jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Yufan Yang | Yuqin Xiao | Qingxin Zhang | Yuxin Yan | Tao Wu | Cheng Heng Pang
Source: Advanced Science (review, 2025-08-24)
Field: Materials Science — Materials Chemistry

Graphene‐Inspired Mono‐Elemental 2D Materials: Synthesis, Properties, and Potential Applications of Xenes Xenes, a class of mono-elemental two-dimensional (2D) materials, have emerged as promising candidate materials for next-generation electronic and energy devices due to their unique structural and electronic properties. This review first systematically categorizes the eighteen experimentally realized Xenes into Group III-VI and other group categories, summarizing their synthesis routes, ranging from top-down exfoliation to bottom-up methods. Based on density functional theory (DFT), this paper focuses on theoretical predictions of stable phases and substrate interactions, which guide experimental preparation. Second, functional applications of Xenes in electronics, optoelectronics, catalysis, energy storage, and biomedicine are also reviewed. The impact of atomic configurations on synthesis difficulty, environmental stability, and scalability across different element groups is also discussed. Finally, emerging strategies such as encapsulation, heterostructure design, and machine learning-guided growth are evaluated to overcome inherent limitations. This paper provides a comprehensive overview of synthesis principles, structure-property relationships, and stabilization strategies, offering insights into future scalable and robust Xene development directions. Nanotechnology ; Density functional theory ; Graphene ; Scalability ; Materials science ; Electronics ; Computer science ; Chemistry ; Computational chemistry 2D Materials and Applications ; MXene and MAX Phase Materials ; Graphene research and applications
Authors: Yafeng Deng | Xinda Zhao | Hanyu Sun | Y. Y. Chen | Xiaorui Wang | Xi Xue | Liangning Li | Jianfei Song | Chang‐Yu Hsieh | Tingjun Hou | Xiandao Pan | Taghrid Saad Alomar | Xiangyang Ji | Xiaojian Wang
Source: Nature Communications (article, 2025-07-31)
Field: Materials Science — Materials Chemistry

RSGPT: a generative transformer model for retrosynthesis planning pre-trained on ten billion datapoints Retrosynthesis planning is a crucial task in organic synthesis, and deep-learning methods have enhanced and accelerated this process. With the advancement of the emergence of large language models, the demand for data is rapidly increasing. However, available retrosynthesis data are limited to only millions. Therefore, we pioneer the utilization of the template-based algorithm to generate chemical reaction data, resulting in the production of over 10 billion reaction datapoints. A generative pretrained transformer model is subsequently developed for template-free retrosynthesis planning by pre-training on 10 billion generated data. Inspired by the strategies of large language models, we introduce reinforcement learning to capture the relationships among products, reactants, and templates more accurately. Experiments demonstrate that our model achieves state-of-the-art performance on the benchmark, with a Top-1 accuracy of 63.4%, substantially outperforming previous models. Transformer ; Retrosynthetic analysis ; Computer science ; Generative grammar ; Artificial intelligence ; Engineering ; Electrical engineering ; Chemistry Machine Learning in Materials Science ; Asymmetric Hydrogenation and Catalysis ; Chemical Synthesis and Analysis
Authors: Türkan Kopaç
Source: Polymers (article, 2025-12-09)
Field: Materials Science — Materials Chemistry

Advancing Polymer Science and Energy Storage Solutions Through the Integration of Artificial Intelligence and Machine Learning: A Transformative Approach Polymers play a pivotal role in advancing energy storage technologies because of their unique properties, including high conductivity, flexibility, and environmental stability. The integration of artificial intelligence (AI) and machine learning (ML) into polymer science has revolutionized the design, discovery, and optimization of polymeric materials, enabling the development of faster, cost-effective, and innovative solutions. This review explores the transformative impact of AI and ML in polymer science, focusing on their applications in polymer design, characterization, and energy storage. Key advancements include the accelerated discovery of materials, predictive modeling of polymer properties, and high-throughput screening of polymer candidates. This review highlights the strengths of AI and ML, including their ability to handle complex datasets, optimize multiproperty trade-offs, and uncover hidden relationships between structure and properties. However, challenges such as data limitations, model interpretability, and synthetic feasibility remain significant barriers to progress. The paper also identifies gaps in the literature, including the need for improved structural descriptors, expanded datasets, and the integration of physical principles into ML models. Future directions emphasize the development of sustainable polymers, generative design frameworks, and interdisciplinary collaboration to address pressing global challenges. By leveraging AI and ML, this work aims to accelerate the development of next-generation polymers for energy storage, fostering clean, efficient, and sustainable energy solutions. Transformative learning ; Work (physics) ; Generative grammar ; Energy storage ; Key (lock) ; Energy (signal processing) ; Big data ; Grand Challenges Machine Learning in Materials Science ; Block Copolymer Self-Assembly ; Conducting polymers and applications
Authors: Osama Tariq Satti | Uzma Ghazanfar | Hassan Wahab | Guoqiang Li | Amro Satti | Amjad Sohail | Sadiq H. Khoreem | Muhammad Numan Nawaz | Saeed Ur Rehman
Source: Scientific Reports (article, 2025-11-25)
Field: Materials Science — Materials Chemistry

Tuning optical and dielectric properties of strontium-zinc ferrite nanomaterials through structure-cation engineering Herein, SrxZn1−xFe2O₄ nanoparticles produced by chemical co-precipitation are examined to determine how strontium (Sr) doping affects their structural, morphological, optical, and dielectric characteristics. The creation of a single-phase cubic spinel structure was verified by X-ray diffraction, and peak shifts indicated lattice expansion brought on by the addition of Sr. A homogeneous grain morphology with nanoscale dimensions was found by FESEM investigation. The metal-oxygen vibrational modes in the Raman and FTIR spectra showed changes that suggested local structural distortion. With a lowered optical bandgap of 2.62 ± 0.1 eV, UV-Vis spectroscopy revealed a red shift in the absorption edge, improving semiconducting properties. AC conductivity and complex modulus tests revealed improved charge transport and relaxation behavior, whereas impedance spectroscopy indicated decreased dielectric loss (tan δ) at high frequencies. Mössbauer spectroscopy revealed that doping resulted in a redistribution of Fe2+ between tetrahedral and octahedral sites. According to these results, Sr-doped ZnFeO₄ is a promising material for use in high-frequency and optoelectronic device applications. This work develops a structure-cation engineering approach, where Mössbauer spectroscopy validates cation redistribution, allowing for simultaneous tuning of optical and dielectric properties, providing a new avenue for the development of ferrite-based optoelectronic and energy storage materials. Dielectric spectroscopy ; Dielectric ; Raman spectroscopy ; Doping ; Spectroscopy ; Nanomaterials ; Conductivity ; Absorption spectroscopy ; Optical conductivity Magnetic Properties and Synthesis of Ferrites ; Magneto-Optical Properties and Applications ; Electromagnetic wave absorption materials
Authors: Ying Zhang | Ming‐Wei Wang | Ran Zhuo | Wenxu Tang | Chaolu Niu | Qiulin Chen | Weihong Yang | Sicheng Zhao
Source: Journal of Applied Polymer Science (article, 2025-02-24)
Field: Materials Science — Polymers and Plastics

Study on Self‐Healing Technology of Epoxy Resin for Insulator Core Rods ABSTRACT Epoxy resin insulation materials are prone to micro‐damage such as scratches and electrical treeing, which can lead to a decline in insulation performance and threaten the safe operation of the entire system. Microcapsule‐based self‐healing technology is one of the most promising solutions to address the micro‐damage issues of epoxy resin. However, research has shown that when the microcapsule doping concentration exceeds 3 wt%, the mechanical strength decreases significantly, while a too low doping concentration affects the healing efficiency. This paper focuses on epoxy resin used in insulator core rods and addresses the contradiction between “low microcapsule introduction” and “high healing efficiency.” This work synthesizes magnetically targeted UV‐sensitive microcapsules suitable for self‐healing insulator core rods. During the curing process of the epoxy resin, the microcapsules can be directionally guided by a magnetic field to distribute in areas prone to damage, thereby ensuring repair efficiency while reducing the quantity of microcapsules used. The microcapsule shells possess UV‐shielding properties, ensuring the stability of the internal repair core material. When damage propagates to the capsules, the core material flows out and cures under UV light, completing the repair of the damage. Additionally, larger‐scale self‐healing epoxy rod specimens were fabricated, demonstrating excellent self‐healing performance against mechanical scratch damage and electrical treeing damage. In comparison, composite materials without microcapsules exhibited a reduction in tensile strength and breakdown strength to 69.06% and 74.77%, respectively, after mechanical damage. Post‐repair, the mechanical strength recovery rate reached 91.6%, and the breakdown strength recovery rate achieved 90.4%. Epoxy ; Rod ; Materials science ; Self-healing ; Core (optical fiber) ; Composite material ; Insulator (electricity) ; Medicine Polymer composites and self-healing ; Epoxy Resin Curing Processes ; High voltage insulation and dielectric phenomena
Authors: Julia Mazurenko | Larysa Kaykan | Владимир Владимирович Мокляк | Mateusz Marzec | L. Yu. Matzui | Л. Л. Вовченко | O. S. Yakovenko
Source: Journal of Materials Science Materials in Electronics (article, 2025-11-01)
Field: Materials Science — Materials Chemistry

Study of charge transfer mechanisms in cobalt-substituted copper ferrites Abstract In this study, Co x Cu 1-x Fe 2 O 4 (x = 0.0–1.0) spinel ferrites were synthesized by the citrate sol–gel autocombustion method and systematically investigated to clarify composition-dependent charge transport mechanisms. X-ray diffraction and FTIR confirmed spinel formation and revealed systematic cation redistribution with cobalt substitution. X-ray photoelectron spectroscopy (XPS) further verified the coexistence of Fe 3+ /Fe 2+ and Co 2+ /Co 3+ redox couples together with oxygen-vacancy–related states, providing direct evidence of multiple charge transfer pathways. Temperature-dependent conductivity showed thermally activated behavior, with a slope change above 373 K in Co-rich samples (x ≥ 0.8), signaling a transition in the dominant conduction process. At low temperatures (298–348 K), transport was directed by grain boundary and defect-related hopping, while long-range small-polaron hopping between Fe 2+ /Fe 3+ dominated at elevated temperatures. Increasing Co content introduced additional Co 2+ /Co 3+ valence fluctuations, enhancing localized dielectric relaxation and structural disorder. AC conductivity analysis demonstrated decreasing activation energy with increasing frequency, consistent with enhanced carrier mobility. The data were successfully fitted using Jonscher’s universal power law, its modified form, and the Almond–West model. Fitting revealed a composition-driven increase in onset frequency ω H from ~ 4 kHz in CuFe 2 O 4 to ~ 87 kHz in CoFe 2 O 4 , together with anomalously high dispersion parameters (s &gt; 1, m &gt; 1) in Co-rich samples, indicating strong interfacial polarization and dipolar relaxation. A distinct low-frequency break near 10 Hz in CuFe 2 O 4 was attributed to structural transformation. The combined structural, spectroscopic, and electrical analyses demonstrating a clear evolution from long-range Fe 2+ /Fe 3+ hopping in Cu-rich ferrites to localized relaxation and interfacial polarization in Co-rich members. This tunability, linked to cation distribution and oxygen-vacancy formation, positions Co x Cu 1-x Fe 2 O 4 as a promising spinel system for high-frequency dielectric, EMI shielding, and microwave absorption applications. Spinel ; Conductivity ; Analytical Chemistry (journal) ; X-ray photoelectron spectroscopy ; Valence (chemistry) ; Grain boundary ; Dielectric ; Dielectric spectroscopy ; Copper Magnetic Properties and Synthesis of Ferrites ; Electromagnetic wave absorption materials ; Advancements in Battery Materials
Authors: Arti Hadap | V. R. Panse | Serhii Tereshchuk
Source: Scientific Reports (article, 2025-07-01)
Field: Materials Science — Materials Chemistry

Investigation of Aloe vera mediated ZnO-β-CD nanocomposite for photocatalysis and antimicrobial applications This study presents the green synthesis of an Aloe vera based ZnO-β-cyclodextrin (β-CD) nanocomposite for photocatalysis and antimicrobial applications. UV-Visible spectroscopy, Fourier transform infrared (FTIR), X-ray diffraction (XRD), Field emission electron microscopy (FESEM), and band gap energy measurement, were employed to investigate the optical and structural features. Due to unique bandgap (3.0 eV) and enhanced electron-hole recombination dynamics, the newly synthesized nanocomposite can not only able to demonstrate the efficient photocatalytic degradation of methylene blue (MB) dye by achieving complete discoloration at 6 pH within 160 min under visible light-a significant improvement over previously reported ZnO-based system, but furthermore, it also strongly combatted by the antibacterial activity against Gram-positive bacteria S. aureus, gram-negative bacteria E. coli, and the fungus strain A. niger. This is due to the generation of singlet oxygen (O<sub>2</sub>*<sup>-</sup>) and hydrogen oxide radical (-OH*) in presence of light and air, which inhibit the growth of cells of bacterial and fungal strains. Notably, the nanocomposite was biocompatible, posing minimal cytotoxicity to healthy cells, making it a promising candidate for environmental and biomedical application. Aloe vera ; Antimicrobial ; Photocatalysis ; Nanocomposite ; Microbiology ; Chemistry ; Materials science ; Biology ; Nanotechnology ; Biochemistry Nanoparticles: synthesis and applications ; Phytochemistry and biological activity of medicinal plants ; Nanotechnology research and applications
Authors: Khoa Nhu Tran | Huong Nguyen Que Tran | Andrew D. Abell | Cheryl Suwen Law | Abel Santos
Source: Microchimica Acta (review, 2025-06-22)
Field: Materials Science — Materials Chemistry

Nanoporous anodic alumina-based gas sensors: insights into advances and perspectives Achieving high-performance gas sensing requires materials and transduction mechanisms that enhance sensitivity, selectivity, and stability, while addressing challenges such as cross-sensitivity and real-time operation. Conventional sensor platforms often involve trade-offs between response time, detection limits, and environmental robustness. Nanoporous anodic alumina (NAA) fabricated by electrochemical oxidation-anodization-of aluminum provides a tunable platform for engineering gas sensors with tailored structural and physicochemical properties, enabling diverse transduction mechanisms and sensor configurations. This review categorizes NAA-based gas sensors into two major groups: electrochemical and optical sensors. The distinct interplay between the nanoporous architecture of NAA and its dielectric properties enhances charge transport in electrochemical sensors while enabling precise optical confinement and modulation in optical sensing platforms. Ongoing efforts in structural modifications, surface functionalization, and hybrid material integration continue to refine the capabilities of NAA-based gas sensors. Tailored nanostructured coatings, such as functionalized metal oxides, polymer composites, and plasmonic nanostructures, present new pathways for improving sensitivity and selectivity. The integration of data-driven signal processing, including machine learning-assisted analysis, is transforming how sensor responses are interpreted, endowing gas sensors with enhanced discrimination and multiplex sensing capabilities. These advancements, combined with innovations in microfabrication and miniaturized sensor arrays, enable new forms of NAA-based gas sensors. This review provides an up-to-date overview of recent progress and emerging directions in the development of NAA-based gas sensing technologies. Nanoporous ; Materials science ; Nanotechnology ; Electrochemical gas sensor ; Surface modification ; Computer science ; Electrochemistry ; Electrode ; Chemistry ; Chemical engineering ; Engineering Anodic Oxide Films and Nanostructures ; Gas Sensing Nanomaterials and Sensors ; Smart Materials for Construction
Authors: Hiroki Umemoto | Shigeo Arai | Shunsuke Muto
Source: Journal of Applied Polymer Science (article, 2025-06-18)
Field: Materials Science — Surfaces, Coatings and Films

Unsupervised Classification of Polymers Using Low‐Loss Spectral Features in Scanning Transmission Electron Microscopy With Electron Energy‐Loss Spectroscopy ABSTRACT This study presents a classification model for nanoscale polymer characterization, utilizing low‐loss spectral data obtained through scanning transmission electron microscopy combined with electron energy‐loss spectroscopy. To enhance interpretability, spectral features are extracted via mixed Gaussian model fitting, where each Gaussian peak corresponds to a specific chemical bond state, facilitating the identification of key descriptors. These features enable effective clustering of seven standard polymers, achieving clear statistical separation based on four principal features. Furthermore, the extracted features are employed to visualize the progression of electron irradiation damage within an adequate data space. Feature changes under varying irradiation conditions are significantly correlated with alterations in the summed spectra. This methodology holds promise for advancing qualitative analyses of polymer alloys without electron staining, allowing detailed investigations into local denaturation and the presence of reaction layers. With the expansion of standard datasets, this approach offers a robust framework for characterizing and understanding polymer behavior at the nanoscale. Electron energy loss spectroscopy ; Polymer ; Materials science ; Transmission electron microscopy ; Biological system ; Spectroscopy ; Gaussian ; Scanning transmission electron microscopy ; Polymer characterization ; Electron beam processing ; Scanning electron microscope ; Spectral shape analysis ; Electron ; Energy filtered transmission electron microscopy ; Analytical Chemistry (journal) ; Spectral line ; Nanotechnology ; Chemistry ; Physics ; Computational chemistry ; Organic chemistry ; Composite material Electron and X-Ray Spectroscopy Techniques ; Machine Learning in Materials Science ; Electrochemical Analysis and Applications
Authors: Harshini Mohan | Subash Mohandoss | B. Natarajan | L. Sivachandiran
Source: Plasma (article, 2025-06-18)
Field: Materials Science — Materials Chemistry

Non-Thermal Plasma-Assisted Synthesis of ZnO for Enhanced Photocatalytic Performance Non-thermal plasma (NTP)-assisted material synthesis and surface modification provide a promising approach in various applications, particularly in wastewater treatment. In this study, we reported the synthesis of photocatalytic zinc oxide (ZnO) from zinc hydroxide (Zn(OH)2) utilizing NTP discharge generated by dielectric barrier discharge (DBD). The results demonstrated that the 40 min plasma treatment at 200 °C (ZnO-P) with a voltage of 20 kV significantly improved the material’s physicochemical properties compared to conventional calcination at 600 °C (ZnO-600). ZnO-P exhibited better crystallinity, a significantly reduced particle size of 41 nm, and a narrower band gap of 3.1 eV compared to ZnO-600. Photocatalytic performance was evaluated through crystal violet degradation, where ZnO-P achieved an 60% degradation rate after 90 min of UV exposure, whereas ZnO-600 exhibited only a 50% degradation rate under identical conditions. These findings underscore the effectiveness of NTP synthesis in enhancing the surface properties of ZnO, leading to superior photocatalytic performance. Photocatalysis ; Crystallinity ; Dielectric barrier discharge ; Materials science ; Calcination ; Degradation (telecommunications) ; Zinc ; Chemical engineering ; Band gap ; Nonthermal plasma ; Hydroxide ; Plasma ; Dielectric ; Catalysis ; Composite material ; Chemistry ; Metallurgy ; Optoelectronics ZnO doping and properties ; Advanced Photocatalysis Techniques ; Ga2O3 and related materials
Authors: Siyu Xu | Fan Li | Congcong Du | Dianchun Ju | Yaqing Hou | Xiangyang Li
Source: npj Materials Degradation (article, 2025-11-07)
Field: Materials Science — Materials Chemistry

Smart material design via accelerated corrosion evaluation: convergence of high-throughput characterization and AI-driven prediction in marine engineering Traditional trial-and-error methods have hindered the rapid development of corrosion-resistant materials in the field of marine engineering. This paper provides a comprehensive review of high-throughput characterization, efficient multi-factor evaluation, and artificial intelligence prediction for metallic materials in marine environments. By integrating these three parts synergistically, this paper presents an innovative paradigm for materials corrosion research, aimed at significantly accelerating the design of next-generation smart materials suitable for harsh marine environments. Characterization (materials science) ; Smart material ; Corrosion ; Convergence (economics) ; Field (mathematics) ; Material Design ; Materials processing Machine Learning in Materials Science ; Corrosion Behavior and Inhibition ; Structural Integrity and Reliability Analysis
Authors: Alexander Yurov | И. Н. Зубков | Alexey Lukonin | Oleg Kaun | Alexander E. Bogachev | Victor А. Klushin
Source: Materials (article, 2025-12-10)
Field: Materials Science — Materials Chemistry

XLPE and Beyond: A Review of Recent Progress in Polymer Nanocomposites for Dielectric Insulation in High-Voltage Cables Crosslinked polyethylene (XLPE) has been the cornerstone material in the power industry for insulating high-voltage cables due to its exceptional properties, including reduced dielectric loss, high dielectric constant and thermal conductivity, and excellent resistance to electrical stress. In the current study, in order to further enhance the electrical and mechanical properties of XLPE's various types of nanofillers such as metal oxides, boron nitride nanosheets of nanosilica and graphene oxide are incorporated into the XLPE matrix. These nanoparticles promote the occurrence of numerous trap sites, even at modest concentrations, due to their extensive interfacial regions, which affect crucial characteristics including breakdown voltage strength, electrical tree growth, structural defects, space charge accumulation, and thermal aging. The present review summarizes the effects of nanoparticles on the dielectric performance of XLPE. At the same time, the current advancements in the development of a new generation of recyclable insulation materials are briefly discussed. Boron nitride ; Dielectric ; Nanocomposite ; Polymer nanocomposite ; Polyethylene ; Graphene ; Space charge ; Oxide High voltage insulation and dielectric phenomena ; Dielectric materials and actuators ; Power Transformer Diagnostics and Insulation