jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Guo Huihua | Gong Qingdi | Li Wang | Jingyuan Li
Source: Corrosion Reviews (article, 2025-04-01)
Field: Materials Science — Metals and Alloys

Impact of plastic deformation on the corrosion behavior of S32304 duplex steel in a simulated industrial solution Abstract This study investigated the impact of different deformations on the corrosion resistance of duplex stainless steel in an industrial environment simulation solution using various electrochemical, electron backscatter diffraction analysis, and surface analysis methods. Electrochemical results show that under small deformation conditions (10 %), the corrosion current of S32304 duplex stainless steel decreases due to the coupling effect of the austenite phase with increased potential and the ferrite phase with decreased potential. However, due to the increased potential difference between the austenite and ferrite phases, the pitting corrosion resistance of the material decreases. Under large deformation conditions, the corrosion current of S32304 duplex stainless steel continuously increases but still remains lower than the corrosion current under undeformed conditions. The pitting potential of duplex stainless steel first decreases and then increases. When the deformation reaches 70 %, high-angle grain boundaries are formed in the austenite phase, leading to a sharp decrease in potential. The potential of austenite begins to be lower than that of ferrite, and the preferentially corroded phase changes from ferrite to austenite. The experimental results found that deformation does not affect the semiconductor properties of the passivation film of S32304 duplex stainless steel. The main components of its passivation film include iron oxides (FeO and Fe 2 O 3 ) and chromium oxides (Cr 2 O 3 and Cr(OH) 3 ). Materials science ; Duplex (building) ; Corrosion ; Severe plastic deformation ; Metallurgy ; Deformation (meteorology) ; Materials processing ; Composite material ; Forensic engineering ; Microstructure ; Process engineering ; Engineering Hydrogen embrittlement and corrosion behaviors in metals ; Corrosion Behavior and Inhibition ; Non-Destructive Testing Techniques
Authors: Jingying Ma | Yufu Han | Jinfeng Ge | Ling Wen | Chao Ma | Yulin Qi | Dietrich A. Volmer
Source: Rapid Communications in Mass Spectrometry (article, 2025-04-01)
Field: Chemistry — Spectroscopy

Comprehensive Two‐Dimensional Gas Chromatography–Mass Spectrometry for the Analysis of Atmospheric Particulate Matter GC × GC-MS offers superior separation and identification of complex pollutants, making it invaluable for environmental analysis and applications. Emerging technologies, such as machine learning, will enhance its analytical capabilities and broaden its future applications. Chemistry ; Mass spectrometry ; Particulates ; Gas chromatography ; Gas chromatography–mass spectrometry ; Resolution (logic) ; Environmental chemistry ; Chromatography ; Analytical Chemistry (journal) ; Organic chemistry ; Computer science ; Artificial intelligence Analytical Chemistry and Chromatography ; Mass Spectrometry Techniques and Applications ; Advanced Chemical Sensor Technologies
Authors: Michael Mendoza | Jonilo Mababa | Isagani Mirador Tano | Keno Piad | Ace C. Lagman | Joseph Espino | Luningning M. Mendoza | Jayson M. Victoriano
Source: International journal of research and scientific innovation (article, 2025-01-01)
Field: Chemistry — Analytical Chemistry

Enhancing Rice Yield Prediction Using UAV-Based Multispectral Imaging and Machine Learning Algorithms This study investigates the integration of Unmanned Aerial Vehicle (UAV) technology into rice yield prediction to address the limitations of conventional methods that rely on time-consuming and labor-intensive manual field assessments. UAV-captured multispectral imagery was utilized to generate vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), providing accurate and timely indicators of crop health, growth stages, and productivity. Collected data underwent systematic preprocessing and analysis to estimate yield outputs, ensuring precision through the use of established statistical evaluation metrics. The developed system was assessed in accordance with ISO/IEC 25010 software quality standards and ISO/IEC 30141:2018 hardware architecture guidelines, receiving high scores in functional suitability, maintainability, and interoperability. Validation through consultations with farmers and agricultural technology experts confirmed its potential to improve decision-making processes, particularly in irrigation scheduling, pest and disease management, and harvest planning. The findings demonstrate that UAV-based monitoring systems offer a practical, data-driven approach to optimizing rice production. By enabling timely interventions and efficient resource allocation, the study underscores the role of UAV technology as a valuable tool in advancing sustainable and precision agriculture practices. Multispectral image ; Precision agriculture ; Normalized Difference Vegetation Index ; Preprocessor ; Software ; Data pre-processing ; Field (mathematics) ; Vegetation (pathology) Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI
Authors: Hui-Lin Chang | Jiazhen Cai | Qin Ouyang
Source: Journal of the Science of Food and Agriculture (article, 2025-05-23)
Field: Chemistry — Analytical Chemistry

Intelligent chlorophyll estimation by attention‐integrated deep learning and dual‐modal fusion in tencha drying using snapshot multispectral camera The results underscore the viability of leveraging snapshot multispectral technology coupled with spectral-image dual-modality fusion for precise chlorophyll content monitoring. This innovative approach provides a rapid, non-invasive solution for assessing chlorophyll levels in tencha, offering enhanced quality control throughout the drying process with emerging technological capabilities. © 2025 Society of Chemical Industry. Multispectral image ; Snapshot (computer storage) ; Computer science ; Artificial intelligence ; Remote sensing ; Sensor fusion ; Correlation coefficient ; Chemometrics ; Pattern recognition (psychology) ; Biological system ; Environmental science ; Machine learning ; Database ; Geography Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Phytochemicals and Antioxidant Activities
Authors: Lourdes Arjona | M.A. Martín‐Lara | Álvaro Montero | M. Calero | Rafael R. Solís | G. Blázquez
Source: Thermal Science and Engineering Progress (article, 2025-08-06)
Field: Materials Science — Materials Chemistry

Thermogravimetric analysis of textile waste: kinetic parameters and pyrolytic decomposition mechanisms • Optimizes pyrolysis recycling by analyzing textile thermal decomposition. • Determines activation energy using model-free and Coats-Redfern methods. • Identifies fiber-specific decomposition temperatures and reaction mechanisms. • Quantifies gaseous emissions, aiding pollution control in textile recycling. Thermogravimetric analysis (TGA) is a powerful technique to elucidate the thermal decomposition behavior of textile materials, a critical step in designing efficient pyrolysis processes. In this study, new insights into the kinetic behavior and activation energies of various textile fibers, 100 % cotton, 100 % polyester, and cotton/polyester blends, using model-free kinetic methods (Flynn-Wall-Ozawa (FWO), Kissinger-Akahira-Sunose (KAS), and Friedman (FR)) and the Coast-Redfern (CR) method were provided. Thermogravimetric analysis (TGA) was performed at multiple heating rates (5, 10, 15, and 20 °C/min) under an N 2 atmosphere to simulate pyrolysis conditions. Results revealed a clear relationship between fiber composition and decomposition behavior. Therefore, while 100 % cotton decomposes at 371 °C and 100 % polyester at 431 °C, blended fibers exhibit two distinct decomposition steps, a feature not previously reported in detail. The model-free methods indicated that the activation energy (E a ) increases with conversion (α), highlighting the complex multi-step decomposition of these fibers. For example, in 100 % cotton, E a increases from 96.9 kJ/mol (α = 0.1) to 195.6 kJ/mol (α = 0.9), indicating a close dependence on the stages of decomposition. Furthermore, the CR method revealed that the most appropriate reaction models differ by fiber type, identifying the nucleation (F1) model as one of the most suitable, offering a predictive tool for optimizing pyrolysis conditions in industrial textile waste management. Thermogravimetric analysis ; Pyrolytic carbon ; Decomposition ; Textile ; Kinetic energy ; Pyrolysis ; Materials science ; Chemical engineering ; Chemistry ; Engineering ; Organic chemistry ; Composite material ; Physics Thermal and Kinetic Analysis ; Thermochemical Biomass Conversion Processes ; Energetic Materials and Combustion
Authors: Malinee Sriariyanun | K. Koppiahraj | Baranitharan Paramasivam | K. Rajeshkumar | V. Kavimani
Source: Environmental Progress & Sustainable Energy (article, 2025-11-10)
Field: Materials Science — Polymers and Plastics

Optimization of mechanical properties for bio‐filler embedded bio‐composites using hybrid optimization techniques Abstract The valorization of eggshell waste as a sustainable biofiller offers a promising approach to improve the mechanical properties of biocomposites while addressing environmental concerns. In addition to reducing landfill accumulation, eggshell powder, which is high in calcium carbonate, also acts as a functional hybrid reinforcement in composites made of polymers. At the same time, cigarette butts are the most common litter in the world. They release dangerous pollutants, including hydrogen cyanide, acetaldehydes, heavy metals, and polycyclic aromatic hydrocarbons, which linger in the environment and seriously endanger both aquatic and terrestrial life. Using duck eggshell powder (DEP) as a bio filler, the mechanical behavior of vinyl ester composites reinforced with silane‐treated palm fruit fibers (STP) and smoked cigarette filter fibers (CFF) is optimized in this study. Compression molding was used to create hybrid composites with different eggshell powder loadings (0%, 2%, and 4%). The Criteria Importance through Inter‐Criteria Correlation (CRITIC) method and the Evaluation Based on Distance from Average Solution (EDAS) methodology were used in an integrated multi‐criteria decision‐making (MCDM) framework to identify the best formulation. With a tensile strength of 49.71 MPa, flexural strength of 37.88 MPa, and impact strength of 38.67 J/m, the CP9 composite (CFF 40 weight percent + STP 40 weight percent + eggshell powder 2 weight percent) outperformed the other manufactured samples in terms of mechanical qualities. The experimental findings and hybrid optimization analysis verify that eggshell‐incorporated bio‐composites, especially CP9, exhibit improved mechanical performance and have a great deal of promise for environmentally friendly, sustainable applications. Eggshell ; Ultimate tensile strength ; Composite number ; Flexural strength ; Molding (decorative) ; Compression molding ; Izod impact strength test ; Compression (physics) Natural Fiber Reinforced Composites ; Nanocomposite Films for Food Packaging ; Electrospun Nanofibers in Biomedical Applications
Authors: Da Shi | Yong Tan | Chenming Yan | Xiaomeng Qin | Lin Ren
Source: ChemRxiv (preprint, 2025-07-04)
Field: Chemistry — Spectroscopy

Agile and multiple modes of self-peristalsis of a slinky-like active gel The ability of agile internal driving is an essential function for the survival of living organisms, from which more sophisticated adaptive locomotion function may have evolved. A general mechanistic description of agile internal driving of active matter is a challenging task. In this paper, inspired by attacking snake and Slinkey toys, a helical-shaped active gel that hosted Ru (II) catalyzed Belousov-Zhabotinsky (BZ) is used to design agile and diverse move-functions. Experiment result show that, under driving by chemical waves, the helical gel undergoes a relative large-scale self-peristalsis along the axial direction with the amplitude of pitch variation exceeds 123.6%. When the propagating mode of wave changes, diverse mode of self-peristalsis, such as, self-twisting, self-rolling and confined self-rotating, will emergent. Detailed analysis indicated this agile peristalsis evolve from a helical-structure induced flexibility along the axis direction of the gel, which is driven by a collective torque-component generated by local bending of the gel. Duo to diverse propagating mode of chemical waves, various spatiotemporal evolving of stress distribution to generate above self-peristalsis modes. We anticipate our new strategy of high efficiency inter-driving of active materials can be widely applied and adapted to manufacture a variety of dynamic flexibility materials and intelligent active motors. Agile software development ; Peristalsis ; Computer science ; Medicine ; Anatomy ; Software engineering Aerogels and thermal insulation
Authors: Yu. A. Nashchekina | А. В. Нащекин
Source: Biomimetics (review, 2025-09-24)
Field: Materials Science — Biomaterials

Collagen Fibril Orientation In Vitro: From Formation to Advanced Biomaterial Development Extracellular matrix proteins have a complex assembly in tissue and it is believed that not only the chemical structure, but also their location, plays an important role in cellular functions. Collagen is one of the main components of the extracellular matrix and the oriented arrangement of collagen fibrils in tissues such as bone, cartilage, tendons, and cornea has a significant impact on various tissue functions. In the body, the orientation of extracellular matrix proteins is determined by cells. Oriented collagen fibrils can not only promote directed cell migration, but also stimulate cells to secrete an extracellular matrix with an oriented structure. However, the creation of collagen fibrils with an oriented structure in vitro is still associated with a number of limitations. Such limitations are primarily because the mechanisms regulating cellular functions in the orientation of extracellular matrix proteins, including collagen, are still unknown. Currently, only physical ways of organizing collagen fibrils in a certain direction are known. We hope that the description of the orientation of collagen fibrils in this review will allow readers to better understand the processes that occur with molecules. The study of methods and conditions for obtaining oriented collagen fibrils can help to obtain tissue biomimetic materials with complex properties identical to native tissues. Therefore, we discuss here various methods and conditions for obtaining oriented collagen fibrils in vitro using mechanical, electric, magnetic, and other fields. The prospects of application in tissue engineering and scientific problems of oriented collagen fibrils are also described. Extracellular matrix ; Fibril ; Collagen fibril ; Extracellular ; Matrix (chemical analysis) ; Biomaterial ; Tissue engineering Collagen: Extraction and Characterization ; Bone Tissue Engineering Materials ; Bone and Dental Protein Studies
Authors: Shota Ushiba | Tomomi Nakano | Hiroki K. Sato | Hitoshi IMAMURA | Shinsuke Tani | Masahiko KIMURA | Kazuhiko Matsumoto
Source: APL Electronic Devices (article, 2025-09-01)
Field: Materials Science — Materials Chemistry

Modeling responses to heterogeneous adsorption in graphene FET biosensors via circuit simulation Graphene field-effect transistors (GFETs) have emerged as highly promising platforms for biosensing applications owing to their exceptional sensitivity and capability for label-free detection. However, interpreting their transfer characteristics remains challenging, primarily because of complex signal variations induced by spatially heterogeneous biomolecular adsorption. In this study, we modeled the heterogeneous graphene channel as a resistor grid network to examine how local modulation of carrier density influences the electrical behavior of GFETs. Our simulations replicated the nonlinear and non-monotonic variations observed in RDS–VGS curves characteristics following biomolecular adsorption. Notably, the peak voltage shift (ΔVpeak) and resistance change (ΔRpeak) exhibited nontrivial dependencies on the adsorption ratio. These findings indicate that conventional metrics, such as the charge neutrality point, are inadequate for reliably quantifying adsorption levels under heterogeneous conditions. The proposed approach offers a fundamental framework for understanding signal variability in GFET-based biosensors and for guiding the development of more robust sensing strategies. Biosensor ; Graphene ; Sensitivity (control systems) ; Resistor ; SIGNAL (programming language) ; Adsorption ; Nonlinear system ; Transistor Graphene research and applications ; Nanowire Synthesis and Applications ; Advancements in Semiconductor Devices and Circuit Design
Authors: Jizheng Song | Yu Hu | Shiyu Yang | Dexue Liu | Yiider Tseng | Lingjun Li
Source: Polymers (article, 2025-01-27)
Field: Materials Science — Biomaterials

Predicting the Key Properties of a Modified Product to Pre-Select a Pluronic F127 Modification Scheme for Preparing High-Quality Nano-Micelles Hydrophobic modification alters the properties of Pluronic F127 to form micelles more efficiently and enhances its drug-loading capacity. However, selecting the appropriate hydrophobic group for modification is laborious. In this paper, we propose an efficient approach for predicting key parameters to select hydrophobic groups for F127 modification prior to synthesis, in order to improve the formability and stability of the micelles. The results of nuclear magnetic resonance and isothermal titration calorimetry were utilized to establish a function for predicting the hydrophile-lipophile balance, critical micelle concentration, and Gibbs free energy of the products based on the structure of raw material. These predicted values can assist us in selecting suitable hydrophobic groups for F127 modification. Subsequently, we successfully tested our method and validated our work using pharmaceutical evaluation methods, such as appearance observation, particle size measurement, drug loading determination, equilibrium binding rate assessment, storage stability testing, and the plotting of accumulation release curves. Therefore, we suggest that our work could provide a model linking the molecular structure to properties, with the purpose of pre-selecting modification products that have advantages in micelle preparation. This can facilitate the application of F127 in preparing nano-micelles. Micelle ; Critical quality attributes ; Isothermal titration calorimetry ; Materials science ; Critical micelle concentration ; Poloxamer ; Chemical engineering ; Particle size ; Chemistry ; Aqueous solution ; Organic chemistry ; Polymer ; Copolymer ; Composite material Nanoparticle-Based Drug Delivery ; Surfactants and Colloidal Systems ; Advanced Polymer Synthesis and Characterization
Authors: Akinobu Yamaguchi | Toshiya Yasunaga | Kyoko Namura | Motofumi Suzuki | Takao Fukuoka
Source: RSC Advances (article, 2025-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Print evaluation of inks with stealth nanobeacons Plasmonic structures using noble metal nano-assemblies are created and printed or stamped with a seal for use as information tags that carry both authenticity and information. We created an ink that contains stealth nanobeacons and evaluated its printing characteristics. Stealth nanobeacons are composed of noble metal nano-assemblies, which are fabricated <i>via</i> a self-assembly process and have indefinite shapes. This plasmonic structure was made into simple ink by mixing it with pure water or existing inkjet printer inks. We discharged this adjusted ink on an inkjet printer to evaluate its surface-enhanced Raman scattering activity and other properties, and confirmed that the ink containing stealth nanobeacons can be printed successfully. The printable ink is expected to be developed into a "Nanotag" information tag and an authenticity tag. Seal (emblem) ; Nanotechnology ; Plasmon ; Computer science ; Carry (investment) ; Noble metal ; Materials science ; Metal ; Optoelectronics ; Art ; Visual arts ; Business ; Metallurgy Gold and Silver Nanoparticles Synthesis and Applications ; Biosensors and Analytical Detection ; Nanomaterials and Printing Technologies
Authors: Alla P. Toropova | Andrey A. Toropov | Alessandra Roncaglioni | Emilio Benfenati
Source: Journal of Composites Science (article, 2025-01-02)
Field: Materials Science — Materials Chemistry

In Silico Simulation of Daphnia magna Immobilization Exposed to Mixtures of TiO2 Nanoparticles with Inorganic Compounds The development of models of the physicochemical and biochemical behavior of nanomaterials is useful for improving the evaluation and management of this material. Quasi-SMILES technology makes it possible to quite successfully cope with this kind of modeling task, accounting for various experimental conditions, where the use of other approaches is difficult or even impossible. Here, we describe the results of using quasi-SMILES to model the toxicity of mixtures of titanium nano oxide with various inorganic substances towards Daphnia magna. The approach is based on the stochastic process of the optimization of correlation weights for different codes used in quasi-SMILES. The optimization process was carried out using special statistical criteria for predictive potential. It is shown that models built using quasi-SMILES have the best predictive potential. Daphnia magna ; In silico ; Process (computing) ; Computer science ; Daphnia ; Process optimization ; Ecotoxicity ; Task (project management) ; Biochemical engineering ; Biological system ; Chemistry ; Environmental science ; Environmental engineering ; Biology ; Toxicity ; Engineering ; Ecology ; Systems engineering Nanoparticles: synthesis and applications ; Field-Flow Fractionation Techniques
Authors: Nadya Hafidzatun Nisa | Rudiati Evi Masithoh | Muhammad Fahri Reza Pahlawan | Andra Tersiana Wati
Source: BIO Web of Conferences (review, 2025-01-01)
Field: Chemistry — Analytical Chemistry

Application of machine learning and deep learning to detect adulteration in food flour based on spectroscopy data: A systematic review Food quality and safety are very important aspects in the food industry, but counterfeiting often occurs, especially in powdered products. The development of non-destructive technology based on spectroscopy, combined with machine learning and deep learning algorithms, is increasingly being applied to quickly and accurately detect adulterants. This study aims to identify, analyze, and review research trends related to the detection of adulterated powdered food products by combining spectroscopy technology and machine learning or deep learning methods through a systematic literature review (SLR) approach. The study identified 32 out of 105 articles selected from Scopus, Web of Science, and PubMed. The research trend shows a significant increase since 2019, dominated by the Asian region. Commonly used spectroscopy technologies include NIR, Vis-NIR, and Raman, combined with algorithms such as PLSR, CNN, and SVM to improve detection accuracy beyond 90% and achieve high R-squared (R²) values. Data pre-processing techniques, such as filtering, have also proven effective in improving analysis results. The development of intelligent detection systems using machine learning models, data augmentation techniques, and transfer learning, along with multidisciplinary collaboration between food science, computer science, and instrumentation fields, will strengthen future research. Deep learning ; Support vector machine ; Quality (philosophy) ; Food products ; Novel food ; Transfer of learning Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food ; Melamine detection and toxicity