jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Ayu Putri Ana | Dwi Retno Mulyanti | M Reza Alfikri | Mahran Mawarid
Source: Jurnal Penelitian Pendidikan IPA (article, 2026-01-31)
Field: Chemistry — Analytical Chemistry

Integration of Portable NIRS Spectroscopy with the Internet of Things (IoT) for a Rice Quality Monitoring System in Storage Warehouses Rapid and non-destructive monitoring of rice quality during storage is essential for supporting effective warehouse management. This study aims to develop and evaluate the integration of Portable Near-Infrared Spectroscopy (NIRS) with an Internet of Things (IoT) framework for real-time rice quality monitoring. A quantitative experimental approach was employed by acquiring NIRS spectra in the wavelength range of 740–1070 nm from fresh and aged rice samples. The spectral data were automatically transmitted via the IoT system to a centralized server for storage and analysis. Rice quality parameters, including moisture, fat, and protein content, were predicted using a Partial Least Squares Regression (PLS-R) model based on raw spectra without spectral pretreatment. The results indicate that the PLS-R model achieved good predictive performance for moisture and fat content, with validation correlation coefficients (R) ranging from 0.87 to 1.00 and Residual Predictive Deviation (RPD) values of 1.11–3.65 for moisture and 3.70–4.65 for fat in both fresh and aged rice samples. In contrast, protein prediction showed limited accuracy, particularly in fresh rice samples with an RPD value of 1.79. The IoT system primarily functioned as a real-time data acquisition and transmission platform, enabling integrated rice quality monitoring. Overall, the findings confirm that NIRS–IoT integration is feasible for monitoring rice quality based on moisture and fat content during storage. Warehouse ; Internet of Things ; Partial least squares regression ; Moisture ; Residual ; Quality (philosophy) ; Data acquisition ; Water content ; Correlation coefficient Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Remote Sensing in Agriculture
Authors: Ismael Sánchez-Gomar | Mercedes Cáceres-Medina | Cristina Cejudo-Bastante | Casimiro Mantell-Serrano | Lourdes Casas-Cardoso | Ma Carmen Durán-Ruiz
Source: Antioxidants (article, 2026-04-04)
Field: Materials Science — Polymers and Plastics

Functionalization of 3D Printed Polylactic Acid by Supercritical CO2 Impregnation with Mango Leaf Extract and Evaluation with Endothelial Colony-Forming Cells and Mesenchymal Stromal Cells Poly(lactic acid) (PLA) devices can be functionalized with plant-derived bioactives to introduce antioxidant activity while maintaining manufacturability and cytocompatibility. Here, a polyphenol-rich mango leaf extract (MLE) was obtained by enhanced solvent extraction and incorporated into PLA using supercritical carbon dioxide-assisted impregnation. Two manufacturing sequences were compared: impregnation after three-dimensional (3D) printing of discs and impregnation of filaments prior to printing. Extract yield and radical scavenging capacity were quantified, and impregnation efficiency was assessed as a function of pressure and temperature. Biological performance was evaluated using adipose tissue-derived endothelial colony-forming cells (ECFCs) and adipose tissue-derived mesenchymal stromal cells (MSCs), cultured separately and in co-culture on functionalized substrates. Impregnation after printing provided higher and more reproducible loading while preserving disc geometry, whereas impregnation before printing promoted swelling and printing-associated deformation that compromised structural fidelity. Cell-based analyses supported improved adhesion, spatial distribution, and proliferative status on discs produced by impregnation after printing under low-temperature and high-pressure conditions, without evidence of selective loss of either population in co-culture by flow cytometry. These results support post-print supercritical impregnation as a robust route to generate antioxidant, cell-supportive PLA scaffolds from agricultural by-products with potential relevance for vascular-oriented biomedical applications. Mesenchymal stem cell ; 3d printed ; Supercritical fluid ; Polylactic acid ; Supercritical carbon dioxide ; Adipose tissue ; Defatting ; Yield (engineering) ; Surface modification Polymer Foaming and Composites ; Additive Manufacturing and 3D Printing Technologies ; biodegradable polymer synthesis and properties
Authors: Timirâzevskaâ selʹskohozâjstvennaâ akademiâ | Belyakov M.V.
Source:  (article, 2026-01-01)
Field: Chemistry — Analytical Chemistry

Identification of soybean seed varieties by spectral luminescence method Optical spectral photoluminescent diagnostic methods, characterized by high speed and low implementation costs, can serve as an alternative to existing methods of varietal seed identification. The study aims to develop a methodology for identifying soybean seed varieties using a spectral luminescence method. The author used a diffraction spectrofluorimetric complex to measure the spectral excitation characteristics of photoluminescence in six soybean varieties: ultra-early maturing (Puma and Sayana), early maturing (Greya and Selena), and mid-maturing (Vilana and Vilana beta). Based on the obtained dependencies, he calculated integral and statistical parameters: integral absorptive capacity, mathematical expectation, variance, skewness, and kurtosis. The photoluminescence excitation characteristics of soybean seeds were found in the range between 330 and 475 nm, with primary peaks at 392 and 420 nm. For Gaussian decomposition, the spectra were converted to the frequency domain using the inverse Fourier transform. Based the research findings, the author selected the integral absorptive capacity in the range between 350 and 396 nm as the variety identification parameter. Skewness was recognized as the most effective statistical parameter for the unambiguous identification of three soybean varieties. Gaussian decomposition parameters – variance, skewness, and frequency-domain mathematical expectation – can be applied for the unique identification of all studied varieties. The methodology for identifying soybean seed varieties includes sample preparation, irradiation in the range between 330 and 475 nm, and registration of photoluminescent signals by a radiation receiver to obtain the U(λ) dependency and, based on it, calculate the varietal identification parameters: Gaussian amplitude and variance, frequency-domain mathematical expectation, integral absorptive capacity, and skewness. Narrow-spectrum LEDs and a broad-spectrum photodiode are used to implement the developed methodology. The characteristics of the U(λ) photo-signals help determine the varietal affiliation of the seeds. The results obtained can be used to develop a portable, high-speed variety control device for both laboratory and field conditions. Photoluminescence ; Gaussian ; Fourier transform ; Luminescence ; Kurtosis ; Skewness ; Photoluminescence excitation ; Range (aeronautics) ; Frequency domain Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Anonymous | Nan Gao | Qingjun Tong
Source: Physical review. B./Physical review. B (article, 2026-01-21)
Field: Materials Science — Materials Chemistry

Origin of moiré potentials in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mi>WS</mml:mi> <mml:mn>2</mml:mn> </mml:msub> <mml:mo>/</mml:mo> <mml:msub> <mml:mi>WSe</mml:mi> <mml:mn>2</mml:mn> </mml:msub> </mml:mrow> </mml:math> heterobilayers: Contributions from lattice reconstruction and interlayer charge transfer Moiré superlattices formed in WS$_2$/WSe$_2$ heterobilayers have emerged as an exciting platform to explore the quantum many-body physics. The key mechanism is the introduction of moiré potentials for the band-edge carriers induced by the lateral modulation of interlayer interactions. This trapping potential results in the formation of flat bands, which enhances the strong correlation effect. However, a full understanding of the origin of this intriguing potential remains elusive. In this paper, we present a comprehensive investigation of the origin of moiré potentials in both R-type and H-type moiré patterns formed in WS$_2$/WSe$_2$ heterobilayers. We show that both lattice reconstruction and interlayer charge transfer contribute significantly to the formation of moiré potentials. In particular, the lattice reconstruction induces a nonuniform local strain, which creates an energy modulation of 200 meV for the conduction band-edge state located at WS$_2$ layer and 20 meV for the valence band-edge state located at WSe$_2$ layer. In addition, the lattice reconstruction also introduces a piezopotential energy, whose amplitude ranges from 40 meV to 90 meV depending on the stacking and band-edge carrier. The interlayer charge transfer induces a built-in electric field, resulting in an energy modulation of 80 meV for an R-type moiré and 40 meV for an H-type moiré. Taking into account both effects from lattice reconstruction and interlayer charge transfer, the formation of moiré potential is well understood for both R-type and H-type moirés. This trapping potential localizes the wavefunctions of conduction and valence bands around the same moiré site for an R-type moiré, while around different moiré site for an H-type one. Trapping ; Stacking ; Lattice (music) ; Superlattice ; Valence (chemistry) ; Thermal conduction ; Charge carrier ; Wave function 2D Materials and Applications ; Chemical and Physical Properties of Materials ; Advanced Physical and Chemical Molecular Interactions
Authors: Jacqueline Marques da Silva Gondim | Elaine Silva de Pádua Melo | Moisés Centenaro | Marta Aratuza Pereira Ancel | Valter Aragão do Nascimento
Source: Sci (article, 2026-02-04)
Field: Chemistry — Analytical Chemistry

Elemental Composition of Ilex paraguariensis Grown in the Brazil–Paraguay Border Region The mineral composition of Ilex paraguariensis is strongly shaped by the physicochemical characteristics and natural fertility of the soils in which it is cultivated. This study evaluated macro- and microelement concentrations in fresh leaves from fourteen rural properties in Mato Grosso do Sul, Brazil, and examined how soil texture, pH, organic matter content, cation exchange capacity (CEC), and aluminum saturation influence nutrient availability and foliar accumulation. Soil, leaf, and environmental data were analyzed using ANOVA, intraclass correlation coefficients, Bayes factors, and principal component analysis (PCA). Sandy and dystrophic soils with low CEC and reduced organic matter showed greater variability in micronutrient retention and favored leaching, resulting in higher fluctuations in foliar Cu, Zn, and Mn. In contrast, clayey eutrophic soils with high CEC and higher organic matter promoted greater nutrient stability and more homogeneous foliar concentrations of K, Mg, and P. PCA confirmed that differences in soil geochemistry, particularly in Se, Cr, Mn, and Zn availability, were reflected in leaf composition. Chromium remained low in leaves despite elevated soil levels, indicating restricted uptake and translocation. Overall, the results demonstrate that edaphic conditions govern the nutritional profile of I. paraguariensis, emphasizing the need for region-specific soil management to maintain leaf quality in emerging cultivation areas. Edaphic ; Soil water ; Organic matter ; Nutrient ; Cation-exchange capacity ; Soil organic matter ; Soil fertility ; Soil pH ; Soil test Heavy Metals in Plants ; Clay minerals and soil interactions ; Amazonian Archaeology and Ethnohistory
Authors: Lakshmi Kanta Das, Debosree Ghosh, Suvendu Ghosh | Partha Sarathi Singha Sourav Das
Source: International Journal of Advanced Research in Science Communication and Technology (article, 2026-02-13)
Field: Chemistry — Organic Chemistry

A Mini Review on Triazine Derivatives as Anti-Cancer Drugs Though several drugs have been found to be effective in combating cancer to some extent yet, no such drugs have are yet commercially available for treating cancer. Hence the search for effective pharmaceutical formulation against the neoplastic cells continues. Triazines being highly versatile and having a stable structural configuration are a wonderful and popular choice for developing drugs against cancer. Because of their unique heterocyclic scaffold, ease of substitution and broad spectrum bioactive potentials, the triazine compounds are of interest for developing anti-cancer drugs. The electron-deficient 1,3,5-triazine core allows extensive modification of the chemical configuration. This helps to make potent triazine derivatives with enhanced efficacy, improved selectivity, increased potency and suitable pharmacokinetic properties. Studies reveal a good number of triazine-based molecules with potent and significant anticancer activity against a wide range of malignancies. Such triazine derivatives have been reported to be effective against lung, breast, colorectal, prostate and hematological cancers. This mini review summarizes recent advances in the design, structure–activity relationships and molecular mechanisms of triazine derivatives as anticancer agents, highlighting their therapeutic potential and future prospects in anticancer drug development. Triazine ; Drug ; Broad spectrum ; Small molecule ; Drug discovery ; Prostate cancer Synthesis and Characterization of Heterocyclic Compounds ; Synthesis and biological activity ; Enzyme function and inhibition
Authors: Yanru Wang | Yuling Li | Fangxu Wu | Demin Liu | Le Yuan | Mei Bi | Xiaolong Weng
Source: Journal of Applied Physics (article, 2026-01-08)
Field: Materials Science — Materials Chemistry

Density functional theory study on the formation mechanism and electronic properties of two-dimensional electron gas in LaInO3/BaSnO3 heterostructures with ferroelectric engineering Compared to the well-studied LaAlO3/SrTiO3 heterostructure (HS), the regulation mechanism of ferroelectric on the interfacial properties of LaInO3/BaSnO3 HS remains relatively unexplored. Here, we investigate the interfacial properties of the LaInO3/BaSnO3 HS models with the BaTiO3 ferroelectric film on different positions and with different ferroelectric polarization directions and intensities using first-principles density functional theory calculations. Our results reveal that the BaTiO3 film deposited on the top of LaInO3/BaSnO3 HS can significantly improve the interfacial electron density of the HS. Moreover, the ferroelectric polarization (electric field) direction and intensity of the upper BaTiO3 film play an important role in optimizing the interfacial electronic property of LaInO3/BaSnO3 HS. When the direction of the electric field in the BaTiO3 film is the same as that in the LaInO3 film, it provides an extra force to drive the electron transfer from the surface to the (LaO)+/(SnO2)0 interface. The largest interfacial charge density is 1.56 × 1014 cm−2 in BaTiO3(−0.005)/LaInO3/BaSnO3 HS. When the direction of the electric field in the BaTiO3 film is opposite to that in the LaInO3 film, the force from the LaInO3 film is counteracted by the BaTiO3 film, resulting in less electron transfer to the (LaO)+/(SnO2)0 interface. The interfacial charge density in BaTiO3(+0.005)/LaInO3/BaSnO3 HS is approximately one-tenth of that in BaTiO3(−0.005)/LaInO3/BaSnO3 HS. These findings provide new insights into ferroelectric-dependent interfacial phenomena and offer valuable guidance for designing functional perovskite oxide interfaces. Ferroelectricity ; Density functional theory ; Heterojunction ; Electric field ; Polarization (electrochemistry) ; Electron ; Electron density ; Perovskite (structure) Electronic and Structural Properties of Oxides ; Ferroelectric and Piezoelectric Materials ; Chemical and Physical Properties of Materials
Authors: Priyadharshini Kannusamy | D. Gayathri | S. Mirdula | B. Ramasubramanian | D. Manikandan | Krishnaraj Ramaswamy
Source: Scientific Reports (article, 2026-02-24)
Field: Materials Science — Surfaces, Coatings and Films

High-precision non-destructive blade surface inspection via self learning transformer networks Accurate identification of defects in Jet Engine Turbine and compressor blade surface plays a vital role in ensuring engine efficiency, safety and secure life. Traditional detection techniques were manual and consumed more time, error prone and need of specialized experts. To address these challenges, this work proposes an automated defect detection system using Swin Transformer Based Deep learning model. High resolution blade surface images were captured, pre-processed and augmented to improve robustness with varying surface condition. The novelty of the proposed work is that it adapts the Swin Transformer architecture to the specific challenges of turbine and compressor blade surfaces and it can detect micro-scale defects with high fidelity, by detecting both local and global features. Experimental results demonstrated that the proposed Swin transformer model produces high detection performance compared to the conventional CNN model with an accuracy of 98.4%, precision of 97.9%, recall of 98.7%, F1-score of 98.3% and mean Average Precision (mAP) of 97.6% on a dataset consisting of 172 high-resolution turbine and compressor blade images. The performance of the proposed method indicate that Swin Transformer model is an efficient tool for Non-Destructive Inspection of jet engine turbine and compressor blade surface which can be integrated into automated maintenance systems for better reliability and minimized operational risks. Gas compressor ; Jet engine ; Robustness (evolution) ; Transformer ; Encoder ; Turbine ; Turbine blade Optical Coatings and Gratings ; Advanced Measurement and Metrology Techniques ; Non-Destructive Testing Techniques
Authors: R. D. V. Ram Prasad | Grandhi Sri Kavya Sudha | Hema Nagalla | B. D. S. N. Ayyappa | Sadhanala Likhith Varma | B. Narasimha Rao
Source: International Journal of Science and Engineering Science Research (article, 2026-03-14)
Field: Chemistry — Inorganic Chemistry

An AI-Driven Advanced Decision Support System for Coconut Yield Prediction and Disease Detection The agricultural economy of India's coastal regions, especially Andhra Pradesh, depends heavily on coconut farming. Coconut farming, however, is extremely vulnerable to weather fluctuations, such as erratic rainfall patterns, pest infestations, and plant diseases, which have a substantial impact on crop output and farmers' earnings. Conventional agricultural methods frequently lack access to data-driven insights and predictive analytics, relying instead on manual observation and experience-based decision-making. The AI-Driven Coconut Farming Decision Support System (CFDSS) presented in this study uses predictive modeling and cognitive analytics to assist farmers and agricultural stakeholders. In order to produce region-specific insights at the district and mandal levels, the suggested approach combines several agricultural datasets, such as rainfall records, coconut yield statistics, pest risk information, and geographic boundary data. Rainfall prediction is done using a Long Short-Term Memory (LSTM) deep learning model, and yield estimation and pest risk classification are done using a Random Forest machine learning model. Python-based technologies including Streamlit, Pandas, NumPy, Plotly, and TensorFlow are used in the system's implementation to enable an interactive dashboard with visualization tools and AI-generated farming advisories. Furthermore, coconut plant problems are identified and preventive measures are suggested by an image-based disease detection module. The suggested method improves agricultural decision-making by offering precise predicted insights and practical suggestions, according to experimental evaluation. The promise of intelligent decision support systems in promoting precision agriculture and sustainable coconut farming is highlighted by the integration of artificial intelligence, geospatial analytics, and interactive visualization. Geospatial analysis ; Agriculture ; Decision support system ; Precision agriculture ; Geographic information system ; Decision tree ; Random forest ; Spatial decision support system Coconut Research and Applications ; Date Palm Research Studies ; Botany and Geology in Latin America and Caribbean
Authors: Satish Prajapati
Source: Research Square (preprint, 2026-04-10)
Field: Materials Science — Materials Chemistry

The Theorem of Topological Entropic Rigidity (TER): A Computational Theory for Thermo-Mechanical Response of Disordered Solids Scaling ; Entropy (arrow of time) ; Computation ; Shear modulus ; Topology (electrical circuits) ; Rigidity (electromagnetism) ; Torsion (gastropod) ; Computational complexity theory Material Dynamics and Properties ; Theoretical and Computational Physics ; Metallic Glasses and Amorphous Alloys
Authors: R. C. Lin | Weidong Sun | J.Y. Chen | Jia Zhang | Kangbo Zhao | Zelei Jiao | Haoning Liu | Jiawei Zhang | Pan Liu | Hong Wang
Source: Nano Research (article, 2026-02-01)
Field: Materials Science — Materials Chemistry

High-endurable memristors based on ReSe <sub>2</sub> /BST:YSZ ferroelectric heterojunctions for optical encryption communication Due to the increasing awareness of space security, encrypted space optic-communication have attracted significant attention. Consequently, ferroelectric memristors with efficient data processing capability and high operational stability become essential. However, inorganic perovskite materials such as Ba<sub>0.6</sub>Sr<sub>0.4</sub>TiO<sub>3</sub> (BST) typically respond only to near-ultraviolet light, exhibiting relatively weak photo-response currents. In this work, we introduce a Two-dimensional ReSe<sub>2</sub>/BST:YSZ [BST doped with (ZrO₂)<sub>0.92</sub>(Y₂O₃)<sub>0.08</sub>] hetero-memristor that demonstrates robust photoelectric capability. The heterostructure achieves visible-light perception through the ferroelectric modulation of ReSe<sub>2</sub> by BST:YSZ, resulting in an optical current switching of up to 50 μA. The device exhibits excellent endurance, maintaining stable optical switching over 30,000 cycles, and enables the simulation implementation of optical logic gates (AND, OR, XNOR, XOR and ODD checker) suitable for airborne information encryption and transmission. Moreover, the hetero-memristor emulates synapse-like regulation behaviors, including transitions between synaptic facilitation and depression under paired-pulse stimulation, and plasticity evolution from long-term potentiation (LTP) to long-term depression (LTD) under continuous stimulation. Based on these properties, an optical encryption communication system is demonstrated, achieving a recognition accuracy of up to 99.8%. This work provides a new approach toward integrating photovoltaic and ferroelectric functionalities for secure space communication applications. Ferroelectricity ; Heterojunction ; Encryption ; Perovskite (structure) ; Memristor ; Optical communication ; Secure communication 2D Materials and Applications ; Advanced Memory and Neural Computing ; Phase-change materials and chalcogenides