhancement of their mechanical and chemical properties, and optimization of thermal and electrical characteristics. An overview of contemporary research dedicated to steel crystallization processes is presented, with an emphasis on the use of rare earth elements, nanoparticles, and computer modeling methods. Experimental techniques for studying crystallization and modification processes, such as X-ray diffraction, scanning electron microscopy, and differential thermal analysis, are discussed. The article also presents the results of studies on the effect of ultrafine powders on the structure and properties of materials, as well as the determination of the optimal powder concentration in a transporting gas medium. In conclusion, the importance of further improving modification methods to create innovative materials with specific characteristics is highlighted. Alloy ; Metallurgy ; Materials science ; Environmental science Material Properties and Failure Mechanisms ; Microstructure and Mechanical Properties of Steels ; Metal Alloys Wear and Properties
Authors: Anton Tamtögl | Marco Sacchi
Source: Nanoscale Horizons (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Nanoscale motion of organic π-conjugated molecules: exploring van der Waals forces, friction, and quantum effects The single-molecule dynamics of π-conjugated organic molecules on surfaces is fundamental for applications ranging from catalysis to molecular electronics. Adsorption and diffusion, in particular of organic aromatics, are typically driven by van der Waals forces, energy dissipation in terms of friction, and quantum effects, making them ideal for probing surface energy landscapes. However, their fast motion at thermal equilibrium poses experimental challenges. Recent advances have provided unprecedented insights into the diffusion mechanisms of several organic molecules on metallic and graphitic surfaces. These studies reveal a spectrum of motion, from ballistic transport to Brownian diffusion, influenced by surface symmetry, molecular size, charge transfer, and molecular degrees of freedom. Notably, friction at 2D material interfaces can be exceptionally low, leading to superlubricity - a phenomenon which highlights the role of atomic-scale interactions in determining energy dissipation and molecular mobility. We review experimental and computational techniques capturing diffusion at atomic length scales, highlighting how density functional theory and molecular dynamics complement experimental findings. Despite recent advances, key questions remain, such as how friction varies across different surfaces and how external factors affect mobility. Understanding these interactions is essential for controlling molecular assembly and surface functionalisation: controlling diffusion and dissipation at the nanoscale may enable self-assembled nanostructures, where controlled molecular motion drives highly ordered surface architectures. Finally, beyond technological applications, surface diffusion is also critical in astrochemistry, where it influences the formation of complex organic molecules. van der Waals force ; Dissipation ; Surface diffusion ; Molecular dynamics ; Diffusion ; Quantum ; Brownian motion ; Thermal fluctuations ; Nanoscopic scale Boron and Carbon Nanomaterials Research ; Force Microscopy Techniques and Applications ; Mechanical and Optical Resonators