jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Tianqu Chen | Mingfeng Xu | Mingbo Pu | Xi Tang | Yuhan Zheng | Qingji Zeng | Yuting Xiao | Yingli Ha | Yinghui Guo | Fei Zhang | Nan Chi | Xiangang Luo
Source: Nanophotonics (article, 2025-01-07)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Free‐form catenary‐inspired meta‐couplers for ultra‐high or broadband vertical coupling Metasurface-assisted waveguide couplers, or meta-couplers, innovatively link free-space optics with on-chip devices, offering flexibility for polarization and wavelength (de)multiplexing, mode-selective coupling, and guided mode manipulation. However, conventional meta-couplers still face challenges with low coupling efficiency and narrow bandwidth due to critical near-field coupling caused by waveguide constraints and unit-cell-based design approach, which cannot be accurately addressed using traditional design methods. In this paper, quasi-continuous dielectric catenary arrays are first employed to enhance efficiency and bandwidth by addressing adjacent coupling issues of discrete metasurface. Then, diffraction analysis demonstrates that the performance of forward-designed couplers is hindered by spurious diffraction orders and destructive interference. To further enhance performance, an adjoint-based topology optimization algorithm is utilized to customize electric near-field, which can effectively suppress spurious diffraction orders and destructive near-field interference, achieving ultra-high coupling efficiency of 93 % with 16.7 dB extinction ratios at 1,550 nm. Additionally, a broadband meta-coupler exceeds 350 nm bandwidth with 50 % average coupling efficiency across O- to L-bands using multiobjective optimization. These high-performance devices may render them suitable for applications in optical communications, sensing, and nonlinear optics. Moreover, the inverse design method shows potential for improving the performance of various metasurface-integrated on-chip devices. Bandwidth (computing) ; Broadband ; Optics ; Electronic engineering ; Diffraction ; Computer science ; Materials science ; Coupling (piping) ; Power dividers and directional couplers ; Diffraction efficiency ; Optoelectronics ; Physics ; Telecommunications ; Engineering Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: David E. Korenchan | Ethan French | Emerenziana Runco | Chetan Dhakan | Jinwu Yan | Hiroshi Nakashima | Michael T. McMahon | Assaf A. Gilad | Christian T. Farrar
Source: Chemistry - A European Journal (article, 2025-09-10)
Field: Materials Science — Materials Chemistry

Optimization of CEST MRI Reporter Protein Design Using Cation‐Pi Networks Nucleic acid-based therapeutics, such as oncolytic virotherapy or gene therapy, would benefit greatly from a reporter gene that induces endogenous production of a protein biomarker to noninvasively track the delivery, persistence, and spread with imaging. Several chemical exchange saturation transfer (CEST) reporter proteins detectable by magnetic resonance imaging (MRI) have been demonstrated to have high sensitivity. However, to date none can provide strong CEST contrast at a distinct resonance from that of endogenous proteins, limiting their specificity. We investigated proteins and peptides containing tyrosine (Tyr), tryptophan (Trp), and lysine (Lys) residues that demonstrate CEST contrast shifted far downfield (4-10 ppm) from water. Although Tyr, Trp, and Lys exchangeable protons are typically not detectable under physiological conditions, those in our tested molecules are, having exchange rates of 400-2500 s<sup>-1</sup>. The large chemical shift dispersion and rapid exchange rates are attributed to unique hydrogen bonding and cation-π network interactions. These discoveries set the stage for designing a stable reporter protein with high detection specificity and sensitivity that can facilitate the in vivo monitoring of viral and gene therapies using MRI. Reporter gene ; Oncolytic virus ; Limiting ; Endogeny ; Gene ; Magnetic resonance imaging ; Tyrosine ; In vivo Lanthanide and Transition Metal Complexes ; Advanced MRI Techniques and Applications ; Electron Spin Resonance Studies
Authors: SHETTAHALLI MANTAIAH VINU KUMAR | R. Thangavel | Ranganathan Soundararajan | CHANDRASEKARAN SASIKUMAR | ERUSAGOUNDER SAKTHIVELMURUGAN | CHINNASAMY NITHIYAPATHI
Source: Cellulose Chemistry and Technology (article, 2025-12-15)
Field: Materials Science — Polymers and Plastics

EVALUATION OF DYNAMIC MECHANICAL PROPERTIES OF FLAX FIBERPOLYPROPYLENE (FP) COMPOSITES USING THE ADAPTIVE NEUROFUZZY INFERENCE SYSTEM Flax fiber reinforced polypropylene (FP) composites were prepared using the compression moulding technique and their dynamic mechanical (DM) properties were studied based on the fiber content. Fiber loading was varied from 0 to 50 vol% with increments of 10 vol% and the samples were designated accordingly as neat PP, FP10, FP20, FP30, FP40, and FP50 composites. The results showed that increased fiber content in the PP matrix improved the DM properties, such as storage modulus (E’), loss modulus (E”), and damping factor (Tanδ). Amongst the fabricated FP laminates, FP40 composites exhibited better viscoelastic performance. Furthermore, the adaptive neuro-fuzzy inference system (ANFIS) was implemented to predict the DM properties, mainly, E’ and E” of the FP composites. The validation of the ANFIS model showed that experimental and predicted results were in good agreement to each other, confirming its reliability in forecasting the DM properties of flax fiber reinforced polypropylene (FP) composites. This study also investigated the thermal degradation behavior of the FP composites using thermogravimetric analysis (TGA). The results showed that thermal stability of the neat PP improved from 432.69 °C to 463.90 °C for optimal fiber loading of 40 vol% flax fiber (FP40). Fractured samples of FP composites were examined using scanning electron microscopy (SEM) to comprehend the interfacial bonding mechanism of the FP composites. Polypropylene ; Fiber ; Thermogravimetric analysis ; Dynamic mechanical analysis ; Viscoelasticity ; Scanning electron microscope ; Thermal stability ; Natural fiber ; Modulus Natural Fiber Reinforced Composites ; Mechanical Behavior of Composites ; Polymer crystallization and properties
Authors: Gemechis Mathewos Fite | Fekadu Tolessa Maremi | Abebe Belay | Girum A. Beyene | Melak Birara
Source: Discover Applied Sciences (article, 2025-12-02)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Highly selective and efficient gas sensor based on a narrow-band IR metamaterial absorber using numerical simulation This study investigates the application of metamaterials for detecting ozone (O₃) and nitric oxide (NO) using Finite Element Method (FEM) simulations. It presents a novel design for a terahertz metamaterial (MTM) absorber that can detect variations in the refractive index (RI) of its environment. The structure is defined by a negative effective permeability and positive permittivity, categorizing it as a µ-negative metamaterial. It features a tungsten swastika pattern on a hafnium dioxide (HfO2) spacer, achieving nearly complete absorption of 99.85% at 2.85 terahertz (THz) with a quality factor (Q-factor) of 167.25. FEM simulations indicate significant resonance shifts when exposed to O₃ and NO, underscoring the potential of metamaterial-based sensors for real-time environmental monitoring. These resonance shifts correspond to gas concentrations, indicating the feasibility of quantitative sensing. The findings highlight the benefits of metamaterials in gas detection and lay the groundwork for future experimental validation and the creation of effective sensor devices to improve air quality monitoring and protect public health. Developed a highly sensitive sensor that detects harmful gas like ozone and nitric oxide in real time. Uses engineered materials to spot gases by observing changes in light absorption at specific frequencies. Offers a promising tool for improving air quality monitoring and protecting public health. Metamaterial ; Terahertz radiation ; Metamaterial absorber ; Refractive index ; Absorption (acoustics) ; Resonance (particle physics) ; Computer simulation ; Ozone Metamaterials and Metasurfaces Applications ; Terahertz technology and applications ; Gas Sensing Nanomaterials and Sensors
Authors: Yan Zhou | Minmin Zhang
Source: IET Power Electronics (article, 2025-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Predicting core losses in power converters based on open source database Abstract Core losses are closely related to flux densities, frequencies, temperatures, exciting waveforms, and DC biases. Hysteresis losses and dynamic losses are considered the main components of core losses. A method for predicting core losses based on an open‐source database and a data‐driven physical model is proposed. To a certain predicted point, two paths in the procedure can be executed automatically. First, if there are two points in the database with similar working conditions to the predicted point, core loss power density can be directly predicted based on separate equations. Secondly, if loss power density for specific waveforms in the database are missing, hysteresis loss power density and dynamic loss power density under sinusoidal excitations can be utilized to estimate core loss power density for specific waveforms. Based on the proposed method, the impact of temperature on hysteresis loss power density and dynamic loss power density can also be individually fitted and analysed. The proposed concepts demonstrate good flexibility in handling various complex waveforms in power electronics and have been accurately verified using the loss data of N49 and N87 in the MagNet database. Core (optical fiber) ; Converters ; Open source ; Computer science ; Power (physics) ; Database ; Telecommunications ; Operating system ; Software ; Physics Magnetic Properties and Applications ; High-Voltage Power Transmission Systems ; HVDC Systems and Fault Protection
Authors: Dongsheng Hong | Chao Chen | Xujia Li | Shuhui Wang | Wenbin Lin | Xiangwen Liao
Source: Proceedings of the AAAI Conference on Artificial Intelligence (article, 2025-04-11)
Field: Materials Science — Materials Chemistry

MSR: A Multifaceted Self-Retrieval Framework for Microscopic Cascade Prediction The microscopic cascade prediction task has wide applications in downstream areas like ''rumor detection''. Its goal is to forecast the diffusion routines of information cascade within networks. Existing works typically formulate it as a classification task, which fails to well align with the Social Homophily assumption, as it just use the features of ''infected'' users while neglecting those of ''uninfected'' users in representation learning. Moreover, these methods focus primarily on social relationships, thereby dismissing other vital dimensions like users' historical behavior and the underlying preferences behind it. To address these challenges, we introduce the MSR (Multifaceted Self-Retrieval) framework. During encoding, in addition to the existing social graph, we construct a preference graph to represent ''behavioral preferences'' and further propose a modified multi-channel GRAU for multi-view analysis of cascade phenomenon. For decoding, our approach diverges from classification-based methods by reformulating the task as an information retrieval problem that predicts the target user with similarity measures. Empirical evaluations on public datasets demonstrate that this framework significantly outperforms baselines on Hits@κ and MAP@κ, affirming its enhanced ability. Cascade ; Computer science ; Artificial intelligence ; Chemistry Machine Learning in Materials Science
Authors: Ke He | Yuan Su | Lei He | Can Hu | Jianfei Xing | Naimov Alisher
Source: Frontiers in Plant Science (article, 2025-12-01)
Field: Chemistry — Analytical Chemistry

Modeling of table grape soluble solids content, titratable acidity and pH prediction during storage based on Vis-NIR spectroscopy This study, for the first time, utilized Vis-NIR spectroscopy to achieve the simultaneous and rapid determination of multiple quality attributes in table grapes, providing a novel and efficient strategy for real-time and non-destructive quality evaluation during storage. The proposed approach showed considerable potential for rapid quality assessment and postharvest management of grapes. Future research will focus on expanding the diversity of grape cultivars and investigating various storage conditions to improve the robustness and transferability of the predictive model, thereby promoting the industrial validation and practical application of Vis-NIR spectroscopy in fruit quality monitoring. Table grape ; Titratable acid ; Postharvest ; Transferability ; Robustness (evolution) ; Spectroscopy Spectroscopy and Chemometric Analyses ; Edible Oils Quality and Analysis ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Jianyu Hu | Junyi Yang | Sulei Hu | Jinxun Liu | Weixue Li
Source: Scientia Sinica Chimica (article, 2025-04-15)
Field: Materials Science — Materials Chemistry

Interpretable machine learning-assisted development of catalytic science theory 催化剂的设计和优化一直是催化科学的重大挑战。发展基于物理本质的理论框架有望推动催化领域向更加高效、稳定、可持续的方向迈进。近年来，人工智能技术在催化科学领域的应用取得了显著进展，为催化理论的建立和优化提供了全新的工具和方法。本文聚焦于催化科学的一般性物理理论的构建，展示了可解释人工智能技术在建立面向工业化催化剂的新理论方面的研究进展。主要介绍了数据驱动方法和可解释机器学习在提出纳米催化剂抗烧结的稳定性理论，发现金属载体相互作用的本质以及分子吸附活化的结构敏感性特征发现等方面的成功应用。最后，对可解释机器学习方法的技术发展和在催化科学领域的潜在应用做了展望。 Biology Machine Learning in Materials Science ; CO2 Reduction Techniques and Catalysts ; Catalysis and Oxidation Reactions
Authors: Yong-Zeng Zhang | Jian Li | Jin Sun | Tian Xia | Yonglin Hai | Yongcheng Yang | Conglong Xia
Source: Molecules (article, 2025-04-22)
Field: Chemistry — Analytical Chemistry

Rapid Identification of Vicatia thibetica de Boiss and Quantitative Analysis of the Content of Six Chemical Components Based on Near-Infrared Spectroscopy This study developed a rapid, non-destructive method combining near-infrared (NIR) spectroscopy with chemometric techniques (OPLS-DA, ANN, and PLS) to accurately identify the geographic origin and quantify six key chemical components of <i>V. thibetica</i> rhizomes. The results demonstrated that the combination of NIR spectroscopy, OPLS-DA, and ANN successfully and accurately distinguished <i>V. thibetica</i> from three distinct origins. Additionally, combining partial least squares (PLS) and NIR spectroscopy, the contents of chlorogenic acid, isochlorogenic acid A, isochlorogenic acid C, umbelliferone (7-hydroxycoumarin), senkyunolide I, and ligustilide measured by HPLC-UV were used as reference values to predict the contents of the six chemical components in <i>V. thibetica</i>, and spectral preprocessing methods optimized the model. The correlation coefficients of the final quantitative model for the contents of the six components in <i>V. thibetica</i> were between 0.7852 and 0.9538, the root mean square error of calibration (RMSEC) was between 0.0027 and 0.2530, and the root mean square error of prediction (RMSEP) was between 0.0031 and 0.4240. The results suggest that NIR spectroscopy combined with OPLS-DA and ANN can be used as a rapid and accurate method to evaluate the quality of <i>V. thibetica</i> herbs. Partial least squares regression ; Near-infrared spectroscopy ; Chlorogenic acid ; Chemistry ; Spectroscopy ; Calibration ; Infrared spectroscopy ; Chromatography ; Analytical Chemistry (journal) ; Chemometrics ; Biological system ; Mathematics Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Traditional Chinese Medicine Analysis
Authors: George Z. Voyiadjis | Peter I. Kattan
Source: Acta Mechanica (article, 2025-04-29)
Field: Materials Science — Materials Chemistry

Interaction of damage processes in continuum damage mechanics Abstract This work presents novel mathematical formulations for the interaction of damage processes within the framework of continuum damage mechanics, focusing on advanced numerical applications. The approach involves an innovative analogy between the decomposition of the damage variable/tensor and the rule of mixtures, leading to both scalar and tensorial representations. Four distinct cases are explored for each formulation: (1) basic interaction of two damage processes, (2) exponential interaction of two damage processes, (3) basic interaction of three damage processes, and (4) unsymmetrical interaction of two damage processes. The study further investigates a detailed plane stress example, where a system of nine coupled algebraic interaction equations is derived for each scenario. In particular, it is shown that these equations reduce to three core interaction equations in a special case, one of which is identified as the coupling interaction equation. The paper emphasizes mathematical rigor, with the goal of extending this research to tackle real-world problems and enhance numerical modeling techniques in future work. Solid mechanics ; Peridynamics ; Damage mechanics ; Continuum mechanics ; Classical mechanics ; Mechanics ; Materials science ; Physics ; Structural engineering ; Finite element method ; Engineering ; Composite material Nonlocal and gradient elasticity in micro/nano structures ; Numerical methods in engineering ; High-Velocity Impact and Material Behavior
Authors: Xiaojuan Tang | Changju Ma | Yuan Ren | Yuan Lv | Yongheng He | Ling Han | Jingjing Wu
Source: Journal of Inflammation Research (article, 2025-04-01)
Field: Chemistry — Organic Chemistry

Revealing the Potential of Solamargine for Anti Metastasis and Angiogenesis Inhibition in Nasopharyngeal Carcinoma SM inhibits NPC cell invasion and migration by regulating EMT, suppressing angiogenesis, and modulating key pathways. These findings highlight SM's potential as an anti-cancer agent for NPC and provide new insights into its mechanisms. Network pharmacology and GO-KEGG analysis further identify its therapeutic targets, offering valuable directions for future drug development. Nasopharyngeal carcinoma ; Angiogenesis ; Metastasis ; Cancer research ; Carcinoma ; Medicine ; Biology ; Oncology ; Internal medicine ; Cancer ; Radiation therapy Synthesis and biological activity ; Bioactive Compounds and Antitumor Agents
Authors: Krishna Lok Singh
Source: Advances in Aerospace Science and Technology (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Pitting Corrosion as a Failure Mechanism in Aircraft Panels: A Modelling and Simulation Approach Pitting corrosion is a significant failure mechanism in aging aircraft structures, potentially leading to catastrophic structural failures. This study investigates the stress distribution around idealized cylindrical corrosion pits in aluminium aircraft panels under uniaxial tensile loading using three-dimensional finite element analysis (3D FEA). A systematic approach was employed to analyse the influence of varying pit diameters and depths on stress concentration. The maximum stress concentration was consistently observed at the pit’s anterior surface, perpendicular to the loading direction. A novel modified formula was developed to calculate the stress concentration factor (SCF) in pitted panels, considering the remaining material thickness, and providing a more accurate prediction compared to traditional methods. The results revealed a clear relationship between the pit aspect ratio (depth/diameter) and the SCF. A bi-linear material model was implemented to determine the yield strength of the panel under these conditions. The analysis also explored the stress concentrations associated with triangular pit geometries, demonstrating elevated stress levels compared to cylindrical pits of equivalent area. These findings offer critical insights into the structural integrity of aircraft panels affected by pitting corrosion. The proposed novel formula improves the prediction of structural failure and can be applied to enhance design and maintenance protocols in the aerospace industry to improve aircraft longevity and safety. Mechanism (biology) ; Pitting corrosion ; Corrosion ; Failure mechanism ; Forensic engineering ; Engineering ; Computer science ; Structural engineering ; Materials science ; Metallurgy ; Physics Anodic Oxide Films and Nanostructures ; Concrete Corrosion and Durability ; Corrosion Behavior and Inhibition
Authors: Daniel Meyer | Sophia Hörnlein | Dietrich Rein | Gertrud E. Morlock
Source: Analytical and Bioanalytical Chemistry (article, 2025-05-19)
Field: Chemistry — Organic Chemistry

Proposed RP–HPTLC–FLD kit for analysis of vitamin A palmitate in edible oils Preschool-aged children and non-pregnant women of reproductive age particularly in countries of a lower socio-demographic index may experience insufficient dietary vitamin A. Fortifying staple foods such as edible oils with vitamin A is a useful approach to reduce malnutrition. To enable better quality oil fortification, producers need reliable and inexpensive tools for assessment of the vitamin A contents of their products. A simple reversed-phase high-performance thin-layer chromatography fluorescence detection (RP-HPTLC-FLD) method was developed and studied for the quantification of vitamin A palmitate (VAP) in five edible plant oils. The challenging matrices of non-refined palm kernel oil and soybean oil, which are known to interfere with the accuracy of some easy-to-use test kits, were separated from VAP using the new RP-HPTLC-FLD method. The standard addition method provided good accuracy and acceptable calibration curves (coefficients of determination R<sup>2</sup> between 0.9874 and 0.9999) even for manual application. The developed RP-HPTLC-FLD method proved simple, robust, sustainable, cost-efficient, and suitable for low-tech (minimum equipment) on-site analysis. Chromatography ; Edible oil ; Palm oil ; Vitamin ; Food science ; Chemistry ; Biochemistry Edible Oils Quality and Analysis ; Antioxidant Activity and Oxidative Stress ; Chemical and Physical Properties in Aqueous Solutions
Authors: Nadia Miftahul Jannah | Karina Primatyas Ningrum | Firhani Anggriani Syafrie
Source: Journal of Food and Pharmaceutical Sciences (article, 2025-06-30)
Field: Chemistry — Analytical Chemistry

Application of Clustering Analysis with Unsupervised Technique on Fish Oil Samples Fish oil contains many fatty acids (FAs) important for human health. Each fish oil tends to have a different fatty acid content. This study aims to group the fish oil content profile in several samples, such as keting fish oil (KFO), catfish oil (CFO), and pomfret fish oil (PFO), based on GC-MS analysis data with unsupervised techniques. GC-MS is a method that can be used to identify the fatty acid content in fish oil. Fish oil is extracted using the dry rendering method combined with a hydraulic press to obtain the oil, then derivatised before being analysed on the GC-MS instrument. Due to the multivariate data from GC-MS, multivariate statistical techniques are required to effectively group the fish oil samples based on their Fatty Acid profiles. Principal Component Analysis (PCA) and Cluster Analysis (CA) chemometrics are unsupervised techniques that can group multivariate data by displaying plot scores and dendrograms of sample analysis results. The fatty acid content of keting fish, catfish, and pomfret fish oil has three dominant compounds in sequence, namely oleic acid, palmitic acid, and stearic acid, with different percentages. Thegrouping profile of fish oil was successfully determined by PCA, total variance explained by the first four components (PC4) of 99.4%, and CA, which produced three groups based on the fatty acid content of fish oil. Fish oil ; Principal component analysis ; Stearic acid ; Fatty acid ; Chemometrics ; Oleic acid ; Palmitic acid ; Multivariate statistics Spectroscopy and Chemometric Analyses