jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Samuel Peña‐Díaz | Yanting Jiang | Zhefei Zhang | Anders Ogechi Hostrup Daugberg | Pedro Ferreira | Marcos López Hernández | Chandrika Mittal | Maria J. Ramos | Jan Skov Pedersen | Morten Simonsen Dueholm | Qin Cao | Huabing Wang | Daniel E. Otzen
Source: Advanced Science (article, 2025-12-05)
Field: Materials Science — Biomaterials

The Importance of Being Imperfect: Structure and Function of Bacterial Amyloid Amyloids, once viewed solely as pathological hallmarks, are now recognized as widespread and versatile functional protein assemblies. Bacterial functional amyloids (FuBAs), particularly curli (CsgA) from Escherichia coli and FapC from Pseudomonas, have emerged as paradigms for understanding amyloid structure, assembly, and function. The recent cryo-EM-based structure of FapC, together with others' combined cryo-EM and integrative computational studies on CsgA, reveal a β-solenoid fold stabilized by imperfect repeats, producing fibrils of exceptional stability and low polymorphism, whose biogenesis is tightly controlled through dedicated accessory factors, ensuring precise secretion and nucleation. FuBAs not only scaffold biofilms but also display intrinsic catalytic activity, expanding the biochemical repertoire of extracellular matrices. They also exhibit hierarchical mechanical properties ranging from GPa stiffness at the fibril core to kPa elasticity in hydrated biofilms. FuBA operons are phylogenetically widespread, with repeat variation contributing to sequence diversity and functional adaptability. FuBAs might be seen as evolutionary intermediates between disordered peptides with significant self-interaction tendencies and highly structured globular proteins. Their simple structures make them robust platforms for biomaterial engineering. Understanding the interplay between sequence repeats, fibril architecture, and emergent functions opens avenues for harnessing amyloids as programmable nanomaterials with applications in catalysis, synthetic biology, and biofilm control. Biogenesis ; Fibril ; Amyloid (mycology) ; Biofilm ; Escherichia coli ; Amyloid fibril ; Protein folding ; Function (biology) ; Biomaterial Supramolecular Self-Assembly in Materials ; Alzheimer's disease research and treatments ; Bacteriophages and microbial interactions
Authors: Chirayu Nilesh Chaudhari | N. J. Rtamanyu | Naga Sai Shreya Kunda | K C Pranave | Mayank Pandey | S Sruthi | Manju Khanna
Source: Scientific Reports (article, 2025-12-13)
Field: Materials Science — Materials Chemistry

Optimizing thermoelectric energy harvesting using deep reinforcement learning for dynamic energy management and system efficiency By addressing the drawbacks of static optimization techniques, this research seeks to improve the dynamic energy management of thermoelectric generators (TEGs). Finding the best deep reinforcement learning (DRL) algorithm to maximize energy distribution, prolong battery life, and boost system efficiency in the face of the variable conditions present in waste heat recovery systems is the goal. The TEG system was modeled using the Markov decision process and implemented in a computer-simulated environment. Three advanced DRL algorithms were used: soft actor-critic (SAC), proximal policy optimization (PPO), and deep Q-networks (DQN); which were trained to act as intelligent controllers. The performance of each algorithm was systematically evaluated and compared using key metrics, including average cumulative reward, battery health, system efficiency, and a novel metric termed the energy fulfillment rate, which measures the ability to meet demand while storing surplus energy. The comparative analysis revealed a critical trade-off between maximizing performance and ensuring hardware longevity. The SAC algorithm demonstrated the best overall performance, achieving the highest average reward (- 7.03) and energy fulfillment rate (22.84%). However, the A2C, DDPG, and PPO algorithms all achieved a perfect average battery health of 100.00%, highlighting their superior capability for preserving system longevity, albeit with slightly lower rewards. The DQN algorithm consistently showed the least effective performance across all metrics, particularly in maintaining battery health (60.73%). The SAC algorithm is the most suitable of the methods tested for dynamically managing TEG systems. Its underlying principle of maximization of entropy enables a better exploration of control strategies, leading to a better balance between immediate energy dispatch and long-term storage goals. The findings confirm the significant potential of DRL to create efficient and adaptive controllers for renewable energy applications, although further validation of physical hardware is required to confirm real-world viability. Reinforcement learning ; Markov decision process ; Maximization ; Battery (electricity) ; Efficient energy use ; Energy management ; Performance metric ; Process (computing) Advanced Thermoelectric Materials and Devices ; Energy Harvesting in Wireless Networks ; Innovative Energy Harvesting Technologies
Authors: Sajad W. Noori | Nada M. Abed | Duaa Alaa Lafta | Mustafa M. Mansour | Alaa M. Lafta | Ahmed A. Ouda | Ahmed Jassim Shkarah
Source: Revue des composites et des matériaux avancés (article, 2025-12-31)
Field: Materials Science — Ceramics and Composites

Microstructural Design and Thermodynamic Optimization of UHT Ceramic Composites for Extreme Thermal Environments This study investigates the microstructural design and thermodynamic optimization of ultra-high temperature (UHT) ceramic composites intended for extreme thermal environments.Through the integration of carbon fiber reinforcement, significant enhancements in fracture toughness (23%) were achieved, as well as improved thermal stability under high-temperature conditions.The optimization process focused on achieving a balanced thermal conductivity and low thermal expansion coefficient, critical for maintaining structural integrity in extreme environments.Furthermore, the study focuses on CMCs, such as their applicability in a wide range of high temperature applications, some of the common problems like thermal shock, load carrying member, and aspect to manufacturing defects are presented within this draft.Results of the fired samples based on a new mixture design concept, were superior to those of the conventional UHT ceramics in thermal shock resistance.This study.Hence, contributes to the frontier of knowledge by introducing an unconventional design route that improves mechanical properties and raises insight into the thermodynamic act for UHT ceramic composite.In contrast to previous reviews, the current study provides experimental evidence and quantifiable performance improvements for both aerospace future generation systems as well as energy technologies.It also aims to relate the intrinsic temperature at which transformation tolerant mechanism's mechanical property alone becomes superior in the zirconia and its toughness.These objectives provide for a pathway to an extensive exploration of the potential microstructure control and thermodynamic stability of high-temperature co-processible ceramic compositions to produce ultra-bases high functional structural ceramics. Ceramic ; Thermal ; Microstructure ; Thermal conductivity ; Composite number Advanced ceramic materials synthesis ; Advanced materials and composites ; Aluminum Alloys Composites Properties
Authors: Lucia Scardia | Ulisse Stefanelli | Florian Theil
Source: Oberwolfach Reports (article, 2025-11-10)
Field: Materials Science — Materials Chemistry

Singularities in Discrete Systems Discrete systems are ubiquitous in applications. Their analysis and simulation call for taming their inherent multiscale character, as microscopic dynamics lead to the emergence of structures across scales. This workshop brought together leading experts in the calculus of variations, discrete systems, and materials science to explore cutting-edge topics at the intersection of mathematics and physical modelling. Presentations spanned a variety of themes, including dislocation dynamics, crystallization, micromagnetics, fracture mechanics, and discrete-to-continuum transitions. Particular emphasis was placed on the rigorous analysis of singular structures, nonlocal interactions, and energy-driven pattern formation. Several talks also underscored emerging connections with data science. Intersection (aeronautics) ; Gravitational singularity ; Variety (cybernetics) ; Dislocation ; Calculus (dental) ; Motion (physics) ; Complex system Microstructure and mechanical properties ; Shape Memory Alloy Transformations ; Theoretical and Computational Physics
Authors: J.A. Dhrisha - | Kumari Chanchala Priya
Source: International Journal on Science and Technology (article, 2025-01-09)
Field: Chemistry — Organic Chemistry

Review on Novel Approach to Food Shelf Life Extension: Fruit Peel Polyphenols as Eco-Friendly Photosensitizers Polyphenols, a group of phytochemicals, have a vast spectrum of biological activities, including activities against microbes and photosensitizing properties. Their antimicrobial activity is attributed to mechanisms, including the disruption of the membrane, enzyme binding and disruption of microbial signaling pathways. Photosensitizers of polyphenols plays significant role in photodynamic therapy in generating reactive species after light activation, showing a marked ability to target microorganism and cancer cells. Because of the bio functional character of polyphenols, they are, in principle, effective players as medicines, food and environmental purposes. This review highlights the chemical diversity of polyphenols, their interactions with microbial systems, and their photodynamic properties, providing insights into their potential applications in combating antibiotic resistance and improving photodynamic therapies. The presentation also addresses the problems and directions of the future applications of polyphenols in these new functions. Shelf life ; Environmentally friendly ; Polyphenol ; Extension (predicate logic) ; Food science ; Chemistry ; Computer science ; Biology ; Biochemistry ; Ecology ; Antioxidant Edible Oils Quality and Analysis ; Phytochemicals and Antioxidant Activities
Authors: Tibor Maliar | Marcela Blažková | Renata Gašparová | Mária Maliarová | Petronela Rezbáriková | Jana Viskupičová
Source: International Journal of Food Science & Technology (article, 2025-07-01)
Field: Chemistry — Organic Chemistry

Computational prediction of 2,2-diphenyl-1-picrylhydrazyl radical scavenging and ferric ion reducing potency of selected compounds Abstract Antioxidant activity is typically assessed by radical scavenging and ferric ion reduction, yet experimental evaluation of large compound sets is resource-intensive. In this study, 16 compounds with known antioxidant properties evaluated in 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical and ferric reducing antioxidant power (FRAP) assays were quantified using DPPH50, FRAP50, and the pro-oxidant/antioxidant balance index (PABI). Substantial differences in activity profiles were observed across compounds. To interpret these findings, an in silico analysis was performed using structural and physicochemical descriptors, including aromatic hydroxyl count and position, heteroatom number, partial charges, unsaturation, and molecular complexity. Correlation matrices, principal component analysis, and regression models identified hydroxylation patterns as the primary determinants of radical scavenging, whereas ferric ion reduction was more influenced by heteroatom content and electronic factors. The models achieved very high predictive accuracy (r2 = 0.986 for DPPH50; r2 = 0.974 for FRAP50). This framework supports computational pre-screening to accelerate the identification of food-related bioactive antioxidants. Ferric ; Scavenging ; Heteroatom ; Antioxidant ; Hydroxyl radical ; Ferric ion ; Hydroxylation ; Potency Free Radicals and Antioxidants ; Phytochemicals and Antioxidant Activities ; Computational Drug Discovery Methods
Authors: Amine Ould Rabah | Abdelmadjid Benmohammed | Abdelkader Chouaıh | Meriem Goudjil | Rachida Rahmani | Nour El Houda Belkafouf | Mohammed Hadj Mortada Belhachemi | Fatima Zohra Boudjenane | Ayada Djafri | Nourdine Boukabcha
Source: Acta chimica slovenica (article, 2025-06-11)
Field: Chemistry — Organic Chemistry

Synthesis, Characterization, DFT Investigation and In Silico Anti-eczema Evaluation of a Novel Thiazolidinone Derivative A new thiazolidinone derivative, (Z)-ethyl 2-((E)-2-((E)-(4-(methylthio) benzylidene) hydrazono)-4-oxo-3-phenylthiazolidin-5-ylidene) acetate (EMBTh), was synthesized via condensation method. This study employs a multidisciplinary approach, including compound characterization, molecular properties evaluation, and biological activity analysis. Single-crystal X-ray diffraction (SC-XRD) revealed that the compound crystallizes in the monoclinic crystal system with the P21/c space group. A theoretical model of EMBTh has been developed and substantiated by comparing SC-XRD results with theoretical calculations using density functional theory (DFT), employing the B3LYP function at a 6-311++G(d,p) level of theory. The study also explores the electronic behavior of the molecule and its molecular interactions, especially highlighting van der Waals forces via analysis of the molecular frontier orbitals and Hirshfeld surface. The results underscore the stability of the molecule and the significant contribution of hydrogen bonds to the crystal packing. Moreover, we conducted a molecular docking study to evaluate the anti-eczema activity of the EMBTh compound. The results revealed a good affinity in inhibiting the receptor (IL-4Rα), pinpointing the therapeutic potential of EMBT against the target protein of atopic eczema. Chemistry ; Hydrogen bond ; Intramolecular force ; Density functional theory ; van der Waals force ; Molecular orbital ; Computational chemistry ; Steric effects ; Polarizable continuum model ; Molecule ; Intermolecular force ; Non-covalent interactions ; Electrophile ; Crystallography ; Stereochemistry ; Organic chemistry Synthesis and biological activity ; Synthesis and Characterization of Heterocyclic Compounds ; Structural and Chemical Analysis of Organic and Inorganic Compounds
Authors: Devajyoti Patowary | Diksha Jain
Source: International Journal of Environmental Sciences (article, 2025-08-20)
Field: Materials Science — Materials Chemistry

Fault Detection And Partial Discharge In Gas Insulated Substations: Leveraging Traveling Wave Technology For High Voltage Grid Stability, Safety And Resilience Modern electrical power systems depend on Gas Insulated Substations (GIS) because they provide miniaturized designs along with excellent reliability and simplified maintenance needs. Maintaining operational integrity in GIS needs advanced monitoring systems which can identify developing breakdowns plus the initial signs of partial discharge events that can cause total system breakdown. This paper investigates the application of traveling wave technology for fault detection and partial discharge monitoring in GIS installations. This paper investigates SF6 partial discharge generation inside insulation systems as well as the electromagnetic wave characteristics within GIS enclosures and methods for using UHF sensors for detection purposes. The analysis investigates existing CIGRE Task Force standard-based protocols for PD sensitivity testing while introducing new methods to improve error localizations in PD measurements. The article explores implementation barriers of traveling wave technology for GIS systems and introduces optimal practices to build complete monitoring solutions which strengthen grid stability alongside enhancing safety features and resilience capabilities. The study confirms that predictive monitoring plays an essential part in lengthening GIS service duration and stopping unexpected outages which results in better grid reliability performance. Partial discharge ; Reliability (semiconductor) ; Resilience (materials science) ; Ultra high frequency ; Grid ; Fault detection and isolation ; Sensitivity (control systems) ; Fault (geology) ; IT service continuity High voltage insulation and dielectric phenomena ; Electrical Fault Detection and Protection ; Elevator Systems and Control
Authors: Jules Marien | Julie Puyo-Fourtine | Chantal Prévost | Sophie Sacquin‐Mora | Élise Duboué-Dijon
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2025-09-02)
Field: Chemistry — Spectroscopy

Sticky salts: overbinding of monovalent cations to phosphorylations in all-atom forcefields Abstract Phosphorylation is a major post-translational modification, which is involved in the regulation of the dynamics and function of Intrinsically Disordered Proteins (IDPs). We recently characterized a phenomenon, which we termed n -Phosphate collaborations ( n P-collabs), where bulk cations form stable bridges between several phosphoresidues in all-atom molecular dynamic simulations. n P-collabs were found to be sensitive to the combination of forcefields and cation types. Here, we attempt to assess the physical relevance of these n P-collabs by evaluating the strength of the cation/phosphate interaction through osmotic coefficient ( ϕ ) calculations on the model and salts, using different classical forcefields for phosphorylations. All force-fields were found to overestimate the strength of the interaction to various degrees. We thus designed new parameters for CHARMM36m and AmberFF99SB-ILDN using the Electronic Continuum Correction (ECC) approach, which provide remarkable agreement for ϕ values for both cation types and over a range of concentrations. We provide a preliminary test of these ECC parameters for phosphorylations by simulating the sevenfold-phosphorylated rhodopsin peptide 7PP and comparing secondary chemical shifts to experimental data. Conformational ensembles resulting from the ECC-derived phosphorylated forcefields display both qualitative and quantitative improvements with regard to full-charge forcefields. We thus conclude that long-lasting n P-collabs are artifacts for classical forcefields born from the lack of explicit polarization, and propose a possible computational strategy for the extensive parameterization of phosphorylations. The presence of long-lived n P-collabs in simulations produced using classical forcefields is therefore a serious concern for the accurate modelling of multiphosphorylated peptides and IDPs, which are at the center of research questions regarding neurodegenerative diseases such as Alzheimer’s or Parkinson’s. Atom (system on chip) ; Chemistry ; Inorganic chemistry ; Computer science ; Parallel computing Molecular spectroscopy and chirality ; Crystallography and molecular interactions ; Mass Spectrometry Techniques and Applications
Authors: Akoramurthy Balasubramaniam | B. Surendiran
Source: Research Square (preprint, 2025-09-30)
Field: Materials Science — Materials Chemistry

QuMo: Benchmarking a Quantum Moiré-Based Classifier for Brain Tumor Diagnosis Quantum ; Benchmarking ; Robustness (evolution) ; Classifier (UML) ; Quantum machine learning ; Feature extraction ; Pattern recognition (psychology) ; Parameterized complexity ; Interpretability Machine Learning in Materials Science ; Brain Tumor Detection and Classification ; Machine Learning in Bioinformatics
Authors: Tianchang Ma | Yuyang Bai | Haomeng Shi | Yanlong Wei | Chunwei Zhang
Source: Metals (article, 2025-09-09)
Field: Materials Science — Materials Chemistry

Influence of Inhomogeneous Plastic Strain and Crystallographic Orientations on Fatigue-Induced Dislocation Structures in FCC Metals Owing to the differences in crystallographic orientations among individual grains, dislocation structures in polycrystals are inherently inhomogeneous from grain to grain. Since intergranular incompatibility is inevitable during plastic deformation, it may consequently lead to unpredictable plastic strain localization, which in turn facilitates the initiation of fatigue crack. Therefore, to elucidate the mechanisms underlying inhomogeneous deformation in polycrystals, this study systematically examines the fatigue-induced dislocation structures in polycrystalline SUS316L stainless steel. We then directly compare them with those in copper single crystals to clarify the dependence of the dislocation structures on crystallographic orientation. SEM characterization demonstrates that high plastic strain near grain boundaries promotes the formation of secondary cell bands (CBs) overlapping the primary CBs, which is attributable to the simultaneous activation of multiple-slip systems under high plastic strain amplitudes. In addition to strain localization, competition among candidate secondary slip systems strongly governs the dislocation structures. Notably, a new type of deformation band (DB) on the (010) plane is identified in a non-coplanar double-slip-oriented grain, a feature not observed in single crystals, indicating that polycrystals accommodate plastic strain through distinct mechanisms. Detailed dislocation structure analysis provides theoretical guidance for mitigating fatigue crack initiation through the manipulation of dislocations. Dislocation ; Crystallite ; Lüders band ; Plasticity ; Slip (aerodynamics) ; Deformation (meteorology) ; Grain boundary ; Dislocation creep ; Strain (injury) ; Deformation bands Microstructure and mechanical properties ; Hydrogen embrittlement and corrosion behaviors in metals ; Fatigue and fracture mechanics
Authors: Ziqing Guo | Binh Huy Nguyen | Hamed Hamzehbahmani | Ruth V. Sabariego
Source: IEEE Transactions on Magnetics (article, 2025-08-18)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Dynamic Hysteresis Model of Grain-Oriented Ferromagnetic Material Using Neural Operators Accurately capturing the behavior of grain-oriented (GO) ferromagnetic materials is crucial for modeling the electromagnetic devices. In this paper, neural operator models, including Fourier neural operator (FNO), U-net combined FNO (U-FNO) and Deep operator network (DeepONet) are used to approximate the dynamic hysteresis models of GO steel. Furthermore, two types of data augmentation strategies including cyclic rolling augmentation and Gaussian data augmentation (GDA) are implemented to enhance the learning ability of models. With the inclusion of these augmentation techniques, the optimized models account for not only the peak values of the magnetic flux density but also the effects of different frequencies and phase shifts. The accuracy of all models is assessed using the L2-norm of the test data and the mean relative error (MRE) of calculated core losses. Each model performs well in different scenarios, but FNO consistently achieves the best performance across all cases. Hysteresis ; Ferromagnetism ; Magnetic hysteresis ; Condensed matter physics ; Materials science ; Grain size ; Magnetic domain ; Computer science ; Magnetization ; Magnetic field ; Physics ; Composite material Magnetic Properties and Applications ; Non-Destructive Testing Techniques