jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Muhammad Alwi Husaini
Source: IRA Jurnal Teknik Mesin dan Aplikasinya (IRAJTMA) (article, 2025-12-30)
Field: Materials Science — Materials Chemistry

Pengaruh Variasi Arus Dan Jenis Elektroda RB-26 Terhadap Kekuatan Tarik Sambungan Las SMAW Pada Baja AISI 1060 Penelitian ini dilakukan untuk menganalisis pengaruh variasi arus pengelasan dan jenis elektroda terhadap kekuatan tarik sambungan las SMAW pada baja karbon tinggi AISI 1060. Metode eksperimental kuantitatif diterapkan di Laboratorium Politeknik Negeri Medan dan Laboratorium Universitas Al-Azhar Medan. Baja AISI 1060 dengan ketebalan 8 mm dan kandungan karbon 0,60-0,70% dilas menggunakan elektroda RB-26 dengan variasi arus 80A, 90A, dan 100A. Pengujian tarik dilakukan sesuai standar ASTM E8/E8M untuk mengukur kekuatan tarik ultimate (UTS), tegangan luluh, dan perpanjangan spesimen. Hasil penelitian menunjukkan bahwa performa mekanis terbaik diperoleh pada arus pengelasan 100A dengan UTS 338,58 N/mm², tegangan luluh 117,77 N/mm², dan perpanjangan 5,42%. Sebaliknya, UTS terendah sebesar 123,4 N/mm² dan perpanjangan 4,47% dihasilkan pada arus 80A akibat input panas yang tidak mencukupi. Peningkatan kekuatan tarik ditemukan sejalan dengan peningkatan arus pengelasan hingga batas optimal, namun perubahan struktur mikro yang merugikan dapat disebabkan oleh arus berlebihan. Disimpulkan bahwa pemilihan parameter arus pengelasan yang tepat sangat penting untuk memperoleh sambungan las berkualitas tinggi pada baja AISI 1060, dengan arus 100A direkomendasikan sebagai parameter optimal. Analytical Chemistry (journal) ; Atomic force microscopy ; Ultimate tensile strength ; Chromium Material Selection and Properties ; Silicon Carbide Semiconductor Technologies ; Geotechnical and construction materials studies
Authors: Rohit Malhotra
Source: International Journal of Science and Research (IJSR) (article, 2025-05-13)
Field: Materials Science — Polymers and Plastics

Coccinia Grandis Natural Composite Fibers in Industrial Engineering With using Artificial Intelligence: Report Testing Analysis The study on Coccinia Grandis as a natural fiber source breathes fresh life into the sustainable materials discourse. Rather than relying solely on synthetic reinforcements, this research opens up the possibility of harnessing an underutilized plant species to fabricate eco -friendly composites. The meticulous fiber extraction methods ranging from retting to chemical treatment are matched by a robust framework of mechanical testing, ensuring that performance isn't sacrificed in the pursuit of sustainability. What truly stands out, however, is the seamless integration of Industrial Engineering tools and Artificial Intelligence. This isn't just a case of crunching numbers it's about drawing meaningful connections between fiber properties, processing parameters, and real -world applications. It is evident that AI's role extends beyond prediction, offering a nuanced lens for pattern recognition and design optimization that traditional methods often miss. That said, challenges in fabrication consistency and environmental exposure remain areas ripe for further exploration. This suggests that while Coccinia Grandis fiber composites may not yet replace conventional materials, they are certainly carving a promising path toward scalable and green industrial solutions. Composite number ; Engineering ; Materials science ; Composite material Natural Fiber Reinforced Composites ; Machine Learning in Materials Science ; Mechanical Behavior of Composites
Authors: HULISSES BONETI MARCON | Elioenai Levi Barbedo | Kokanov Sa | Lucas Moreira Ferreira | Patrícia Capellato | Gilbert Silva
Source: Preprints.org (preprint, 2025-01-20)
Field: Materials Science — Materials Chemistry

Microstructural Investigation and Mechanical Characterization of β-Type Ti-15Mo-13Nb, Ti-15Mo-16Nb, and Ti-15Mo-19Nb Alloys After Heat Treatment With increasing longevity in many countries, the demand for prostheses to replace damaged hard tissue is growing. In recent years, efforts have focused on developing new titanium (Ti) alloys with a lower Young’s modulus, closer to that of human bone (30 GPa), given the average cost of $32,933 for prosthesis replacement procedures. While such alloys already exist, metastable β-Ti alloys have drawn attention due to their excellent combination of good strength, biocompatibility, and the abundance of titanium in the Earth’s crust. A better understanding of their properties and behavior, such as structure and element interaction, could create more efficient and long-lasting materials. To address this demand, this study aims to develop Ti-15Mo-yNb alloys (13, 15, and 19 at%) through arc melting, heat treatment, forging, and quenching. The alloys were analyzed using XRD, SEM, EDS, and mechanical testing. The β-Ti and α”-Ti phases were found, with Vickers hardness values ranging from 290 HV to 392 HV and Young’s modulus between 66 GPa and 75 GPa. The results show that higher Nb content helps form the α”-Ti phase at grain boundaries and improves the mechanical properties of the β-Ti matrix alloys. Materials science ; Metallurgy Titanium Alloys Microstructure and Properties ; Intermetallics and Advanced Alloy Properties ; Surface Treatment and Coatings
Authors: V. Sahithi Yellanki
Source: International Journal of Environmental Sciences (article, 2025-09-27)
Field: Chemistry — Analytical Chemistry

Grain Quality Testing Using Neural Networks Grain quality plays a crucial role in agriculture, affecting health, economic efficiency, and market pricing. Traditional manual testing methods are often slow, inconsistent, and labour-intensive. This project presents an automated system that leverages image processing and machine learning to transform grain quality assessment and price estimation, offering direct benefits to farmers and stakeholders throughout the supply chain. High-resolution images of grains, captured under controlled lighting conditions, are processed to extract essential features such as size, color, shape, and texture. These are the key features for identifying grain types and evaluating quality metrics like moisture content, protein levels, and impurities. The system utilizes a Multilayer Perceptron (MLP) as its final model for classification and analysis. Trained on extensive datasets of labelled images, the MLP ensures precise grain classification, impurity detection, and quality evaluation. Furthermore, it estimates grain prices based on these quality metrics, enabling farmers to receive fair compensation for their produce and make informed decisions regarding market timing and quality enhancement. By automating grain testing and pricing, this non-destructive approach eliminates human error, preserves grain integrity, and offers a reliable, efficient, and scalable solution. Farmers benefit from quicker quality assessments, enhanced pricing transparency, and reduced reliance on manual testing, empowering them to optimize productivity and profitability in a competitive market. Profitability index ; Quality (philosophy) ; Multilayer perceptron ; Artificial neural network ; Scalability ; Key (lock) ; Productivity Spectroscopy and Chemometric Analyses ; Mineral Processing and Grinding
Authors: Philippe Brunet | Adrian Daerr | Laurent Limat | Benoît Scheid
Source: The European Physical Journal Special Topics (article, 2025-05-15)
Field: Materials Science — Surfaces, Coatings and Films

Recent advances in wetting, drying and coating processes Wetting ; Coating ; Materials science ; Environmental science ; Nanotechnology ; Composite material Surface Modification and Superhydrophobicity ; Adhesion, Friction, and Surface Interactions
Authors: Roya Boodaghi Malidarre
Source: Multidisciplinary Materials Chronicles. (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

The effect of TeO2, ZnO, and NiO ratios in enhancing the radiation shielding, structural, and mechanical features of the provided glass sample This paper focuses on the radiation shielding, structural, and mechanical properties of the Te glass system using the FLUKA Monte Carlo (MC) environment and Phy-X: PSD software. In this work, three selected glass specimens with the formula of TeO2+ZnO+xNiO, where x=4,8 and 12 mol.%, NiO have been used. This study assessed the key radiation metrics such as Half Value Layer (HVL) and Effective Atomic Number (Zeff) for wide energy ranges. The results show a clear relationship between increased NiO concentration and gamma photon shielding performance in the provided specimens. Furthermore, micro-Hardness (H) and poisson’s ratio σ have been improved. Moreover, findings reveal that increasing the density gives rise to the Vt, while the inverse trend is mirrored in Gt values. The outcomes of the present work are suitable for future studies related to the novel Te glass series. The findings highlight the effectiveness of Te-enriched glass specimens in terms of radiation shielding. Radiation shielding ; Electromagnetic shielding ; Materials science ; Sample (material) ; Non-blocking I/O ; Radiation ; Composite material ; Optics ; Chemistry ; Physics Radiation Shielding Materials Analysis ; Glass properties and applications ; Nuclear materials and radiation effects
Authors: Peng Li | Huaming Liu | Defang Liu | Liguo Han | Chuanzong Li
Source: Chemosensors (article, 2025-11-19)
Field: Chemistry — Analytical Chemistry

Geographical Origin Identification of Rhizoma Atractylodis macrocephalae Using Hyperspectral Imaging Combined with Broad Learning System and SHapley Additive exPlanations Rhizoma Atractylodis macrocephalae (RAM) is a renowned food–medicine homologous herb in China, the quality and efficacy of which are inherently linked to its geographical origin. However, traditional origin identification methods for RAM are time-consuming, laborious, and destructive. This study introduces an innovative framework integrating hyperspectral imaging (HSI), broad learning system (BLS), and SHapley Additive exPlanations (SHAP) for RAM origin identification. RAM samples were collected from three origins, 100 samples from per origin, and imaged using a visible and short-wave near-infrared HSI system. BLS was used to build identification models with full and important wavelengths, and compared against seven traditional algorithms, including K-nearest neighbors (KNN), random forest (RF), support vector machine (SVM), back propagation neural network (BPNN), gradient boosting decision tree, (GBDT), extreme gradient boosting (XGBoost), and adaptive boosting (AdaBoost). Additionally, SHAP was used to enhance interpretability and identify important wavelengths highly correlated with RAM origin. Results showed that the full-wavelength BLS model achieved a test accuracy of 95.56%, which outperformed other models including KNN (77.78%), RF (85.56%), GBDT (88.89%), AdaBoost (90.00%), BPNN (91.11%), XGBoost (92.22%), and SVM (94.44%). SHAP identified important wavelengths similar to traditional methods (competitive adaptive reweighted sampling and successive projections algorithm), and the BLS model using SHAP-selected top 25 wavelengths achieved 94.44% accuracy with minimal performance loss. This study not only provides a rapid and accurate approach for RAM origin identification but also establishes a promising data-driven paradigm for non-destructive geographical origin traceability of other traditional Chinese medicines. Hyperspectral imaging ; Boosting (machine learning) ; Pattern recognition (psychology) ; Interpretability ; Support vector machine ; Random forest Spectroscopy and Chemometric Analyses ; Remote-Sensing Image Classification ; Traditional Chinese Medicine Analysis
Authors: Ukpe Ajima | Adetunji Alakija | Bongdap Nanzing | O. W. Johnson | Jane L. David | O. John Ehoche
Source: Nigerian Journal of Pharmacy (article, 2025-05-24)
Field: Chemistry — Analytical Chemistry

Development of a Colorimetric Method for Determination of Piroxicam in Pharmaceutical Formulation Based on Charge Transfer Complex Formation Using Picric Acid Background: Piroxicam is a non-steroidal anti-inflammatory drug (NSAID) that is used to manage mild to moderate pain, arthritis, and other inflammatory conditions. There is a dearth of simple, cost-effective, and reliable colorimetric methods for the routine determination of piroxicam in pharmaceutical formulations. The study was aimed at developing a colorimetric method for quantifying piroxicam based on charge-transfer complexation between piroxicam and picric acid. Methods: The method is based on the formation of a charge-transfer complex between piroxicam an electron donor and picric acid as the electron acceptor. The yellow coloured product formed was quantified at the absorption maximum of 420 nm. The effect of various experimental conditions (reaction time, solvent type and reagent concentration) on complex formation were also investigated. The method was validated as per ICH guidelines. The accuracy was evaluated using recovery studies while precision was evaluated on intra-day and inter-day basis. The limit of detection (LOD), limit of quantification (LOQ) and molar absorptivity were determined and the method was compared with the official titrimetric assay method for the drug. Results: The optimized conditions for complex formation were found to involve the use of Dichloromethane as solvent, a reaction time of 10 minutes and 2.5 ml of 0.001% picric acid solution. 2 Beer's law was obeyed in the concentration range of 20 – 100 μg/ml (r = 0.994). The method showed good precision with inter-day precision in the range of 0.03 – 0.91 % RSD while intra-day precision was from 0.02 – 0.85 % RSD. A comparison of the proposed method with the official method revealed that they produce comparable analytical results. Conclusion: The developed method was applied successfully to the analysis of piroxicam in capsule formulation with good accuracy and precision and without any interference from the excipients. As such, the newly developed method can serve as a useful technique for the quality assessment of piroxicam. Picric acid ; Piroxicam ; Chemistry ; Chromatography ; Combinatorial chemistry ; Organic chemistry ; Medicine Analytical Methods in Pharmaceuticals ; Phenothiazines and Benzothiazines Synthesis and Activities ; Analytical Chemistry and Chromatography
Authors: Madhusudan Roy | Mahule Roy
Source: Journal of Diagnosis & case Reports (article, 2025-05-31)
Field: Materials Science — Surfaces, Coatings and Films

AI Approach for Predicting Superhyrophobicity of Thermal Sprayed Copper Coated Aluminum Surfaces Wettability, characterized by the contact angle of a liquid on a surface, is a critical property that influences numerous natural and industrial applications. In this study, I have developed a CNN-based model to predict the hydrophobicity or super-hydrophobicity of copper-coated aluminum surfaces treated with various reagents or etchants. The data set has been created by analyzing copper-coated aluminum samples with a 3D non-contact profilometer, and contact angle measurements were done to correlate surface properties with the resultant contact angle values. After reagent treatments, the approach had been to preprocess 3D profilometer images to extract surface morphology and structure features. These images and associated contact angle measurements were used as inputs to train the CNN model to classify whether the treated surfaces are hydrophobic or super-hydrophobic. Although the model may initially have limited training accuracy, this study demonstrates the potential of deep learning to predict wettability based on surface characteristics. The results also highlight the need for improvements, such as data set expansion, the inclusion of more varied reagent treatments, and the exploration of hybrid modeling approaches to enhance the model. Contact angle ; Wetting ; Reagent ; Profilometer ; Aluminium ; Surface (topology) ; Copper ; Thermal Surface Modification and Superhydrophobicity ; Fluid Dynamics and Heat Transfer ; Aerosol Filtration and Electrostatic Precipitation
Authors: Ana-Maria Nicoleta Codreanu | Daniela Simina Ștefan | Lidia Kim | Ionut Cristea | Rachid Aziam
Source: Polymers (article, 2025-08-27)
Field: Materials Science — Biomaterials

Optimization of Chromium Removal Conditions from Tanned Leather Waste for Collagen Valorization The large amounts of chrome-tanned leather waste (CLTW) produced annually can be valorized by applying circular economy principles in various fields due to the valuable substances contained (mainly collagen). The main problem for the direct valorization of these wastes is the presence in their composition of dangerous substances, such as chromium. Thus, before being used as raw material in new processes, chrome-tanned leather waste must be subjected to a preliminary stage of chromium removal. In this article, we propose to identify the optimal working conditions for the extraction of chromium ions from chrome-tanned hides in the presence of oxalic acid with various concentrations, at various temperatures and contact times, so that the degree of collagen hydrolysis is minimal. In this sense, the response surface methodology (RSM) method was used to optimize the working conditions, to maximize the efficiency of chrome extraction from the leather, and to minimize the efficiency of collagen hydrolysis: An undesirable process. To optimize both the extraction yield (%) and the degree of hydrolysis (%), the key operational variables, namely oxalic acid concentration (%), contact time (%), and temperature (°C), were systematically adjusted using the Box-Behnken design within the response surface methodology (RSM). The most favorable extraction conditions were identified at an oxalic acid concentration of approximately 7%, a contact time close to 120 min, and a temperature near 49 °C. Under these optimized parameters, the hydrolysis degree remained very low, around 0.38%, indicating minimal degradation during the process. Chromium ; Pulp and paper industry ; Waste management ; Chemistry ; Materials science ; Organic chemistry ; Engineering Collagen: Extraction and Characterization
Authors: Divya Aggarwal | Pramod Reddy | Milind Patil | A. Senthil Kumar | Qingchang Guo | S SARATH AJAY KUMAR | Piyush Pal
Source: International Academic Journal of Science and Engineering (article, 2025-12-30)
Field: Materials Science — Polymers and Plastics

Biodegradable Polymer Nanocomposites from Agricultural Waste for Sustainable Packaging Applications Coupled with the rapid generation of non-biodegradable plastic waste, which accounts for about 400 million tons of global production each year, there is increased pressure to seek sustainable alternatives to conventional packaging. Traditional petroleum-based plastics are the most common packaging materials, accounting for almost 40% of overall plastic consumption in the packaging sector, and they cause serious environmental and ecological issues. This paper will research the production of biodegradable polymer nanocomposites from agricultural waste as a sustainable solution for packaging. Solution casting and melt blending methods were used to prepare agricultural residues into nano-sized fillers (20-80 nm) for use in a biodegradable polymer framework. The mechanical strength, thermal stability, barrier properties, and biodegradability of the nanocomposite films were characterized. The tensile strength increased by 32 %, and the Young's modulus increased by 27 % when the experimental results were compared with those of the neat biodegradable polymer. The permeability of water vapor was also reduced by 21%, indicating improved barrier performance in food packaging. The thermogravimetric analysis showed an increase in the thermal degradation temperature by 150 °C, indicating enhanced thermal stability. The laboratory test of soil burial revealed that the degradation of soil burial was 85 % in 90 days, which is much higher in comparison with conventional plastic (less than 5 % degradation). The life cycle assessment also revealed that a carbon footprint might decrease by 38 % when using the petroleum-based packaging material. Its results affirm that biodegradable nanocomposites reinforced with agricultural waste are mechanically strong, thermally resistant, and environmentally friendly for use in packaging. This method not only glorifies agro-residues but also facilitates the development of the circular economy, which has less impact on the environment but functions well in commercial packaging solutions. Biodegradation ; Biodegradable polymer ; Thermogravimetric analysis ; Environmentally friendly ; Nanocomposite ; Food packaging ; Bioplastic Natural Fiber Reinforced Composites ; Polymer Science and PVC ; Microplastics and Plastic Pollution
Authors: Sathya Narayanasamy | Jon G. Bell | Sumit Tiwari | Thibault Charpentier | Jean‐Marc Delaye | Émeline Cournède | Antoine Thill | Olivier Taché | Joséphine Lai‐Kee‐Him | Aurélie Ancelin | Martiane Cabié | Stéṕhane Gin
Source: npj Materials Degradation (article, 2025-09-30)
Field: Materials Science — Ceramics and Composites

Insights into gel maturation from alteration of borosilicate glass from 7 days to 27 years Prediction of glass alteration kinetics evolution is key to assessing chemical durability. A mechanistic understanding of the different processes controlling the alteration kinetics will enable the development of robust models. The “gel” that forms on the glass surface because of alteration is known to have “passivation” properties that reduce glass alteration rates. However, open questions remain about the passivation mechanism. Tracing experiments using 10B and 18O and characterization of gel layers aging from 7 days to 27 years, formed at pH90°C 9 and 90 °C, provided some insights into the evolution of the gel properties (maturation) and their influence on alteration kinetics. The probable mechanisms by which the glass alteration kinetics reduces have been examined. It has been suggested that both the reactive diffusion of water and the boron diffusion through the gel layer towards the solution have decreased over time. The potential causes and consequences of this decrease have been reviewed. Borosilicate glass ; Kinetics ; Diffusion ; Layer (electronics) ; Passivation ; Surface layer Glass properties and applications ; Recycling and utilization of industrial and municipal waste in materials production ; Building materials and conservation