jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: A. Al Maofari | Y. Otifah | Mohammed Benmessaoud | Souad El Hajjaji
Source: Baghdad Science Journal (article, 2025-09-16)
Field: Chemistry — Organic Chemistry

Quantum Chemical Studies, Characterization and Understanding the Inhibition Effect of &lt;i&gt;Pulicaria Jaubertii&lt;/i&gt; Oil, Growing in Yemen, as a New Eco-Friendly Inhibitor for C38 Steel Corrosion in 1 M HCl Medium The inhibitive action of Pulicaria Jaubertii essential oil (PJEO), as green inhibitor, has been investigated on the carbon (C38) steel corrosion in 1 M HCl by using inductively coupled plasmas spectrometry (ICP), electrochemical impedance spectroscopy (EIS), potentiodynamic polarization and gravimetric measurements. The increasing of oil concentrations increases the carbon steel corrosion resistance (The inhibition efficiency), which rose to 94% in the optimal concentration (2.5 g/l). The specimen surfaces were analysed by using Infra-Red spectroscopy (IR) and scanning electronic microscope (SEM). The obtained results showed the presence of oil molecules adsorbed onto the specimen surface. Langmuir adsorption model was followed by PJ essential oil compounds which adsorbed onto the carbon steel surface to form a protective layer. PJEO was analysed by using gas chromatography coupled with mass spectra before it was used as green inhibitor. Several DFT parameters such as LUMO and HOMO energy, gap energy (ΔE), electronegativity (χ), softness (σ) and global hardness (η) were derived for all major molecules found in PJ oil. The theoretical results showed that there is a good agreement with the experimental data. Adsorption ; Corrosion ; Carbon steel ; Dielectric spectroscopy ; Langmuir adsorption model ; Gravimetric analysis ; Electronegativity ; Analytical Chemistry (journal) ; Langmuir Inorganic and Organometallic Chemistry
Authors: Y. Jin | Hong Yang | Jan Bohlen | Björn Wiese | Yan Su
Source: Materials (article, 2025-12-04)
Field: Materials Science — Biomaterials

Distinct Responses of Corrosion Behavior to the Intermetallic/Impurity Redistribution During Hot Processing in Micro-Alloyed Mg Alloys By tuning the extrusion parameters, the corrosion performances of as-extruded Mg-0.5Zn(-0.2X) alloys (X: Ca/Sr/Ag/In/Cu, denoted as Z05, Z0502-Ca, Z0502-Sr, Z0502-Ag, Z0502-In and Z0502-Cu, respectively) with similar grain sizes were investigated and compared with their as-cast counterparts. The formed Fe-Si precipitates after hot processing significantly accelerate the corrosion rates of Z05, Z0502-Ag and Z0502-In, whereas the driving force from the Fe-encapsulated MgCaSi(Fe) and MgSrSi(Fe) precipitates are not as strong in Z0502-Ca and Z0502-Sr. Impacts from Fe impurity in Z0502-Cu are masked in the fast corrosion due to the noble Mg2Cu intermetallics. Fe precipitation during hot processing is critical for micro-alloyed systems, as the changes in intermetallic/impurity distributions impact the corrosion performances profoundly. The enthalpy of formation and the potential difference are the key factors that influence the distribution of precipitate during hot processing. Corrosion ; Extrusion ; Redistribution (election) ; Precipitation ; Impurity ; Precipitation hardening Magnesium Alloys: Properties and Applications ; Aluminum Alloy Microstructure Properties ; Advanced Welding Techniques Analysis
Authors: Wei Zhang | Qiwei Yang | Yuanyuan Jin | Yuebo Meng | Leyu Shen | Xuran Zhu | Haifeng Gao | Chuan Chen
Source: Coatings (article, 2025-11-11)
Field: Materials Science — Surfaces, Coatings and Films

Novel Omniphobic Teflon/PAI Composite Membrane Prepared by Vacuum-Assisted Dip-Coating Strategy for Dissolved Gases Separation from Transformer Oil Omniphobic membranes have gained extensive attention for mitigating membrane wetting in robust membrane separation owing to the super-repulsion toward water and oil. In this study, a Teflon/PAI composite membrane with omniphobic characteristics was prepared by a vacuum-assisted dip-coating strategy on the PAI hollow fiber membrane. A series of characterizations on morphological structure, surface chemical composition, wettability, permeability, mechanical properties, and stability were systematically investigated for pristine PAI and Teflon/PAI composite membranes. Subsequently, the experiment was conducted to explore the oil–gas separation performance of membranes, with standard transformer oil containing dissolved gas as the feed. The results showed that the Teflon AF2400 functional layer was modified, and C-F covalent bonds were introduced on the composite membrane surface. The Teflon/PAI composite membrane exhibited excellent contact angles of 156.3 ± 1.8° and 123.0 ± 2.5° toward DI water and mineral insulating oil, respectively, indicating omniphobicity. After modification, the membrane tensile stress at break increased by 23.0% and the mechanical performance of the composite membrane was significantly improved. In addition, the Teflon/PAI composite membrane presented satisfactory thermal and ultrasonic stability. Compared to the previous membranes, the Teflon/PAI composite membrane presented a thinner Teflon AF2400 separation layer. Furthermore, the omniphobic membrane demonstrated anti-wetting performance by reaching the dynamic equilibrium within 2 h for the dissolved gases separated from the insulating oil. This suggests an omniphobic membrane as a promising alternative for oil–gas separation in monitoring the operating condition of oil-filled electrical equipment online. Membrane ; Composite number ; Contact angle ; Wetting ; Thermal stability ; Gas separation Surface Modification and Superhydrophobicity ; Membrane Separation Technologies ; Membrane Separation and Gas Transport
Authors: Mariasole Gobbo | Riccardo Gallorini | Luca Rosi
Source: Energies (article, 2025-12-11)
Field: Materials Science — Biomaterials

Energetic Valorization of Leather Solid Waste Through Thermochemical and Biochemical Methods The leather industry generates large amounts of solid waste, creating environmental concerns for the presence of hazardous compounds such as chromium. In fact, conventional disposal practices, including landfill and incineration, promote the formation of hexavalent chromium (Cr6+) and polluting emissions. This work reviews biochemical and thermochemical processes for the energetic valorization of different leather solid wastes, namely untanned, tanned with chromium or vegetable tanning agents, and post-consumer leather. Thermochemical routes, i.e., pyrolysis, gasification, and hydrothermal treatment (HT), can convert leather waste into energy carriers including bio-oil, syngas, and char, while anaerobic digestion (AD) is a biochemical method used to produce biogas. Particularly, pyrolysis is promising for fuel precursors and chromium stabilization, HT suits wet, raw waste, while gasification enables syngas recovery. In AD, microbial chromium inhibition is mitigated through the co-digestion of degradable substrates. This review takes a waste-type-driven rather than process-driven approach to provide new insights into the conversion of leather solid waste into value-added products, showing that the optimal recycling route depends on the waste characteristics. Moreover, these methods have not yet been directly compared in terms of their energy production performance with regard to leather waste. Future work should improve process conditions, evaluate chromium and finishing additive impacts, and assess scalability. Municipal solid waste ; Hazardous waste ; Chromium ; Raw material ; Anaerobic digestion ; Pyrolysis ; Hexavalent chromium ; Chromium Compounds ; Waste-to-energy Collagen: Extraction and Characterization ; Metal Extraction and Bioleaching ; Materials Engineering and Processing
Authors: M.K. Qasim | Rabah A. Khalil
Source: Chemistry Journal of Moldova (article, 2025-12-01)
Field: Materials Science — Materials Chemistry

Employment of in silico in prediction of furan derivatives as efficient corrosion inhibitors for mild steel in acidic media This study highlights the role of computational approaches in advancing the design of corrosion inhibitors by virtually screening novel candidate molecules. In silico treatment based on quantitative structure-activity relationship (QSAR) analysis was performed on already published experimental results of corrosion inhibition efficiency (IE%) of mild steel in acidic media for eighteen furan derivatives. The theoretical treatments are based on density functional theory (DFT) at B3LYP level. It was found that the global minimum of the furan derivatives can be reached at a medium basis set of 6-21G. A sophisticated model consisting of four descriptors excluding the sulphur correction term with physical meaning and good statistical criteria of squared correlation coefficient (r2) and standard error (SE) equal to 0.914 and 5.029, respectively, is presented. The suggested model can be considered as a powerful tool for understanding the role of chemical composition in preventing corrosion which helps researchers in the development process. The in silico treatment was utilized for suggesting twelve furan derivatives with an extremely high IE% which might be used as excellent materials for corrosion inhibition when synthesized and applied experimentally. Furan ; In silico ; Corrosion ; Sulfur ; Density functional theory ; Quantitative structure–activity relationship Corrosion Behavior and Inhibition ; Synthesis of Tetrazole Derivatives ; Concrete Corrosion and Durability
Authors: Jing Sun | Junge Zhi | Li Zhang | Yan Qi | Jiefang Sun | Yushen Jin | Jie Yin | Kai Yao | Bing Shao
Source: Molecules (article, 2025-04-29)
Field: Materials Science — Materials Chemistry

An “On–Off” AIE-Based Lock-and-Key Fluorescent Probe System for Detection of Fentanyl/Norfentanyl The misuse of fentanyl poses significant social risks, and accurately and swiftly detecting fentanyl in field settings presents a considerable challenge. Herein, we have designed and synthesized a fluorescent probe TP-CF<sub>3</sub>-COOH, which is composed of carboxyl- and trifluoromethyl-binding center tetraphenyl butadiene. The unique centrosymmetric configuration of the TP-CF<sub>3</sub>-COOH probe allows for the construction of a fluorescence "on-off" mechanism recognition platform by spatially matching fentanyl and its metabolite norfentanyl. Importantly, this study reveals that the interaction of fentanyl or norfentanyl with TP-CF<sub>3</sub>-COOH results in spontaneous self-assembly, generating a three-dimensional complex sphere that is smaller than the two-dimensional sheet fluorescence probe. This self-assembly process results in the quenching of fluorescence. Theoretical calculations demonstrate that this process is accompanied by intermolecular through-space charge transfer during self-assembly, leading to a blue shift in emission wavelength. As a result, the TP-CF<sub>3</sub>-COOH fluorescent probe enables the quantitative detection of fentanyl/norfentanyl within a range of 1 × 10<sup>-2</sup>-1 × 10<sup>3</sup> μg/L, with limits of detection of 2 × 10<sup>-4</sup> μg/L and 3 × 10<sup>-4</sup> μg/L, respectively. This cost-effective, rapid, and sensitive fluorescent probe holds great potential for the onsite screening and detection of fentanyl and its analogues. Fluorescence ; Fentanyl ; Chemistry ; Intermolecular force ; Quenching (fluorescence) ; Photochemistry ; Combinatorial chemistry ; Biophysics ; Molecule ; Organic chemistry ; Optics ; Pharmacology ; Physics ; Biology Luminescence and Fluorescent Materials ; Molecular Sensors and Ion Detection ; Nicotinic Acetylcholine Receptors Study
Authors: Zhaoqiang Chen | Pengcheng Song | Chuanfa Shen | Xianglong Meng | Hui Chen | Jingjie Zhang | Mingdong Yi | Guangchun Xiao | Chonghai Xu
Source: Materials (article, 2025-12-07)
Field: Materials Science — Ceramics and Composites

Enhancement of Cutting Performance of Ceramic Tools by Addition of Exogenous Precursor Restorers To address brittle cracks in ceramic tools, an exogenous precursor ceramic repair agent was developed and applied to Al<sub>2</sub>O<sub>3</sub>/TiC/NiMo composite ceramic tools, which were treated by a two-step heat treatment process (heating at 3 °C/min to 300 °C for 60 min, heating the sample at 5 °C/min to 500, 600, 700, 800, and 900 °C, holding each for 60 min). The crack healing mechanism and temperature dependency of the repair agent were investigated. Cutting performance, including surface roughness, cutting force, and tool life, was optimized using an L9(34) orthogonal design. The results show that at 900 °C, the repair agent decomposed to form SiOC (Silicon Oxycarbide) amorphous phase and TiB<sub>2</sub> reinforced phase, filling the cracks and achieving atomic-level diffusion bonding. The flexural strength of the repaired sample recovered to 79.9% of the initial value (456.5 MPa), a 196.4% increase compared to the unrepaired sample. Optimal cutting parameters were found to be a cutting speed of 200 m/min, back draft of 0.1 mm, and feed of 0.1 mm/r. Under these conditions, surface roughness was 0.845 μm, cutting temperature was 258 °C, and stable tangential force was 70 N. The effective cutting distance of the repaired tool was increased from 1300 m to 1700 m. Wear was primarily abrasive and adhesive wear, and the SiOC phase formed by the repair agent helped to fill and repair the flank, thus extending tool life. Ceramic ; Flexural strength ; Abrasive ; Brittleness ; Surface roughness ; Composite number ; Surface finish ; Adhesive Advanced ceramic materials synthesis ; Advanced materials and composites ; Advanced Surface Polishing Techniques
Authors: Alankar Shrivastava
Source: International Journal of Newgen Research in Pharmacy & Healthcare (article, 2025-12-31)
Field: Chemistry — Spectroscopy

Chromatography and Artificial Intelligence Chromatography is a fundamental analytical technique widely applied in pharmaceutical, biotechnological, and environmental sciences for separating and quantifying complex mixtures. Advancements in instrumentation, miniaturization, and computational technologies have extended its capabilities. More recently, artificial intelligence (AI) has emerged as a transformative tool capable of improving method development, retention prediction, peak deconvolution, and overall data quality. This study provides a detailed methodological framework for chromatographic analysis and evaluates the expanding role of AI in optimizing workflows, enhancing analytical performance, and increasing automation in chromatographic systems. A comprehensive methodological description covers the selection of analytical-grade solvents, stationary phases, sample preparation techniques, mobile-phase conditioning, instrument setup, and method development strategies. Validation parameters such as accuracy, precision, linearity, specificity, and robustness are outlined in accordance with international guidelines. The study further reviews emerging chromatographic platforms including microfluidics, 2D-LC, and advanced detection systems. AI applications were examined across five major domains: automated method development, retention time prediction, peak deconvolution, predictive maintenance, and intelligent data processing. Modern chromatographic workflows benefit significantly from optimized sample preparation, controlled mobile-phase conditions, and high-resolution detection. AI-driven tools demonstrated improvements in prediction accuracy, reduction in experimental workload, enhanced peak interpretation, and early detection of instrument anomalies. Integration of machine learning models into chromatographic software increased efficiency and data reliability. AI is reshaping chromatographic science by enabling predictive, automated, and adaptive workflows. Future advancements are likely to result in fully autonomous chromatographic systems, improving analytical precision and throughput across scientific disciplines. Workflow ; Robustness (evolution) ; Automation ; Software ; Sample (material) ; Artificial neural network ; Chromatographic separation Analytical Chemistry and Chromatography ; Computational Drug Discovery Methods ; Metabolomics and Mass Spectrometry Studies
Authors: D. D. Seitov | K. A. Nekrasov | Sergey S. Pitskhelaury | Ф. У. Абуова | Gaukhar Kabdrakhimova | Aisulu U. Abuova | Sanjeev K. Gupta
Source: Crystals (article, 2025-06-02)
Field: Materials Science — Materials Chemistry

Computational Modeling of Cation Diffusion in Isolated Nanocrystals of Mixed Uranium, Plutonium and Thorium Dioxides A classical molecular dynamics simulation of cation diffusion in isolated crystals (UxPuyTh1−x−y)O2 bounded by a free surface was performed. It was shown that in the bulk of the same model crystallite, the diffusion coefficients of cations of all types were practically identical. At the same time, the cation diffusion coefficients changed with the melting temperature of nanocrystals, which increased with increasing thorium content. At a given temperature, the diffusion coefficients were the higher, the lower were the melting points of the (UxPuyTh1−x−y)O2 crystallites. The temperature dependences of the diffusion coefficients in crystallites of different compositions converged when using coordinates normalized to the melting points. Crystallite ; Thorium ; Diffusion ; Uranium ; Nanocrystal ; Plutonium ; Molecular dynamics ; Self-diffusion ; Materials science ; Melting point ; Thermodynamics ; Melting temperature ; Chemistry ; Analytical Chemistry (journal) ; Crystallography ; Radiochemistry ; Metallurgy ; Computational chemistry ; Nanotechnology ; Physics Nuclear Materials and Properties ; Radioactive element chemistry and processing ; Nuclear materials and radiation effects
Authors: Yufeng Chen | Yutong Li
Source: Research Square (preprint, 2025-04-17)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Detection of Carbendazim with SA-AgNPs-CD functionalized silver nanoparticles as substrates based on Surface-Enhanced Raman Scattering Silver nanoparticle ; Raman scattering ; Carbendazim ; Nanoparticle ; Materials science ; Nanotechnology ; Raman spectroscopy ; Chemistry ; Nuclear chemistry ; Optics ; Physics ; Fungicide Gold and Silver Nanoparticles Synthesis and Applications ; Nanocluster Synthesis and Applications ; Carbon and Quantum Dots Applications
Authors: Szymon Błazucki | Junfeng Qiao | Nicola Marzari
Source: ArXiv.org (preprint, 2025-12-01)
Field: Materials Science — Materials Chemistry

First-principles screening of materials with extreme effective masses The effective mass of charge carriers is a fundamental descriptor of the electronic structure of materials, and can be used to assess performance in electronics applications, or to screen for thermoelectrics and transparent conductors. Here, we perform a high-throughput computational screening of approximately 20,000 experimentally known three-dimensional stoichiometric inorganics obtained from the Materials Cloud 3D structure database. By combining density-functional theory calculations and maximally localized Wannier functions, we are able to compute the full conductivity effective mass tensor for electrons and holes from the Boltzmann transport equation in the constant relaxation-time approximation. This approach captures the effects of band non-parabolicity, anisotropy, and valley multiplicity that would be neglected by standard parabolic fittings. The screening identifies a curated set of candidates exhibiting extreme electronic properties, from ultra-low to ultra-large effective masses, these latter associated with flat-band physics. We validate the workflow by recovering established high-mobility semiconductors and highlight promising novel candidates. Furthermore, we classify materials by their mass anisotropy and discuss the physical limits of defining a conductivity effective mass in narrow-gap regimes at room temperature. The resulting dataset provides a systematic roadmap to search for high-performance materials in novel chemical spaces. Effective mass (spring–mass system) ; Workflow ; Anisotropy ; Electronic structure ; Boltzmann constant ; Conductivity ; Semiconductor ; Electron Machine Learning in Materials Science ; 2D Materials and Applications ; Electronic and Structural Properties of Oxides
Authors: Chafaa Hamrouni | Aarif Alutaybi | Jacer Hamrouni | Naif Muidh Alsubaie
Source: Sound&Vibration (article, 2025-06-16)
Field: Materials Science — Polymers and Plastics

Biodegradable microcrystalline cellulose composites: Optimization of isotropic polybutene-1 crystallization and its vibration and noise reduction properties With the acceleration of industrialization, environmental noise and mechanical vibration problems are becoming increasingly serious. Traditional polymer damping materials have shortcomings in durability, environmental protection and performance optimization. In this study, MCC-iPB biodegradable composites were prepared. The interface and crystallization behavior were optimized by introducing maleic anhydride grafted polybutene-1 (MAPB). Experimental results showed that MCC can accelerate the crystal transformation and significantly improve the thermal stability and storage modulus. In the comparative experiment under the simulated operating conditions of industrial motors, compared with traditional polyurethane foam materials, the MCC-iPB composite material can reduce the vibration acceleration by about 40%, the sound pressure level by 6–9 dB, and the power fluctuation by more than 50% in the range of 500–2500 Hz, showing excellent energy dissipation and vibration suppression capabilities. This material has broad engineering application prospects in the fields of building sound insulation, automobile structure noise reduction and high-frequency industrial equipment shock absorption, and provides a new theoretical basis and experimental support for the development of sustainable vibration and noise reduction materials. Microcrystalline cellulose ; Composite material ; Materials science ; Crystallization ; Isotropy ; Reduction (mathematics) ; Vibration ; Cellulose ; Noise reduction ; Noise (video) ; Chemical engineering ; Acoustics ; Mathematics ; Computer science ; Engineering ; Physics ; Geometry ; Optics Natural Fiber Reinforced Composites ; Advanced Cellulose Research Studies ; biodegradable polymer synthesis and properties
Authors: Timothy Mulya Cahyana | Muhammad Akrom | Gustina Alfa Trisnapradika
Source: Jurnal Algoritma (article, 2025-11-30)
Field: Materials Science — Materials Chemistry

Perbandingan Model Ensemble untuk Memprediksi Efisiensi Penghambatan Korosi Senyawa N-Heterosiklik Penelitian ini mengevaluasi dan membandingkan efektivitas berbagai model regresi ensemble dalam memprediksi Corrosion Inhibition Efficiency (CIE) dari senyawa N-heterosiklik. Model-model yang dievaluasi adalah Extra Trees Regressor, Random Forest Regressor, Light Gradient Boosting Regressor, Gradient Boosting Regressor, Extreme Gradient Boosting Regressor, Adaptive Boosting Regressor, Bagging Regressor, dan Categorical Boosting Regressor, menggunakan fitur molekul seperti highest occupied molecular orbital (HOMO), lowest unoccupied molecular orbital (LUMO), celah energi (Delta E), momen dipol (mu), potensi ionisasi (I), afinitas elektron (A), keelektronegatifan (chi), kekerasan global (eta), kelembutan global (sigma), elektrofilisitas (omega), dan fraksi elektron yang ditransfer (Delta N). Di antara model yang dievaluasi, Extreme Gradient Boosting Regressor memberikan kinerja terbaik, dengan skor R-squared (R2) tertinggi sebesar 0.9776. Temuan ini menunjukkan efektivitas model ensemble dalam meningkatkan akurasi prediksi inhibisi korosi dan pentingnya pembelajaran mesin dalam mengembangkan inhibitor korosi yang lebih baik. Boosting (machine learning) ; Gradient boosting ; Ensemble learning ; AdaBoost ; Random forest Corrosion Behavior and Inhibition ; Machine Learning in Materials Science ; Computational Drug Discovery Methods