jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: K. Otsuka | R. Fujiwara | S. Maruyama
Source: ArXiv.org (article, 2026-01-07)
Field: Materials Science — Materials Chemistry

Robust chirality memory in carbon nanotubes growing under modulated and evolving environments Controlling the chirality and yield of carbon nanotubes is essential for their diverse applications from macroscopic composites to nanoelectronics. Floating-catalyst chemical vapor deposition is widely employed as a scalable synthesis route, where catalysts inevitably traverse spatially varying environments. However, prevailing interpretations of nanotube growth largely rely on ensemble monitoring or static, post-growth snapshots. Here, we combine digital isotope labeling with programmed temperature modulation to reconstruct the dynamic growth histories of supported individual nanotubes. Growth rates exhibit hysteresis and extraordinary sensitivity to temperature changes, indicating irreversible catalyst coarsening; nevertheless, the nanotube chirality remains robustly preserved across lengths exceeding 300 um. This sharp contrast between kinetic adaptability and structural memory in nanotube growth indicates that chirality control can be established at the nucleation stage, while allowing independent optimization of subsequent elongation. Our findings further call for a re-examination of static interpretations of diameter-determination mechanisms derived from post-growth snapshots. Chirality (physics) ; Carbon nanotube ; Nanotube ; Nucleation ; Hysteresis ; Chemical vapor deposition ; Kinetic control Carbon Nanotubes in Composites ; Chemical and Physical Properties of Materials ; Zeolite Catalysis and Synthesis
Authors: Tsukasa Irie | Saikat Das | Yuichi Negishi
Source: Nanoscale Horizons (article, 2026-01-01)
Field: Materials Science — Materials Chemistry

Covalent organic frameworks as precision nanocarriers for targeted drug delivery: developments, hurdles, and horizons Covalent organic frameworks (COFs) have emerged as a versatile class of crystalline reticular materials distinguished by their high surface area, permanent porosity, and atomically precise structural tunability. Their modular synthesis enables precise control over pore size, geometry, and surface functionality, while offering excellent chemical stability and intrinsic biocompatibility. These attributes make COFs uniquely suited for applications as precision nanocarriers in targeted drug delivery. Recent advances demonstrate that COFs can encapsulate therapeutic agents with high loading efficiency and facilitate controlled, stimuli-responsive release profiles. Furthermore, the incorporation of targeting moieties through linker design or post-synthetic modification enables site-specific delivery, minimizing off-target cytotoxicity and enhancing therapeutic efficacy-particularly in oncological contexts. This review critically evaluates the current landscape of COF-based drug delivery systems, detailing structural design strategies, loading and release mechanisms, and functionalization approaches for precision targeting. We also highlight key challenges-such as scalable synthesis, pharmacokinetics, and <i>in vivo</i> stability-and outline promising research directions toward the clinical translation of COF nanocarriers for personalized medicine. Nanocarriers ; Surface modification ; Linker ; Drug delivery ; Targeted drug delivery ; Modular design ; Nanomedicine Covalent Organic Framework Applications ; Advanced Photocatalysis Techniques ; Metal-Organic Frameworks: Synthesis and Applications
Authors: Yong Zhang | Yongqiang Lan | Faze Jin | Guang Li
Source: Coatings (article, 2026-02-25)
Field: Materials Science — Materials Chemistry

Y3+-Stabilized Zirconia (YSZ) Coatings for Protection Against Water Vapor Corrosion To enhance the protection of zirconium alloys during loss-of-coolant accident conditions, the water vapor corrosion resistance of Y3+-stabilized zirconia coatings fabricated by plasma electrolytic oxidation on zirconium alloy was remarkably improved in this study. The corrosion resistance mechanisms of the coating were disclosed by simulating water vapor reaction processes in cubic zirconia (c-ZrO2) and tetragonal zirconia (t-ZrO2). The results revealed that the mass fraction of c-ZrO2 in the coatings was increased from 9% to 32% by adjusting the Y3+ concentration. The mass gain and corrosion rate of the enhanced coating were approximately 60% and 37% after 3600 s water vapor corrosion at 1000 °C separately compared to those of traditional zirconia coating. This enhancement is attributed to the slower reaction rates of c-ZrO2 with water vapor than t-ZrO2, which suppresses corrosion and reduces the formation of Zr(OH)4. Thus, less cracks appeared in coatings with higher c-ZrO2 fractions, as their corrosion layers contained fewer corrosion products that induced stress concentration, which, in turn, protects the subsurface coatings from further corrosion. This study provides a viable strategy for developing coatings to protect zirconium alloys against water vapor corrosion in nuclear energy applications. Corrosion ; Cubic zirconia ; Water vapor ; Zirconium ; Coating ; Alloy Nuclear Materials and Properties ; Magnesium Alloys: Properties and Applications ; High-Temperature Coating Behaviors
Authors: Simon Hall
Source: CrystEngComm (article, 2026-01-01)
Field: Materials Science — Materials Chemistry

Still life – fast moving: a kinetic view of crystal growth This highlight review article shows how modern imaging and far-from-equilibrium experiments deepen our understanding of the kinetics of crystal growth. Crystal growth ; Kinetic energy ; Kinetics ; Crystal (programming language) ; Still life Solidification and crystal growth phenomena ; nanoparticles nucleation surface interactions ; Crystallization and Solubility Studies
Authors: Trinadh Ballanki | A. Subramanian | Vaishnu Suresh Kumar | Mohit Garg | Pravin Chinnappa | Jebiti Haribabu | Daniel Moraga | Baby Viswambharan
Source: ChemRxiv (article, 2026-01-13)
Field: Chemistry — Organic Chemistry

Potassium Hydrogen Sulfate - Promoted One-pot Synthesis of Bis(indolyl)alkane Esters from α-Keto Carboxylic Acids: In Silico and In Vitro Anticancer Studies Sustainable and efficient synthetic strategies for bioactive bis and tris(indolyl) alkane (BIM and TIM) derivatives remain a central challenge because of their acid sensitivity. Herein, we demonstrate an eco-friendly synthesis of 3,3′-bisindolylalkane esters from α-keto carboxylic acids and indoles employing potassium hydrogen sulfate as a green promoter, with methanol acting as both reagent and solvent, in excellent yields. Beyond that, the methodology was further extended to the esterification of α-keto carboxylic acids and N-protected L-amino acid derivatives. Synthetic applications of the developed methodology were demonstrated in the concise total synthesis of Streptindole and Arsindoline B, a bioactive natural product. Complementary computational investigations, including SwissADME analyses, DFT, MEP, molecular docking, and MD simulations, demonstrated promising pharmacokinetic profiles, favourable electronic properties, and strong EGFR binding affinities, highlighting the potential of selected novel compounds as effective anticancer agents. Guided by these in silico predictions, experimental anticancer evaluation using in vitro MTT assays identified compound C26 as the most potent and selective derivative against A549 and T24 cancer cell lines, with reduced toxicity toward normal MCF-10a cells, underscoring its potential as a promising anticancer lead. In silico ; In vitro ; Carboxylic acid ; Reagent ; MTT assay ; Methanol ; Chemical synthesis ; Potassium Synthesis of Indole Derivatives ; Multicomponent Synthesis of Heterocycles ; Synthesis and biological activity
Authors: Zilin Qu | En Yang | Mustafa Zeb | Jian Zhu | Yoonseob Kim | Janine Magalhães Guedes Simão | Wei Ma
Source: Agricultural Products Processing and Storage (article, 2026-04-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

SERS-active nanostructures for food microorganisms and toxins biosensing: compositional tailoring, structural regulation, and signal amplification Surface-enhanced Raman spectroscopy (SERS) has gained prominence as an effective technique for identifying pathogens and toxins in food products. This is attributed to its remarkable sensitivity, swift detection speed, and precise identification capacity. This paper reviews the latest developments in the field of SERS-based biosensors for food safety, highlighting the design of SERS-active nanomaterials and their role in sensing a wide range of foodborne microorganisms and microbial toxins. We discuss the synthesis methods for single-component and multi-component nanomaterials, strategies for structural regulation of SERS-active materials, and the unique advantages of SERS in detecting pathogens such as Staphylococcus aureus, Salmonella, Escherichia coli, etc. and related toxins. Additionally, we highlight the integration of SERS with artificial intelligence (AI) for enhanced detection efficiency and accuracy. The combination of advanced nanomaterials and SERS technology has shown great potential in improving the effectiveness and precision of food safety testing, with broad application prospects in complex food matrices. Nanomaterials ; Food safety ; Biosensor ; Identification (biology) ; Microorganism ; Food microbiology Gold and Silver Nanoparticles Synthesis and Applications ; Biosensors and Analytical Detection ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Qiudi Lu | Yudong Zhang | Xingyu Wu | Weijia Zong | Xiao Xiao | Jiahui Li
Source: Journal of Intelligent Material (article, 2026-02-05)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Soft Magnetoelastic Generators Advances in Energy Harvesting and Sensing A new class of soft energy harvesters, known as magnetoelastic generators (MEGs), has been made possible by the giant magnetoelastic effect. These generators can efficiently convert low-frequency and irregular mechanical stimuli into electricity. This review summarises the mechanism of magnetoelastic coupling and recent progress in soft magnetic composites, flexible architectures, and bio-inspired designs. We focus on the application of MEGs in some specific fields, such as wearable electronics, self-powered sensing, acoustic energy harvesting, and blue energy systems, demonstrating their unique advantages over traditional harvesters. Despite the rapid advances, there are still some challenges remain in improving energy density, such as how to improve energy density, maintain long-term stability, realize large-scale manufacturing, and do a good job in system-level power management. Finally, we point out the important opportunities and future directions, hoping to help develop and integrate the next generation magnetoelastic energy system. Energy harvesting ; Wearable computer ; Energy (signal processing) ; Mechanical energy ; Point (geometry) ; Electricity generation ; Magnetostriction ; Power (physics) Multiferroics and related materials ; Innovative Energy Harvesting Technologies ; Shape Memory Alloy Transformations
Authors: H. M. Ragab | N. S. Diab | Rosilah Ab Aziz | Shimaa Mohammed Aboelnaga | Ammar Qasem | A. Al Ojeery | M. O. Farea
Source: Scientific Reports (article, 2026-03-02)
Field: Materials Science — Polymers and Plastics

Enhanced optical and electrical properties of polyvinyl alcohol polyethylene oxide nanocomposite films incorporating hybrid carbon nanofillers This work reports the fabrication and characterization of PVA/PEO-based nanocomposite films reinforced with a synergistic combination of graphene nanoplates (GNPs) and multi-walled carbon nanotubes (MWCNTs) using a modified solution casting method. Structural analysis revealed that the incorporation of carbon nanofillers effectively reduced the crystallinity of the polymer blend, promoting an amorphous structure favorable for charge transport. FTIR results confirmed strong interactions between the polymer matrix and the nanofillers. Optical investigations showed a systematic narrowing of the optical band gap and an enhancement in the refractive index with increasing nanofiller content, indicating significant modification of the electronic structure. In addition, the nanocomposite films exhibited markedly improved AC electrical conductivity and dielectric performance due to the formation of an interconnected conductive network and enhanced interfacial polarization. The combined enhancement in optical and electrical properties highlights the effectiveness of the synergistic MWCNTs/GNPs reinforcement strategy. These results demonstrate that the developed PVA/PEO nanocomposite films are promising candidates for advanced optoelectronic devices, energy storage systems, and flexible electronic applications. Nanocomposite ; Graphene ; Crystallinity ; Carbon nanotube ; Polyvinyl alcohol ; Dielectric ; Casting ; Band gap ; Polymer nanocomposite Polymer Nanocomposite Synthesis and Irradiation ; Conducting polymers and applications ; Carbon Nanotubes in Composites
Authors: Saurabh Tiwari | K. Dash | Seongjun Heo | Nokeun Park | N.S. Reddy
Source: Crystals (article, 2026-01-15)
Field: Materials Science — Materials Chemistry

Machine Learning-Driven Prediction of Microstructural Evolution and Mechanical Properties in Heat-Treated Steels Using Gradient Boosting Optimizing heat treatment processes requires an understanding of the complex relationships between compositions, processing parameters, microstructures, and properties. Traditional experimental approaches are costly and time-consuming, whereas machine learning methods suffer from critical data scarcity. In this study, gradient boosting models were developed to predict microstructural phase fractions and mechanical properties using synthetic training data generated from an established metallurgical theory. A 400-sample dataset spanning eight AISI steel grades was created based on Koistinen–Marburger martensite kinetics, the Grossmann hardenability theory, and empirical property correlations from ASM handbooks. Following systematic hyperparameter optimization via 5-fold cross-validation, gradient boosting achieved R2 = 0.955 for hardness (RMSE = 2.38 HRC), R2 = 0.949 for tensile strength (RMSE = 87.6 MPa), and R2 = 0.936 for yield strength, outperforming the Random Forest, Support Vector Regression, and Neural Networks by 7–13%. Feature importance analysis identified the tempering temperature (38.4%), carbon equivalent (15.4%), and carbon content (13.0%) as the dominant factors. Model predictions demonstrated physical consistency with the literature data (mean error of 1.8%) and satisfied the fundamental metallurgical relationships. This methodology provides a scalable and cost-effective approach for heat treatment optimization by reducing experimental requirements based on learning curve analysis while maintaining prediction accuracy within the measurement uncertainty. Gradient boosting ; Hyperparameter ; Tempering ; Artificial neural network ; Boosting (machine learning) ; Ultimate tensile strength ; Martensite Machine Learning in Materials Science ; Microstructure and Mechanical Properties of Steels ; Additive Manufacturing Materials and Processes
Authors: Zheyong Fan | Wenjun Zhang | Zhang, Zhenhao | Ke Xu | Xuecheng Shao | Haikuan Dong
Source: arXiv (Cornell University) (article, 2026-03-01)
Field: Materials Science — Materials Chemistry

NEP-CG and NEP-AACG: Efficient coarse-grained and multiscale all-atom-coarse-grained neuroevolution potentials Machine-learned coarse-grained (CG) models often suffer from noisy training data, limiting their accuracy and transferability. We propose a method to generate low-noise training data based on the potential of mean force by constraining CG beads during atomistic simulations and accumulating time-averaged forces. Implemented within the neuroevolution potential (NEP) framework, our approach achieves training accuracy comparable to atomistic models trained on density functional theory data. For liquid water, the NEP-CG model accurately reproduces densities from 1 bar to 1 GPa, successfully extrapolating beyond the 0.5 GPa training limit, with a virial correction essential for the correct equation of state. For an anisotropic C$_{60}$ monolayer, distinguishing crystallographically distinct bead types reduces stress errors by an order of magnitude and captures directional thermal conductivity. We further introduce a multiscale NEP-AACG model integrating all-atom (AA) and CG degrees of freedom, demonstrated for gold nanowire fracture at an experimentally relevant strain rate. Computational speeds for NEP-CG models reach hundreds to thousands of ns/day using a single consumer-grade GPU. This work provides a robust framework for constructing accurate, transferable, and efficient CG models across diverse systems. Limiting ; Work (physics) ; Anisotropy ; Multiscale modeling ; Robustness (evolution) ; Bar (unit) ; Observable ; Inverse problem Machine Learning in Materials Science ; Block Copolymer Self-Assembly ; Advanced Electron Microscopy Techniques and Applications
Authors: G. Yu. Korobov | М. К. Рогачев | Vladislav Krylov
Source: Eng—Advances in Engineering (article, 2026-03-02)
Field: Chemistry — Analytical Chemistry

Mechanisms of Asphaltene–Resin–Paraffin Deposit Formation and Prevention in Oil Production: From Physicochemical Processes to Inhibition and Delivery Strategies Asphaltene–resin–paraffin deposits (ARPDs) represent one of the most complex flow assurance challenges in oil production, particularly under late-stage reservoir development conditions characterized by pressure depletion, temperature gradients, multiphase flow, and compositional changes. Despite extensive industrial experience, ARPD control strategies are often applied empirically, without explicit linkage to the underlying physicochemical mechanisms governing deposit formation. This review presents a comprehensive and mechanism-oriented analysis of ARPD formation and mitigation in a reservoir–wellbore system. The multicomponent composition, structural heterogeneity, and interfacial activity of paraffins, resins, and asphaltenes are examined alongside thermodynamic, hydrodynamic, and operational factors controlling precipitation, transport, adhesion, and deposit growth. Particular attention is paid to the correspondence between ARPD formation stages and applicable prevention or removal technologies. The analysis demonstrates that preventive strategies targeting early-stage physicochemical processes are fundamentally more effective than post-formation removal methods. The mechanisms of inhibitor action—adsorption, desorption, and dissolution—are shown to operate in a complementary manner, while delivery efficiency is strongly influenced by spatial distribution and retention in the formation. Advanced delivery technologies, including microencapsulation and nanocarrier-based systems, provide enhanced control over inhibitor release and persistence under complex reservoir conditions. Overall, this review establishes an integrated framework linking crude oil properties, formation mechanisms, inhibition chemistry, and delivery technologies, providing a rational basis for designing adaptive and efficient ARPD mitigation strategies in modern oil production systems. Enhanced oil recovery ; Oil production ; Petroleum industry ; Asphaltene ; Control (management) ; Lead (geology) ; Production (economics) Petroleum Processing and Analysis ; Enhanced Oil Recovery Techniques ; Hydrocarbon exploration and reservoir analysis
Authors: Tim Benjamin Riemer | Anna Kampwerth | Tim Sinnhoffer | Moritz Prange | Marc Häusler | Dieter Vogt | Thomas Seidensticker
Source: Green Chemistry (article, 2026-01-01)
Field: Chemistry — Inorganic Chemistry

Next-generation multiphase systems for homogeneous catalyst recycling: overcoming the reactivity <i>vs.</i> separation dilemma A new generation of thermomorphic multiphase systems combines key advantages of homogeneous catalyst recycling: reactions proceed under monophasic conditions in green solvents, avoiding mass-transfer limitations and the need for extraction solvents. Homogeneous ; Catalysis ; Reactivity (psychology) ; Homogeneous catalysis ; Mass transport ; Heterogeneous catalysis ; Work (physics) ; Mixing (physics) Zeolite Catalysis and Synthesis ; Catalysis for Biomass Conversion ; Microwave-Assisted Synthesis and Applications
Authors: Masuk Abdullah | Joao Vitor de Andrade Porto | Husi Géza
Source: Discover Mechanical Engineering (article, 2026-02-23)
Field: Chemistry — Spectroscopy

Engineering integration of graphene aerogels in aerospace mechanics current state of research and future application Graphene aerogel is an ultralight material with outstanding thermal, electrical, and mechanical properties, which positions it as a promising candidate for advanced aerospace engineering applications. Recent advances in additive manufacturing, including three-dimensional printing and bio-inspired fabrication strategies, have enabled the design of architected graphene aerogel structures that draw on hierarchical and cellular architectures found in natural systems. By translating biological structural principles into engineered materials, bio-inspired design allows precise control over porosity, load transfer, and functional grading, thereby enhancing strength-to-weight ratios, energy dissipation, and multifunctional integration, all of which are critical requirements for aerospace structures. This review examines the convergence of graphene aerogel research with these advanced fabrication approaches, highlighting their implications for structural efficiency, weight reduction, and the integration of sensing and electromagnetic interference (EMI) shielding functionalities. Despite persistent challenges related to mechanical fragility under extreme loading conditions, energy-intensive production routes, and scalability constraints, reported properties such as ultra-low densities as low as 3.13 mg/cm3 and EMI shielding effectiveness of up to 87 dB at a thickness of 2.0 mm underscore the technological relevance of graphene aerogels. By synthesizing current literature and identifying key knowledge gaps, this work outlines critical research pathways grounded in bio-inspired design principles to advance the application of graphene aerogels in future aerospace structures. Aerospace ; Graphene ; Aerogel ; Electromagnetic shielding ; Fabrication ; Scalability Aerogels and thermal insulation ; Magnesium Oxide Properties and Applications ; Graphene research and applications
Authors: David Greten | Konstantin S. Jakob | Karsten Reuter | Johannes T Margraf
Source: ChemRxiv (article, 2026-02-13)
Field: Materials Science — Materials Chemistry

Benchmarking Local Geometry Optimization Algorithms for Computational Materials Discovery Most current computational materials discovery workflows are dependent on efficient and reliable structure relaxations in order to predict a hypothetical material's equilibrium structure.Besides an accurate description of the potential energy surface, this requires efficient and reliable optimization algorithms.In this study, we investigate how different optimization algorithms affect the relaxation of inorganic crystal structures using general-purpose machine-learned interatomic potentials (MLIPs).Our findings emphasize the critical role of optimizer selection in large-scale computational materials science workflows, particularly in the context of element-substitution based materials discovery.This can guide the community towards choosing appropriate algorithms for the efficient and reliable prediction of new crystalline materials. Benchmarking ; Optimization algorithm ; Minification ; Key (lock) ; Computational geometry Machine Learning in Materials Science ; Topological and Geometric Data Analysis ; Advanced Optimization Algorithms Research