jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Michał Rogala | Agnieszka Kochmańska
Source: Metallurgical and Materials Transactions A (article, 2025-06-24)
Field: Materials Science — Materials Chemistry

The Influence of Cold-Forming Residual Stresses on Crashworthiness Efficiency of Thin-Walled Structures Abstract This study investigates the behavior of thin-walled column energy absorbers made from 6063-T6 alloy, incorporating spherical crush initiators. Such absorbers are widely used in automotive and aerospace applications due to their high energy absorption efficiency under axial impact. Experimental and numerical analyses revealed the presence of residual stresses resulting from the embossing process used to form the spherical triggers. Detailed examination of the embossed zones using X-ray diffractometer confirmed localized structural changes. To assess the effect of thermal stress relief, specimens were furnace annealed at four temperatures: 100 °C, 150 °C, 200 °C, and 250 °C. Subsequently, they were dynamically crushed using an Instron Ceast 9350 HES system. The crushing process was recorded with a Phantom Miro M310 high-speed camera to capture the real-time initiation and propagation of deformation. Comparative analysis of the structure, energy absorption indicators ( e.g. , peak crushing force, crush force efficiency), and failure modes demonstrated that annealing significantly influenced the crushing behavior. These findings emphasize the critical role of manufacturing parameters and thermal post-processing in the performance of thin-walled energy-absorbing structures. Crashworthiness ; Residual stress ; Cold forming ; Materials science ; Structural engineering ; Composite material ; Residual ; Finite element method ; Engineering ; Computer science High-Velocity Impact and Material Behavior ; Mechanical Behavior of Composites ; Cellular and Composite Structures
Authors: Jebel Haji Mahamud | Abebe Belay | Alemu Kebede Hordofa | Getachew Abebe Argaw | Tola Demiyo Ketebo | Tesfaye Feyisa Hurrisa | Umer Sherefedin
Source: Journal of Spectroscopy (article, 2025-01-01)
Field: Chemistry — Analytical Chemistry

Detection of Common Tomato Leaf Diseases Using Fluorescence Spectroscopy Technique Tomato leaf diseases pose significant challenges to the agricultural sector in Ethiopia, leading to substantial productivity losses. To address this issue, accurate disease detection and timely intervention are critical for effective management. In this study, we collected leaf samples from diverse growth conditions, including lighthouses and farm fields, at the Melkassa Agricultural Research Centre (MARC). In this research, the fluorescence spectrophotometer equipped with a xenon lamp as a source of light was employed for the detection of tomato leaf disease (bacterial leaf spot, powdery mildew, and early blight) based on unique fluorescence emission spectra characteristics. The fluorescence emission spectra were recorded at varying excitation wavelengths of 250, 350, 450, and 550 nm. The acquired emission spectra patterns served as distinct fingerprints, enabling the differentiation of healthy and diseased tomato leaf samples. The spectral properties of diseased tomato leaves show broadened, flattened, and low fluorescence intensity features. On the other hand, healthy leaves exhibit sharp and high fluorescence intensity. Principal component analysis (PCA) was employed to analyze the fluorescence emission spectra of healthy and diseased tomato leaves using the loading plots. PCA effectively distinguished between them, particularly at excitation wavelengths of 250 and 550 nm, achieving a classification accuracy of 90%. However, excitation wavelengths of 350 and 450 nm failed to accurately classify the tomato leaf samples using the first two principal components (PC1 and PC2). Fluorescence ; Excitation wavelength ; Wavelength ; Fluorescence spectroscopy ; Emission spectrum ; Principal component analysis Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Leaf Properties and Growth Measurement
Authors: Arjen M. Punt | Ruben E.A. Musson | Alwin D. R. Huitema | Kim C. M. van der Elst
Source: Pure and Applied Chemistry (article, 2025-12-20)
Field: Chemistry — Spectroscopy

The correct use of the term isobar for molecules Abstract In analytical chemistry literature, the term isobar is frequently used to describe small molecules with identical molecular formulas, often interchangeably used with isomer. This usage conflicts with the historical and International Union of Pure and Applied Chemistry (IUPAC) definition of isobar, which refers to nuclides of different elements with equal mass numbers but different proton-to-neutron ratios. In small-molecule LC-MS/MS analysis, this terminological overlap leads to confusion, particularly when distinguishing between compounds with identical exact masses (isomers) and those with different elemental compositions but nearly identical masses (molecular isobars). This article explores the origin and definitions of both terms and provides examples highlighting that the term isobar can be used for molecules but not for isomers, thereby emphasizing the importance of precise nomenclature for accurate molecular identification and interpretation in mass spectrometry. Isobar ; Term (time) ; Nuclide ; Chemical nomenclature ; Molecule Mass Spectrometry Techniques and Applications ; Pesticide Residue Analysis and Safety ; Forensic Fingerprint Detection Methods
Authors: Maico Lechner | Pierre Sabatier | Jesper V. Olsen
Source: Communications Chemistry (article, 2025-09-26)
Field: Chemistry — Spectroscopy

High-throughput proteome integral solubility alteration assay for low cell input using One-Tip Mass spectrometry-based versions of the cellular thermal shift assay (CETSA), like proteome integral solubility alteration (PISA), enable simultaneous monitoring of thousands of proteins for drug-target engagement. These methods are constrained in throughput and scalability, while the sample requirement limits the applicability to widely available material. Here, we combine PISA with the One-Tip method to simplify and streamline sample preparation. Using the mass spectrometry-compatible n-Dodecyl-β-D-Maltoside (DDM) non-ionic detergent for cell lysis in PISA sample preparation enables direct transfer to One-Tip with decreasing cell requirements down to 200 cells per µL. One-Tip provides similar depth and higher reproducibility, with lower material and solvent usage and a faster proteolytic digestion compared to a conventional sample cleaning and digestion protocol, making it a cost-effective, fast, and user-friendly option. To demonstrate its scalability, we applied One-Tip-PISA in a 96-well plate format, profiling a kinase inhibitor panel, allowing cell treatment to injection within 12 h, enhancing workflow efficiency and accessibility for a wide range of laboratories. Proteome ; Solubility ; Lysis ; Sample preparation ; Digestion (alchemy) ; Cell ; Throughput Advanced Proteomics Techniques and Applications ; Protein Degradation and Inhibitors ; Protein purification and stability
Authors: Fiorella Stagno | Angela Randazzo | G. Roccuzzo | Roberto Ciorba | Tiziana Amoriello | Roberto Ciccoritti
Source: Land (article, 2025-06-06)
Field: Chemistry — Analytical Chemistry

Assessment of Citrus Water Status Using Proximal Sensing: A Comparative Study of Spectral and Thermal Techniques Early detection of plant water status is crucial for efficient crop management. In this research, proximal sensing tools (i.e., hyperspectral imaging HSI and thermal IR camera) were used to monitor changes in spectral and thermal profiles of a citrus orchard in Sicily (Italy), managed under five irrigation systems. The irrigation systems differ in the amount of water distribution and allow four different strategies of deficit irrigation to be obtained. The physiological traits, stem water potential, net photosynthetic rate, stomatal conductance and the amount of leaf chlorophyll were measured over the crop’s growing season for each treatment. The proximal sensing data consisted of thermal and hyperspectral imagery acquired in June–September during the irrigation seasons 2023–2024 and 2024–2025. Significant variation in physiological traits was observed in relation to the different irrigation strategies, highlighting the highest plant water stress in July, in particular for the partial root-zone drying irrigation system. The water-use efficiency (WUE) values in subsurface drip irrigation were similar to the moderate deficit irrigation treatment and more efficient (up to 50%) as compared to control. Proximal sensing measures confirmed a different plant water status in relation to the five different irrigations strategies. Moreover, four spectral indices (Normalized Difference Vegetation Index NDVI; Water Index WI; Photochemical Reflectance Index PRI; Transformed Chlorophyll Absorption Ratio Index TCARI), calculated from HSI spectra, highlighted strong correlations with physiological traits, especially with stem water potential and the amount of leaf chlorophyll (coefficient of correlation ranged between −0.4 and −0.5). This study demonstrated the effectiveness of using proximal sensing tools in precision agriculture and ecosystem monitoring, helping to ensure optimal plant health and water use efficiency. Environmental science ; Thermal ; Remote sensing ; Geography ; Meteorology Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Water Quality Monitoring and Analysis
Authors: Abhishek Pathak | M. Saravanan | Pooja \ Srishti | Mary Praveena J | Mahesh Kurulekar | Madhur Taneja
Source: ShodhKosh Journal of Visual and Performing Arts (article, 2025-12-28)
Field: Materials Science — Materials Chemistry

PREDICTIVE ANALYTICS FOR FOLK ART MATERIAL REQUIREMENTS Predictive analytics is a more rational direction of converting material planning to the old folk art manufacturing systems. The use of experiential estimation tends to create shortages in materials, excessive stocking and unviable use of resources further enhanced by seasons and change in demand in the market. To overcome such difficulties, a hybrid forecasting model was created that would have incorporated ARIMA, XGBoost, and LSTM models to forecast the material demand information based on multi-source data, such as past production data, climate indices, and sightseeing event schedules. The ensemble approach is also successful in capturing both linear and nonlinear demand patterns with a high prediction accuracy (R 2 = 0.96) and minimal error in the forecasting process minimized by 14.5 percent relative to the best single model. Pilot tests in Madhubani, Pattachitra and Warli clusters revealed that the number of wastages in procurement was decreased by 22 percent and the Sustainability Efficiency Index (SEI) was also enhanced by 18 percent indicating improved alignment of the production and material availability. The cloud-based device-supported dashboard will help artisans and cooperatives decide in an informed and eco-friendly manner by supplying real-time visualisations and procurement advice, as well as sustainability analytics. The balance between the precision and cultural authenticity of technologies is one of the other gains of the framework, where predictive intelligence is not in conflict with traditional craftsmanship but is rather its complement. The incorporation of sustainability constraints into the optimization layer also makes the model more consistent with the principles of the circular economy and UN Sustainable Development Goals (SDG 12). All in all, the study provides a scalable and culture adaptable model that improves efficiency, heritage value and fosters environmentally friendly development of folk art ecosystems. Predictive analytics ; Sustainability ; Analytics ; Production (economics) ; Procurement ; Demand forecasting ; Supply chain ; Production planning Machine Learning in Materials Science ; Conservation Techniques and Studies ; Image Processing and 3D Reconstruction
Authors: Salman O. Alharbi | Hamdoon A. Mohammed | Lotfi M. Aroua
Source: JOURNAL of QASSIM UNIVERSITY FOR SCIENCE (article, 2025-12-26)
Field: Materials Science — Biomaterials

Anticancer Potential of <i>Calotropis procera</i> : A Contemporary Update Review Calotropis procera (Aiton) Dryand. is an herbal remedy that has been known for various traditional uses. Its diverse content of biologically potent compounds includes tannins, flavonoids, steroids, cardenolides, alkaloids, terpenoids, and enzymes. The rich composition has prompted extensive research on the antitumor properties against an array of malignant cell lines. The research outcomes reveal a promising potential in different cell lines. Multiple components of the shrub, including stems, roots, leaves, flowers, and aerial parts, showed anticancer properties against sarcoma 180, human colon cancer in both types HCT-8 and HCT-116, breast MDA-MB-435, breast MCF-7, brain SF-295, human leukemia HL-60, and ovarian OVCAR-8 malignant cell lines. Several anticancer compounds are present in the shrub, including calotoxin, calotropin, uscharin, calactoprocin, proceraside A, methyl ferulate, and frugoside. Both in vivo and in vitro studies have revealed marked cytotoxicity, in some cases comparable with the effect of standard anticancer drugs. Despite the claimed anticancer activity of the shrub, the toxicity of its extracts includes salivation, stomatitis, emesis, diarrhea, mydriasis, tetanic convulsions, collapse, and in some cases death. Therefore, thorough research to examine the toxic effects of the shrub and its extracts on humans is an essential step to guarantee that it is safe for humans and facilitate the process to develop anticancer drugs based on this important medicinal shrub. Moreover, the novel topic of nanoparticles derived from Calotropis procera is emerging with promising results and should be explored for use as anticancer drugs or as drug-delivery agents. Cancer ; Leukemia ; Toxicity ; Breast cancer ; Sarcoma ; Cell ; Human breast Phytochemistry and Bioactive Compounds ; Phytochemistry and Biological Activities ; Phytochemistry and Bioactivity Studies
Authors: Dharell B. Siano | Abigail Garcia Abuan | Carla I. Bautista
Source: International Journal of Latest Technology in Engineering Management & Applied Science (article, 2025-11-24)
Field: Chemistry — Analytical Chemistry

Detection of Free-Range Chicken Egg Freshness using a Portable Near-Infrared Spectrometer at Different Egg Orientations Abstract - Egg quality in terms of freshness for unfertilized free range chicken eggs was investigated in the study using a portable near-infrared spectrometer operating at 900 nm to 1700 nm. The egg freshness is commonly quantified based on the Haugh unit which is time consuming and destructive. Near-infrared spectroscopy can be used to assess the quality of eggs at the various stages of the supply chain. The portable near infrared spectrometer operating in reflectance mode was used to scan the egg sample in vertical and horizontal position. The result showed that the highest classification accuracy was from the free-range chicken egg obtained from the BPSU farm with a cross-validation accuracy of 68.20% and a test accuracy of 63.60 %. Position 1 (vertical) gives the highest accuracy and it is attributed to the changes in air cell height during ageing which affects the spectral data obtained from the egg samples. The spectra were pretreated using Savitzky Golay 1st derivative with a smoothing point =7 and analyzed using stepwise discriminant analysis. The result showed the potential of the portable near infrared spectrometer to predict the freshness of free-range chicken egg real time. It can be implemented in online grading and can be a nondestructive technique for detecting egg freshness. Spectrometer ; Near infrared reflectance spectroscopy ; Analytical Chemistry (journal) ; Reflectivity ; Near-infrared spectroscopy ; Infrared Spectroscopy and Chemometric Analyses ; Animal Nutrition and Physiology ; Biopolymer Synthesis and Applications
Authors: Sepehr Behrouzifar | Iman Mirafzal | Fazel Mehraein | Amir Shamloo
Source:  (article, 2025-10-20)
Field: Materials Science — Biomaterials

AI-GUIDED MAGNETIC NANOPARTICLE TARGETING IN ABDOMINAL AORTIC FLOW Abdominal aortic aneurysm ; Nanoparticle ; Magnetic nanoparticles ; Flow (mathematics) ; Magnetic resonance imaging Nanoparticle-Based Drug Delivery ; Aortic aneurysm repair treatments ; Micro and Nano Robotics
Authors: Hakan Güney | Serdal SIRLIBAŞ | Bülent SARI | Mert Güney
Source: Agricultural and Food Technologies (article, 2025-12-31)
Field: Materials Science — Polymers and Plastics

Sustainability Assessment of Natural Fibers Used in the Textile Industry: A Literature Review The textile industry uses natural or synthetic fibers, or both, as raw materials. Global climate change affects the production potential of natural fibers by increasing pressure on air, soil, and water resources. Consequently, the production of these fibers, which the sector requires, faces significant sustainability challenges. This literature review comparatively examines the natural fibers commonly used in the textile sector cotton, jute, flax, and wool, based on environmental, economic, and social sustainability criteria. Each fiber's production process was evaluated, along with factors such as water consumption, chemical input requirements, carbon and water footprints, biodegradability, soil health impacts, and production conditions. The findings indicate that the sustainability performance of fibers varies significantly depending on fiber type, production method, and geographical conditions. This review aims to assess the impact of natural fibers on sustainable fashion and circular textile systems and to provide guidance for future research and industrial applications. Sustainability ; Textile ; Production (economics) ; Natural (archaeology) ; Textile industry ; Raw material ; Sustainable production ; Process (computing) Natural Fiber Reinforced Composites ; Dyeing and Modifying Textile Fibers ; Textile materials and evaluations
Authors: Salvatore Angelo Cancemi | Rosa Lo Frano | M. Angelucci | Andrea Pucciarelli | F. Subba | H. Wu
Source: Journal of Physics Conference Series (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

HPC modelling for nuclear safety assessment Abstract High Performance Computing (HPC) has taken on an increasingly important role in recent years since it enables to model efficiently the complex behaviour of Systems, Components, and Structures (SSCs) and their interactions, and to perform simulations of the operational scenarios faster. Particularly in the nuclear field, HPC is currently used and expected to be utilized in nearly all areas, such as design optimization, safe and long-term safe operation, integrity evaluation, etc. The latter, as an example, requires an exhaustive SSCs assessment, which in turn requires higherfidelity models, both in terms of resolution and physics, increased knowledge of the physics of the phenomena or mechanisms affecting them, parametric studies, and better estimation of margins by reducing uncertainties and optimising operations. In this paper some case studies are presented and described. The first case consists in the modelling of creep behaviour of a fuel element. Finite Element Modelling (FEM) on hardware designed for parallel computation allows to simulate increasingly complex physical systems and reduce the computation time of the performed transient non-linear analyses. Results point out on the reliable prediction of creep behaviour obtained with a surrogate model. Understanding the thermo-mechanical properties of structural and nuclear materials and their changes provided essential for the plant safe operation as well as the Uncertainty Quantification (UQ). The second case deals with a thermal-hydraulics application in support of Generation IV (GEN IV) Liquid Metal Fast Reactors (LMFRs). Results from RANS calculations will be compared with experimental data for a selected steady-state condition occurring in a rod-bundle geometry. UQ analyses are especially performed using deterministic sampling techniques to assess how much the results are affected by uncertainties in the input parameters. Nuclear engineering ; Computer science ; Reliability engineering ; Engineering Graphite, nuclear technology, radiation studies ; Nuclear and radioactivity studies ; Nuclear reactor physics and engineering
Authors: Damián Rodríguez‐Trujillo | Alicia E. Torres‐García | Mikel Aldea | Jorge Teniente | Asier Marzo‐Pérez | Miguel Beruete
Source: Advanced Optical Materials (article, 2025-11-08)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Phase Smoothing for Mutual Coupling Mitigation in Multifunctional Metasurfaces Designed with Diffractive Neural Networks Abstract Multifunctional metasurfaces hold great promise for next‐generation communication systems, enabling spectral efficiency, dynamic adaptability, and hardware scalability for performing multiple wavefront manipulation tasks. However, traditional designs often neglect critical near‐field interactions, leading to performance degradation in complex aperiodic configurations. In this work, an AI‐driven design model is presented for a single‐layer, passive, transmission‐mode multifunctional metasurface capable of projecting different holographic patterns at 86 GHz (W‐band) through spatial multiplexing of the input excitation. The approach integrates a diffractive neural network with an optimization algorithm and a phase‐smoothing regularization scheme to mitigate mutual coupling between unit cells. The proposed model refines the phase profile to balance target performance and physical constraints, enhancing the validity of the local periodicity approximation. The experimental results closely match the simulations, validating the proposed method. This work demonstrates that an AI‐driven model, enhanced by physical regularization, offers a scalable and efficient path toward high‐performance multifunctional metasurfaces, enabling dynamic‐like functionalities without active components—crucial for next‐generation wireless communication systems. Scalability ; Wavefront ; Artificial neural network ; Multiplexing ; Holography ; Aperiodic graph ; Coupling (piping) ; Wireless ; Smoothing Metamaterials and Metasurfaces Applications ; Advanced Wireless Communication Technologies ; Advanced Antenna and Metasurface Technologies
Authors: Anna Gliszczyńska‐Świgło | Dorota Klensporf-Pawlik
Source: Scientific Journal of Gdynia Maritime University (article, 2025-01-01)
Field: Chemistry — Organic Chemistry

A PRACTICAL APPROACH TO ASSESS THE OXIDATIVE STABILITY OF COSMETIC BUTTERS: QUALITY CONTROL PERSPECTIVE Oxidative stability is an important parameter determining the quality of fat products. The oxidation time (OT) of cosmetic butters measured using RapidOxy can be predicted using simple equations based on unsaturated fatty acid / saturated fatty acid content (UFA/SFA), calculated oxidizability (CoxV) and calculated iodine values (CIV). This predictive capability increases the efficiency of the quality control processes for these products. Similar predictive relationships also exist for other fat-based products, such as oils. This simple but innovative approach to assessing the oxidative stability of fats is quick, eliminates chemical reagents and minimizes waste production, making it both cost-effective and environmentally friendly. It is in line with the idea of green chemistry and sustainable development, making it the preferred technique in modern chemical analytics. Quality (philosophy) ; Oxidative phosphorylation ; Simple (philosophy) ; Stability (learning theory) ; Model predictive control ; Control (management) ; Reagent ; Fatty acid Edible Oils Quality and Analysis ; Food Chemistry and Fat Analysis ; Antioxidant Activity and Oxidative Stress