jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Salita Ulitia Prini
Source: Jurnal Elektronika dan Telekomunikasi (article, 2025-12-31)
Field: Materials Science — General Materials Science

Appendix Vol. 25 No. 2 Koi fish farming requires careful monitoring of water temperature and pH to prevent adverse impacts on the fish.This study presents a prototype IoT-based autofeeder that integrates real-time water quality monitoring and automatic feeding, controllable via both an Android application and local device buttons.The system allows users to configure feeding schedules, feed throw levels, and durations, as well as set pH thresholds.When the pH exceeds the safe range, the system automatically stops feeding and sends notifications, enabling the user to inspect and maintain pond water quality.The findings demonstrate that the dispensing level significantly influences the feed-throwing distance; higher dispensing levels result in longer distances.Small-sized feed (S) consistently produced the highest output, followed by medium-sized (M) and large-sized (L).Increasing the feeding duration enhanced the weight of the released feed.Additionally, the average delay in sensor data transmission to the database was recorded at 5.48 seconds.The data loss rate during the testing period was 1.72%, which is considered acceptable and does not adversely affect system operations.The data transmission system demonstrated good and stable performance with relatively low data loss. Data transmission ; Android (operating system) ; Water quality ; Android application ; Water level ; Transmission (telecommunications) Engineering and Material Science Research ; Diverse Scientific and Economic Studies ; Educational Robotics and Engineering
Authors: Ghali Muhammad Rabiu | Musa Hamisu | Ladi Lawan | Mohammed Hussaini | Abba Haruna Adamu
Source: Iconic Research and Engineering Journals (article, 2025-09-22)
Field: Chemistry — Organic Chemistry

Unraveling Acid–Base Contributions in P-Nitrophenyl Acetate Hydrolysis: Kinetics, Mechanism, And Activation Parameters in Aqueous Media Hydrolysis of p-nitrophenyl acetate (PNPA) serves as a classical model for studying acid–base catalysis in aqueous solution. Despite its widespread use in enzymology and mechanistic chemistry, comprehensive datasets unifying acid- and base-catalyzed pathways remain limited. In this study, PNPA hydrolysis was monitored spectrophotometrically across pH 2–11 and temperatures 20–45 °C. Pseudo-first-order rate constants (kobs) were determined from exponential fits of absorbance–time traces at 400 nm. A characteristic U-shaped pH–rate profile was obtained, confirming contributions from both acid- and base-catalyzed pathways. Arrhenius and Eyring analyses yielded an activation energy (E?) of 54.7 kJ·mol?¹, enthalpy of activation (?H) of 52.2 kJ·mol?¹, and entropy of activation (?S) of ?47.8 J·mol?¹·K?¹, consistent with a bimolecular, ordered transition state. The results bridge existing gaps by integrating acid- and base-mediated hydrolysis within a single mechanistic framework, providing a reference dataset for both physical organic chemistry and enzymatic catalysis. Activation energy ; Arrhenius equation ; Hydrolysis ; Enthalpy ; Aqueous solution ; Catalysis ; Entropy (arrow of time) ; Aqueous medium ; Entropy of activation Chemical Reaction Mechanisms ; Spectroscopy and Quantum Chemical Studies
Authors: Sergey Anufriev | Paul Hellier | Nicos Ladommatos
Source: Energy & Fuels (article, 2025-06-30)
Field: Materials Science — Materials Chemistry

Generation of Novel Fuels Optimized for High-Knock Resistance with a Long Short-Term Memory Model The chemical structure of fuels significantly influences the properties of ignition and energy release during combustion, making the exploration of molecular structure-property relationships a key focus for the research and development of new sustainable fuels. Given the vast combinatorial possibilities of potential fuel candidates, prioritization is essential. This study explored the use of generative modeling to propose novel molecular structures for future fuels. Specifically, the long short-term memory (LSTM) autoregressive model was fine-tuned using a hill-climb optimization algorithm to generate structures optimized for high-knock resistance. The generated compounds, unseen during training, were evaluated for their physical properties and research octane number (RON). The generated molecules contained features commonly associated with knock resistance, such as branching and aromaticity, while also uncovering unconventional structures, including oxygenates with ether linkages. This work underscores the promise of generative modeling in fuel design and highlights the strategic advantage of initiating molecular generation from predefined fragments related to known feedstocks and production processes to enhance practicality in synthesis and resource utilization. Term (time) ; Gene knockin ; Materials science ; Environmental science ; Chemistry ; Physics ; Gene Machine Learning in Materials Science ; Nuclear Materials and Properties ; Petroleum Processing and Analysis
Authors: Dian Anggraini Indrawan | Bono Pranoto | Lisna Efiyanti | Irman Firmansyah | Gustan Pari | Kusnandar Kusnandar | Lina Karlinasari
Source: International Food Research Journal (article, 2025-04-01)
Field: Materials Science — Biomaterials

Advancements in carbon-based food packaging with antimicrobial properties: A bibliometric and content analysis This review presents a comprehensive bibliometric analysis of advancements in antimicrobial food packaging involving carbon-based materials. By systematically examining research from January 1991 to December 2023, we highlight the evolution of studies focusing on the integration of antimicrobial agents to enhance food safety and extend product shelf life. The analysis utilises bibliometric indicators and thematic content analysis, covering key trends, publication outputs, and collaboration networks. Insights into the multidimensional research landscape reveal the pivotal role of carbon-based compounds in developing sustainable antimicrobial packaging solutions, aligning with global sustainability and public health objectives. Food packaging ; Sustainability ; Food safety ; Antimicrobial ; Food products ; Bibliometrics ; Thematic analysis ; Food industry ; Content analysis Nanocomposite Films for Food Packaging ; Consumer Packaging Perceptions and Trends ; Agriculture Sustainability and Environmental Impact
Authors: S M Nazmuz Sakib | Mohammad Nasir Uddin | Atif Ishtiaq | Md Shariful Islam | M. R. Rana | N. A. Roktim | Md. Emran Hossain | M. A. Ali | Karimul Hoque
Source: Research Square (preprint, 2025-06-06)
Field: Materials Science — Materials Chemistry

Prediction and Stability of Y2AB MAX Phase Boride: A DFT study Boride ; Stability (learning theory) ; Phase (matter) ; Materials science ; Metallurgy ; Chemistry ; Computer science ; Machine learning MXene and MAX Phase Materials ; Boron and Carbon Nanomaterials Research ; Advanced ceramic materials synthesis
Authors: Jiajun Wang | Aikun Lin | Ling Fang | Yang Lu | Zhiyuan Zou | Zhiguo Zhang | Y. Yin
Source: npj Heritage Science (article, 2025-12-22)
Field: Chemistry — Organic Chemistry

Inferring ancient from modern: a deep learning approach for species identification of archaeological wood Identification of archaeological wood species is critical for decoding the biogeographical, historical, and cultural narratives of artifacts, but remains a challenge in practice. To address this challenge, we developed a deep learning framework integrating computer vision and archaeological wood species analysis. Images of modern and waterlogged archaeological wood specimens were collected and augmented through rotation, scaling, and contrast adjustments. The deep learning model was established through embedded self-attention mechanisms, optimizing feature extraction capabilities. The model yielded an overall accuracy of 94.20% on 12 modern woods and 97.83% on 2 archaeological woods. The binary classifier was further evaluated on three batches of archaeological woods and achieved the accuracy of 98.31%, 96.19% and 91.82%, respectively. The deep learning approach proposed in this study achieved good performance on waterlogged archaeological wood identification while requiring less wood anatomy expertise and minimal intervention of cultural artifacts, providing a critical advancement for archaeology applications. Deep learning ; Identification (biology) ; Classifier (UML) ; Species identification ; Archaeological record ; Feature (linguistics) Wood and Agarwood Research ; Wood Treatment and Properties ; Remote Sensing and LiDAR Applications
Authors: Renu Yadav | Mohit Johri
Source: Journal of Advances and Scholarly Researches in Allied Education (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Thermodynamic Stability and Bandgap Trends in Mixed Alkaline Earth Chalcogenides Mixed alkaline earth chalcogenides (AECs) are a promising class of materials with tunable bandgap properties, making them highly suitable for applications in optoelectronics, thermoelectrics, and energy storage. This study investigates the thermodynamic stability and bandgap trends in mixed AECs, focusing on the effects of cation and anion mixing on their structural and electronic properties. Using density functional theory (DFT) calculations and experimental validation, we explore the stability and bandgap variations in mixed AECs. The results demonstrate that mixed AECs exhibit enhanced thermodynamic stability and tunable bandgaps, providing new opportunities for advanced material design. Alkaline earth metal ; Stability (learning theory) ; Materials science ; Earth (classical element) ; Mathematics ; Computer science ; Metallurgy Solid-state spectroscopy and crystallography ; Crystal Structures and Properties ; Rare-earth and actinide compounds
Authors: Lucila M. Carias Duron | Julián Pulido García | Chetna Mandurai | Jordon Hoyer | Japneet Kukal | Manish Sakhakarmy | Sushil Adhikari | Brian K. Via | Iris Beatriz Vega Erramuspe | Armando G. McDonald | Marı́a L. Auad
Source: Sustainability (article, 2025-11-21)
Field: Materials Science — Polymers and Plastics

Kinetics and Mechanical Performance of Bio-Based Polyurethane Wood Composites for Sustainable 3D-Printed Construction Materials Developing bio-based polyurethane (BPU) composites that incorporate bio-oil and wood dust as sources of hydroxyl groups (-OH) presents a compelling approach to advancing sustainable polymer systems. This study examines the impact of isocyanate-to-hydroxyl equivalent ratios and varying proportions of bio-oil and wood dust on the processability and mechanical properties of molded composite panels. Formulations were systematically optimized based on equivalent ratio calculations to enhance extrusion behavior and final structural performance. Extrusion trials demonstrated that an -NCO/-OH ratio of 1.5:1, with 50% wood dust serving as an -OH donor, resulted in the most stable material flow, characterized by minimized surface defects and an ideal viscosity for processing. Compression molding and mechanical testing revealed that a balanced formulation with 50% bio-oil and 50% wood dust, with an equivalent ratio of -OH groups, achieved the best combination of Young’s modulus, stress, and strain performance, even under wet conditions. SEM confirmed improved filler dispersion and interfacial adhesion in these optimized systems. Although full 3D-printing trials were not conducted, the observed extrusion stability and controlled curing behavior indicate strong potential for application in extrusion-based additive manufacturing. These results highlight that precise resin–filler balancing enables continuous extrusion, structural resilience, and reduced activation energy, reinforcing the viability of BPUs as scalable, sustainable materials for construction and additive manufacturing. Extrusion ; Polyurethane ; Composite number ; Curing (chemistry) ; Wood-plastic composite ; Filler (materials) ; Compression molding ; Molding (decorative) Polymer composites and self-healing ; Natural Fiber Reinforced Composites ; Additive Manufacturing and 3D Printing Technologies
Authors: Ruiling Xu | Yifan Zhang | Qingyun Wang | Christopher R.W. Edwards | Heng Ji
Source: ArXiv.org (preprint, 2025-10-09)
Field: Materials Science — Materials Chemistry

oMeBench: Towards Robust Benchmarking of LLMs in Organic Mechanism Elucidation and Reasoning Organic reaction mechanisms are the stepwise elementary reactions by which reactants form intermediates and products, and are fundamental to understanding chemical reactivity and designing new molecules and reactions. Although large language models (LLMs) have shown promise in understanding chemical tasks such as synthesis design, it is unclear to what extent this reflects genuine chemical reasoning capabilities, i.e., the ability to generate valid intermediates, maintain chemical consistency, and follow logically coherent multi-step pathways. We address this by introducing oMeBench, the first large-scale, expert-curated benchmark for organic mechanism reasoning in organic chemistry. It comprises over 10,000 annotated mechanistic steps with intermediates, type labels, and difficulty ratings. Furthermore, to evaluate LLM capability more precisely and enable fine-grained scoring, we propose oMeS, a dynamic evaluation framework that combines step-level logic and chemical similarity. We analyze the performance of state-of-the-art LLMs, and our results show that although current models display promising chemical intuition, they struggle with correct and consistent multi-step reasoning. Notably, we find that using prompting strategy and fine-tuning a specialist model on our proposed dataset increases performance by 50% over the leading closed-source model. We hope that oMeBench will serve as a rigorous foundation for advancing AI systems toward genuine chemical reasoning. Benchmarking ; Mechanism (biology) ; Chemical space ; Benchmark (surveying) ; Foundation (evidence) ; Chemical process Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Advanced Graph Neural Networks
Authors: Biaz S Lal | R. Rajesh | M. Dev Anand | K. S. Jai Aultrin
Source: Preprints.org (preprint, 2025-08-27)
Field: Materials Science — Polymers and Plastics

Reinforcement Testing of Sun-Dried Coconut Fiber Impregnated Composite Materials The design, production, and characterization of coir fiber-reinforced composites employing epoxy resin modified with CNSL are investigated in this work. A 1:1.25 epoxy-to-hardener ratio, 15-20% CNSL, and vacuum bagging were used to create fiber arranged for sun-dried coir composites. Structural and thermal properties were assessed using mechanical tests (tensile, flexural, and impact) as well as FTIR, TGA, and SEM investigations. The findings show that CNSL improved impact resistance and thermal stability, while interlocking coir composites had greater mechanical strength. However, impact hardness was decreased by over-mercerization. The results show that coir fiber composites are environmentally friendly substitutes for construction, automotive, and aerospace applications. To improve performance, future studies can optimize fiber loading and biodegradability. Coir ; Materials science ; Composite material ; Epoxy ; Flexural strength ; Ultimate tensile strength ; Fiber ; Thermal stability ; Composite number ; Fourier transform infrared spectroscopy ; Chemical engineering Natural Fiber Reinforced Composites ; Electrospun Nanofibers in Biomedical Applications ; Mechanical Behavior of Composites
Authors: Yunpeng Chu | Tianyong Jiang | Han Huang | Gangxin Yi | Bo Huang
Source: Materials (article, 2025-12-05)
Field: Materials Science — Materials Chemistry

Study on Preparation and Properties of Phosphogypsum-Based Lightweight Thermal Insulation Materials At present, phosphogypsum, as an industrial by-product, is a solid waste in phosphoric acid production, and its accumulation has caused serious environmental pollution. Furthermore, due to the insufficient insulation properties of traditional wall materials, the issue of a rising proportion of building energy consumption in total social energy consumption has become increasingly pressing. The study investigated vitrified beads as a light aggregate and phosphogypsum, mineral powder, and quicklime as an inorganic composite cementitious system to prepare the phosphogypsum-based lightweight thermal insulation material. The effect mechanism of the initial material ratio on the mechanical properties and micro-morphology of insulation materials was studied by macroscale mechanical property testing, X-ray diffraction, and scanning electron microscopy. Meanwhile, in order to meet the performance indexes specified in relevant standards, insulation materials were modified by adding sulfate aluminate cement, basalt fibers, and a waterproof agent to improve the strength, toughness, and water resistance. Based on the single-factor experimental design, the optimal dosage of various admixtures was obtained. The results indicated that the optimal properties of the sample were achieved when the binder-bead ratio was 1:4, the water-binder ratio was 1.6, the dosage of hydroxypropyl methylcellulose was 0.1%, and the solid content of waterborne acrylic emulsion was 24%. The optimal dosages of cement and fibers were 8% and 0.9%, respectively. The cement hydration products and gypsum crystals lapped through each other, filling the pores in the matrix and increasing the strength of the sample. In addition, the fibers could form a disordered network structure inside the matrix, disperse external force, weaken the stress concentration at the tip of internal cracks, and significantly improve the toughness of the modified sample. By incorporating 2.0% paraffin emulsion in the mortar and spraying 5 dilutions of sodium methyl silicate on the external surface, dense protective layers were formed both inside and outside the modified sample. The water absorption rate reduced from 30.27% to 23.30%, and the water resistance was increased to satisfy the specified requirement for the insulation material. Cementitious ; Cement ; Thermal insulation ; Gypsum ; Pipe insulation ; Composite number ; Filler (materials) ; Aluminate ; Polymer ; Aggregate (composite) Magnesium Oxide Properties and Applications ; Recycling and utilization of industrial and municipal waste in materials production ; Concrete and Cement Materials Research
Authors: Vytautas Mickevičius | Kazimieras Anusevičius | Birutė Sapijanskaitė-Banevič | Ilona Jonuškienė | Linas Kapočius | Birutė Grybaitė | Ramunė Grigalevičiūtė | Povilas Kavaliauskas
Source: Molecules (article, 2025-08-07)
Field: Chemistry — Organic Chemistry

Synthesis and Biological Evaluation of β-Phenylalanine Derivatives Containing Sulphonamide and Azole Moieties as Antiproliferative Candidates in Lung Cancer Models In this study, a series of novel <i>β</i>-phenylalanine derivatives were synthesised and evaluated for their anticancer activity. The 3-(4-methylbenzene-1-sulfonamido)-3-phenylpropanoic acid (<b>2</b>) was prepared using <i>β</i>-phenylalanine as a core scaffold. The <i>β</i>-amino acid derivative <b>2</b> was converted to the corresponding hydrazide <b>4</b>, which enabled the development of structurally diverse heterocyclic derivatives including pyrrole <b>5</b>, pyrazole <b>6</b>, thiadiazole <b>8</b>, oxadiazole <b>11</b>, triazoles <b>9</b> and <b>12</b> with Schiff base analogues <b>13</b> and series1,2,4-triazolo [3,4-<i>b</i>][1,3,4]thiadiazines <b>14</b>. These modifications were designed to enhance chemical stability, solubility, and biological activity. All compounds were initially screened for cytotoxicity against the A549 human lung adenocarcinoma cell line, identifying <i>N</i>-[3-(3,5-dimethyl-1<i>H</i>-pyrazol-1-yl)-3-oxo-1-phenylpropyl]-4-methylbenzenesulfonamide (<b>5</b>) and (<i>E</i>)-<i>N</i>-{2-[4-[(4-chlorobenzylidene)amino]-5-thioxo-4,5-dihydro-1<i>H</i>-1,2,4-triazol-3-yl]-1-phenylethyl}-4-methylbenzenesulfonamide (<b>13b</b>) as the most active. The two lead candidates were further evaluated in H69 and H69AR small cell lung cancer lines to assess activity in drug-sensitive and multidrug-resistant models. Schiff base <b>13b</b> containing a 4-chlorophenyl moiety, retained potent antiproliferative activity in both H69 and H69AR cells, comparable to cisplatin, while compound <b>5</b> lost efficacy in the resistant phenotype. These findings suggest Schiff base derivative <b>13b</b> may overcome drug resistance mechanisms, a limitation commonly encountered with standard chemotherapeutics such as doxorubicin. These results demonstrate the potential role of <i>β</i>-phenylalanine derivatives, azole-containing sulphonamides, as promising scaffolds for the development of novel anticancer agents, particularly in the context of lung cancer and drug-resistant tumours. Chemistry ; Schiff base ; Moiety ; Cytotoxicity ; Stereochemistry ; Phenylalanine ; Pyrazole ; Combinatorial chemistry ; Oxadiazole ; Hydrazide ; Knoevenagel condensation ; Amino acid ; Biochemistry ; Organic chemistry ; In vitro Synthesis and biological activity ; Synthesis and Biological Evaluation ; Click Chemistry and Applications
Authors: Salwa B. Alreshaidan | R. S. Alanazi | Omalsad Hamood Odhah | Ahmed A. Ibrahim | Fekri Abdulraqeb Ahmed Ali | Naif Alarifi | Khaled M. Banabdwin | Sivalingam Ramesh | Ahmed S. Al‐Fatesh
Source: Catalysts (article, 2025-07-29)
Field: Materials Science — Materials Chemistry

The Impact of Sm Promoter on the Catalytic Performance of Ni/Al2O3-SiO2 in Methane Partial Oxidation for Enhanced H2 Production This study investigates the effects of samarium (Sm) promotion on the catalytic activity of 5 weight percent Ni catalysts for partial oxidation of methane (POM)-based hydrogen production supported on a Si-Al mixed oxide (10SiO2+90Al2O3) system. Several 5% Ni-based catalysts supported on silica–alumina was used to test the POM at 600 °C. Sm additions ranged from 0 to 2 wt.%. Impregnation was used to create these catalysts, which were then calcined at 500 °C and examined using BET, H2-TPR, XRD, FTIR, TEM, Raman spectroscopy, and TGA methods. Methane conversion (57.85%) and hydrogen yield (56.89%) were greatly increased with an ideal Sm loading of 1 wt.%, indicating increased catalytic activity and stability. According to catalytic tests, 1 wt.% Sm produced high CH4 conversion and H2 production, as well as enhanced stability and resistance to carbon deposition. Nitrogen physisorption demonstrated a progressive decrease in pore volume and surface area with the addition of Sm, while maintaining mesoporosity. At moderate Sm loadings, H2-TPR and XRD analyses showed changes in crystallinity and increased NiO reducibility. Sm incorporation into the support and its impact on the ordering of carbon species were indicated by FTIR and Raman spectra. The optimal conditions to maximize H2 yield were successfully identified through optimization of the best catalyst, and there was good agreement between the theoretical predictions (87.563%) and actual results (88.39%). This displays how successfully the optimization approach achieves the intended outcome. Overall, this study demonstrates that the performance and durability of Ni-based catalysts for generating syngas through POM are greatly enhanced by the addition of a moderate amount of Sm, particularly 1 wt.%. Catalysis ; Methane ; Production (economics) ; Chemistry ; Organic chemistry ; Economics Catalytic Processes in Materials Science ; Catalysts for Methane Reforming ; Catalysis and Oxidation Reactions