jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Samuel Ibezim Orjiocha | F. C. Eze | Mansour A.S. Salem | Anushree S. Bhat | Rabiya Mehndi | Hillary Onyeka Abugu | Vivian Chinekwu Onwujogu
Source: Discover Materials (article, 2025-10-14)
Field: Materials Science — Biomaterials

Plant-derived extracts for mitigating scale formation in pipelines and industrial systems: a review of status The application of plant materials in scaling industries is necessary, considering the environmental effects and cost implications of conventional anti-scalants. Plant materials are readily available, and most time, over 20% are disposed of as waste. Deploying its extracts will reduce the heavy cost incurred by procuring alternative scale inhibitors, improve farmers’ income, and reduce environmental fouls. To establish a technology for controlling or handling corrosion or scale depositions on solid surfaces, it is very important to understand the reactions of some parameters and their properties. Different search engines such as Scopus, Web of Science, were used to obtain the necessary data on different scaling parameters (surface roughness, wettability of the surface, the crystallization kinetics on the surface, deposition, surface induction time, the surface scaling based on the flow regime and the saturation rate) regarding the utilization of plant materials in industrial-scale deposition management. This literature assessment revealed that plant materials have substantial inhibitory tendency against the growth of CaCO3, CaSO4, and BaSO4 scales on any solid surface, with some of them showing up to 100 % inhibiting efficiency. Agro-materials that are reportedly rich in phenolics, tannins, alkaloids, saponins, and other foaming agents have a greater inhibiting tendency. Scaling ; Pipeline transport ; Corrosion ; Wetting ; Scale (ratio) ; SCALE-UP Calcium Carbonate Crystallization and Inhibition ; Minerals Flotation and Separation Techniques ; Metal Extraction and Bioleaching
Authors: Hemiao Wang | Guanlin Huo | G. F. Xu | Dehai Yu | Shanshan Liu | Qiang Wang
Source: Polymers (review, 2025-11-03)
Field: Materials Science — Biomaterials

Flexible Intelligence on a Green Skeleton: Progress and Challenges of CNF-Enabled Multimodal Sensing Platforms Cellulose nanofibrils (CNFs) provide a green scaffold for next-generation flexible sensors. They unite abundance, mechanical robustness, biocompatibility, and an easily engineered surface. This review synthesizes advances from the past five years in low-carbon CNF manufacturing. We cover biomass pretreatment, high-solid mechanical fibrillation, and in situ functionalization. We then elucidate mechanisms that govern CNF films, aerogels, and double-network hydrogels used across humidity, temperature, strain/pressure, optical, electrochemical, and biosensing platforms. Particular attention is given to multiscale conductive networks, surface-charge regulation, and reversible dynamic crosslinking. Together, these motifs raise sensitivity, widen the linear response windows, and strengthen environmental tolerance. We interrogate bottlenecks that impede scale-up, including energy demand, batch-to-batch variability, and device-level integration. We also assess prospects for deep-eutectic-solvent recycling, roll-to-roll digital printing, and algorithm-guided structural design. Finally, we outline directions for self-healing and self-powered biomimetic architectures, fully degradable life-cycle design, and integrated "sense-store-compute" nodes. These analyses chart a credible path from laboratory discovery to industrial deployment of CNF-based sensing technologies. Software deployment ; Cover (algebra) ; Structural health monitoring ; Biomimetics ; Suite ; Biocompatible material ; Path (computing) Advanced Cellulose Research Studies ; Advanced Sensor and Energy Harvesting Materials ; Carbon and Quantum Dots Applications
Authors: F. L. Kherfane | A. BOUKRAA | B. Beladel | A. Douara | I. E. Tibermacine | A. Rabehi | M. Benghanem
Source: Journal of the Nigerian Society of Physical Sciences (article, 2025-11-05)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Structural, electronic and optical properties of theFeAs&lt;sub&gt;(1-x)&lt;/sub&gt;La&lt;sub&gt;(x)&lt;/sub&gt; ternary alloys: A first principles calculations This study investigates the structural, electronic, and optical properties of FeAs(1-x)La(x) alloys (x = 0, 0.25, 0.5, 0.75, 1) using the FP-LAPW method within the framework of density functional theory (DFT). The lattice parameter, bulk modulus, and its derivative were determined through Murnaghan’s equation of state, revealing deviations from Vegard's law with increasing lanthanum concentration. Analysis of the electronic band structure and refractive indices highlights changes in the band gap, while energy-volume relationships indicate stability in the Zinc-Blende structure. Further exploration of the orthorhombic phase is suggested to confirm the structural properties. Doping FeAs with rare-earth elements introduces significant challenges due to disparities in ionic size, charge, and chemical behavior, yet it can profoundly impact structural, electronic, and superconducting properties such as charge carrier density and lattice parameters. The results emphasize the importance of precise control over doping concentrations and preparation techniques to achieve stable compounds. This theoretical work underscores the potential of FeAs-based materials for advanced applications, paving the way for further experimental validation. Ternary operation ; Orthorhombic crystal system ; Density functional theory ; Doping ; Electronic band structure ; Ionic bonding ; Electronic structure ; Lattice (music) ; Lanthanum Iron-based superconductors research ; Heusler alloys: electronic and magnetic properties ; Electronic and Structural Properties of Oxides
Authors: Luka Benić | Federico Grasselli | Chiheb Ben Mahmoud | Dino Novko | Ivor Lončarić
Source: Journal of Chemical Theory and Computation (article, 2025-08-18)
Field: Materials Science — Materials Chemistry

Machine Learning Model for Efficient Nonthermal Tuning of the Charge Density Wave in Monolayer NbSe<sub>2</sub> Understanding and controlling the charge density wave (CDW) phase diagram of transition-metal dichalcogenides are long-studied problems in condensed matter physics. However, due to the complex involvement of electron and lattice degrees of freedom and pronounced anharmonicity, theoretical simulations of the CDW phase diagram at the density-functional-theory level are often numerically demanding. To reduce the computational cost of first-principles modeling by orders of magnitude, we have developed an electronic free-energy machine learning model for monolayer NbSe<sub>2</sub> that allows us to control the electronic temperature as a parameter of the model. The ionic temperature is modeled via the stochastic self-consistent harmonic approximation. Our approach relies on a machine learning model of the electronic density of states and zero-temperature interatomic potential. This allows us to explore the CDW phase diagram of monolayer NbSe<sub>2</sub> both under thermal and laser-induced nonthermal conditions. Our study provides an accurate estimate of the CDW transition temperature at low cost and can disentangle the role of hot electrons and phonons in the nonthermal ultrafast melting process of the CDW phase in NbSe<sub>2</sub>. Monolayer ; Charge (physics) ; Charge density wave ; Computer science ; Charge density ; Materials science ; Physics ; Nanotechnology ; Condensed matter physics ; Quantum mechanics ; Superconductivity Machine Learning in Materials Science ; 2D Materials and Applications ; Molecular Junctions and Nanostructures
Authors: Sara Tanovic | Ewa Wieczorek | Fernanda Duarte
Source: Digital Discovery (article, 2025-12-29)
Field: Materials Science — Materials Chemistry

An exploration of dataset bias in single-step retrosynthesis prediction We investigate how the size and diversity of training datasets influence various single-step retrosynthesis models. Accuracy is primarily affected by template frequency, and models show limited generalisation, highlighting a fundamental class-imbalance problem in retrosynthesis prediction. Retrosynthetic analysis ; Training set ; Diversity (politics) ; Field (mathematics) ; Training (meteorology) Machine Learning in Materials Science ; Catalysis and Oxidation Reactions ; Synthetic Organic Chemistry Methods
Authors: Yekbun Avşar Teymur | Fuat Güzel
Source: Research Square (preprint, 2025-06-02)
Field: Chemistry — Organic Chemistry

WITHDRAWN: Green synthesis of a novel CuFe2O4@activated carbon magnetic nanocomposite from black seed (Nigella sativa L.) industrial processing waste: Physicochemical properties and sorption behavior toward oxytetracycline hydrochloride antibiotic Sorption ; Nigella sativa ; Nanocomposite ; Oxytetracycline ; Chemistry ; Nuclear chemistry ; Pulp and paper industry ; Materials science ; Organic chemistry ; Antibiotics ; Nanotechnology ; Engineering ; Adsorption ; Traditional medicine ; Medicine ; Biochemistry Nanomaterials for catalytic reactions ; Nigella sativa pharmacological applications
Authors: Vinod Kumar Enugala
Source: International Journal of Computational and Experimental Science and Engineering (article, 2025-07-16)
Field: Materials Science — Materials Chemistry

Quantum Sensors for Micro-Corrosion Detection Quantum magnetometry holds the potential for non-destructive monitoring of micro-corrosion. The proposed study combines narrow-field-of-view nitrogen-vacancy (NV) diamond imaging with cryogenic imaging scanning superconducting quantum interference devices (SQUIDs) and machine-learning analytics to benchmark the detection precision against classical methods. Two hundred eighty ASTM A36 steel coupons were subjected to 0-168 hours of neutral salt spray, and dual-mode sensors collected 12 TB of magnetic data, which was then denoised, dimensionally reduced, and classified by a convolutional neural network. Galvanic currents were resolved on the platform with a spatial resolution of 0.1 0.5 ( 1 ) and sensitivity to sub-nanotesla, rapid detection of 50 % of 5 (m) pits in 3.8 (h) relative to 22 (h) galvanic current using the electrochemical-impedance spectroscopies and ultrasonic shear-wave probes. The F1-score was 0.953, the Matthews correlation coefficient 0.91, and the ROC-AUC 0.987 in quantitative performance, even though the classes were so severely imbalanced. In 87% of the scans, morphological fidelity and inversion reliability were confirmed by two bespoke indicators: Magnetic Gradient Integrity (MGI) and Gradient-to-Noise Ratio (GNR). The Kaplan-Meier Kaplan-Meier and Bayesian hazard modeling showed that the early warning would accelerate by 6 times, and the estimated lifetime cost saving would be 24% of a typical offshore pipeline. The major weaknesses were caused by weld-spatter magnetization and a temperature-dependent NV contrast drift, which were improved using spatial-frequency masking and adaptive laser control. Plans involve fiber-coupled sub-millimeter-scale NV probes, high-temperature SQUID arrays, and edge-ASIC inference to provide certified, perpetual positioning quantum diagnostics for aviation, petrochemical, and maritime assets. Simultaneously, an open Magnetic Corrosion Image (MCI) data standard and FAIR repository will enable regulatory vetting and algorithm comparison. Long-term. Long-term field tests on flow lines offshore and aircraft fuselages in retirement will prove her ability, reliability, and overall cost-of-ownership estimates. Materials science ; Magnetometer ; Quantum sensor ; Magnetic field ; Computer science ; Physics ; Quantum ; Quantum computer ; Quantum simulator Diamond and Carbon-based Materials Research ; High-pressure geophysics and materials ; Metal and Thin Film Mechanics
Authors: Sihui Guo | Zhengling Yang
Source: ArXiv.org (preprint, 2025-12-11)
Field: Materials Science — Materials Chemistry

Infusing Experimental Reality into Complex Many-Body Hamiltonians: The Observable-Constrained Variational Framework (OCVF) Deep learning potentials for complex many-body systems often face challenges of insufficient accuracy and a lack of physical realism. This paper proposes an "Observable-Constrained Variational Framework" (OCVF), a general top-down correction paradigm designed to infuse physical realism into theoretical "skeleton" models (H_o) by imposing constraints from macroscopic experimental observables (\mathfrak{O}_{\text{exp},s}). We theoretically derive OCVF as a numerically tractable extension of the "Constrained-Ensemble Variational Method" (CEVM), wherein a neural network (ΔH_θ) learns the correction functional required to match the experimental data. We apply OCVF to BaTiO3 (BTO) to validate the framework: a neural network potential trained on DFT data serves as H_o, and experimental PDF data at various temperatures are used as constraints (\mathfrak{O}{\text{exp},s}). The final model, H_o + ΔH_θ, successfully predicts the complete phase transition sequence accurately (s', s \neq s'). Compared to the prior model, the accuracy of the Cubic-Tetragonal (C-T) phase transition temperature is improved by 95.8\% , and the Orthorhombic-Rhombohedral (O-R) T_c accuracy is improved by 36.1\%. Furthermore, the lattice structure accuracy in the Rhombohedral (R) phase is improved by 55.6\%, validating the efficacy of the OCVF framework in calibrating theoretical models via observational constraints. Observable ; Artificial neural network ; Experimental data ; Phase transition ; Sequence (biology) ; Lattice (music) ; Representation (politics) Machine Learning in Materials Science ; Quantum many-body systems ; Model Reduction and Neural Networks
Authors: Naeemeh Yasrebi | Jafarsadegh Moghaddas
Source: Research Square (preprint, 2025-09-01)
Field: Chemistry — Inorganic Chemistry

Optimization of Operational Parameters for Improved Light Olefin Production in Gasoil Cracking over HZSM-5 Catalyst: Temperature and Catalyst Loading Weight as Key Parameters Catalysis ; Cracking ; Olefin fiber ; Fluid catalytic cracking ; Key (lock) ; Materials science ; Production (economics) ; Fuel oil ; Chemical engineering ; Process engineering ; Waste management ; Composite material ; Chemistry ; Organic chemistry ; Computer science ; Engineering ; Economics ; Microeconomics Zeolite Catalysis and Synthesis ; Catalysis and Hydrodesulfurization Studies ; Catalytic Processes in Materials Science
Authors: Kunlin Shu | Changsong Zhou | Yongzhi Shang | Pengbo Wang | Jiacheng Xu | Pinghua Xu | Qiangqiang Ren | Hao Wu | Hongmin Yang
Source: Research Square (preprint, 2025-10-29)
Field: Chemistry — Inorganic Chemistry

K⁺-Doped Cu-BTC Achieves Doubled CO₂ Adsorption Capacity and Unprecedented Cycle Stability via Atomic-Scale "Rivet" Architecture Adsorption ; Ion ; Copper ; Slippage ; Ionic bonding ; Doping ; Density functional theory ; Chemical stability Metal-Organic Frameworks: Synthesis and Applications ; Carbon Dioxide Capture Technologies ; Covalent Organic Framework Applications
Authors: Wuxu Zhang | Ziyin Xiang | Tengfei Ma | Baoru Bian | Jinyun Liu | Yuanzhao Wu | Yiwei Liu | Jie Shang | Run-Wei Li
Source: Research Square (preprint, 2025-04-21)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Self-supported β-Ga2O3 nanowires and for stretchable solar-blind UV photodetectors Photodetector ; Nanowire ; Optoelectronics ; Materials science Ga2O3 and related materials ; Advanced Photocatalysis Techniques ; ZnO doping and properties
Authors: Maria Dimitrova | G. Hodjaoglu | S. Tanev | A. Miteva
Source:  (article, 2025-11-12)
Field: Materials Science — Materials Chemistry

RADIATION SHIELDING EFFICIENCY OF TITANIUM ALLOYS AND COMPOSITES FOR NEAR-SPACE APPLICATIONS Spacecraft and satellite materials are continuously exposed to ionizing radiation from solar and cosmic sources. These high-energy particles can induce material degradation, reduce mechanical strength and affect the performance of sensitive onboard equipment. This paper investigates the radiation shielding performance of titanium alloys and titanium-based composites as potential materials for near-space and low Earth orbit applications. The study evaluates the attenuation capacity, structural stability and radiation- induced microstructural changes of selected titanium alloys compared to conventional aluminum alloys. The results contribute to the development of lightweight and durable shielding solutions that enhance spacecraft longevity and safety in radiation-rich environments. Electromagnetic shielding ; Radiation shielding ; Titanium alloy ; Titanium ; Aluminium ; Attenuation ; Radiation Silicone and Siloxane Chemistry ; Radiation Shielding Materials Analysis ; Spacecraft Design and Technology
Authors: C.A. León‐Patiño | Pablo Díaz | N. Vidal-Silva | Eduardo Cisternas | Eugenio Vogel | Fabian Dietrich
Source: ArXiv.org (preprint, 2025-12-10)
Field: Materials Science — Materials Chemistry

Theoretical Characterization of the Magnetic Properties of Vanadium-doped Ti2C MXenes MXenes are two-dimensional materials composed of transition metals and light elements, known for their high conductivity and versatile surface chemistry. The introduction of spin centers via doping can lead to promising materials for spintronics, magnetic sensing, and data storage. We study the effect of V doping in Ti2C using first principle and Monte-Carlo simulations. Our results show that pristine Ti2C exhibits ferromagnetic intralayer and antiferromagnetic interlayer exchange interactions, yielding an antiferromagnetic ground state. Vanadium incorporation alters these couplings, yet all doped configurations - Ti7VC4 and three Ti6V2C4 variants - retain predominantly antiferromagnetic order. Despite the preserved ground state, V doping enhances the magnetic response, most notably in the p-Ti6V2C4 configuration, which displays increased low-field susceptibility and partial spin alignment across layers. As experimentally isolating individual doped phases is unlikely, samples will consist of mixed configurations whose collective behavior nonetheless exhibits clear signatures of V-induced magnetic modification. These results reveal how transition-metal substitution tunes exchange interactions in MXenes and offer guidance for engineering their magnetic functionalities. MXenes ; Antiferromagnetism ; Ferromagnetism ; Doping ; Characterization (materials science) ; Ground state ; Vanadium ; Spin (aerodynamics) MXene and MAX Phase Materials ; 2D Materials and Applications ; Electromagnetic wave absorption materials
Authors: Anggara Mahatma Wicaksono | Eva Arifi | Devi Nuralinah
Source: Evergreen (article, 2025-12-01)
Field: Materials Science — Polymers and Plastics

NSM Polyester-Reinforced Albizia chinensis Beams: Flexural Performance Evaluation This study investigates the flexural performance of Albizia chinensis wood beams strengthened using Near Surface Mounted (NSM) polyester resin under four-point bending tests.The primary objective of this study is to evaluate the enhancement in flexural behavior due to the addition of NSM polyester reinforcement.Three beam configurations were tested: unreinforced (TO), single-groove reinforced (TPSE), and double-groove reinforced (TPR).The strengthening process involved embedding polyester resin into pre-cut grooves on the beam surface, where the resin served as both adhesive and filler for bonding the reinforcement with the wood substrate.The experimental results demonstrate that beams reinforced with NSM polyester exhibit higher load capacity and improved stiffness.Specifically, the TPR specimen achieved an increase in the ultimate load of more than 30% compared with the TO specimen.Furthermore, the use of polyester resin as an infill material in the grooves effectively bonded the reinforcement to the surrounding wood matrix.This not only contributed to improved mechanical performance but also showed promise due to its ease of application and cost-effectiveness.The strain distribution in the reinforced specimens suggested a more favorable deformation profile, especially in TPR.Additionally, cyclic testing on the reinforced beams revealed enhanced resilience against repeated loading, making the reinforcement system suitable for dynamic conditions.The results were validated using a theoretical flexural strength estimation based on section modulus and characteristic strength of Albizia chinensis wood.The findings further confirm the feasibility of using polyester as an effective shear reinforcement in structural timber applications, especially in low-cost rural construction.The study concludes that NSM polyester reinforcement is effective in improving the flexural performance of Albizia chinensis wood beams and offers a practical alternative for timber strengthening in engineering practice. Flexural strength Natural Fiber Reinforced Composites ; Cellular and Composite Structures ; Structural Behavior of Reinforced Concrete
Source: International Journal of Progressive Research in Engineering Management and Science (article, 2025-06-18)
Field: Materials Science — Materials Chemistry

Recent Advances in Green Synthesis of Nanoparticles Using Plant Extracts The green synthesis of nanoparticles (NPs) using plant extracts has emerged as an environmentally benign and sustainable alternative to conventional physical and chemical methods.This approach leverages the reducing and stabilizing agents naturally present in plants to produce metal and metal oxide nanoparticles with controlled shapes and sizes.The methodology aligns with principles of green chemistry, offering advantages like cost-effectiveness, biocompatibility, and eco-friendliness.In recent years, significant progress has been made in understanding the role of phytochemicals in nanoparticle formation, optimizing synthesis parameters, and exploring biomedical, environmental, and agricultural applications.This review highlights the latest trends, mechanisms, plant species employed, characterization techniques, and application areas, while presenting comparative data in tabular formats and incorporating up-to-date references. Nanoparticle ; Nanotechnology ; Chemistry ; Traditional medicine ; Materials science ; Medicine Nanoparticles: synthesis and applications ; Nanomaterials for catalytic reactions