jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Shiqiang Zhao | Yuancheng Fan | Ruisheng Yang | Zhehao Ye | Fuli Zhang | Chen Wang | Weijia Luo | Yongzheng Wen | Ji Zhou
Source: Opto-Electronic Advances (article, 2025-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Smart reconfigurable metadevices made of shape memory alloy metamaterials Reconfigurable metamaterials significantly expand the application scenarios and operating frequency range of metamaterials, making them promising candidates for use in smart tunable device. Here, we propose and experimentally demonstrate that integrating metamaterial design principles with the intrinsic features of natural materials can engineer thermal smart metadevices. Tunable extraordinary optical transmission like (EOT-like) phenomena have been achieved in the microwave regime using shape memory alloy (SMA). The strongly localized fields generated by designed metadevices, combined with the intense interference of incident waves, enhance transmission through subwavelength apertures. Leveraging the temperature-responsive properties of SMA, the morphology of the metadevice can be recontructed, thereby modifying its response to electromagnetic waves. The experiments demonstrated control over the operating frequency and transmission amplitude of EOT-like behavior, achieving a maximum transmission enhancement factor of 126. Furthermore, the metadevices with modular design enable the realization of multiple functions with independent control have been demonstrated. The proposed SMA-based metamaterials offer advantages in terms of miniaturization, easy processing, and high design flexibility. They may have potential applications in microwave devices requiring temperature control, such as sensing and monitoring. Shape-memory alloy ; Metamaterial ; Alloy ; Computer science ; Materials science ; Optoelectronics ; Composite material ; Artificial intelligence Metamaterials and Metasurfaces Applications ; Advanced Materials and Mechanics
Authors: Guilin Li | Yan Huang | Yurong Wang | Weiwei Qu | Hu Deng | Li‐Ping Shang
Source: Photonics (article, 2025-06-24)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Efficient Design of a Terahertz Metamaterial Dual-Band Absorber Using Multi-Objective Firefly Algorithm Based on a Multi-Cooperative Strategy Terahertz metamaterial dual-band absorbers are used for multi-target detection and high-sensitivity sensing in complex environments by enhancing information that reflects differences in the measured substances. Traditional design processes are complex and time-consuming. Machine learning-based methods, such as neural networks and deep learning, require a large number of simulations to gather training samples. Existing design methods based on single-objective optimization often result in uneven multi-objective optimization, which restricts practical applications. In this study, we developed a metamaterial absorber featuring a circular split-ring resonator with four gaps nested in a “卍” structure and used the Multi-Objective Firefly Algorithm based on Multiple Cooperative Strategies to achieve fast optimization of the absorber’s structural parameters. A comparison revealed that our approach requires fewer iterations than the Multi-Objective Particle Swarm Optimization and reduces design time by nearly half. The absorber designed using this method exhibited two resonant peaks at 0.607 THz and 0.936 THz, with absorptivity exceeding 99%, indicating near-perfect absorption and quality factors of 31.42 and 30.08, respectively. Additionally, we validated the absorber’s wave-absorbing mechanism by applying impedance-matching theory. Finally, we elucidated the resonance-peak formation mechanism of the absorber based on the surface current and electric-field distribution at the resonance frequencies. These results confirmed that the proposed dual-band metamaterial absorber design is efficient, representing a significant step toward the development of metamaterial devices. Multi-band device ; Metamaterial ; Firefly algorithm ; Terahertz radiation ; Computer science ; Firefly protocol ; Metamaterial absorber ; Dual (grammatical number) ; Multi band ; Optoelectronics ; Materials science ; Optics ; Algorithm ; Telecommunications ; Physics ; Tunable metamaterials Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: Cheng Pang | Yuzhong Wang | Pengcheng Wang | Axiang Yu | Yicheng Liu | Ziang Yue | Mingshuang Hu | Jianqi Hu | Yongkang Dong | Jiaran Qi
Source: PhotoniX (article, 2025-09-28)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Dispersion-engineered compact twisted metasurfaces enabling 3D frequency-reconfigurable holography Abstract Flexible dispersion manipulation is critical for holography to achieve broadband imaging or frequency division multiplexing. Within this context, metasurface-based holography offers advanced dispersion control, Yet dynamic reconfigurability remains largely unexplored. This work develops a dispersion-engineered inverse design framework that enables 3D multi-plane frequency-reconfigurable holography through a twisted metasurface system. The physical implementation is based on a compact bilayer configuration that cascades the broadband radiation-type metasurface (RA-M) and phase-only metasurface (P-M). The RA-M provides a phase-adjustable input to excite P-M, while the rotation of P-M creates a reconfigurable response of holograms. By employing the proposed scheme, dynamic switching of space-frequency multiplexing and achromatic holograms is designed and experimentally demonstrated in the microwave region. This method advances flexible dispersion engineering for metasurface-based holography, and the compact system holds significant potential for applications in near-field computational imaging/detection, high-speed high-data-capacity near-field wireless communication, and switchable meta-devices. Achromatic lens ; Holography ; Reconfigurability ; Broadband ; Dispersion (optics) ; Multiplexing ; Computer-generated holography ; Rotation (mathematics) Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: Stef Lauwers | Anne-Sophie Weyns | Annelies Breynaert | Tim Van Rillaer | Valerie Van Huynegem | Erik Fransén | Wout Bittremieux | Sarah Lebeer | Emmy Tuenter | Nina Hermans
Source: Metabolites (article, 2025-01-07)
Field: Chemistry — Organic Chemistry

Comparison of In Vitro Biotransformation of Olive Polyphenols Between Healthy Young and Elderly Both age groups produced the same metabolites, suggesting that the potential for polyphenols to exert their health-promoting benefits persists in healthy older individuals. Polyphenol ; Biotransformation ; In vitro ; Chemistry ; Food science ; Medicine ; Pharmacology ; Biochemistry ; Antioxidant ; Enzyme Edible Oils Quality and Analysis ; Protein Hydrolysis and Bioactive Peptides ; Tea Polyphenols and Effects
Authors: Nan Chen | Xiaoyu Zhang | Zhi Liu | Tianyu Zhang | Qingrong Lai | Bin Li | Yong Lu | Bo Hu | Xiaogang Jiang | Yande Liu
Source: Agriculture (article, 2025-05-31)
Field: Chemistry — Analytical Chemistry

Fusion of Acoustic and Vis-NIRS Information for High-Accuracy Online Detection of Moldy Core in Apples Moldy core is a common disease of apples, and non-destructive, rapid and accurate detection of moldy core apples is essential to ensure food safety and reduce post-harvest economic losses. In this study, the acoustic method was used for the first time for the online detection of moldy core apples, and we explore the feasibility of integrating acoustic and visible–near-infrared spectroscopy (Vis–NIRS) technologies for precise, real-time detection of moldy core in apples. The sound and Vis–NIRS signals of apples were collected using a novel acoustic online detection device and a traditional Vis–NIRS online sorter, respectively. Based on this, traditional machine learning and deep learning classification models were developed for the prediction of healthy, mild, moderate, and severe moldy apples. The results show that the acoustic detection method significantly outperforms the Vis–NIRS method in terms of moldy apple identification accuracy, and the fusion of acoustic and Vis–NIRS data can further improve the model prediction performance. The MLP-Transformer shows the best prediction performance, with the overall classification accuracies for the fusion of Vis–NIRS, acoustic, Vis–NIRS and acoustic reached 89.66%, 96.55%, and 98.62%, respectively. This study demonstrates the excellent performance of acoustic online detection for intra-fruit lesion identification and shows the potential of the fusion of acoustics and Vis–NIRS. Computer science ; Sensor fusion ; Artificial intelligence ; Pattern recognition (psychology) Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Date Palm Research Studies
Authors: Kai Zhang | Heyuan Sun | Yuna Qian | Jianliang Shen | Zhongke Zhang
Source: Macromolecular Bioscience (review, 2025-05-20)
Field: Materials Science — Biomaterials

Protein‐Based Multifunctional Hydrogel Adhesive for Wound Healing Wound healing is a complex and highly orchestrated biological process that encompasses four distinct stages including: hemostasis, inflammation, proliferation, and remodeling. Each stage is characterized by specific physiological responses and tissue repair mechanisms that collectively facilitate the restoration of tissue integrity. To achieve comprehensive wound management, the development of targeted hydrogel bioadhesives is of paramount importance. Hydrogel-based bioadhesives, characterized by their excellent physical properties and biocompatibility, have demonstrated significant potential in the field of wound treatment. However, the current research on protein-based hydrogel bioadhesives for wound healing remains limited. This review systematically examines the design principles of ideal hydrogel bioadhesives and their essential functions in wound repair. It provides an overview of the latest advancements multifunctional hydrogel bioadhesives derived from various proteins, including collagen, silk fibroin (SF), sericin, fibrin, gelatin (Gel), keratin, and casein. It also evaluates their performance in practical applications. Finally, the review highlights the primary challenges facing protein-based hydrogel bioadhesives in the field of wound healing and outlines prospective research directions, with the goal of advancing the development and clinical application of these technologies. Wound healing ; Self-healing hydrogels ; Gelatin ; Bioadhesive ; Hemostasis ; Biomedical engineering ; Wound dressing ; Chemistry ; Nanotechnology ; Materials science ; Medicine ; Drug delivery ; Surgery ; Biochemistry Silk-based biomaterials and applications ; Surgical Sutures and Adhesives ; Wound Healing and Treatments
Authors: S. Anand | Venkatachalam Gopalan | Shenbaga Velu Pitchumani
Source: Scientific Reports (article, 2025-05-14)
Field: Materials Science — Polymers and Plastics

Optimization of thermal conductivity in coir fibre-reinforced PVC composites using advanced computational techniques This research focuses on enhancing the thermal conductivity of coir fibre-reinforced polyvinyl chloride (PVC) composites using advanced optimization techniques. While coir fibre adds sustainability and biodegradability, it poses challenges in achieving optimal thermal performance when integrated into PVC. To address these challenges, the study uses Response Surface Methodology (RSM) and three nature-inspired optimization methods viz. Particle Swarm Optimization (PSO), Dragonfly Optimization (DFO) and Cuckoo Search Algorithm (CSA) to improve factors like fibre content, particle size and chemical treatment. A Box-Behnken experimental design helps to create composite samples using hydraulic injection moulding and thermal conductivity is measured with a two-slab guarded hot plate device. Among the optimization methods, CSA emerges as the most effective, achieving a maximum thermal conductivity of 0.801 W/mK with minimal error deviation (0.01-5.5%) by the process parameters such as potassium hydroxide treatment, coir content of 2 wt% and powder diameter of 75 (µm). DFO delivers consistent results with slightly higher error rates, while PSO demonstrates rapid convergence but greater variability. The comparison shows that CSA performs better, providing a dependable and long-lasting way to create high-quality coir-reinforced PVC composites that are good for industrial use. This work is among the first to compare multiple bio-inspired optimization algorithms for enhancing the thermal properties of coir-reinforced PVC composites, offering a new pathway for developing high-performance, eco-friendly materials for industrial applications. Materials science ; Coir ; Composite material ; Thermal conductivity ; Particle swarm optimization ; Response surface methodology ; Computer science ; Algorithm Natural Fiber Reinforced Composites ; Polymer Foaming and Composites ; Advanced Cellulose Research Studies
Authors: Rajan Gyawali | Ashwin Dhakal | Jianlin Cheng
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2025-07-03)
Field: Materials Science — Materials Chemistry

Multimodal deep learning integration of cryo-EM and AlphaFold3 for high-accuracy protein structure determination Cryo-electron microscopy (cryo-EM) is a key technology for determining the structures of proteins, particularly large protein complexes. However, automatically building high-accuracy protein structures from cryo-EM density maps remains a crucial challenge. In this work, we introduce MICA, a fully automatic and multimodal deep learning approach combining cryo-EM density maps with AlphaFold3-predicted structures at both input and output levels to improve cryo-EM protein structure modeling. It first uses a multi-task encoder-decoder architecture with a feature pyramid network to predict backbone atoms, Cα atoms and amino acid types from both cryo-EM maps and AlphaFold3-predicted structures, which are used to build an initial backbone model. This model is further refined using AlphaFold3-predicted structures and density maps to build final atomic structures. MICA significantly outperforms other state-of-the-art deep learning methods in terms of both modeling accuracy and completeness and is robust to protein size and map resolution. Additionally, it builds high-accuracy structural models with an average template-based modeling score (TM-score) of 0.93 from recently released high-resolution cryo-EM density maps, showing it can be used for real-world, automated, accurate protein structure determination. Deep learning ; Artificial intelligence ; Cryo-electron microscopy ; Computer science ; Biophysics ; Biology Enzyme Structure and Function ; Protein Structure and Dynamics ; Advanced Electron Microscopy Techniques and Applications
Authors: Yeqin Huang | Haniyeh Ebrahimi | Elena Berselli | Mario C. Foti | Riccardo Amorati
Source: Antioxidants (article, 2025-12-26)
Field: Chemistry — Organic Chemistry

Essential Oils as Antioxidants: Mechanistic Insights from Radical Scavenging to Redox Signaling Essential oils (EOs) are complex volatile mixtures that exhibit antioxidant activity through both chemical and biological pathways. Phenolic constituents act as efficient chain-breaking radical-trapping antioxidants, whereas some non-phenolic terpenes operate through distinct mechanisms. Notably, γ-terpinene functions via a "radical export" pathway, generating hydroperoxyl radicals that intercept lipid peroxyl radicals and accelerate chain termination. Recent methodological advances, such as inhibited autoxidation kinetics, oxygen-consumption assays, and fluorescence-based lipid peroxidation probes, have enabled more quantitative evaluation of these activities. Beyond direct radical chemistry, EOs also regulate redox homeostasis by modulating signaling networks such as Nrf2/Keap1, thereby activating antioxidant response element-driven enzymatic defenses in cell and animal models. Phenolic constituents and electrophilic compounds bearing an α,β-unsaturated carbonyl structure may directly activate Nrf2 by modifying Keap1 cysteine residues, whereas non-phenolic terpenes likely depend on oxidative metabolism to form active electrophilic species. Despite broad evidence of antioxidant efficacy, molecular characterization of EO-protein interactions remains limited. This review integrates radical-chain dynamics with redox signaling biology to clarify the mechanistic basis of EO antioxidant activity and to provide a framework for future research. Antioxidant ; Autoxidation ; Radical ; Terpene ; Lipid peroxidation ; KEAP1 ; Redox ; Electrophile Free Radicals and Antioxidants ; Genomics, phytochemicals, and oxidative stress ; Phytochemicals and Antioxidant Activities
Authors: Lee-Anne J Walter | Michael Scherdel | Iman Taha
Source: Journal of Composites Science (article, 2025-05-14)
Field: Materials Science — Polymers and Plastics

Fabrication and Characterisation of Fully Bio-Based Flax Fibre-Reinforced Polyester Composites The development of lightweight construction is of crucial importance for the development of sustainable technologies and for the reduction in carbon dioxide emissions, especially in the automotive industry. This study aims to address the challenges associated with manufacturing plant fibre-based polymer composites. The investigation focused on two novel formulations of bio-based unsaturated polyester resins, assessing their viability as a matrix in plant fibre-reinforced composites within the context of automotive applications. The study addresses the challenges related to the preparation and processing of the system, leading to the necessity of diluting the resin with (hydroxymethyl)methacrylate (HEMA) to achieve an applicable viscosity. Two different flax fibre textiles, in the form of a short fibre mat and a woven fabric, were used as reinforcement. The composite panels were manufactured using the vacuum-assisted resin infusion (VARI) process. The most efficacious material combination, comprising Bcomp® ampliTex™ 5040 and STRUKTOL® POLYVERTEC® 3831, with viscosity modified by 39% HEMA, exhibited a consistent fibre volume fraction of 40% and a glass transition temperature of 70 °C. In addition, the mechanical behaviour in the 0°-direction demonstrated tensile strength and modulus values of approximately 99 MPa and 9 GPa, respectively, accompanied by an elongation at break of 2%. The flexural modulus was found to be 7 GPa, and the flexural strength 94 MPa. Fabrication ; Composite material ; Polyester ; Materials science Natural Fiber Reinforced Composites ; Mechanical Engineering and Vibrations Research
Authors: Michiki Taniwaki | Ryunosuke Nagaoka | Ken Masuzawa | Shunsuke Sato | Alexandre Lira Foggiatto | Chiharu Mitsumata | Takahiro Yamazaki | Ippei Obayashi | Yasuaki Hiraoka | Yasuhiko Igarashi | Yuta Mizutori | Sepehri Amin Hossein | Tadakatsu Ohkubo | Hisashi Mogi | Masato Kotsugi
Source: Scientific Reports (article, 2025-07-15)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Automated identification of the origin of energy loss in nonoriented electrical steel by feature extended Ginzburg–Landau free energy framework This study presents the automated identification of the complex magnetization reversal process in nonoriented electrical steel (NOES) using the feature extended Ginzburg-Landau (eX-GL) free energy framework. eX-GL provides a robust connection between microscopic magnetic domains and macroscopic magnetic hysteresis using a data science perspective. This method employs physically meaningful features to analyze the energy landscape, providing insights into the mechanisms behind function. We obtained features representing both the microstructure and energy of the domain wall. The causes of iron loss were traced to the original domain structure, through which we could successfully distinguish and visualize the role of pinning as a promoting and resisting factor. We found that the reversal process was governed not only by general grain boundary pinning but also by segmented magnetic domains within the grain. This method revealed the complex interplay between magnetism and metallography and introduced a new means for transformative material design, bridging structures and functions. Magnetism ; Condensed matter physics ; Magnetic domain ; Hysteresis ; Domain (mathematical analysis) ; Grain boundary ; Materials science ; Magnetization ; Energy (signal processing) ; Microstructure ; Electrical steel ; Computer science ; Nuclear magnetic resonance ; Physics ; Magnetic field ; Metallurgy ; Mathematics ; Mathematical analysis Magnetic Properties and Applications ; Magnetic properties of thin films ; Geomagnetism and Paleomagnetism Studies
Authors: Mithony Keng | Kenneth M. Merz
Source: Journal of the American Society for Mass Spectrometry (article, 2025-02-10)
Field: Chemistry — Spectroscopy

In Silico Characterization of Glycan Ions from IM-MS Collision Cross Section Ion mobility mass spectrometry (IM-MS) can assist in the identification of isobaric chemical analytes by exploiting the difference in their gas phase collision cross-section (CCS) property. In glycomics, reliable glycan characterization remains challenging, even with IM-MS, because of closely related isomeric species and the available binding arrangements of substituted monosaccharides, allowing for the formation of complex structures. Here, we present a computational procedure to obtain gas-phase structural information from the experimental IM-MS CCS data of carbohydrates. The workflow proceeds with high throughput charge modeling of glycan seed structures to determine the precise protonation or deprotonation site. The charge models were then screened by using density functional theory (DFT) to produce candidate charge states for conformation generation. An extensive conformational scoring of the glycan ions was performed quantum mechanically at the DFT D3-B3LYP/6-31G+(d,p) level for the negative mode, [M - H]<sup>-</sup>, and at the D3-B3LYP/6-31G(d,p) level for the positive mode, [M + H]<sup>+</sup>. For most of our test set, the computed CCS values from the final geometry optimized structures showed good agreement with experiment. We also demonstrated the capability of characterizing configurational and constitutional isomeric species. Altogether, we believe that the method we used in this work can be used to build a reliable theoretical reference database for glycans that can be used for experimental quality control and for assigning molecular structure to experimental IM-MS CCS information. Chemistry ; Glycan ; In silico ; Characterization (materials science) ; Mass spectrometry ; Collision ; Ion ; Nanotechnology ; Computational biology ; Chromatography ; Biochemistry ; Organic chemistry ; Glycoprotein Mass Spectrometry Techniques and Applications ; Analytical chemistry methods development ; Microfluidic and Capillary Electrophoresis Applications