jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Irfan Farooq | Abdulhamid Al-Abduljabbar | Ibrahim A. Alnaser
Source: Polymers (article, 2025-08-17)
Field: Materials Science — Biomaterials

Development of Biopolymer Polylactic Acid–Cellulose Acetate–Silicon Dioxide Nanocomposite Membranes for Multifunctional Protective Textiles In this study, multifunctional nanocomposite membranes were fabricated using biopolymeric polylactic acid (PLA) and cellulose acetate (CA) composites via electrospinning. The hydrophobic nanocomposite membranes were reinforced with varying concentrations of silicon dioxide (silica/SiO<sub>2</sub>) nanoparticles. The developed PLA-CA-SiO<sub>2</sub> nanofibrous membranes are characterized using field emission scanning electron microscopy (FE- energy-dispersive SEM), energy-dispersive X-ray (EDX), elemental mapping, X-ray diffraction analysis (XRD), Fourier-transform infrared spectroscopy (FT-IR), thermal gravimetric analysis (TGA), and differential scanning calorimetry (DSC) techniques. Various physical and mechanical properties of the bio-nanocomposite membrane, such as tensile testing, infrared thermal imaging, ultraviolet-visible spectroscopy (UV-Vis), water contact angle, hydrostatic pressure resistance, and breathability are also investigated. The analysis revealed that a small concentration of silica nanoparticles improves the morphological, mechanical, and thermal characteristics of nanocomposite membranes. The addition of silica nanoparticles improves the UV (A & B), visible and infrared blocking efficiency while also enhancing the waterproofness of protective textiles. The PLA-CA-SiO<sub>2</sub> biopolymer nanocomposite membrane has a fibrous microstructure and demonstrated the tensile strength of 11.2 MPa, a Young's modulus of 329 MPa, an elongation at break of 98.5%, a hydrostatic pressure resistance of 27 kPa, and a water contact angle of 143.7°. The developed electrospun composite membranes with improved properties provide strong potential to replace petroleum-based membranes with biopolymer-based alternatives, promising improved and wider usage for bio-related applications. Polylactic acid ; Biopolymer ; Nanocomposite ; Membrane ; Silicon dioxide ; Materials science ; Cellulose ; Cellulose acetate ; Chitosan ; Chemical engineering ; Polymer science ; Chemistry ; Organic chemistry ; Polymer ; Nanotechnology ; Composite material ; Biochemistry ; Engineering biodegradable polymer synthesis and properties ; Microplastics and Plastic Pollution ; Electrospun Nanofibers in Biomedical Applications
Authors: Maria Tarapoulouzi | Ioannis Pashalidis | Charis R. Theocharis
Source: Chemosensors (review, 2025-09-03)
Field: Chemistry — Analytical Chemistry

Use of Chemometrics for the Authentication, Characterization and Detection of Adulteration of Cypriot Products Registered Under EU Quality Schemes: A Review This review explores the application of chemometric techniques for the authentication, characterization, and adulteration detection of Cypriot agri-food products registered under European Union quality schemes, including Protected Designation of Origin (PDO) and Protected Geographical Indication (PGI). Given the increasing global demand for premium and geographically linked food products, ensuring their authenticity and integrity has become critical. Although Halloumi cheese, wines, and Zivania are the most researched Cypriot products, additional studies are still needed. Chemometrics, when coupled with spectroscopy, offers robust analytical tools for distinguishing genuine products from their imitations by characterizing them. This review provides an overview of certified Cypriot products and focuses on published applications where chemometric approaches have been used to assess product origin, composition, and adulteration. The paper concludes with current challenges, methodological limitations, and future directions for expanding the role of chemometrics in food integrity verification within the context of EU geographical indications. Chemometrics ; Authentication (law) ; Quality (philosophy) ; Characterization (materials science) ; Mathematics ; Chemistry ; Chromatography ; Computer science ; Materials science ; Nanotechnology ; Computer security ; Physics Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food ; Advanced Chemical Sensor Technologies
Authors: Tiantian Chen | Fanglin Zha | Qian Luo | ﻿Lei Shi | Tao Wan | Bo Chen
Source: Polymers (article, 2025-11-12)
Field: Materials Science — Materials Chemistry

Microstructure Evolution Study of the Field-Serviced Silicone Rubber Insulator via X-Ray Micro-CT Imaging Composite silicone rubber insulators are widely used in overhead transmission lines but undergo inevitable aging-induced performance degradation or failure. Understanding their aging process is crucial for optimizing manufacturing and on-site service, yet studies on microstructural changes-especially three-dimensional (3D) microstructural evolution during aging-remain scarce. This study employed X-ray micro-computed tomography (X-ray micro-CT) to characterize and compare the 3D microstructure of one fresh and one field-serviced composite silicone rubber insulator (which underwent 10 years of outdoor service). For the field-serviced insulator, key findings include the following: (1) pore number decreased (from 2200 to 1600), while pore size increased (equivalent diameter: from 3.5 ± 1.3 μm to 10.4 ± 7.2 μm); (2) porosity increased (from 0.04% to 0.69%); (3) new cracks formed (length: 100-900 μm); and (4) pore shape remained nearly unchanged relative to the fresh sample. Notably, the aging depth of the field-serviced insulator was less than 300 μm. These results clarify the 3D microstructural evolution of composite silicone rubber insulators during aging, providing a basis for improving their long-term reliability. Silicone rubber ; Microstructure ; Porosity ; Composite number ; Insulator (electricity) ; Silicone High voltage insulation and dielectric phenomena ; Polymer Nanocomposites and Properties ; Aerogels and thermal insulation
Authors: Nicholas McInchak | Laura Stawikowska | Haylee Mesa | Jonathan Meade | Qi Zhang | Maciej Stawikowski
Source: Sci (article, 2025-05-07)
Field: Chemistry — Spectroscopy

L-Lysine-Linked Modular Fluorescent Cholesteryl Mimics: Biophysical Properties, Molecular Interactions, and Cellular Applications Fluorescent cholesterol probes are indispensable tools for studying membrane structure, dynamics, and trafficking. To better understand the structure-function relationship of fluorescent cholesteryl probes, we developed a series of five new modular naphthalimide-containing cholesteryl probes (CND15-CND19). These probes incorporate an L-lysine linker between the cholesterol moiety and the fluorophore, along with a series of distinct head groups. We conducted extensive biophysical characterizations of these probes, including the determination of their solvatochromic properties and lipid partitioning behavior using giant unilamellar vesicles. Molecular dynamics simulations were employed to identify key molecular interactions of these probes within model lipid membranes. Furthermore, live-cell imaging in 3T3 fibroblasts demonstrated the potential applications of these analogs in live-cell imaging, measuring cellular membrane dynamics and studying cholesterol-related processes. The results of this study underscore the critical role of the linker and head group in designing fluorescent cholesterol-mimicking probes. These findings provide valuable insights into optimizing probe designs for future cholesterol and membrane biology research. Lysine ; Fluorescence ; Chemistry ; Biophysics ; Biochemistry ; Biology ; Amino acid Molecular Sensors and Ion Detection ; Carbohydrate Chemistry and Synthesis ; Photochromic and Fluorescence Chemistry
Authors: Zakiah Mohd Yusoff | Siti Aminah Nordin | Zuraida Muhammad | Nurlaila Ismail
Source: Journal of Electrical & Electronic Systems Research (article, 2025-10-30)
Field: Chemistry — Organic Chemistry

Examining the Trend in Agarwood Oil Studies for the 5 Recent Years (2019-2023): A Comprehensive Bibliometric Analysis using VOSviewer This bibliometric article investigates the burgeoning research landscape surrounding agarwood oil, derived from the Aquilaria tree species. The historical and cultural significance of agarwood, coupled with its diverse applications in perfumery, traditional medicine, and religious practices, has fueled a surge in scientific interest. However, a comprehensive understanding of the current state of agarwood oil research is lacking. This study addresses this gap through a systematic review and bibliometric analysis, utilizing the SCOPUS database as the primary source of scholarly. By employing techniques such as co-citation analysis and keyword co-occurrence, the research aims to quantify patterns, relationships, and collaborations within the literature. The methodology involves a focused exploration of a specified timeframe to capture recent developments, with the anticipation that the outcomes will include the identification of key contributors, thematic clusters, and emerging trends in agarwood oil research. The study is poised to contribute valuable insights for researchers, policymakers, and industry stakeholders, offering a holistic perspective on the interconnectedness of agarwood oil research and guiding future exploration in this dynamic field. Agarwood ; Scopus ; Identification (biology) ; Perspective (graphical) ; Key (lock) ; Thematic map ; Anticipation (artificial intelligence) Wood and Agarwood Research ; Ginger and Zingiberaceae research ; Forensic Fingerprint Detection Methods
Authors: Binhao Wang | Yu Shen | Rui Hao | Shize Pan | Ruizhi Han | Ye Ni
Source: Chirality (article, 2025-01-01)
Field: Chemistry — Spectroscopy

Novel Approach for Efficient Separation of Primary Amines Using Supercritical Fluid Chromatography Efficient enantioselective separation is a critical process in pharmaceutical and chemical industries for the production of chiral compounds. Herein, we developed a novel approach for the efficient enantioselective separation of primary amines using supercritical fluid chromatography (SFC) with a commercially available SFC column, Cel1. The key factors of separation, including cosolvent ratios, total cosolvent percentages, and temperature, were systematically assessed in this study. It revealed that utilization of a cosolvent mixture consisting of methanol and isopropanol in a 1:3 (v/v) ratio with a low total cosolvent percentage of 5% resulted in superior retention and selectivity. Additionally, it was observed that maintaining mid-range temperatures at 30 and 35°C achieved optimal balance between retention and efficiency. Employment of commercially available SFC columns streamlined the separation process, reducing analysis time and labor. This study highlights the effectiveness of SFC as a powerful tool for conducting high-throughput enantioselective separations in pharmaceutical and fine chemical industries. Chemistry ; Supercritical fluid chromatography ; Supercritical fluid ; Enantioselective synthesis ; Chromatography ; Selectivity ; Methanol ; Separation process ; Organic chemistry ; Column chromatography ; Catalysis Analytical Chemistry and Chromatography ; Chromatography in Natural Products ; Crystallization and Solubility Studies
Authors: Tuser Tirtha Biswas | M. Will | Nawar Kadi
Source: Advanced Theory and Simulations (article, 2025-05-12)
Field: Materials Science — Polymers and Plastics

Predicting Fiber Length Characteristics of Recycled Cotton and Cellulose Fiber Blends Using Machine Learning Models Abstract As the textile industry faces growing challenges related to sustainability, recycled fiber blending for making new yarns has emerged as a key area for reducing environmental impacts. This study aims to investigate the role of fiber length features in predicting the quality of blended yarns, particularly focusing on natural‐based fiber blends such as recycled cotton (ReCo) and Lyocell. Machine learning models, including Random Forest, Gradient Boosting, and Support Vector Regression, alongside linear and polynomial regressions, are used to predict fiber properties based on empirical data. The results show fiber length features from the Staple Diagram and Fibrogram as the most significant factors. Hyperparameter tuning has enhanced model accuracy, especially for Random Forest and Gradient Boosting, showing significant reductions in error metrics. Cross‐validation is performed to ensure the reliability of the models and prevent overfitting during the predictive analysis of fiber length features. Shapley Additive Explanations (SHAP) analysis reveals that specific fiber length ranges have the most influence on model predictions, highlighting their importance in optimizing blended yarn properties. These findings contribute to advancing sustainable textile production through data‐driven approaches and textile fiber blend optimization. Fiber ; Materials science ; Cellulose ; Composite material ; Cellulose fiber ; Polymer science ; Chemical engineering ; Engineering Textile materials and evaluations ; Natural Fiber Reinforced Composites
Authors: Qiang Wu | Xi Chen | Mingwen Luo | Ao Li | Qing Yuan | Daliang Yu | Qingwei Dai
Source: AIP Advances (article, 2025-09-01)
Field: Materials Science — Materials Chemistry

Research on the optimization of seamless steel pipe cooling process based on large language models To address technical challenges such as non-uniform cooling and microstructural delamination during the cooling process of seamless steel pipes, this study proposes an intelligent process parameter optimization approach that integrates a large language model with a domain-specific knowledge base. Built upon the open-source DeepSeek-R1-Distill-Qwen-14B model, two parameter-efficient fine-tuning strategies, such as LoRA and P-Tuning V2, are applied. Fine-tuning is performed using a curated knowledge base tailored to the steel pipe cooling domain. The jointly fine-tuned model achieves an accuracy of 0.871—an improvement of 7.7% over the base model—substantially enhancing the reliability of process parameter recommendations and the overall precision of cooling process optimization. By integrating LangChain to enable natural language interaction and process parameter recommendation, the proposed system is experimentally validated through studies on the effects of different cooling strategies on the microstructural properties of steel tubes. Experimental results demonstrate that, in terms of cooling uniformity, the cut-circle spraying method markedly outperforms vertical spraying, reducing the maximum inner wall temperature difference to 49 °C under continuous spraying at 60 kPa. Notable strength enhancements were observed across various spray pressures, with tensile and yield strengths reaching 1088 and 634 MPa, respectively, at 150 kPa. These improvements highlight a favorable balance between strength and toughness. Furthermore, all performance indices under 60 kPa cooling met API standards, underscoring the robustness of the proposed reusable engineering workflow and technical framework for generating and optimizing process parameters. Workflow ; Robustness (evolution) ; Process (computing) ; Reliability (semiconductor) ; Water cooling ; Ultimate tensile strength ; Process variable ; Process modeling ; Delamination (geology) ; Yield (engineering) Corrosion Behavior and Inhibition ; Hydrogen embrittlement and corrosion behaviors in metals ; Machine Learning in Materials Science
Authors: Yassine El Kiri | Laidi Zahiri | Khalifa Mansouri | Zakaria Mighouar
Source: Research on Engineering Structures and Materials (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Assessment of the harmfulness of corrosion defects in a pressurized pipeline with a single corrosion defect using FEA and ANN External corrosion is a significant issue that can lead to ruptures in long-distance liquid transportation facilities such as pipelines. Highlighting the need for regular monitoring of their condition, which can compromise their integrity and safety. Three types of external corrosion defects were studied since it is necessary in some to prioritize interventions when multiple defects appear simultaneously on different sections considering burst pressure of the structure. These pressures were determined using numerical simulations in SolidWorks, based on models validated by previous experimental results. An artificial neural network was developed to quickly predict burst pressures, optimizing the network's topology through detailed analysis and thus avoiding the need for complex finite element analyses in the future. The results indicate that the defect having parabolic shape is generally the most detrimental to the structure, although the circumferential defect may be more damaging in certain cases. Additionally, the depth of the defect is a crucial parameter compared to geometric characteristics, emphasizing the importance of continuous monitoring to prevent corrosion risks. Corrosion ; Pipeline (software) ; Materials science ; Forensic engineering ; Metallurgy ; Engineering ; Mechanical engineering Material Properties and Failure Mechanisms ; Engineering Diagnostics and Reliability ; Non-Destructive Testing Techniques
Authors: Natasha Dantas Lorenzo | Roney Alves da Rocha | Emmanouil H. Papaioannou | Letícia Tessaro | Cleiton Antônio Nunes
Source: Journal of Food Composition and Analysis (article, 2025-05-15)
Field: Chemistry — Analytical Chemistry

Rapid estimation of natural pigments in olive and avocado oils using a colorimetric sensor Pigment ; Olive oil ; Food science ; Food composition data ; Chemistry ; Botany ; Environmental science ; Biology ; Environmental chemistry ; Organic chemistry Spectroscopy and Chemometric Analyses ; Edible Oils Quality and Analysis ; Advanced Chemical Sensor Technologies
Authors: Babylon Education Directorate, Ministry of Education, Iraq | Iman Sami Majli | Ayat Monther Alqudsi | Hussein Dhahir Ayyez Al-fatlawiy | Ali A. Al-fahham
Source: International Journal of Medical Science and Dental Health (article, 2025-09-17)
Field: Chemistry — Organic Chemistry

Kinetic And Thermodynamic Principles Underlying Drug–Target Interactions: A Review Article All drugs interact with their biological targets. The nature of the thermodynamic and kinetic laws of such interactions is what needs to be well known for subsequent discovery of new drugs and modern design. Thermodynamic affinity, enthalpy, and entropy parameters describe the strengths and stabilities of drug-target complexes; kinetic parameters describe how rapidly binding occurs as well as for how long the interaction takes place most often expressed "on/off" rates (kon/koff). "Recent years have seen a shift in focus towards kinetic behavior, more specifically residence time which has emerged as an excellent indicator of a drug's efficacy within living organisms." "It acquires high relevance particularly in the case of large biopharmaceuticals like monoclonal antibodies, peptides, and nucleic acid-based therapeutics since they have broad binding surfaces due to which there is a need for careful control over interaction dynamics." Kinetic energy ; Entropy (arrow of time) ; Relevance (law) ; Review article ; Focus (optics) Free Radicals and Antioxidants ; Computational Drug Discovery Methods ; Chemical Reaction Mechanisms
Authors: Ji Hoon Hong | Min Sung Kang | Inho Ha | Hong-Lae Park | Kyungwook Park | Joohyun Jeon | Wonseok Yoo | Jueun Kim | Chul Chung | Sung Park | Sung Beom Cho
Source: Journal of Applied Physics (article, 2025-01-02)
Field: Materials Science — Materials Chemistry

Residual strain optimization in 3D MOSFET structures for enhanced mobility via nanoscale heat transfer This study addresses the optimization of strain in continuous MOSFET downscaling, particularly at the nanoscale, where traditional Fourier models fail due to non-diffusive phonon transport effects. We introduce a multi-physics simulation approach that combines Finite Element Method (FEM) and Density Functional Theory (DFT) calculations to design strain-optimized 3D MOSFET structures. By implementing the kinetic collective model within FEM simulations, we accurately predict thermal-induced strains in the Si channel layer. Our DFT calculations further elucidate the impact of these strains on the electronic properties, particularly the electron effective mass, thereby offering insights into mobility enhancement strategies. The study not only advances the implications of nanoscale heat transfer for device performance but also provides a robust framework for optimizing next-generation semiconductor devices through strain engineering and sophisticated multi-physics simulations. Nanoscopic scale ; MOSFET ; Materials science ; Residual stress ; Strain (injury) ; Optoelectronics ; Nanotechnology ; Composite material ; Transistor ; Electrical engineering Thermal properties of materials ; Advancements in Semiconductor Devices and Circuit Design ; Metal and Thin Film Mechanics
Authors: Muhammad Shahidul Islam | Debela T. Tadele | Tizazu H. Mekonnen
Source: Advanced Sustainable Systems (article, 2025-09-23)
Field: Materials Science — Biomaterials

Corn Zein Nanocarriers for Agrochemical Delivery and Smart Packaging Abstract Zein, a prolamin protein derived from corn, has emerged as a multifunctional and scalable nanocarrier for addressing critical sustainability challenges in agriculture and packaging. This review critically synthesizes and evaluates recent advances in zein‐based nanocarriers for targeted delivery of pesticides, herbicides, fungicides, micronutrients, and in smart packaging systems. Drawing from biomedical nanomedicine, it highlights innovations in stimuli‐responsive release of bioactives, hybridization of zein with natural polymers, and plant translocation. Zein, with a Generally Recognized as Safe (GRAS) status, biodegradability, and ability to form stable nanoparticles, positions it as a low‐toxicity alternative to conventional synthetic agrochemical carriers and petroleum‐based plastics. Applications in postharvest preservation, humidity‐triggered release, and biosensor‐enabled packaging further elucidates its multifunctionality. Despite strong lab‐scale performance, major challenges remain in field‐scale agrochemical delivery, gaps in its environmental fate, and regulatory approval. This critical review outlines strategies for overcoming these barriers. Overall, zein nanotechnology, framed within the broader goals of climate‐resilient, resource‐efficient, and circular agriculture, offers a roadmap for leveraging zein nanotechnology to reduce environmental burden while improving agricultural productivity. In addition, the challenges that this review paper addresses strongly promote several United Nations Sustainability Development Goals, including UN SDG2 (zero hunger), SDG 12 (responsible consumption and production), SDG 13 (Climate action), and SDG 15 (life on land). Nanocarriers ; Agrochemical ; Sustainability ; Agriculture ; Applications of nanotechnology ; Active packaging Nanocomposite Films for Food Packaging ; Nanoparticles: synthesis and applications