jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Zhangjiao Li | Ao Peng | Lin WANG | Wenqiang Gao | Hanxing Liu | Weijia Zhou
Source: Chinese Science Bulletin (Chinese Version) (article, 2026-02-01)
Field: Materials Science — Materials Chemistry

Physics-Informed Soft Label Driven Prediction and Interpretable Modeling of Intrinsic Dielectric Breakdown Strength for Perovskites 钙钛矿材料因其独特的结构稳定性与组成可调性, 成为高电场耐受介电材料极具潜力的候选体系. 本征击穿强度(<i>F</i><sub>b</sub>)作为表征其击穿理论极限的参数, 存在计算成本高昂、标签数据严重匮乏等问题, 严重阻碍了该体系电场耐受机制研究与高理论击穿极限材料筛选. 针对上述问题, 本文提出一种物理可信软标签驱动的<i>F</i><sub>b</sub>预测建模框架. 基于现有高质量<i>F</i><sub>b</sub>标签的绝缘体数据集构建<i>F</i><sub>b</sub>高精度概率化预测模型后, 将其迁移至钙钛矿材料体系, 以生成含有不确定性量化的软标签. 基于此构建了监督可信度加权的<i>F</i><sub>b</sub>准确预测模型(验证集<i>R</i><sup>2</sup>= 0.8952), 并通过单特征主效应分析、特征间协同作用解析等方法, 对模型内部决策逻辑进行可视化分析, 确保预测结果的物理可信性. 基于该模型, 本文构建了基于可信度加权的符号回归方法, 将重要特征对<i>F</i><sub>b</sub>值的影响规律映射为可显式计算的数学关系式. 该关系式在真实钙钛矿样本上的预测误差较已发表<i>F</i><sub>b</sub>值计算公式降低1~2个数量级, 且对高不确定性样本的预测偏差缩小60%~80%. 本文所提出的软标签构建策略与基于可信度加权的符号回归方法, 不仅显著缓解了因高质量标签数据稀缺所导致的建模局限问题, 更为广泛材料体系在标签数据匮乏场景下的本征物性预测, 提供了一种可迁移的建模范式. Dielectric ; Perovskite (structure) ; Dielectric strength ; Dielectric loss ; Work (physics) Machine Learning in Materials Science ; Dielectric materials and actuators ; Ferroelectric and Piezoelectric Materials
Authors: Jeannette Jacqueline Łucejko | Irene Bertelli | Renata Costa | Bettina Ebert | Andreu Falcó | Rodica-Mariana Ion | Paul R. B. Kozowyk | Zorica Mojović | Federica Nardella | Alessandra Pecci | Erika Ribechini | Hannes Schroeder | Magdalena Zborowska | Maria Perla Colombini
Source: npj Heritage Science (article, 2026-03-17)
Field: Chemistry — Organic Chemistry

Characterising terpenic plant resins, wood tars and pitches in heritage science: analytical methods and applications Abstract This review examines natural plant resins, wood tars and pitches in heritage science, focusing on their historical uses, chemical composition and analytical characterisation. Particular attention is given to diterpenoid and triterpenoid resins and to chemical transformations induced by ageing, degradation and thermal processing. The identification of diagnostic molecular markers supports the determination of botanical origins and technological practices, while an overview of complementary analytical methods highlights current challenges and perspectives. Identification (biology) ; Triterpenoid ; Natural (archaeology) ; Terpenoid ; Chemical composition Wood and Agarwood Research ; Cultural Heritage Materials Analysis ; Plant biochemistry and biosynthesis
Authors: Francisco Seco | Sandro Amador | Felipe Conzuelo | Ana Catarina Baptista | Leonor Morgado | Ana Sofia Pina
Source: Journal of Materials Chemistry B (article, 2026-01-01)
Field: Materials Science — Biomaterials

Molecular versatility of polyproline II helices: from natural proteins to biomimetic materials The polyproline II helix is more common as a secondary structure than previously thought. Its significance extends to mediating various protein-protein interactions, both structurally and functionally, in natural systems. This structure is associated with the formation of supramolecular assemblies, which have been investigated for biomimetic applications. In this review, we highlight three examples of polyproline II helix utilization: structurally in collagen and in biomolecular condensates, and as functional motifs in hyperactive antifreeze proteins. The review examines the mechanisms underlying the properties of PPII and consolidates practical design principles for engineering PPII-based assemblies, with an emphasis on sequence composition, residue propensity, and crosslinking strategies that enhance stability and functionality. Additionally, by critically comparing spectroscopic methods (CD, VCD, ROA and NMR) and AI-based prediction tools, we summarize their respective strengths and limitations, providing a practical decision framework for selecting the most suitable characterization techniques for different sample types and research objectives. Polyproline helix ; Helix (gastropod) ; Supramolecular chemistry ; Sequence (biology) ; Peptide ; Characterization (materials science) ; Protein secondary structure Silk-based biomaterials and applications ; Supramolecular Self-Assembly in Materials ; Advanced Polymer Synthesis and Characterization
Authors: T. N Amadi | V. O Izionworu | P. L Nwambo
Source: Iconic Research and Engineering Journals (article, 2026-03-03)
Field: Materials Science — Materials Chemistry

Investigation of the Inhibitive Properties of Mangifera indica (Mango) and Annona Muricata (Soursop) Blend Leaves Extract on Carbon Steel in 0.5M H2SO4 The inhibition efficiency of mango (Mangnifera indica) and Soursop (Anonna muricata) blend leaves extract as inhibitor of carbon steel in 0.5M H2SO4 acidic solution is presented. The corrosion inhibition study was carried out using, gravimetric method. Gas Chromatography (GC) and Fourier Transform Infrared Spectroscopy (FTIR) were used to analyze the Mangifera indica and Annona muricata blend leaves extract. Scanning Electron Microscopy (SEM) was employed to investigate the surface morphology of steel coupons before and after exposure to the corrosive environment. Analyses of the results revealed that adsorption of the Mangifera indica and Annona muricata blend leaves extract on the surface of the carbon steel was spontaneous and occurred according to the mechanism of physical adsorption. The inhibition efficiency was dependent on concentration of the extract and time. Mangifera indica and Annona muricata blend leaves extract exhibited the highest inhibition efficiency (about 93.68%) observed at 48 hours of 1.0 g/ml of extract concentration. At increased concentration of extract, the corrosion rate of carbon steel samples gradually decreased as the days progressed. The least corrosion rate of 2.99 mm/yr was obtained at 1.0g/ml extract concentration. The result showed that Mangifera indica and Annona muricata blend leaves extract is a good inhibitor for the corrosion of carbon steel in H2SO4 media. It has a high significant effect on the reduction of the corrosion of carbon steel at room temperature as a result of the formation of films on the substrate thereby displacing water molecules from the metal surface when compared with the control experiment. Annona muricata ; Mangifera ; Carbon steel ; Corrosion ; Annona squamosa ; Annona ; Adsorption Corrosion Behavior and Inhibition ; Concrete Corrosion and Durability ; Hydrogen embrittlement and corrosion behaviors in metals
Authors: Alejandra León
Source: arXiv (Cornell University) (article, 2026-03-20)
Field: Materials Science — Materials Chemistry

A cellular automaton model for thermal transport in low-dimensional systems In this work, we formulate a theoretical model based on a cellular automaton (CA) to study thermal transport in low-dimensional nanostructures across ballistic, diffusive, and transition regimes. Unlike computationally intensive methods such as the Boltzmann Transport Equation (BTE), our model stands out for its geometrical robustness, allowing the seamless integration of substitutional impurities, vacancies, and irregular edges. We validated the model using graphene nanoribbons (AGNRs), successfully replicating the dependence of thermal conductivity on ribbon width and temperature. Results demonstrate that the model captures critical scattering and confinement effects with a linear scalability O(N). Given the increasing pressure to optimize computational resources and reduce the carbon footprint associated with AI infrastructure, this CA model emerges as a highly efficient tool for the parametric exploration and design of next-generation thermal devices. Cellular automaton ; Thermal conductivity ; Boltzmann equation ; Thermal ; Scalability ; Parametric statistics ; Scattering ; Ribbon ; Solver Thermal properties of materials ; Advanced Thermoelectric Materials and Devices ; Topological Materials and Phenomena
Authors: Liping Luo | Shiqing Zhou | Jianfei Zhou | Jingquan Wang | Han Wu | Hongguang Guo
Source: Environmental Science and Ecotechnology (article, 2026-02-27)
Field: Chemistry — Organic Chemistry

Phenolic contaminants generate persistent phenoxyl radicals to accelerate antibiotic degradation Water pollution by coexisting multiple contaminants presents escalating challenges to environmental remediation and public health protection. In advanced oxidation processes, contaminant interactions are invariably regarded as detrimental, introducing competitive reactions and matrix interferences that diminish treatment efficiency. However, phenolic compounds-a prevalent class of recalcitrant water pollutants-possess latent oxidative capabilities that remain strategically unexploited. Whether their reactivity can be harnessed to accelerate, rather than impede, the removal of priority contaminants remains fundamentally unclear. Here we show that in the permanganate/chlorite (Mn(VII)/ClO<sub>2</sub> <sup>-</sup>) system, phenolic compounds undergo a counterintuitive transformation into persistent phenoxyl radicals that enhance sulfamethoxazole degradation by 3.5- to 20-fold. Mechanistic investigations reveal that these radicals exhibit exceptional stability and selectivity, preferentially attacking target pollutants while demonstrating robust resistance to common matrix interferences-properties unattainable with conventional oxidants alone. Quantitative structure-activity relationships provide predictive frameworks for optimizing this contaminant-assisted oxidation strategy across diverse chemical scenarios. This contaminant-mediated oxidation strategy inverts the traditional paradigm of mutual interference, transforming recalcitrant phenolics from obstacles into powerful mediators. The findings open new avenues for self-adaptive remediation of multi-pollutant systems and suggest broader applications in environmental cleanup where contaminant interactions can be strategically exploited. Radical ; Degradation (telecommunications) ; Environmental remediation ; Pollutant ; Reactivity (psychology) ; Contamination ; Redox Free Radicals and Antioxidants ; Advanced oxidation water treatment ; Pharmaceutical and Antibiotic Environmental Impacts
Authors: Mahamadou Lamine Ousmane Diallo | Ádám Sarankó | Tamás István Pataki | László Zsidai
Source: Applied Physics A (article, 2026-02-09)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Metamaterials and their applications in engineering metamaterials: classification, applications - a comprehensive review Metamaterials are artificially engineered structures that exhibit properties not found in natural materials. This comprehensive review explores the diverse types of metamaterials and their wide-ranging applications across multiple fields. The article covers electromagnetic metamaterials and their application in superlenses, invisibility cloaks (hiding object from detection of radar par example), and advanced antennas; acoustic metamaterials for noise reduction and acoustic cloaking; mechanical metamaterials for vibration control, impact protection, and flexible electronics; and thermal metamaterials for heat management. In this article, we explore the different metamaterials, their capabilities and their importance in industry. The review also discusses various production technologies for metamaterials, including additive manufacturing, subtractive manufacturing, and micro/nanolithography techniques. We point out new technological solutions for the production of metamaterials, highlighting additive 3D printing as a technological possibility. This becomes particularly important due to the intrinsic geometrical characteristics of metamaterials. Recent advancements in fabrication methods have expanded the possibilities for creating materials with extraordinary properties, enabling innovations in fields such as telecommunications, medical imaging, aerospace, and energy management. Metamaterial ; Invisibility ; Cloaking ; Point (geometry) ; Noise (video) ; Acoustic metamaterials Metamaterials and Metasurfaces Applications ; Cellular and Composite Structures ; Nanomaterials and Printing Technologies
Authors: Dr. Salman Arafath Mohammed
Source: International Journal of Integrated Research and Practice (article, 2026-03-03)
Field: Materials Science — Biomaterials

Bioinspired Materials: Mimicking Nature to Solve Human Engineering Challenges The use of bioinspired materials has emerged as a revolutionary frontier in the engineering field since it can provide the old design principles that have been applied in the design world to new inventions of technology. Living systems are highly effective, versatile, robust, and multi-functional- qualities that are not generally easy in inorganic materials of synthetic substances. This research article will discuss the conceptual foundation, methodology of fabrication and actual applications of bioinspired material, and in particular, how the material is applied to address the current-day engineering challenges. General examples of the lotus-leaf-inspired superhydrophobic surfaces, nacre-inspired layered composites, gecko-inspired adhesive surfaces, and spider-silk-inspired high-strength fibers are a foundation of the research because such structural hierarchy, self-assembly, and energy-efficient design result in the best performance features. A review of advances made in nanotechnology, additive manufacturing, and biomolecular engineering that enable the re-creation of biological structures at a micro- and nanoscale accuracy is also discussed in the paper. The innovations have introduced tremendous improvements in such fields as aerospace, biomedical devices, sustainable construction, robotics, and environmental remediation. Bioinspired materials improve performance and this is what contributes to the concept of sustainability through reducing the use of materials, extending the life of the service and being environmental friendly. In spite of the rapid development pace, not all of the difficulties are eliminated yet, including the scalability, cost-efficiency, long-term stability, and the ability to integrate with the already existing industrial processes. The study and new research opportunities that can remove these limitations are critically evaluated and interdisciplinary approach that involves materials scientists, biologists, and engineers points to the new directions. A mix of theoretical and case analysis shows that bioinspired materials are not the other cosmetic imitation of forms existing in nature; however, it is a paradigm shift to the concept of the function-oriented and sustainable engineering design. Biological intelligence has emerged as an opportunity and prospective whereby it can be developed to develop a robust material that can withstand the transformative facet of infrastructure and technology in the contemporary world. Sustainability ; Field (mathematics) ; Biomimetic materials ; Foundation (evidence) ; Design elements and principles ; Human life ; Biological systems engineering Calcium Carbonate Crystallization and Inhibition ; Microbial Applications in Construction Materials ; Silk-based biomaterials and applications
Authors: Zijian Tang | Si Shen | Gu C | Sixin Li | Jiang Ni | Dongjie Yang | Yuanyuan Mi
Source: International Journal of Nanomedicine (article, 2026-01-01)
Field: Materials Science — Biomaterials

Novel Strategies for Precision Diagnosis and Treatment of Prostate Cancer Based on Multifunctional Nanocarrier Systems Prostate cancer (PCa) is one of the most common malignancies in men worldwide, and its current diagnostic and therapeutic methods still face severe challenges in terms of specificity, efficacy, and toxicity. The emergence of nanotechnology provides a powerful platform to overcome these obstacles. Through the design of sophisticated nanocarriers, targeted delivery and controlled release of therapeutic agents, as well as the synergy of multiple treatment modalities, can be achieved, thereby significantly improving efficacy and reducing side effects. Meanwhile, nanotechnology shows great potential in developing highly sensitive diagnostic tools and theranostic platforms, laying the foundation for early detection and precise treatment of PCa. Although challenges such as scalability and safety remain to be addressed before clinical translation, nanotechnology is undoubtedly reshaping the landscape of PCa management and driving the field towards personalized medicine. This review aims to provide a systematic overview of significant advancements in nanotechnology for the diagnosis and treatment of PCa over the past three years. It focuses on innovative research in novel nanocarrier design, targeting strategies, and the construction of integrated diagnostic and therapeutic platforms. Furthermore, current challenges and future directions for clinical translation are discussed, with the aim of offering valuable insights and references for researchers and clinicians in this field. Nanocarriers ; Prostate cancer ; Nanomedicine ; Applications of nanotechnology ; Translational research ; Targeted therapy ; Clinical Practice ; Cancer treatment Nanoparticle-Based Drug Delivery ; Nanoplatforms for cancer theranostics ; Advanced Nanomaterials in Catalysis
Authors: Jagruti Mutualikdesai | Rhythm Bains
Source:  (article, 2026-04-01)
Field: Materials Science — Biomaterials

Clinical applications of self-assembling peptides in dentistry: Enamel remineralization, dentin repair, and tissue regeneration Dental caries is a dynamic process driven by an imbalance between demineralization and remineralization, traditionally managed by invasive restorative methods that sacrifice healthy tooth structure. The shift toward minimally invasive and regenerative dentistry has promoted interest in biomimetic materials, particularly self-assembling peptides (SAPs). P11-4 and RADA16 are among the most widely investigated peptides, capable of undergoing pH-triggered self-assembly into β-sheet nanofibers that form a three-dimensional hydrogel scaffold. This matrix acts as a template for hydroxyapatite nucleation, promoting guided enamel remineralization. Evidence demonstrates that P11-4 effectively regenerates early enamel lesions, including post-orthodontic white-spot lesions, with superior remineralization efficacy compared to fluoride and without compromising bracket bond strength. SAP-mediated biomineralization also shows potential in managing dentinal hypersensitivity through intratubular crystal deposition, as well as emerging applications in bone regeneration and pulp revascularization, supported by favorable biocompatibility and scaffold characteristics. However, challenges persist regarding stability, standardization of peptide design, and sensitivity of self-assembly to environmental conditions. This narrative review summarizes the mechanisms, applications, and limitations of SAPs in dentistry. Enamel paint ; Biocompatibility ; Dentin ; Regeneration (biology) ; Demineralization ; Biomineralization ; Amelogenin ; Tooth enamel ; Dentinal Tubule Supramolecular Self-Assembly in Materials ; Bone and Dental Protein Studies ; Bone Tissue Engineering Materials
Authors: Antonina Dobrowolska | Julian Świerczyński | Paweł Tecmer | Emil Sujkowski | Somayeh Ahmadkhani | Grzegorz Mazur | Klemens Noga | Jeff Hammond | Katharina Boguslawski
Source: arXiv (Cornell University) (article, 2026-03-21)
Field: Materials Science — Materials Chemistry

Efficient Coupled-Cluster Python Frameworks for Next-Generation GPUs: A Comparative Study of CuPy and PyTorch on the Hopper and Grace Hopper Architecture In this work, we introduce new batching algorithms to effectively handle large contractions encountered in coupled-cluster singles and doubles (CCSD) implementations in Python on the Video Random Access Memory (VRAM) of graphical processing units (GPUs), thereby improving performance. Specifically, we benchmark the performance of the CuPy and PyTorch libraries on a single NVIDIA Hopper (H100) and the Grace Hopper (GH200) architectures. We begin by optimizing the particle-particle ladder bottleneck contraction in CCSD using an asymmetric and dynamic splitting recipe, and then move toward a generic tensor contraction protocol that enables tensor contractions to be performed almost exclusively on GPUs. We benchmark our new, fully generic GPU-accelerated coupled-cluster implementations for various molecular systems and basis-set sizes, using both the CuPy and PyTorch libraries. While PyTorch outperforms CuPy on H100 by approximately 20\%, both perform similarly on the GH200 architecture. Compared to our initial GPU implementation [J. Chem. Theory Comput. 2024, 20, 3, 1130--1142], we achieve a 10-fold speedup. In molecular CCSD calculations, we report additional speedups between 3 and 16 for a single CCSD iteration using Cholesky-decomposed electron repulsion integrals compared to our original GPU-CPU hybrid implementation. Python (programming language) ; Bottleneck ; Implementation ; Benchmark (surveying) ; Architecture ; Tensor (intrinsic definition) Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Protein Structure and Dynamics
Authors: Aswin Karkadakattil
Source: Materials Technology Reports (article, 2026-03-05)
Field: Materials Science — Materials Chemistry

Physics-informed surrogate modelling of finite-size scaling and Curie temperature suppression in ferroelectric perovskite nanostructures Finite-size suppression of the Curie temperature (Tc) in ferroelectric perovskite nanostructures remains an important yet insufficiently resolved problem, with reported scaling exponents varying considerably across experimental and theoretical studies. Although density functional theory provides atomistic insight into size-dependent behaviour, its high computational cost limits systematic exploration across broad size ranges. Conversely, purely empirical fitting approaches often lack physical interpretability and formal uncertainty quantification. In this work, a physics-informed surrogate modelling framework is developed to investigate finite-size scaling in BaTiO₃ and KNbO₃ nanostructures using a structured dataset compiled from the literature. The model is based on thermodynamically motivated scaling behaviour, enabling extraction of physically meaningful size-dependent parameters. Bootstrap resampling is employed to quantify statistical robustness, yielding scaling exponents of 1.59 (95% confidence interval: 1.43–1.72) for BaTiO₃ and 1.40 (95% confidence interval: 1.31–1.52) for KNbO₃. Gaussian Process regression is further integrated to provide uncertainty-aware predictions across the nanoscale domain. In addition to forward prediction, the framework enables inverse estimation of the minimum particle size required to preserve ferroelectric stability at a specified operating temperature. For a threshold of 300 K, the predicted critical sizes are approximately 4.96 nm for BaTiO₃ and 2.89 nm for KNbO₃. Extension to a coupled size–strain formulation produces a two-dimensional stability map, demonstrating tunable interactions between confinement and strain. Overall, the proposed methodology provides a transparent, statistically rigorous, and computationally efficient framework for predictive analysis and rational design of nanoscale ferroelectric materials. Scaling ; Curie temperature ; Ferroelectricity ; Perovskite (structure) ; Stability (learning theory) ; Interpretability ; Inverse Machine Learning in Materials Science ; Model Reduction and Neural Networks ; Gaussian Processes and Bayesian Inference