jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Qiufang Dai | Ying Huang | Zhen Li | Shilei Lyu | Xiuyun Xue | Shuran Song | Shiyao Liang | Jiyang Fu | Shaoyu Zhang
Source: Agriculture (article, 2025-08-31)
Field: Chemistry — Analytical Chemistry

Field-Based, Non-Destructive and Rapid Detection of Citrus Leaf Physiological and Pathological Conditions Using a Handheld Spectrometer and ASTransformer Citrus diseases severely impact fruit yield and quality. To facilitate in-field, non-destructive, and rapid detection of citrus leaf physiological and pathological conditions, this study proposes a classification method for citrus leaf physiological and pathological statuses that integrates visible/near-infrared multispectral technology with deep learning. First, a handheld spectrometer was employed to acquire spectral images of five sample categories—Healthy, Huanglongbing, Yellow Vein Disease, Magnesium Deficiency and Manganese Deficiency. Mean spectral data were extracted from regions of interest within the 350–2500 nm wavelength range, and various preprocessing techniques were evaluated. The Standard Normal Variate (SNV) transformation, which demonstrated optimal performance, was selected for data preprocessing. Next, we innovatively introduced an adaptive spectral positional encoding mechanism into the Transformer framework. A lightweight, learnable network dynamically optimizes positional biases, yielding the ASTransformer (Adaptive Spectral Transformer) model, which more effectively captures complex dependencies among spectral features and identifies critical wavelength bands, thereby significantly enhancing the model’s adaptive representation of discriminative bands. Finally, the preprocessed spectra were fed into three deep learning architectures (1D-CNN, 1D-ResNet, and ASTransformer) for comparative evaluation. The results indicate that ASTransformer achieves the best classification performance: an overall accuracy of 97.7%, underscoring its excellent global classification capability; a Macro Average of 97.5%, reflecting balanced performance across categories; a Weighted Average of 97.8%, indicating superior performance in classes with larger sample sizes; an average precision of 97.5%, demonstrating high predictive accuracy; an average recall of 97.7%, showing effective detection of most affected samples; and an average F1-score of 97.6%, confirming a well-balanced trade-off between precision and recall. Furthermore, interpretability analysis via Integrated Gradients quantitatively assesses the contribution of each wavelength to the classification decisions. These findings validate the feasibility of combining a handheld spectrometer with the ASTransformer model for effective citrus leaf physiological and pathological detection, enabling efficient classification and feature visualization, and offer a valuable reference for disease detection of physiological and pathological conditions in other fruit crops. Spectrometer ; Mobile device ; Environmental science ; Materials science ; Remote sensing ; Optics ; Computer science ; Physics ; Geography Spectroscopy and Chemometric Analyses ; Potato Plant Research ; Banana Cultivation and Research
Authors: H. Omar | Nestor Ankah | Mohamed S. Gomaa | Malak Y. Alkhaldi | Nadir M. A. Osman | Abdullah Al‐Subaie | Ibrahim Aldossary | Irshad Baig | Ashraf A. Bahraq | Marwah Aljohani | Ihsan‐ul‐Haq Toor | Aeshah H. Alamri
Source: Materials (article, 2025-06-19)
Field: Materials Science — Materials Chemistry

Towards a Sustainable Material Protection: Olanzapine Drugs and Their Derivatives as Corrosion Inhibitors for C1018 Steel in 1 M Hydrochloric Acid This study investigates the synthesis process and characterization methods and evaluates the inhibition behavior of olanzapine (2-methyl-4-(4-methyl-1-piperazinyl)-10H-thieno-[2,3-b] 1,5]benzodiazepine (OLZ)) and its derivatives, such as 3-(2-methyl-4-(4-methylpiperazin-1-yl)-10H-benzo[b]thieno[2,3-e] [1,4]diazepin-10-yl) propenamide (OLZ1) and Ethyl 2-(2-methyl-4-(4-methylpiperazin-1-yl)-10H-benzo[b]thieno[2,3-e][1,4]diazepin-10 yl) acetate (OLZ2) for carbon steel (C1018) in a 1 M HCl acidic solution. Fourier Transform Infrared Spectroscopy (FTIR) and Nuclear Magnetic Resonance (NMR) were employed to verify their molecular structures and functional groups, which characterized the derivatives after synthesis. Their corrosion inhibition potential for C1018 steel in acidic media was estimated by weight loss (WL) and electrochemical techniques, such as electrochemical impedance spectroscopy (EIS), linear polarization resistance (LPR), and potentiodynamic polarization (PDP), accompanied by surface analysis methods. The findings revealed that all three derivatives demonstrated exceptional inhibition performance, achieving maximum efficiencies of 88.83%, 91.20%, and 91.82% for OLZ, OLZ1, and OLZ2 at 300 ppm, respectively. Weight loss experiments across different temperatures further explored their inhibitory behavior. Although inhibition efficiency decreased with a temperature increase to 318 K, the derivatives still displayed notable performance, with maximum efficiencies of 74.75% for OLZ, 81.63% for OLZ1, and 79.44% for OLZ2. Polarization studies identified the corrosion inhibition mechanisms as an anodic type. Surface characterization of the C1018 steel coupons, both with and without the inhibitors, was performed using FTIR and scanning electron microscopy (SEM) combined with energy-dispersive X-ray spectroscopy (EDX). These analyses indicated the creation of a protective inhibitor layer on the carbon steel surface, reducing corrosion in the acidic environment. Overall, this study underscores the potential of these drug derivatives as corrosion inhibitors, combining structural insights and performance assessments to support their industrial application. Corrosion ; Hydrochloric acid ; Dielectric spectroscopy ; Electrochemistry ; Nuclear chemistry ; Methyl orange ; Fourier transform infrared spectroscopy ; Carbon steel ; Polarization (electrochemistry) ; Materials science ; Chemistry ; Organic chemistry ; Metallurgy ; Electrode ; Catalysis ; Chemical engineering ; Physical chemistry Corrosion Behavior and Inhibition ; Concrete Corrosion and Durability ; Electrochemical Analysis and Applications
Authors: R. K. S. Tomar | M. Sinhamahapatra | Pradip Kumar Sharma
Source: Journal of Advances in Biology & Biotechnology (article, 2025-04-02)
Field: Materials Science — Biomaterials

Recent Progress and Emerging Trends of Antimicrobial Edible Food Packaging Recent advancements in antimicrobial edible food packaging have revolutionized food safety and sustainability. With growing consumer awareness, there is an increasing demand for ecofriendly packaging materials that prevent microbial contamination, foodborne illnesses, and spoilage. To address this concern, scientists have developed novel edible packaging materials infused with antimicrobial agents. These innovations aim to extend shelf life while reducing reliance on non-biodegradable plastics. Natural antimicrobial applications play a key role in these developments. The incorporation of essential oils, antimicrobial peptides, and plant extracts into biopolymers such as polysaccharides and proteins has garnered significant attention for their potential in antimicrobial edible films. Additionally, nanotechnology has enhanced the mechanical properties and antimicrobial efficacy of these biopolymers. Future applications of these materials may be customized for specific food products, with improved sensory attributes through the integration of various flavors and aromas. Production processes are also expected to scale up for commercial viability. A promising emerging trend is the integration of smart technology with antimicrobial edible films, enabling real-time monitoring of product quality through freshness indicators, including microbiological contamination. Furthermore, future research should focus on developing fully biodegradable films through nanotechnology-driven advancements. These innovations would not only reduce environmental impact but also shape the future of the packaging industry while meeting the evolving demands of modern consumers. Antimicrobial ; Biotechnology ; Food packaging ; Food science ; Business ; Biology ; Microbiology Nanocomposite Films for Food Packaging
Authors: Nuno Calheiros-Lobo | Manuel Au‐Yong‐Oliveira | José Vasconcelos Ferreira
Source: Information (article, 2025-07-25)
Field: Materials Science — Materials Chemistry

DEEPEIA: Conceptualizing a Generative Deep Learning Foreign Market Recommender for SMEs This study introduces the concept of DEEPEIA, a novel deep learning (DL) platform designed to recommend the optimal export market, and its ideal foreign champion, for any product or service offered by a small and medium-sized enterprise (SME). Drawing on expertise in SME internationalization and leveraging recent advances in generative artificial intelligence (AI), this research addresses key challenges faced by SMEs in global expansion. A systematic review of existing platforms was conducted to identify current gaps and inform the conceptualization of an advanced generative DL recommender system. The Discussion section proposes the conceptual framework for such a decision optimizer within the context of contemporary technological advancements and actionable insights. The conclusion outlines future research directions, practical implementation strategies, and expected obstacles. By mapping the current landscape and presenting an original forecasting tool, this work advances the field of AI-enabled SME internationalization while still acknowledging that more empirical validation remains a necessary next step. Generative grammar ; Recommender system ; Deep learning ; Computer science ; Generative model ; Artificial intelligence ; Business ; Knowledge management ; Data science ; Machine learning Machine Learning in Materials Science ; Big Data and Business Intelligence
Authors: H. Shoba | Swati Jain | N. L. Panwar | S. S. Lakhawat | Deepak Rajpurohit | Naveen Jain
Source: Discover Food (article, 2025-11-03)
Field: Materials Science — Biomaterials

A review on sources of biopolymers, antimicrobial agents, and biodegradable packaging Biopolymer-based antimicrobial packaging integrates renewable polymers such as polylactic acid (PLA), chitosan, cellulose, and protein-based matrices with active agents including essential oils, plant extracts, bacteriocins, and metallic nanoparticles to inhibit microbial proliferation, preserve food quality, and extend shelf life. Recent advances (2023–2025) emphasize migration-controlled and non-migratory delivery systems, nanoencapsulation, and electrospinning to enhance antimicrobial stability, release kinetics, and compatibility with diverse food matrices. Comparative studies demonstrate that polymer–antimicrobial compatibility, food surface characteristics, and storage conditions critically influence preservation efficacy. Applications span perishable commodities such as dairy, meat, seafood, and fresh produce, with reported reductions of > 90% in Listeria monocytogenes, Escherichia coli, and Staphylococcus aureus populations under optimized formulations. This review consolidates recent developments in material design, antimicrobial mechanism elucidation, and sustainability assessment, highlighting synergistic interactions between active agents, biopolymer matrices, and targeted food systems. Future research priorities include multifunctional systems integrating antimicrobial, antioxidant, and smart sensing capabilities, as well as regulatory harmonization to accelerate commercialization. Antimicrobial ; Listeria monocytogenes ; Polylactic acid ; Food packaging ; Food preservation ; Biopolymer ; Food industry ; Active packaging Nanocomposite Films for Food Packaging ; Antimicrobial agents and applications ; Microbial Inactivation Methods
Authors: Franck W. Boyom‐Tatchemo | François Devred | Elie Acayanka | Georges Kamgang‐Youbi | Samuel Laminsi | Éric M. Gaigneaux
Source: Catalysts (article, 2025-05-05)
Field: Materials Science — Materials Chemistry

Gliding Arc Plasma Synthesis of MnO2 Nanomaterials for Catalytic Oxidation of Benzene: Effect of Plasmagenic Gas MnO2 nanostructures were successfully synthesized via the reduction of KMnO4 solutions using the gliding arc plasma (Plasma Glidarc) approach. Here, we highlight the effect of different plasmagenic gases, such as moist air (atmospheric air), dry air, nitrogen (N2) or oxygen (O2). The obtained materials were characterized by X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), nitrogen physisorption and scanning electron microscopy (SEM). The crystalline structures of obtained MnO2 polymorphs are mainly γ-MnO2 and α-MnO2, regardless of the feeding gas. The main reactive species, in addition to nitrogenous species like NO· radical generated with moist air, dry air or N2 gas, other oxygenated species such as H2O2 (E°(O2/H2O2) = 0.69 V) are produced with O2 able to reduce KMnO4 solution (E°(KMnO4/MnO2) = 1.70 V). Helium gas did not allow for the plasma reduction of the KMnO4 solution, even after 60 min of exposure. Furthermore, gas humidification did not significantly affect the precipitation time or the properties of plasma-synthesized MnO2. Atmospheric humidified air appears to be the best plasmagenic gas, as it allows for a shorter synthesis time and leads to a large specific surface area. All plasma-synthesized MnO2 showed good activity during the catalytic oxidation of benzene. The use of different MnO2 polymorphs (α-, δ- and γ-MnO2) showed that, in addition to the specific surface area, the crystalline structure significantly affects the catalytic oxidation of benzene. K+ species inserted within the MnO2 structure allow for their stability during the catalytic process. This work highlights the possibility to use different plasmagenic gases to prepare MnO2 nanostructures through plasma glidarc for the catalytic oxidation of benzene. Benzene ; Catalysis ; Nanomaterials ; Chemistry ; Materials science ; Chemical engineering ; Nanotechnology ; Organic chemistry ; Engineering Catalytic Processes in Materials Science ; Plasma Applications and Diagnostics ; Electrocatalysts for Energy Conversion
Authors: C. S. Pai | Hung‐Chung Hsueh | Shu-Han Hsu
Source: Machine Learning Science and Technology (article, 2025-09-23)
Field: Materials Science — Surfaces, Coatings and Films

Reliability of deep learning models for scanning electron microscopy analysis Abstract Scanning electron microscopy (SEM) provides high-resolution nanoscale imaging crucial for advanced materials characterization. Recent advancements in deep learning have significantly enhanced SEM analysis by automating the identification of nanoscale features. However, the reliability of these models remains insufficiently explored. We investigate two popular deep learning architectures, ResNet-50 and Swin Transformer, by systematically injecting faults into their weight parameters for SEM characterization. Our analysis demonstrates how performance degrades under varying fault scenarios, and also pinpoints which layers and bit positions exhibit heightened vulnerability. These findings provide insights for dependable, high-throughput automated materials characterization, thereby paving the way for more reliable deployment of SEM-based deep learning in industrial and research environments. Deep learning ; Reliability (semiconductor) ; Nanoscopic scale ; Software deployment ; Scanning electron microscope ; Microscopy ; Fault (geology) Electron and X-Ray Spectroscopy Techniques
Authors: Wenqing Zhou | Qian Xiao | Yanyang Yin | Xiaodong Liu | Licheng Li | Gang Liu
Source: High Voltage (article, 2025-04-01)
Field: Materials Science — Materials Chemistry

Repair of defects in buffer layer of high voltage cable based on additive liquid silicone rubber material Abstract In recent years, the issue of defects in the buffer layers of high‐voltage cables has garnered significant attention due to their widespread occurrence and the substantial potential damages they pose. Although progress has been made in understanding the mechanisms behind these defects and in developing detection methods, effective repair solutions remain limited. This study addresses this challenge by proposing a novel repair material: a two‐component, additive liquid silicone rubber‐based compound that utilises vinyl silicone oil as its base. The electrical, thermal, and mechanical properties of the cured silicone‐based repair fluid are thoroughly analysed. To evaluate its effectiveness, an experimental platform was constructed using a 17‐m‐long, 110 kV retired cable with known buffer layer defects. A specialised injection process was developed to facilitate the application of the repair fluid. The thermal characteristics, buffer layer voltage distribution, and partial discharge behaviour of the defective cable were analysed both before and after the repair. The results indicate that following the repair, the cable's heat dissipation capacity under full load increased by 6.25%. Additionally, the buffer layer voltage at the rated voltage ( U 0 ) decreased from 1.97 to 0.34 V, representing an 82.74% reduction. Notably, no partial discharge signals exceeding background noise were detected post‐repair. This study demonstrates the effectiveness of the addition‐cure liquid silicone rubber‐based semi‐conductive material in repairing cable buffer layer defects and provides valuable experimental support for its practical application in engineering. Silicone rubber ; Buffer (optical fiber) ; Materials science ; Composite material ; Layer (electronics) ; Silicone ; High voltage ; Voltage ; Electrical engineering ; Engineering High voltage insulation and dielectric phenomena ; Epoxy Resin Curing Processes ; Polymer Nanocomposites and Properties
Authors: Samuel Holden | Zhezi Zhang | Jianting Lin | Yuanyuan Zhang | Fangqin Cheng | Junzhi Wu | Dongke Zhang
Source: International Journal of Energy for a Clean Environment (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

AN EXPERIMENTAL INVESTIGATION INTO AMMONIA COMBUSTION AND NOx EMISSION IN A FLUIDIZED-BED REACTOR Ammonia (NH&lt;sub&gt;3&lt;/sub&gt;) combustion and NOx emission in a fluidized-bed reactor with quartz particles (size fraction 295 &amp;mu;m-354 &amp;mu;m) as the bed material has been experimentally studied over a range of furnace set temperatures (900 K-1300 K), equivalence ratios (&amp;phi; &amp;#61; 0.6, 0.7, 0.8, 0.9, 1.0, 1.1), and fluidization numbers (1, 3, 5, 7, 9). NH&lt;sub&gt;3&lt;/sub&gt; oxidation commenced at &amp;#126; 900 K and complete NH&lt;sub&gt;3&lt;/sub&gt; conversion was achieved at 1250 K-1300 K. Greater NH&lt;sub&gt;3&lt;/sub&gt; conversion was generally achieved at lower equivalence ratios. IIncreasing fluidization number led to more sharply increasing NH&lt;sub&gt;3&lt;/sub&gt; conversion with increasing furnace set temperature, as well as complete NH&lt;sub&gt;3&lt;/sub&gt; consumption at lower furnace set temperatures. The measured axial temperature profiles of the reactor indicated that increasing fluidization number resulted in the combustion moving from the bed surface into and through the emulsion phase towards the distributor of the fluidized-bed. Under all experimental conditions tested, NO emission was negligible at furnace set temperatures &amp;#60; 1250 K, experienced a maximum at 1250 K, and declined thereafter with increasing furnace set temperature. Increasingly fuel-lean conditions resulted in increasing NO emission, while fuel-rich conditions returned far lower or negligible NO concentrations. Experiments conducted at higher fluidization numbers resulted in increasing NO emissions compared to those conducted at lower fluidization numbers. Overall, fluidized-bed NH&lt;sub&gt;3&lt;/sub&gt; combustion is a new and innovative concept which has been identified as a technology that may be suitable for carbon-free large-scale power generation applications. The present study reports original work that facilitates future research which may be aimed at investigating the influence of fluidization regime, particle size, type of bed material, flame behavior, fuel handing, fuel injection, etc., while also being able to assist in engineering scale-up and industrial design of a fluidized-bed NH&lt;sub&gt;3&lt;/sub&gt; combustor. NOx ; Combustion ; Waste management ; Environmental science ; Ammonia ; Nuclear engineering ; Chemistry ; Engineering Catalytic Processes in Materials Science
Authors: Du Dongyuan | Yanpeng Hao | Yunhua He
Source: Polymers (article, 2025-05-22)
Field: Materials Science — Materials Chemistry

High Frequency Electric-Field-Assisted Preparation of BN/Epoxy Resin Composites with Excellent Electrical, Thermal, and Mechanical Properties Since epoxy resin has excellent mechanical and insulating qualities, it is frequently utilized in dry transformers. Low thermal conductivity, however, has prevented it from be developed further in high-frequency and large-capacity dry transformers. This study describes the preparation of sheet boron nitride (BN)/epoxy resin composites with superior electrical, thermal, and mechanical properties through the application of varying strengths of high-frequency alternating-current (AC) electric fields. Using an optical microscope, the orienting process of BN in epoxy resin under an electric field was studied. In parallel, tests were conducted on the BN/epoxy resin composites made with varying electric field strengths. The findings indicate that the preparation using a high-frequency AC electric field decreases BN agglomeration and improves the composite's properties. The overall performance is comparatively ideal when the applied electric field strength is 30 V/mm, the tensile strength is 48.3 MPa, the breakdown field strength is 37.65 kV/mm, and the thermal conductivity of the BN/epoxy resin composite is 0.95 W/(m·K). The thermal conductivity greatly increased and BN was organized into chains when the electric field approached 60 V/mm. The tensile strength and breakdown field strength, on the other hand, declined. Epoxy ; Materials science ; Composite material ; Ultimate tensile strength ; Boron nitride ; Electric field ; Composite number ; Field strength ; Electrical resistivity and conductivity ; Thermal conductivity ; Magnetic field ; Electrical engineering High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Carbon Nanotubes in Composites
Authors: Srinivasa Kishore K | V. K.
Source: Revue des composites et des matériaux avancés (article, 2025-06-30)
Field: Materials Science — Polymers and Plastics

Optimal Fiber Selection for Automobile Roof Top Application Using a Multi Criteria Decision-Making Framework Selection (genetic algorithm) ; Roof ; Computer science ; Fiber ; Operations research ; Engineering ; Structural engineering ; Machine learning ; Materials science ; Composite material Textile materials and evaluations