jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Victor Ziapkoff | François Boulogne | Anniina Salonen | Emmanuelle Rio
Source: ArXiv.org (preprint, 2025-11-26)
Field: Materials Science — Materials Chemistry

White light interferometry analysis for measuring thin film thickness down to few nanometers We present a practical white-light interferometric method, supported by an open-source Python library \textit{optifik} for automated spectrum-to-thickness deduction, enabling foam film measurements down to a few nanometers. We describe three typical spectral scenarii encountered in this method: spectra exhibiting numerous interference fringes, spectra with a moderate number of peaks, and spectra with only a few identifiable features, providing illustrative examples for each case. We also discuss the main limitations of the technique, including spectral range constraints, the necessity of knowing the refractive index, and the influence of spectral resolution and signal quality. Finally, we demonstrate the application of the method in a time-resolved study of a TTAB (tetradecyltrimethylammonium bromide) foam film undergoing elongation and thinning. This method can be adapted to measure any thin non-opaque layer. Interferometry ; Thin film ; White light interferometry ; Spectral line ; White light ; Nanometre ; Spectral resolution ; Resolution (logic) Material Dynamics and Properties ; Optical Polarization and Ellipsometry ; Spectroscopy and Quantum Chemical Studies
Authors: Seham Ebrahim
Source: The Visual Computer (article, 2025-12-24)
Field: Materials Science — Materials Chemistry

Using transfer learning to determine the type of mathematical fractals image of Islamic geometric patterns Abstract Islamic geometric patterns (IGPs) are one of the most elegant forms of art that reflect the Islamic cultural and religious heritage. These patterns are characterized by their complexity and precision. Which makes them a source of inspiration for the design of decorations in light of technological progress. Geometric patterns have never been distinguished before using deep Learning. This data is the first to be used and classified. The research includes classifying IGP into 8 classes Arabesque, Tessellation, Euclidean tiling by convex regular polygons, Koch snowflake, logarithmic spiral, Mandelbrot set, Pythagorean Fractal Tree, Sierpinski Triangles using Transfer Learning. Six deep Learning modes are used VGG19, Mobilenetv2, inception_resnet_v2, xception, NASNetLarge, and Rasnet v2. Adjusting the initialized performance parameters for all model to be able to compare between them. The evaluated performance parameters are training accuracy and loss, evaluation accuracy and loss, precision, recall, confusion matrix, and F1 score. Rasnetv2 gives the higher accuracy, F1 score at small size data. Fractal ; Geometric pattern ; Computer graphics ; Euclidean geometry ; Logarithm ; Image (mathematics) ; Type (biology) ; Pattern recognition (psychology) ; Regular polygon ; Transfer of learning ; Golden ratio Quasicrystal Structures and Properties ; Aesthetic Perception and Analysis ; Architecture and Cultural Influences
Authors: Antonio Formisano | Dario De Fazio | Giuseppe Irace | Massimo Durante
Source: Preprints.org (preprint, 2025-05-20)
Field: Materials Science — Polymers and Plastics

Incremental Forming of Natural Fiber-Reinforced Polypropylene Composites: Considerations on Formability Limits and Energy Consumption Incremental sheet forming originated as an excellent alternative to conventional forming techniques for incrementally deforming flat metal sheets into complex three-dimensional profiles. Recently, its use has been extended to polymers and composites. Among these, the use of natural fiber-reinforced composites is increasing rapidly compared to synthetic fiber-reinforced composites, due to the availability and unique properties of natural fibers in polymer applications. One of the dominant thermoplastics used as a matrix is polypropylene. This experimental study focuses on the incremental forming of natural fiber-reinforced polypropylene composites. Cones and spherical caps were manufactured from composite laminates of polypropylene reinforced with hemp and flax long-fiber fabrics. The formability limits, observed through failures and defects, as well as the forming forces, power, and energy consumption, were investigated to examine the feasibility of incremental forming applied to these composite materials. Formability ; Composite material ; Materials science ; Polypropylene ; Fiber ; Natural fiber ; Energy consumption ; Engineering Natural Fiber Reinforced Composites ; Innovations in Concrete and Construction Materials
Authors: Roman Shendrik | Е. А. Раджабов | Alexandra Myasnikova | Viktorija Pankratova | Anatolijs Šarakovskis | A. I. Nepomnyashchikh | Alexander Bogdanov | Veronika Gavrilenko | Екатерина Канева | Dmitry Sofich | Tatiana Garmysheva | Vladimir Pankratov
Source: Research Square (preprint, 2025-04-15)
Field: Materials Science — Materials Chemistry

Ultrafast core-to-core luminescence in BaF 2 -LaF 3 single crystals Core (optical fiber) ; Luminescence ; Ultrashort pulse ; Materials science ; Optoelectronics ; Optics ; Physics ; Laser ; Composite material Luminescence Properties of Advanced Materials ; Inorganic Fluorides and Related Compounds
Authors: 罗芷昕 Luo Zhixin | 张蕾萍 Zhang Leiping | 石高军 Shi Gaojun | 廉哲 Lian Zhe | 朱世元 Zhu Shiyuan | 卢亮 Lu Liang | 仲利静 Zhong Lijing | 刘浩田 Liu Haotian
Source: Laser & Optoelectronics Progress (article, 2025-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

5款便携式拉曼光谱仪的检测性能对比研究 对比了法庭科学领域中5款便携式拉曼光谱仪（PRS）的检测性能。通过对5款PRS的深入剖析，并与1款台式拉曼光谱仪（BRS）进行对比，揭示5款PRS的性能和功能优势及其局限性。研究结果显示，这5款PRS在各项关键指标上展现出显著的质量差异：产品B、C的综合质量最优异，产品B的输出速度较慢，产品C的光谱分辨率不足；产品A在硬件参数上表现良好；产品D、E相较同类产品仍需进一步优化仪器性能条件；BRS光谱分辨率最优，但PRS在本研究的分析方向中实用性更高。本研究不仅为法庭科学领域相关PRS产品的质量监督工作提供了参考思路，协助相关部门明确产品的筛查方向从而实现成本控制与效益的最大化，还为未来相关产品的优化和升级指明了方向。 Computer science Gold and Silver Nanoparticles Synthesis and Applications ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Mathieu Leroy | Astrid Avellan | Morgan Légnani | Emmanuel Flahaut | Camille Larue
Source: Colloids and Surfaces A Physicochemical and Engineering Aspects (article, 2025-12-22)
Field: Materials Science — Materials Chemistry

Unravelling the physicochemical drivers of heavy metal adsorption on carbonaceous nanomaterials: Implications for the environmental fate of contaminants in mixtures Adsorption ; Environmental remediation ; Metal ; Organic matter ; Limiting ; Contamination ; Kinetics ; Sorption Nanoparticles: synthesis and applications ; Environmental remediation with nanomaterials ; Heavy metals in environment
Authors: Juan Felipe Huan Lew-Yee | Ion Mitxelena | Jorge M. del Campo | and Mario Piris
Source: ArXiv.org (preprint, 2025-12-15)
Field: Materials Science — Electronic, Optical and Magnetic Materials

DoNOF 2.0: A modern Open-Source Electronic Structure Program for Natural Orbital Functionals In this work, we present the second version of the Donostia Natural Orbital Functional Software, an open-source program for natural orbital functional calculations. The new release incorporates improved optimization algorithms, capabilities for excited-state computations, support for ab initio molecular dynamics, and integration with the libcint library. DoNOF 2.0 also extends its property toolbox by enabling the evaluation of nonlinear optical responses, including static polarizabilities and higher-order hyperpolarizabilities via a finite-field Romberg-Richardson scheme. Program Summary [Title: DoNOF; Developer's repository link: http://github.com/DoNOF/; Program's Manual link: https://donof.readthedocs.io/; Licensing provisions: GPLv3; Programming language: Fortran; additional implementations available in Python (PyNOF) and Julia (DoNOF.jl); Multinode capability: Support for distributed execution through a hybrid OpenMPI and OpenMP implementation] Toolbox ; Python (programming language) ; Ab initio ; Electronic structure ; Property (philosophy) ; Nonlinear system ; Fragment molecular orbital ; Density functional theory Nonlinear Optical Materials Research ; Molecular spectroscopy and chirality ; Spectroscopy and Quantum Chemical Studies
Authors: Laura Gargiulo | Assunta Napolitano | Sabrina Maria Marsala | Anna Di Salle | Giacomo Mele
Source: Food Science & Nutrition (article, 2025-08-31)
Field: Chemistry — Analytical Chemistry

Olive Variety Classification and Prediction From <scp>3D</scp> Morphology of Fruit and Stone: A Study Case on Five South Italy Autochthone Cultivars Accurate olive cultivar identification is critical for ensuring quality control and traceability in the olive oil industry. The International Olive Council (IOC) and the International Union for the Protection of New Varieties of Plants (UPOV) have established standardized protocols for varietal characterization. Over the past two decades, two-dimensional image analysis techniques have been increasingly employed for olive variety identification, utilizing various morphological parameters and machine learning approaches. This study investigates olive varietal classification through three-dimensional morphological analysis of fruits and stones using X-ray microtomography. The research evaluates the discriminative power of different trait combinations using both Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) algorithms to contribute to an optimized protocol for cultivar identification. Five autochthonous olive cultivars from the Campania region (Southern Italy) were analyzed. A preliminary comparison of classification performance between continuous and discrete morphological olive data revealed superior effectiveness of the continuous ones. Integrating quantitative morphometric traits with selected visual discrete UPOV characteristics yielded optimal overall classification accuracy of 88.41% using LDA with 84.4% for Ravece, 81.5% for Ortice, 100% for Frantoio, 81.3% for Rotondella, and 90.9% for Minucciola olive varieties. The best variety prediction rates, based on an olive sample not used for training, were provided by SVM, obtaining 70.0% for Ravece, 87.5% for Ortice, 54.5% for Frantoio, 60.0% for Rotondella, and 66.7% for Minucciola. Quantification of varietal overlap through Bhattacharyya coefficients identified Ortice and Ravece as the most phenotypically similar varieties, while Rotondella and Minucciola exhibited the most distinctive fruit morphology. Notably, all varieties showed at least one misclassification with the Frantoio variety. Morphological analysis demonstrated that endocarp surface traits provided the most discriminative power, and internal cavity characteristics also contributed significantly to varietal differentiation. These findings suggest two key implications: potential updates of UPOV guidelines for distinctness evaluation protocols and promising applications in authenticity verification for high-quality olive products. Cultivar ; Linear discriminant analysis ; Support vector machine ; Identification (biology) ; Discriminative model ; Biology ; Artificial intelligence ; Horticulture ; Mathematics ; Botany ; Computer science Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Identification and Quantification in Food
Authors: Gaofeng Cao | Hongnan Hu | Qiang Zhan | Tianwei Zhang | Yingbo Wang | Shiang Zhang | Lixue Zhu
Source: Sensors (article, 2025-12-13)
Field: Chemistry — Analytical Chemistry

A Preliminary Study of Hyperspectral Imaging Combined with Dual-Threshold Segmentation Technique for Peeling Rate Determination in Potatoes Peeling is essential in potato processing, yet conventional assessment methods face issues like inefficiency and environmental concerns. This study proposed a hyperspectral imaging approach combined with dual-threshold segmentation to quantify potato peeling rates. This method was in the preliminary research stage. The objectives of this work were to experimentally validate the feasibility and accuracy of this method. A hyperspectral system captured images of potatoes after water-jet peeling. By analyzing spectral data from peel and flesh regions and applying principal component analysis, the key wavelength of 592 ± 20 nm was identified, where the reflectance difference between flesh and peel was most pronounced. Grayscale images derived from this band were processed via median filtering and dual-threshold segmentation to differentiate flesh from peel. The peeling rate was calculated as the pixel ratio of flesh to total potato area. In validation tests, the calculated peeling rates showed an average absolute error of 0.69% compared to manual measurement, confirming the potential and feasibility of this technique. The proposed method offers a promising, non-destructive, and eco-friendly alternative for monitoring peeling quality in agricultural processing, though further research is warranted. Hyperspectral imaging ; Segmentation ; Principal component analysis ; Grayscale ; Flesh ; Pixel ; Pattern recognition (psychology) Spectroscopy and Chemometric Analyses ; Potato Plant Research ; Smart Agriculture and AI
Authors: César Francisco Piscoya Briones | GIÚLIA TORRES SILVEIRA | Alan Gomes Câmara | CELMY MARIA BEZERRA DE MENEZES BARBOSA | José Geraldo De Andrade Pacheco
Source:  (article, 2025-07-21)
Field: Chemistry — Inorganic Chemistry

APRIMORAMENTO DA PERFORMANCE FOTOCATALITICA DO TIO2 VIA HETEROJUNÇÃO COM G-C3N4 NA DEGRADAÇÃO DO CORANTE TEXTIL RB5 Class (philosophy) ; Raw material ; Process (computing) Pigment Synthesis and Properties
Authors: Phanendra Kumar Attada | Rishi Raj | Dineshkumar Harursampath | Sathiskumar A. Ponnusami
Source: Composites Science and Technology (article, 2025-07-05)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Integrated experimental and computational approach to analyse and design multiphase nanocomposites for broadband reflection loss This study presents an integrated experimental and computational methodology for analysing multiphase composites with ceramic (BaTiO 3 , CoFe 2 O 4 ) inclusions and carbon-based inclusions (MWCNTs) aimed at broadband electromagnetic (EM) reflection loss (RL) applications. Characterisation techniques (SEM, TGA, and X-ray 3-D tomography) were employed to analyse the nanocomposite. Fabricated nanocomposites were tested using a two-port VNA, and the EM properties of the composites were derived using the Nicolson-Ross-Weir (NRW) algorithm. An in-house optimisation tool is used to extract the EM properties of individual nanoparticles and later validate them using the experimental results. The RL spectrum in the frequency range is attained using the in-house Transfer Matrix Method (TMM)-based tool, which is validated using the scattering parameters obtained from the two-port VNA. Later, parametric studies are carried out using the validated in-house tools by varying the influencing parameters. Results have shown that composites with high BaTiO 3 or MWCNT contents exhibited impedance mismatches, leading to immediate EM reflection upon interaction with the nanocomposite surface. In contrast, CoFe 2 O 4 -dominant composites achieved broadband RL ( < -10 dB) over a bandwidth of 4.4 GHz across different thicknesses even at higher loading due to improved impedance matching. Incident transverse magnetic (TM) polarised EM waves provided broadband RL up to 80° incidence. In contrast, transverse electric (TE) polarised EM waves showed broadband RL at angles up to 40° due to different field interactions. The proposed generalised approach offers a versatile framework for designing nanocomposites tailored for specific broadband or frequency-selective RL applications. Materials science ; Nanocomposite ; Broadband ; Reflection (computer programming) ; Composite material ; Reflection loss ; Engineering physics ; Optics ; Composite number ; Computer science ; Engineering ; Physics Electromagnetic wave absorption materials ; Dielectric materials and actuators ; Polymer Nanocomposite Synthesis and Irradiation
Authors: Challa Ravi Teja | Imdadul Hoque Mondal | Kshirod Kumar Dash | Himanshu Bana | Ayaz Mukarram Shaikh | Béla Kovács
Source: Journal of Food Processing and Preservation (article, 2025-01-01)
Field: Materials Science — Biomaterials

Development and Characterization of Banana Starch– and Guava Peel Extract–Based Sustainable Packaging Films In order to compensate the use of plastics, biodegradable starch–based polymer films have been introduced. Banana starch is considered suitable for use in food packaging applications, implying that films made from banana starch can be used directly for the packaging of various food products without causing any health hazards. This study focuses on development of a biodegradable film using banana starch incorporated with guava leaf extract. Guava leaf extract serves as an antimicrobial agent to the formulation. Thereby, banana starch–based film can display antimicrobial properties, which could potentially prolong the shelf life of perishable food items by preventing microbial spoilage. The film was analyzed for solubility, water absorption capacity, water vapor transfer rate, total polyphenol, moisture content, and antimicrobial activity for varied starch (2%–6%), guava leaf extract (1%–3%), and glycerol (10%–25%) concentrations. The analysis affirmed the optimum combinations as 2.28% starch, 1.37% guava leaf extract, and 15.26% glycerol. Corresponding response variables such as thickness, solubility, water absorption capacity, total polyphenol, zone of inhibition against Escherichia coli , and moisture content achieved were 0.081 mm, 42.35%, 50.66%, 31.92 mg gallic acid equivalent (GAE)/g, 7.12 mm, and 7.94%, respectively. In summary, antimicrobial banana starch–based packaging film presents a promising alternative for food packaging on commercial basis. Further, this would cause minimum environmental impact and help in food preservation. Starch ; Food science ; Characterization (materials science) ; Food packaging ; Chemistry ; Business ; Horticulture ; Materials science ; Biology ; Nanotechnology Nanocomposite Films for Food Packaging ; Postharvest Quality and Shelf Life Management ; Agricultural and Food Sciences
Authors: Fränze Müller | Karel Stejskal | Karl Mechtler
Source: Research Square (preprint, 2025-07-30)
Field: Chemistry — Spectroscopy

Breaking Barriers in Crosslinking Mass Spectrometry: Enhanced Throughput and Sensitivity with the Orbitrap Astral Mass Analyzer Orbitrap ; Mass spectrometry ; Spectrum analyzer ; Sensitivity (control systems) ; Throughput ; Chemistry ; Analytical Chemistry (journal) ; Chromatography ; Computer science ; Engineering ; Telecommunications Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Mohmad Mujtaba Nabi Chadroo | Gurvinder Singh
Source:  (article, 2025-06-20)
Field: Chemistry — Analytical Chemistry

ENHANCING RICE QUALITY PREDICTION USING A HYBRID DEEP LEARNING MODEL WITH EXPLAINABLE AI TECHNIQUES This research explores the use of a hybrid deep model in rice quality prediction using Explainable AI methods like SHAP and Grad-CAM.The model is compared with ResNet50, VGG16, CNN, and MobileNetV2 based on Kaggle's dataset, which includes images of rice grains and their physical and biochemical properties.Experiment results confirm that the hybrid architecture outperforms other architectures on critical performance measures with the best accuracy (0.95) compared to ResNet50 (0.92) over VGG16 and CNN, which are not good.Sensitivity analysis also confirms the high true positive rate of the hybrid model with the least false negatives, while CNN has the poorest sensitivity.In terms of specificity, the suggested model performs the best via the accurate identification of negative cases alongside minimizing false positives.F1-score analysis testifies to its strength in the trade-off between recall and precision concerning existing architectures.It enhances the classification accuracy and extraction of features based on multiple means of learning and thus makes for more reliable prediction.The Computer science ; Artificial intelligence ; Deep learning ; Quality (philosophy) ; Machine learning Spectroscopy and Chemometric Analyses
Authors: Javeria Zaheer
Source: Journal of American Medical Science and Research. (article, 2025-04-20)
Field: Materials Science — Biomaterials

Nanotechnology in Stroke Management: From Neuroprotection to Post-Stroke Recovery Background: Stroke is a major global health burden, representing one of the leading causes of death and long-term disability. Current therapeutic strategies are limited by narrow treatment windows, poor drug penetration across the blood–brain barrier (BBB), and insufficient support for neuroregeneration. Objective: This review aims to evaluate the role of nanotechnology in stroke management, focusing on its potential in enhancing neuroprotection, promoting post-stroke recovery, and overcoming existing therapeutic limitations. Approach: A comprehensive analysis of recent literature was conducted, emphasizing the application of various nanomaterials—lipid-based, polymeric, metallic, and hybrid nanoparticles—in stroke therapy. Their mechanisms of action, including targeted drug delivery, thrombolysis, BBB penetration, anti-inflammatory effects, and neural repair, are critically reviewed. Discussion: Nanotechnology enables precise, site-specific delivery of therapeutic agents, facilitates real-time imaging, and supports tissue regeneration through multifunctional platforms. Several preclinical studies have demonstrated improved outcomes in stroke models using nanoformulations. Emerging clinical trials further validate their translational potential. Conclusion: Nanotechnology offers a transformative approach in stroke care, addressing both acute intervention and long-term rehabilitation. However, challenges related to safety, scalability, and regulatory approval must be resolved to enable clinical adoption. Future research should focus on multifunctional, biocompatible, and targeted nanoplatforms for integrated stroke management. Neuroprotection ; Stroke (engine) ; Medicine ; Nanotechnology ; Materials science ; Pharmacology ; Engineering ; Mechanical engineering Nanoparticle-Based Drug Delivery ; Advanced Nanomaterials in Catalysis ; Conducting polymers and applications
Authors: Manuel Antonio Cardoza Sernaqué | Víctor Alejandro García Farías | Rafael Arturo Alba Callacná | Liz Maribel García Salirrosas | Cristian Raymound Gutiérrez Ulloa | María Félix Sánchez Villavicencio | Yudy Lisbeht Alfaro Zavaleta
Source:  (article, 2025-01-01)
Field: Chemistry — Physical and Theoretical Chemistry

Teaching Chemistry: A Comprehensive Analysis of Virtual Simulators as Pedagogical Tools The objective of this research is to design a laboratory program (LP) for Energy Engineering students at a public university in Ancash. The methodology used is a qualitative, propositional approach, based on the development of sessions under the Problem-Based Learning (PBL) model. This approach is based on diverse epistemologies such as constructionism, complexity epistemology, critical rationalism, pragmatism, and experiential knowledge. The LP is structured in four main phases: planning, execution, evaluation, and formative feedback, which guide the teaching-learning process. Furthermore, the laboratory strategy is developed through five didactic moments: Experiment: Application of the topic using prior knowledge and appropriate materials and instrumentation. Problematize: Reflect on students' prior ideas to define the problem and the problematic situation to be addressed. Analyze: Identification of the problem variables, decomposition, and establishment of relationships for their generalization. Discussion: Analysis of the results obtained in the previous phase, encouraging the exchange of ideas and solutions. Achievement: Explanation of the observed phenomenon, consolidating the knowledge acquired through problem-solving. This program is designed to foster critical, reflective, and collaborative skills in the training of future engineering professionals. Visualization ; Key (lock) ; Virtual reality ; Work (physics) Various Chemistry Research Topics ; Science Education and Pedagogy ; Innovative Teaching Methods