jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Kirti Vishwakarma | O. P. Vishwakarma
Source: International Journal of Latest Technology in Engineering Management & Applied Science (article, 2025-08-18)
Field: Materials Science — Biomaterials

Revolutionizing Cancer Care Through Smart Drug Delivery Technologies Abstract: Smart materials that react to environmental stimuli, such as temperature, pH, light, or electromagnetic fields are transforming cancer treatment by enabling precisely controlled drug release. Nanoparticle-based delivery systems enhance drug solubility, prolong circulation time, and concentrate therapeutics at tumor sites, mitigating damage to healthy tissues. Stimuli-responsive systems triggered by internal or external cues offer spatiotemporal control over release, improving safety and efficacy. This review outlines recent advances in smart nanocarriers for cancer therapy, examines their mechanisms, highlights clinical successes, addresses current challenges, and explores future directions including AI-driven personalization and emerging nanotechnologies. Cancer ; Drug delivery ; Drug ; Cancer drugs ; Medicine ; Computer science ; Pharmacology ; Nanotechnology ; Internal medicine ; Materials science Nanoparticle-Based Drug Delivery ; Graphene and Nanomaterials Applications ; Nanoplatforms for cancer theranostics
Authors: Seyyed Khalil Hosseinihashemi | Mojtaba Esfandyar
Source: Mobilya ve Ahşap Malzeme Araştırmaları Dergisi (article, 2025-12-25)
Field: Materials Science — Polymers and Plastics

Non-destructive assessment of dynamic properties of acetylated beech wood (Fagus orientalis L.) under varying impregnation and reaction times The aim of this study was to investigate the effect of impregnation and reaction times during acetylation on the dynamic mechanical and acoustic properties of beech wood using non-destructive vibration testing. Acetylated solid wood from beech (Fagus orientalis L.) was prepared with acetic anhydride, without catalyst, by soaking impregnation. Oven-dried, defect-free specimens (20 × 20 × 360 mm3; R × T × L) were treated at 120 ± 3 °C under oven-dry conditions with impregnation times of 60 or 180 min and reaction times of 60 or 120 min. Dynamic properties of modified and unmodified samples were measured by free flexural and longitudinal vibration tests in radial and tangential directions. Impregnation and reaction durations significantly affected physical and dynamic properties. Longer impregnation (Im180) increased density and weight percent gain (WPG ≈ 4%), indicating greater chemical uptake and reduced porosity. In contrast, extended reaction time (Re120) reduced the dynamic modulus of elasticity and acoustic coefficient by about 6-8%, suggesting partial stiffness loss at higher acetylation intensity. The best balance between mass gain, stiffness retention, and acoustic performance occurred at moderate conditions (Im60-Re60). Beech ; Stiffness ; Dynamic mechanical analysis ; Young's modulus ; Mass fraction ; Acetic anhydride ; Flexural strength ; Elasticity (physics) Natural Fiber Reinforced Composites ; Agricultural Engineering and Mechanization ; Wood Treatment and Properties
Authors: Yogal Prasad Ghimirey | Laxman Nagireddy | Céphise Cacho | Neil R. Wilson | Matthew D. Watson
Source: ArXiv.org (preprint, 2025-10-06)
Field: Materials Science — Materials Chemistry

The two conduction bands of monolayer CrSBr on Au We report the electronic structure of monolayer CrSBr exfoliated onto mica template-stripped gold substrates. Angle-resolved photoemission spectroscopy reveals charge transfer from the substrate, populating the conduction band of monolayer CrSBr, accompanied by a pronounced reduction in the quasiparticle band gap. Furthermore, we observe two separate conduction bands that exhibit a splitting at the X point. This indicates a breaking of glide-mirror symmetry, which in the bulk or in a free-standing monolayer protects the band degeneracies at the Brillouin zone boundary. Our results demonstrate that ultraflat gold substrates do more than modify carrier densities and screening: they can lift symmetry-protected degeneracies and thus fundamentally reshape the band topology of 2D materials. Monolayer ; Brillouin zone ; Mica ; Conduction band ; Quasiparticle ; Thermal conduction ; Electronic band structure ; Semimetal 2D Materials and Applications ; MXene and MAX Phase Materials ; Chalcogenide Semiconductor Thin Films
Authors: Ramiro Sánchez | Fernando Díaz | Lina Viviana Melo Niño
Source: Preprints.org (preprint, 2025-09-23)
Field: Chemistry — Organic Chemistry

IOC-Aligned Screening of Virgin Olive Oils via Digital Olfaction: Classification and Estimation of Sunflower-Oil Adulteration Extra virgin olive oil (EVOO) can degrade during production or storage to virgin olive oil (VOO) or lampante olive oil (LOO). Fraud can also occur during commercialisation through adulteration of EVOO (Ad-EVOO) with cheaper sunflower oil (SFO). Therefore, rapid screening techniques for quality control are needed. We evaluated an electronic nose (EN) with chemometrics—linear discriminant analysis (LDA), artificial neural-network discriminant analysis (ANN-DA), and partial least-squares regression (PLS)—in two scenarios: (i) classification into four classes (EVOO, VOO, LOO, and Ad-EVOO adulterated with 25% w/w SFO); and (ii) Ad-EVOO series containing 5–40% w/w SFO. Classes were corroborated by HS-SPME-GC-MS, with elevated (E)-2-hexenal and 3-hexen-1-ol in EVOO and increases in nonanal, ethyl acetate, and 2-propanol in deteriorated oils. Using the EN, LDA separated the classes, and ANN-DA achieved 90% accuracy under cross-validation, with the greatest confusion between VOO and LOO. In adulteration, discrimination emerged from 20% SFO, and PLS estimated %Ad-EVOO with R²pred = 0.972 (RMSEC/RMSEP = 8.059/5.627). In conclusion, the EN provides objective, rapid, and non-destructive screening that supports sensory panels and chromatographic analyses during reception and storage in industrial settings. Electronic nose ; Olive oil ; Linear discriminant analysis ; Sunflower oil ; Edible oil ; Vegetable oil Edible Oils Quality and Analysis ; Advanced Chemical Sensor Technologies ; Essential Oils and Antimicrobial Activity
Authors: T. Yoshiie
Source: Metals (article, 2025-05-17)
Field: Materials Science — Materials Chemistry

Rate Equation Analysis of the Effect of Damage Distribution on Defect Evolution in Self-Ion Irradiated Fe Ion irradiations have a damage peak near the beam incident surface. A simulation model with reaction kinetic analysis using rate equations was employed to study the defect evolution caused by localized damage distribution in self-ion irradiated iron. Comparisons were made between the localized damage irradiation by ions (the damage peak near the specimen surface) and homogeneous damage irradiation (the flat damage rate across the specimen) such as those caused by neutron irradiation. The irradiation conditions were as follows: the accelerating voltage was 2 MeV and 100 MeV, the irradiation temperatures was 273 K and 573 K, the damage rate was 1 × 10−5 dpa/s, and the total damage was 1 dpa. The distribution of residual point defects in clusters is complex due to the influence of the surface and the sharp distribution of the damage peak. The effects of the damage distributions on defect production were obtained, revealing a dependence on irradiation temperatures. At 573 K irradiation, localized damage irradiation produced higher residual interstitials than homogeneous damage irradiation when using the peak damage rate. The 100 MeV irradiation was more prominent than 2 MeV irradiation. However, the remaining vacancies were almost identical. At 273 K irradiation, the residual point defects, interstitials, and vacancies, were nearly identical in both the localized and homogeneous damage irradiations, even if the accelerating voltage was different. Irradiation ; Ion ; Materials science ; Distribution (mathematics) ; Physics ; Mathematics ; Nuclear physics ; Mathematical analysis ; Quantum mechanics Fusion materials and technologies ; Ion-surface interactions and analysis ; Silicon and Solar Cell Technologies
Authors: C. Chil | Adrien Pivano | Bruno Michel | Émeric Bourasseau
Source: Journal of the American Ceramic Society (article, 2025-10-20)
Field: Materials Science — Materials Chemistry

Fracture behavior of grain boundaries in (U,Pu)O <sub>2</sub> fuels: An atomistic study Abstract Classical atomistic simulations using the Cooper–Rushston–Grimes potential were carried out to observe the stability and the fracture properties of six special grain boundaries in (, . The formation energy decreases as a function of Pu content, while the cleavage energy increases. Mechanical tensile tests were performed on these grain boundaries to calculate the fracture stress and fracture energy. Some grain boundaries exhibit a phase transition prior to brittle fracture. The conditions for the appearance of this phase transition depend on the stress field values before the fracture, which are influenced by the Pu content. The Pu content appears to enhance the fracture resistance of the grain boundaries, as indicated by the fracture energy and cleavage energy. Grain boundary ; Cleavage (geology) ; Fracture (geology) ; Grain boundary strengthening ; Brittleness ; Stress field ; Grain size ; Ultimate tensile strength Nuclear Materials and Properties ; Radioactive element chemistry and processing ; Nuclear reactor physics and engineering
Authors: Michaela Vasilaki | Effie Marcoulaki | Antonis Kokossis
Source: Systems and Control Transactions (article, 2025-06-30)
Field: Chemistry — Analytical Chemistry

A Generalized Optimization Approach for the Characterization of Non-Conventional Streams This study provides standardized models for the chemical characterization of complex streams, ensuring the necessary adaptations while considering the differences in biomass types and forms. Several datasets are compiled and examined to establish a valid representation of the mixture, according to industry accepted standards and laboratory protocols. For reliable property estimation, correlations of key biomass properties are obtained from both computational models and experimental measurements. Existing data are used to create datasets for the biomass and the biocrude streams. This model builds upon existing knowledge and data technologies with emphasis on hydrothermal liquefaction (HTL). The proposed approach shows potential as a starting point for the design and modelling of more biorefinery-associated technologies. Sludge and pine wood are used as case studies for biomass feedstocks. Two biocrude samples are employed for biocrude characterization. The performance of the developed optimization model is compared favorably with results obtained using previous works. To ensure a variety of possible and valid solutions, integer cuts are implemented producing solution pools for the analysed streams. STREAMS ; Computer science ; Characterization (materials science) ; Mathematical optimization ; Mathematics ; Materials science ; Computer network Petroleum Processing and Analysis ; Advanced Control Systems Optimization ; Analytical Chemistry and Chromatography
Authors: Muhammed Bahattin Kurt | Azmi Gençten
Source: International Journal of Pure and Applied Sciences (article, 2025-11-25)
Field: Materials Science — Materials Chemistry

Artificial Neural Network Approach for Quantum Defect Prediction in Alkali Atoms In this study, an Artificial Neural Network (ANN) model was suggested and trained to predict the quantum defect values of alkali atoms. The dataset was divided into training and testing subsets with a % 60 – % 40, respectively. To prevent overfitting, the number of training epochs was limited to 250, and the learning rate was set to 0.25. The training process employed the Gradient Descent optimization algorithm for updating the network weights. Two different activation functions, ReLU and Swish, were utilized to evaluate their impact on prediction accuracy. The predicted quantum defect values obtained from the ANN were compared with corresponding experimental results to assess the model’s performance. Artificial neural network ; Gradient descent ; Quantum ; Process (computing) ; Set (abstract data type) ; Alkali metal ; Training set ; Quantum chemical Machine Learning in Materials Science ; Quantum Computing Algorithms and Architecture ; Chemical and Physical Properties of Materials
Authors: Jing Cao | Zhuofeng Chen | Xin Liu | Yan Su | Yuhu Li | Bingjie Mai
Source: npj Heritage Science (article, 2025-12-15)
Field: Materials Science — Biomaterials

Smart packaging solution: Na2B8O13·4H2O-loaded QCS/PAM double-network hydrogel for microbial control in paper heritage preservation Archive storage boxes are preventive tools used by museums and archives to mitigate the impact of adverse external factors. In this study, quaternized chitosan and polyacrylamide double-network gel were used to load sodium octaborate tetrahydrate, which was then combined with paper fibers to produce storage boxes. By analyzing the physiological and biochemical changes of microbial cells and the microenvironment around the boxes, the antifungal effect of these storage boxes was explored. In addition to physical barrier function, the storage boxes can damage the permeability and morphological structure of mold spore membranes. They inhibit mold reproduction by affecting metabolic pathways such as protein synthesis, which can significantly reduce the number of microorganisms and the proportion of dominant bacterial species in library environments. This enhances the ability of the collection environment to resist harmful organisms and reduces the incidence of microbial diseases in cultural relic collections. Metabolic activity ; Food packaging ; Microorganism ; Antifungal ; Mold ; Food preservation ; Resist Advanced Cellulose Research Studies ; Building materials and conservation ; Nanocomposite Films for Food Packaging
Authors: Ankush Singhal | T.J.J van Daalen | G. J. A. Sevink
Source: ChemRxiv (preprint, 2025-06-30)
Field: Chemistry — Organic Chemistry

The significance of lipid membrane curvature and lipid order for nano-C60 uptake Interactions that invasive mesoscopic nanoparticles (NPs) experience with the variety of lipid membranes present in our body have the potential to trigger diverse biological responses and endocytic pathways. From a safety perspective, it is therefore crucial to comprehend how these NPs are absorbed by complex biological environments and how they subsequently disperse and disassemble within them. Previous computational research has focussed on evaluating the compositional dependence of NP binding and translocation to 'model' lipid membranes, i.e. membranes that are in equilibrium, flat, fluid and composed of a few lipid species. The observation of strong local variation of curvature and phase along many membranes in biology, however, suggests that these features are important for membrane-related processes. In particular, the thermodynamic factors underlying curvature formation and phase separation appear to be essential for regulating intricate membrane functions such as insertion and dispersion in a precise and controllable manner. In this study, we have employed coarse-grained simulation to shed light on the role of curvature and phase on the adsorption and dispersion of a typical hydrophobic NPs like nano-C60 (or n-C60), for a setup that mimics a lung membrane at biologically relevant scales. The effect of curvature on n-C60 uptake, which is particularly striking when the membrane is in the gel phase, is explained in terms of lipid defects, and we find that uptake modulates the fluidity and defect characteristics of the resulting membrane in a state-dependent fashion, and will affect protein binding. Our discovery offers key functional insight in the role of the particular curvature and phase, i.e. a combination of a flat gel state and curved fluid state, that the lung membranes exhibits as a primary barrier. Membrane curvature ; Curvature ; Nano- ; Order (exchange) ; Nanotechnology ; Membrane ; Lipid bilayer ; Chemistry ; Biophysics ; Materials science ; Biochemistry ; Business ; Biology ; Mathematics ; Composite material Fullerene Chemistry and Applications
Authors: Ziping Wang | Fei Li | Yabin Sun | Yanling Shi | Xiaojin Li
Source: International Journal of Numerical Modelling Electronic Networks Devices and Fields (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Comprehensive Electrothermal Characterization Analysis for Scaled Nanochannels in Gate‐All‐Around Field‐Effect Transistors ABSTRACT Gate‐all‐around field‐effect transistors (GAAFETs) have garnered extensive research interest and industrial attention due to the higher gate control capability and remarkable scalability. However, as the nanochannel scales down, the phonon‐boundary scattering inside channels is dramatically strengthened, resulting in a significant decrease in phonon mean free path (MFP), which in turn leads to a decrease in thermal conductivity and deteriorates electrothermal characteristics. In this paper, to accurately evaluate the degradation of thermal conductivity for confined nanochannels, an analytical model is developed by revising the boundary‐induced reduction function related to both nanochannel width and thickness. The results show that the thermal conductivity calculated by the proposed model agrees well with the experimental data within 1% error over large temperature range for nanosheet and nanowire structures. Moreover, significant deviations of 6.11% in on‐state current and 41.7 K in temperature are observed between the proposed and conventional models for three‐stacked GAAFETs. The proposed revised methodology offers invaluable insights for assessing the electrothermal characteristics of nanodevices. Characterization (materials science) ; Materials science ; Field-effect transistor ; Field (mathematics) ; Transistor ; Optoelectronics ; Nanotechnology ; Electronic engineering ; Electrical engineering ; Engineering ; Voltage ; Mathematics Thermal properties of materials ; Advancements in Semiconductor Devices and Circuit Design ; Graphene research and applications
Authors: Emmanuel Agboeze | Vitus Anayo Ofordile | Henry Okechukwu Agboeze | Nwanneka Emiliann Ireh
Source: Research Square (preprint, 2025-10-28)
Field: Materials Science — Biomaterials

Structural Characterization and Life Cycle Assessment of Sustainable Biocomposites from Raphia farinifera Inflorescence Cellulose Cellulose ; Life-cycle assessment ; Biodegradation ; Thermogravimetric analysis ; Ultimate tensile strength ; Crystallinity ; Lignin ; Polymer ; Bioplastic Advanced Cellulose Research Studies ; Natural Fiber Reinforced Composites ; Polymer Science and PVC
Authors: Iman Tahmasbian | Negar Omidvar | Tony Charles | Shahla Hosseini Bai
Source: Food and Bioprocess Technology (article, 2025-09-23)
Field: Chemistry — Analytical Chemistry

Soft-Shell Prawns (Penaeus monodon) Can Be Identified Using Hyperspectral Imaging and Machine Learning – A Novel Approach to Ensure Consistency, Accuracy and Speed Abstract Soft-shell prawns (shrimps), which yield lower market value than their hard-shell counterparts, are currently identified through manual inspection—a subjective and inconsistent process. This study explores the use of shortwave infrared (SWIR; 950–2515 nm) hyperspectral imaging (HSI) combined with machine learning as a real-time, non-destructive alternative for classifying prawn shell hardness. A total of 380 farmed prawns spanning four manually assessed hardness categories were scanned using a HSI camera. Two classification models—support vector machine (SVM) and partial least squares discriminant analysis (PLS-DA)—were trained on 50% of the total samples (training data set) to associate spectral signatures with shell hardness classes and evaluated using the remaining 50% (independent test data set). PLS-DA marginally outperformed SVM in overall classification accuracy, achieving 92.1%, compared to SVM’s 90% on the independent test set. Although SVM showed better performance for intermediate hardness classes, its higher misclassification rate for the extreme classes (hard and soft) made it slightly less reliable for practical application. Reduced sensitivity in the intermediate classes across both models likely stems from limited sample size and subjectivity in the manual reference classifications. These results demonstrate the potential of HSI as a consistent and objective tool for prawn classification, offering significant advantages for automating shell hardness assessment and sorting. Implementing this technology could enhance processing efficiency and product quality within the prawn industry. Hyperspectral imaging ; Prawn ; Support vector machine ; Linear discriminant analysis ; Pattern recognition (psychology) ; Partial least squares regression ; Test data Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality ; Fish Biology and Ecology Studies
Authors: Sanja Gligic
Source:  (article, 2025-01-01)
Field: Chemistry — Physical and Theoretical Chemistry

Artificial Intelligence as a Tool for Efficient Implementation of the REACH Regulation in Serbia The REACH Regulation has introduced a fundamental shift in chemical governance by transferring the burden of proof from regulators to industry (business entities). This approach requires producers and importers to provide comprehensive evidence of chemical safety before substances are allowed on the EU market. While EU Member States have developed strong institutional and technical capacities to manage REACH obligations, candidate countries such as Serbia face significant structural and resource limitations. Artificial intelligence, as a rapidly evolving technology, offers solutions that can help bridge these gaps. AI can process large datasets, support predictive toxicology, and automate compliance monitoring, thereby improving efficiency and reducing costs. This paper examines the specific challenges Serbia faces in implementing REACH and evaluates the potential role of AI as an enabling tool in this process. Process (computing) ; Bridge (graph theory) ; Corporate governance ; Resource (disambiguation) ; Face (sociological concept) ; European union ; Resource efficiency History and advancements in chemistry ; Law, AI, and Intellectual Property ; Environmental Science and Water Management
Authors: Gabriel Pinto Cañón | María Victoria Alcázar Montero | Marina P. Arrieta Dillon
Source: Archivo Digital UPM (Universidad Politécnica de Madrid) (article, 2025-09-06)
Field: Materials Science — Materials Chemistry

Recent Advances and Future Directions in Thermal, Electrical, and Mechanical Properties of Polymer Composites Polymer composites continue to redefine the boundaries of what materials can achieve [...]. His paper serves as the editorial for the Special Issue “Advances in Thermal, Electrical and Mechanical Properties of Polymer Composites”, which presents a representative and forward-looking collection of 16 peer-reviewed articles. These contributions cover fundamental insights, modeling strategies, novel material systems, and application-oriented studies, highlighting how the design and processing of composites can be optimized to achieve multifunctionality and enhanced performance. Polymer ; Cover (algebra) ; Advanced composite materials ; Materials processing Thermal properties of materials ; Dielectric materials and actuators ; High voltage insulation and dielectric phenomena