jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Faijan | Jean‐Marc Delaye | Ryuki Kayano | Takahiro Ohkubo | Stéphane Gin
Source: npj Materials Degradation (article, 2026-04-10)
Field: Materials Science — Ceramics and Composites

A multi parameter approach for predicting initial dissolution rate of silicate glasses The prediction of a glass’ initial dissolution rate (r0) is crucial for various applications in industry, nuclear waste management, and healthcare. The primary limitations of existing approaches are the lack of dissolution behavior classification and the choice of appropriate and robust criteria to relate the glass composition to its dissolution rate. This work introduces congruence-focused, multi-variable, and MD-agnostic methodology to estimate the dissolution rate of silicate glasses. The employed criteria reliably discriminate between congruent and incongruent dissolution behaviors and the corresponding descriptors demonstrate reasonable (R² > 0.9) and proportional correlation with ln r0 for all studied glasses. Therefore, holistic structural models that consolidate the fundamental chemistry and topology of the glass network offer a systematic means to capture complex property relationships and evaluating durability through r0. Dissolution ; Silicate glass ; Silicate ; Durability ; Work (physics) ; Network topology Glass properties and applications ; CO2 Sequestration and Geologic Interactions ; Recycling and utilization of industrial and municipal waste in materials production
Authors: Raoudha Ben Ameur | Sarra Akermi | Theodoros Varzakas | Slim Smaoui | L Mellouli | Hichem Ben Salah | Noureddine Allouche
Source: Chemistry & Biodiversity (article, 2026-01-01)
Field: Chemistry — Organic Chemistry

Decoding the Bioactivity of <i>Prunus armeniaca</i> L. Essential Oil: Cheminformatics‐Supported Exploration of Its Antioxidant and Antibacterial Potential This study explores the antioxidant and antibacterial activities of Prunus armeniaca L. essential oil (PAEO) through the use of in vitro and in silico approaches. It also evaluates its predicted chemo-computational toxicity and pharmacological profiles. The analysis using the gas chromatography-mass spectrometry method revealed the abundance of benzaldehyde. Moreover, PAEO exhibited a potent antioxidant activity demonstrated by its efficient scavenging effect on the 2,2-diphenyl-1 picrylhydrazyl radical (DPPH) (IC<sub>50</sub> = 43.5 µg/mL), a significant ferric ion reducing power activity (EC<sub>50</sub> = 51.22 µg/mL), and a total antioxidant capacity concentration (160.67 mg GAE/g EO). Microbiological assays, evaluated by minimal inhibitory concentrations (MICs), showed that PAEO exerts a powerful antibacterial activity against Staphylococcus aureus ATCC 6538, Listeria monocytogenes ATCC 19117, Salmonella enterica Typhimurium ATCC 10028, and Escherichia coli ATCC 8739. Molecular modeling simulations stipulated PAEO unveiled a multitarget mechanism of action by inhibiting vital bacterial pathways involved in cell division (FtsZ) and peptidoglycan synthesis of bacterial cell wall (MurE), as well as an antioxidant potential by hindering the function of xanthine oxidase and NADPH oxidase enzymes, with free energies of binding values (ΔG) ranging from -6.1 to -7.1 kcal/mol. Furthermore, chemo-computational toxicity assessments and pharmacological evaluations of PAEO components have confirmed their safety and efficacy. Antioxidant ; Escherichia coli ; Listeria monocytogenes ; Staphylococcus aureus ; Salmonella enterica ; Antibacterial activity ; Xanthine oxidase ; Minimum inhibitory concentration Edible Oils Quality and Analysis ; Phytochemicals and Antioxidant Activities ; Neurological Disease Mechanisms and Treatments
Authors: A. S. Ushakova | V. V. Vasilevskaya
Source: Journal of Polymer Science (article, 2026-02-12)
Field: Materials Science — Surfaces, Coatings and Films

Split Spike Structures of an Amphiphilic Polymer Layer Grafted Onto a Spherical Nanoparticle ABSTRACT The article aims to describe specific split spike structures that can be found in grafted layers of comb‐like macromolecules. The split spike was defined here as a filamentous thread‐like «solvophobic core‐solvophilic shell» aggregate that, at some distance from the grafting surface, disintegrates into thinner filaments due to a decrease in the local density of the grafted layers. An analytical theory is proposed that describes the diversity of stable split structures from amphiphilic A‐graft‐B macromolecules grafted onto a spherical nanoparticle, the conditions of their formation, and the pathway of their transformation. The proposed theory allowed us to analyze the impact of solvent quality and selectivity, as well as chain grafting density and polymerization degree, to the formation of such structures. The theory interprets the literature experimental data and describes the results of computer simulations. It provides a basis for the designing of nanoparticles with a complex branched surface. Grafting ; Amphiphile ; Polymer ; Nanoparticle ; Spike (software development) ; Polymerization ; Macromolecule Polymer Surface Interaction Studies ; Advanced Polymer Synthesis and Characterization ; Electrostatics and Colloid Interactions
Authors: Changyue Yao | Weiguo Hu | Huali Liu | Zhihong Ran | Jingrui Hou | Q. Song
Source: Technology in Cancer Research & Treatment (article, 2026-04-01)
Field: Materials Science — Materials Chemistry

Innovative Value of Amide Proton Transfer Imaging in the Diagnosis and Treatment of Brain Gliomas: From Basic Principles to Clinical Applications Conventional magnetic resonance imaging (MRI) exhibits notable limitations in the diagnosis, grading, and therapeutic assessment of gliomas, making it insufficient to meet the demands of precision medicine. As a chemical exchange saturation transfer MRI technique, amide proton transfer (APT) imaging enables molecular-level visualization by detecting the chemical exchange of amide protons in endogenous mobile proteins and peptides. Previous studies have demonstrated that APT imaging provides substantial advantages over conventional MRI in the diagnosis, grading, and treatment monitoring of gliomas. This review systematically summarizes the development of APT imaging technology, emphasizing its innovative clinical applications, including preoperative grading, differentiation of postoperative recurrence, and dynamic evaluation of radiotherapy and chemotherapy efficacy. Furthermore, it discusses current challenges and future directions for clinical implementation, aiming to offer new perspectives for advancing precision medicine in glioma management. Magnetic resonance imaging ; Amide ; Value (mathematics) ; Proton therapy ; Magnetization transfer ; Radiation therapy ; Proton Lanthanide and Transition Metal Complexes ; Electron Spin Resonance Studies ; Sulfur Compounds in Biology
Authors: Alex Turyahabwe | Milon Selvam Dennison | Onep Samuel George
Source: Scientific Reports (article, 2026-03-23)
Field: Materials Science — Polymers and Plastics

Investigation of multi-performance optimization of banana/bark cloth reinforced epoxy composites using grey relational analysis for automotive interior applications This study presents a novel multi-performance optimization of underexplored hybrid banana- and bark-cloth fiber-reinforced epoxy composites for automotive interior applications, using Grey Relational Analysis (GRA). Unlike previous studies that mainly examine banana fiber alone or other conventional natural fiber hybrids, the present work investigates the synergistic combination of banana fiber and bark cloth in an epoxy matrix with 5 wt% aluminium trihydrate (ATH) to simultaneously improve mechanical performance, flame resistance, and moisture-related durability. The composites were produced through compression moulding with varying fiber ratios, and their tensile, flexural, impact, flammability, and water absorption behaviours were systematically evaluated. Among the tested configurations, Sample C7 (40% banana, 5% bark cloth) exhibited the best overall performance, with tensile strength of 28.29 MPa, flexural strength of 37.86 MPa, specific impact energy of 106.92 J/g, and a burning rate of 1.053 mm/s. GRA was used to rank the composite formulations based on multiple response criteria, identifying C7 as the optimal configuration. SEM, EDAX, and FTIR analyses further confirmed improved fibre-matrix interaction, additive retention, and chemical compatibility. The findings demonstrate the potential of banana/bark cloth hybrid composites as sustainable multifunctional materials for automotive interiors. Grey relational analysis ; Epoxy ; Ultimate tensile strength ; Flexural strength ; Composite number ; Fiber ; Natural fiber ; Automotive industry Natural Fiber Reinforced Composites ; Mechanical Behavior of Composites ; Scientific and Engineering Research Topics
Authors: Julián Coronel-Reyes | Alexander Fernando Haro Sarango | Carlota Delgado-Vera | Johnny Javier Triviño-Sanchez
Source: AgriEngineering (article, 2026-03-06)
Field: Chemistry — Analytical Chemistry

Comparative Evaluation of Machine Learning Algorithms for the Identification and Morphological Classification of Rice Grains Machine learning has enhanced rice grain classification by enabling accurate, automated, and objective morphological analysis, supporting quality control and varietal selection. This study compared the performance of several algorithms in identifying three Ecuadorian rice varieties (INIAP-11, INIAP-12, and INIAP-20) using a balanced dataset of morphological features. Five models were trained with cross-validation and evaluated using multi-class metrics. Significant differences among varieties particularly in area, length, and eccentricity confirmed their discriminative potential. Initially, models were trained using all morphological variables. However, to optimize training time and computational cost, the study also evaluated model performance after applying dimensionality reduction through Principal Component Analysis (PCA). This approach enabled assessing whether reduced feature spaces could maintain competitive predictive performance while improving efficiency. Overall, all algorithms performed well, but only the Artificial Neural Network (ANN) and Support Vector Classifier (SVC) demonstrated strong generalization without overfitting. In contrast, Random Forest achieved perfect accuracy in training but decreased performance in testing. In conclusion, ANN and SVC emerged as the most robust alternatives for rice grain morphological classification, while the PCA results highlight the value of dimensionality reduction as a strategy to enhance computational scalability without substantially compromising accuracy. The objective of the present study is to train, evaluate, and compare different machine learning algorithms for the classification of three types of rice grains, in order to determine the best model for this task based on seven morphological characteristics of the grains applying machine learning algorithms with and without dimensional reduction. Dimensionality reduction ; Principal component analysis ; Random forest ; Discriminative model ; Artificial neural network ; Support vector machine ; Classifier (UML) ; Pattern recognition (psychology) Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Food composition and properties
Authors: Xianguo Tuo | Lu Li | Guiyu Zhang | Kerong Chen | Xianglin Zeng
Source: Research Square (preprint, 2026-04-02)
Field: Chemistry — Analytical Chemistry

Discrimination of Chinese Baijiu Base Liquor Grades Using Near- Infrared Spectroscopy Based on SHAP and Multi-scale Pyramid Feature Fusion Pattern recognition (psychology) ; Feature selection ; Cluster analysis ; Feature (linguistics) ; Pyramid (geometry) ; Fusion ; Silhouette ; Redundancy (engineering) Spectroscopy and Chemometric Analyses ; Fermentation and Sensory Analysis ; Remote-Sensing Image Classification
Authors: Marcin H. Kudzin | M. Sikora | Zdzisława Mrozińska | Jerzy J. Chruściel
Source: Materials (article, 2026-01-29)
Field: Materials Science — Surfaces, Coatings and Films

Polymeric Fibrous Materials for Procoagulant and Anticoagulant Applications: A Review of Molecular Blood–Material Mechanisms and Strategies Fiber-forming polymers are increasingly used to control blood coagulation, either by accelerating the onset of hemostasis or by limiting thrombogenic events in contact with blood. Despite rapid progress in materials engineering, a unified view linking the molecular mechanisms of the coagulation cascade with specific design strategies of procoagulant and anticoagulant polymeric fibers is still missing. In this review, we summarize current knowledge on how natural and synthetic polymers interact with plasma proteins, platelets, and coagulation factors, emphasizing the role of fiber morphology, surface chemistry, charge distribution, and functionalization. Particular attention was paid to systems based on natural polysaccharides (e.g., chitosan, alginate, and cellulose derivatives), as well as synthetic polymers (e.g., PLA, PCL, polyurethanes, and zwitterionic materials). Two possible courses of action were described: their bioactivity may activate the contact pathway and/or support platelet adhesion or their ability to minimize protein adsorption and inhibit thrombin generation. We discuss how metal-polymer coordination, surface immobilization of heparin or nitric oxide donors, and nanoscale texturing modulate coagulation kinetics in opposite directions. Finally, we highlight emerging fiber-based strategies for achieving either rapid hemostasis or long-term hemocompatibility and propose design principles enabling precise tuning of coagulation responses for wound dressings, vascular grafts, and blood-contacting devices. This general compendium of knowledge on blood-material interactions provides a foundation for further design of biomaterials based on fiber-forming polymers and the development of manufacturing processes. Coagulation ; Hemostasis ; Polymer ; Heparin ; Natural polymers ; Adhesion ; Antithrombin ; Protein adsorption Polymer Surface Interaction Studies ; Hemostasis and retained surgical items ; Trauma, Hemostasis, Coagulopathy, Resuscitation
Authors: Chenglong Wen | Ying Jiang | Tianruo Shen | Xuefeng Jiang | Shiqi Fan | Taorui Yang | Xiaogang Liu | Qiong Luo | Xin Li
Source: Nature Communications (article, 2026-01-27)
Field: Chemistry — Organic Chemistry

Sensight enables quantitative multivariate engineering of high-performance chemical imaging tools Chemical imaging probes enable the visualization of dynamic biology; however, engineering high sensitivity in live cells remains challenging. Here we present Sensight, a quantitative multivariate framework that integrates key photophysical and physicochemical descriptors to predict and optimize probe performance. Using a structurally diverse library, we identify five dominant parameters, define their optimal ranges, and unify them into a radar map representation with strong predictive power and intuitive visualization. This framework extends the structure-activity relationship analysis into imaging sensitivity, capturing complex structure-function relationships that shape probe behavior in live cells. Guided by Sensight, we design G<sub>3</sub>, a superoxide probe with exceptional sensitivity for detecting early oxidative events. The framework's generality is further demonstrated across distinct systems, including tetrazine-bicyclononyne bioorthogonal chemistry and formaldehyde sensing. Together, these findings establish Sensight as a predictive and generalizable strategy for high-performance probe design, with broad implications for sensing, imaging, and even theranostics. Bioorthogonal chemistry ; Generality ; Sensitivity (control systems) ; Visualization ; Multivariate statistics ; Representation (politics) ; Pattern recognition (psychology) ; Predictive power Click Chemistry and Applications ; Molecular Sensors and Ion Detection ; Photochromic and Fluorescence Chemistry
Authors: José Manuel Ezquerra-Aznárez | Raquel Alonso-Román | Ainhoa Lucía | Raquel Andreu | S. LLORENTE FRANCO | J. L. Bada Ainsa | Santiago Ramón-García
Source: Antibiotics (article, 2026-03-20)
Field: Chemistry — Organic Chemistry

New Chemical Scaffold with Antimicrobial Activity Identified in a Screening of Industrial Photoactive Compounds <b>Background/Objectives</b>: The emergence of antimicrobial resistance threatens advances achieved by medicine in the last century. This situation has been exacerbated by the suboptimal outcome of screening campaigns to provide novel antimicrobials. <b>Methods</b>: An alternative strategy was employed to identify new chemical scaffolds with antimicrobial activity. A collection of photoactive compounds originally synthesized for industrial purposes was screened for antibacterial activity. <b>Results</b>: 4<i>H</i>-pyran-4-ylidenes were identified as active against Gram-positive bacteria. Compounds belonging to this family displayed dose-dependent bactericidal activity against both wild-type and methicillin-resistant <i>Staphylococcus aureus</i>. No cytotoxicity was observed in the HepG2 hepatic cell line at the concentrations required for antimicrobial activity against <i>S. aureus</i>. Resistance to 4<i>H</i>-pyran-4-ylidenes in <i>S. aureus</i> was associated with point mutations in the <i>rny</i> locus, which encodes for a ribonuclease that plays a key role in RNA homeostasis. <b>Conclusions</b>: These findings indicate that chemical libraries not originally intended for drug discovery can be an innovative source of chemical diversity for the development of novel antimicrobials. Antimicrobial ; Staphylococcus aureus ; Antibiotic resistance ; Antibacterial activity ; Bacteria ; Drug discovery ; Drug resistance ; Cytotoxicity Synthesis of heterocyclic compounds ; Click Chemistry and Applications ; Synthesis and Reactivity of Heterocycles
Authors: Lakshmi Vegesna | Ginni Nijhawan | Upendra Dabral | Hussein A. Abbas | Anju Katyal | Bhanu Juneja | O. Jeba Shiney | Brijesh Prasad
Source: AIP conference proceedings (article, 2026-01-01)
Field: Materials Science — Materials Chemistry

Thermal nano wonders: Differential scanning calorimetry’s deep dive into nanomaterials Conducted through Differential Scanning Calorimetry (DSC), this contribution endeavors to explore the intricate thermal characteristics of nanoscale composites to identify their thermal profile.The specific thermal properties and the compositional percent of the materials like nanotubes, nanoparticles, nanowires, and nanofibers were analyzed profusely.C tip nanotubes were found to be the component in the highest proportion with an overall percentage of 65 %, while nanofibers had a proportion of 55 % nanoparticles had an overall proportion of 30 %, and nanowires 45 % according to the research conducted.Hence, in terms of thermal conductivity, the compared material ranked in the order: nanotubes: 300 W/mK nanowires: 250 W/mK nanoparticles: 200 W/mK and nanofibers: 180 W/mK.Based on the information derived from the melting point investigation, the four common nanomaterials are nanotubes, nanowires, nanoparticles and nanofibers with melting points of 1500C, 1300C, 1200C, and 1100C respectively.Consequently, heat capacities were estimated to be 800 J/kgK for the nanotubes, while the nanowires had a heat capacity of 700 J/kg K, the nanoparticles had a heat capacity of 600 J/kg K and the nanofibers had a heat capacity of 500 J/kg K.The results presented and discussed here underscore the compositional, thermal, melting point, and heat capacity dominance of nanotubes that has familiarized researchers with the significant thermal divergences of nanomaterials.This study reveals the utility of Differential Scanning Calorimetry in determining the numerous thermal characteristics of nanomaterials and thereby contributes to the advancement of enhanced thermal energy storage, new efficient thermal control systems, and high-temperature applications. Nanomaterials ; Nano- ; Thermal ; Nanoparticle ; Thermal stability Thermal properties of materials ; nanoparticles nucleation surface interactions ; Carbon Nanotubes in Composites
Authors: Kai Zheng | Ning Xie | Li-Feng Zhu | Jiao Jin | Pengfei Liu
Source: Journal of Materials Science Materials in Electronics (article, 2026-02-01)
Field: Materials Science — Materials Chemistry

Enhanced piezoelectric performance and thermal stability in KNN-BNZ ceramics modified by CaHfO3 Abstract (K, Na)NbO 3 (KNN) is regarded as a promising lead-free piezoelectric candidates due to its high Curie temperature and environmental compatibility. However, its piezoelectric performance remains inferior to Pb-based ceramics, mainly due to the rigid lattice and high coercive field that restrict domain switching. In this study, CaHfO 3 was introduced to modify the perovskite structure of KNN through a homologous co-doping mechanism. The simultaneous substitution of Ca 2+ and Hf 4+ modifies the local bonding environment and induces lattice softening, which effectively reduces the coercive field and facilitates polarization switching. At the optimal composition of 0.95(K 0.5 Na 0.5 )NbO 3 -0.02(Bi 0.5 Na 0.5 )ZrO 3 -0.03CaHfO 3 (0.95KNN-0.02BNZ-0.03CHO), the ceramics exhibit significant improvements in both ferroelectric and piezoelectric properties, while maintaining a balanced Curie temperature. This work provides clear evidence that structural softening induced by Ca-Hf incorporation provides an effective materials design strategy for enhancing the performance of lead-free KNN-based ceramics, while the compositional limits and long-term device-level behavior require further investigation. Coercivity ; Piezoelectricity ; Curie temperature ; Ceramic ; Softening ; Ferroelectricity ; Thermal stability ; Lattice (music) Ferroelectric and Piezoelectric Materials ; Ferroelectric and Negative Capacitance Devices ; Advanced Sensor and Energy Harvesting Materials