jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Heiber Andres Trujillo | Pedro Alexander Velasquez Vasconez | Rafael Mateus Alves | Fernando Henrique Iost Filho | Francisco Guilhien Gomes-junior
Source: Tekirdağ Ziraat Fakültesi Dergisi (article, 2026-01-07)
Field: Chemistry — Analytical Chemistry

Hyperspectral Imaging and Machine Learning for Assessing the Germination of Hydroprimed Lettuce Seeds Hyperspectral imaging (HSI) provides high-resolution spectral information across broad wavelength ranges and has emerged as a promising non-destructive approach for assessing seed quality. This study validated the use of HSI combined with machine learning to identify spectral features associated with germination performance in hydroprimed lettuce seeds. Seeds of the Roxa and Vanda genotypes were subjected to hydropriming, dried, and stored prior to evaluation. Hyperspectral images were acquired using 300 spectral bands spanning 384.7–1020.7 nm for each treatment, and mean spectra were used as predictors in classification models. Machine learning analysis was performed primarily with Random Forest to discriminate seed performance categories, including normal seedlings, abnormal seedlings, non-germinated seeds, and dead seeds. Feature-importance results indicated that wavelengths near 390 nm were among the most informative predictors of germination performance, whereas bands at 473–475 nm contributed comparatively less. The Random Forest models showed high sensitivity and specificity across the defined classes, supporting the feasibility of spectral-based categorization of seed outcomes. In complementary analyses, Ridge regression reinforced the relevance of peripheral regions of the spectrum, highlighting 384.73 nm and 874.57 nm as important for classification and underscoring the value of targeted band selection to improve model interpretability and efficiency. Hydropriming affected both spectral signatures and physiological responses, with genotype- and lot-dependent outcomes. In Roxa, selected seed lots exhibited superior performance in germination and vigor tests after hydropriming and storage. In Vanda, specific lots displayed greater uniformity and improved emergence indices. Overall, the integration of HSI and machine learning captured strong associations between spectral data and seed performance metrics, with high canonical correlations (R² = 0.91–0.99). These results demonstrate that HSI coupled with predictive modeling is an effective, rapid, and non-destructive strategy to assess the physiological quality of hydroprimed lettuce seeds and to support decision-making in seed lot classification. Hyperspectral imaging ; Interpretability ; Random forest ; Germination ; Categorization ; Feature selection ; Spectral signature ; Pattern recognition (psychology) Spectroscopy and Chemometric Analyses ; Seed Germination and Physiology ; Smart Agriculture and AI
Authors: Natanel Nissan | Sherman W. Marcus | Dan Raviv | Giryes, Raja | Ariel Epstein
Source: ArXiv.org (article, 2026-03-04)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Harnessing Selective State Space Models to Enhance Semianalytical Design of Fabrication-Ready Multilayered Huygens' Metasurfaces: Part II - Generative Inverse Design (MetaMamba) We present a generative framework for inverse design of five-layer transmissive Huygens' metasurfaces (HMSs), addressing a longstanding challenge in achieving full-phase, high-efficiency unit cell designs with minimal full-wave simulations. The key to achieving this is our reliance on the field-based semianalytical (SA) scheme developed in Part I of this paper, which allows rapid and highly effective synthesis of such multilayer composites, however with limited accuracy. To overcome the prohibitive data demands of traditional pipelines, we employ Mamba, a selective state space model well suited for long-range sequence modeling as the backbone of our learning framework. A bidirectional Mamba (Bi-Mamba) forward surrogate is first trained on SA-generated data and subsequently fine-tuned with full-wave CST samples. An ablation over a 1080-sample CST pool shows that as few as 270 full-wave calibration samples suffice to reach near-CST-level agreement at a fraction of the simulation cost. An autoregressive Mamba inverse generator is subsequently trained on surrogate-augmented data, treating unit-cell synthesis as a sequential generation task. The resulting one-to-many generative model produces diverse unit cell geometries conditioned on target scattering responses. It achieves CST-validated designs with field transmission magnitude 0.9 across the full 0-$2π$ phase range at 20 GHz. Moreover, a CST-calibrated surrogate trained to accurately predict frequency responses (18-22 GHz) enables functional post-selection of inverse generated designs. Together, the hybrid SA-generative methodology in this two-part compilation establishes a scalable and data-efficient solution for multilayer HMS synthesis, with natural extensions toward broadband, oblique-incidence, and higher-dimensional electromagnetic inverse-design problems. Inverse ; Scalability ; Range (aeronautics) ; Generator (circuit theory) ; Sequence (biology) ; Field (mathematics) ; Transmission (telecommunications) ; Inverse problem ; Surrogate model ; Generative Design Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Advanced Wireless Communication Technologies
Authors: T. Hu | Dongming Zhu | Xiao Jin | Yanan Chen | Meng Gao | Xuanyuan Zhang | Min Nie | Bingnan Yao | Wei Xu | Lijian Song | Juntao Huo | Wenbo Wang | Xiaojun Zhao | Mingliang Xiang | Jun‐Qiang Wang | Yan Zhang
Source: Advanced Science (article, 2026-01-26)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Designing Advanced Soft Magnetic Powder Cores with Ultralow Energy Loss by Combining Ultrasonic and Static Compaction Power inductors are critical in electronics and automotive systems, with integrated inductors gaining attention for miniaturization and high power efficiency. Iron-based amorphous/nanocrystalline soft magnetic powders offer high permeability and low core loss, yet their high strength and brittleness pose compaction challenges. This study introduces an ultrasonic vibration-assisted cold pressing (UVP-CP) technique, which promotes particle rearrangement and interlocking by reducing interparticle friction, enabling the fabrication of dense powder cores under reduced forming pressure. Compared with conventionally cold pressed cores fabricated from the same powder system, the UVP-CP samples exhibit improved soft magnetic performance, achieving an effective permeability (µ<sub>e</sub>) of 47.8 at 10 MHz and a core loss of 175.8 mW/cm<sup>3</sup> at 50 mT/100 kHz. These values represent a 21.0% improvement in permeability and a 43.4% reduction in core loss over conventional counterparts, establishing a new paradigm for high performance integrated inductor fabrication. Miniaturization ; Inductor ; Compaction ; Fabrication ; Pressing ; Permeability (electromagnetism) ; Ultrasonic sensor ; Core (optical fiber) ; Brittleness Magnetic Properties of Alloys ; Metallic Glasses and Amorphous Alloys ; Nanomaterials and Printing Technologies
Authors: Qichen Xu | Anna Delin
Source: npj Computational Materials (article, 2026-02-06)
Field: Materials Science — Materials Chemistry

A general optimization framework for mapping local transition-state networks Abstract Understanding how complex systems transition between states requires mapping the energy landscape that governs these changes. Local transition-state networks reveal the barrier architecture that explains observed behaviour and enables mechanism-based prediction across computational chemistry, biology, and physics, yet in many practical settings current approaches either require pre-specified endpoints or rely on single-ended searches that provide only a limited sample of nearby saddles. We present a general optimization framework that systematically expands local coverage by coupling a multi-objective explorer with a bilayer minimum-mode kernel. The inner layer uses Hessian-vector products to recover the lowest-curvature subspace, the outer layer optimizes on a reflected force to reach index-1 saddles, then a two-sided descent certifies connectivity. The GPU-based pipeline is portable across autodiff backends and eigensolvers and, on large atomistic-spin tests, matches explicit-Hessian accuracy while cutting peak memory and wall time by orders of magnitude. Applied to a DFT-parameterized Néel-type skyrmionic model, it recovers known routes and reveals previously unreported mechanisms, including meron-antimeron-mediated Néel-type skyrmionic duplication, annihilation, and chiral-droplet formation, enabling up to 32 pathways between biskyrmion ( Q = 2) and biantiskyrmion ( Q = −2). The same core transfers to Cartesian atoms, automatically mapping canonical rearrangements of a Ni(111) heptamer, underscoring the framework’s generality. Pipeline (software) ; Layer (electronics) ; Energy (signal processing) ; Cartesian coordinate system ; Coupling (piping) ; Gradient descent ; Scheme (mathematics) ; Point (geometry) ; Core (optical fiber) Machine Learning in Materials Science ; Surface Chemistry and Catalysis ; Advanced Chemical Physics Studies
Authors: Peter Kepič | Petra Kalousková | Tomáš Šikola | Filip Ligmajer
Source: ArXiv.org (article, 2026-04-07)
Field: Materials Science — Polymers and Plastics

Controlled dewetting and phase transition hysteresis of VO2 nanostructures As artificial intelligence continues to grow, so does the need for more efficient ways to process data. Besides moving from electronic to photonic circuits, a promising approach is to integrate phase-change materials. Vanadium dioxide (VO$_2$) exhibits an ultrafast, near-room-temperature phase transition, characterized by hysteresis and large optical modulation -- making it a promising candidate for short-term memories and for mimicking neural behavior in brain-like computing systems. While the hysteresis behavior of VO$_2$ has been well studied in thin films and nanostructures, practical control and device integration have been limited only to thin films. Here, we demonstrate control over the phase transitions of VO$_2$ nanocylinders via lithographic patterning, controlled crystallization, and controlled dewetting. Because nanostructures are easier to address and consume less power than films, the ability to fabricate them with tailored geometry and hysteresis properties directly on integrated platforms is a key step toward scalable, energy-efficient memory and neuromorphic photonic devices. Dewetting ; Hysteresis ; Neuromorphic engineering ; Photonics ; Nanostructure ; Phase transition ; Thin film ; Phase (matter) ; Modulation (music) Transition Metal Oxide Nanomaterials ; Chemical and Physical Properties of Materials ; Phase-change materials and chalcogenides
Authors: Zuoyong Zhang | Chuang Deng
Source: Acta Materialia (article, 2026-03-05)
Field: Materials Science — Materials Chemistry

Disconnection formation via segregation-induced grain boundary phase transitions Disconnections, long recognized as the key mediators of grain boundary (GB) kinetics in polycrystalline materials, have traditionally been understood to nucleate through thermal or mechanical activation. In this work, using atomistic simulations, we reveal a distinct nucleation mechanism driven exclusively by solute interstitial segregation across multiple substitutional binary alloy systems (e.g., Al-Ni, Al-Fe). This process exhibits zero-nucleation energy barriers, contrasting sharply with the nucleation mechanisms in pure systems. We identify states which are activated through segregation induced GB phase transitions: (i) isolated disconnections or phase junctions that promote GB migration and disappear with continuous segregation, and (ii) composite disconnections that are formed via two oppositely oriented isolated disconnections. The disconnections are mechanically robust, suppressing shear-coupled migration and instead resulting in GB amorphization and pure sliding under applied shear loading. The long-range stress fields associated with these composite disconnections further attract solute atoms and assist the nucleation of precipitates. These disconnections, absent in pure materials, follow unique nucleation pathways as confirmed through dichromatic pattern analysis and persist across different alloy chemistries and crystal structures. Our findings demonstrate that solute interstitial segregation provides a powerful and previously unrecognized pathway for barrier-free disconnection formation, thereby fundamentally extending current understanding of GB kinetics in alloy systems. Nucleation ; Grain boundary ; Crystallite ; Alloy ; Phase (matter) ; Kinetics ; Phase boundary ; Phase transition Microstructure and mechanical properties ; Metallic Glasses and Amorphous Alloys ; Solidification and crystal growth phenomena
Authors: Hongyu He | Li Ma | Zhiyi Xie | Yufan Liu | Chao Wu | Qiye Zheng | Yi Tao | Yunfei Chen | Chenhan Liu
Source: ArXiv.org (article, 2026-01-15)
Field: Materials Science — Surfaces, Coatings and Films

Interference-governed electromagnetic-thermal coupling and heat transport in pulse EUV-irradiated multilayer nanofilms Mo-Si multilayer mirrors are central to extreme ultraviolet lithography, where nanoscale optical interference and heat accumulation together constrain reflectivity and operational stability. Here we develop an analytical electromagnetic-thermal coupling model that directly links transfer-matrix-based interference-controlled energy deposition with transient heat conduction in EUV-irradiated multilayers. The model reveals a fundamental trade-off whereby increasing the multilayer period number enhances reflectivity but simultaneously elevates temperature by impeding heat dissipation. Interference-driven volumetric absorption further gives rise to pronounced axial temperature gradients and a post-pulse downward migration of the heat-flux maximum, a delayed-heating effect inaccessible to conventional surface-flux-based models. Systematic analysis establishes scaling laws connecting interfacial thermal resistance, beam size, and incident energy density to thermal confinement and temperature rise. By incorporating interfacial compaction kinetics, the model enables a quantitative assessment of mirror lifetime. This work offers a theoretical tool for thermal-optical co-design of multilayer nanostructures including EUV mirrors under pulsed irradiation across a wide spectral range. Thermal conduction ; Extreme ultraviolet lithography ; Coupling (piping) ; Thermal ; Deposition (geology) ; Work (physics) ; Interference (communication) ; Absorption (acoustics) ; Heat transfer ; Nanoscopic scale Optical Coatings and Gratings ; Silicon and Solar Cell Technologies ; Advanced X-ray Imaging Techniques
Authors: Ruomeng Huang
Source: Micromachines (article, 2026-03-31)
Field: Materials Science — Materials Chemistry

Thermoelectric Materials and Devices Thermoelectric (TE) materials and devices enable the direct conversion between thermal and electrical energy, offering solid-state solutions for power generation and cooling without moving parts or working fluids [...] Thermoelectric materials ; Thermal ; Thermoelectric effect ; Thermoelectric cooling ; Seebeck coefficient ; Thermoelectric generator ; Electricity generation Advanced Thermoelectric Materials and Devices ; Chemical and Physical Properties of Materials ; Nanomaterials and Printing Technologies
Authors: John Yeow | Wentao Gao | Jiaqi Wang | Guanxuan Lu | Yifei Yuan
Source: Research Square (preprint, 2026-02-03)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Inhomogeneous Metasurface–CNN System for Filter-Free Single-Pixel Wavelength Recognition Photodetector ; Photodetection ; Broadband ; Detector ; Responsivity ; Wavelength ; Convolutional neural network ; Plasmon ; Filter (signal processing) Metamaterials and Metasurfaces Applications ; Plasmonic and Surface Plasmon Research ; Random lasers and scattering media
Authors: Shu WANG | L. Yin | Yanlong Meng | Han Gao | Yuhan Fu | Jihui Hu | Chunlian Zhan
Source: Preprints.org (preprint, 2026-01-19)
Field: Materials Science — Electronic, Optical and Magnetic Materials

A Review of Aggregation-Based Colorimetric and SERS Sensing of Metal Ions Utilizing AuAg Nanoparticles The accurate monitoring and dynamic analysis of metal ions are of considerable practical significance in environmental toxicology and life sciences. Colorimetric analysis and surface-enhanced Raman scattering (SERS) sensing technologies, utilizing the aggregation effect of gold and silver nanoparticles (Au/Ag NPs), have emerged as prominent methods for rapid metal ion detection, serving as effective complements to conventional bulky instrumental analysis techniques. This is propelled by their distinctive localized surface plasmon resonance (LSPR) response and electromagnetic field enhancement mechanisms. This article evaluates contemporary optical sensing methodologies utilizing aggregation effects and their advancements in the detection of diverse metal ions. It comprehensively outlines methodological advancements from nanomaterial fabrication to signal transduction, encompassing approaches such as biomass-mediated green synthesis and functionalization, targeted surface ligand engineering, digital readout systems utilizing intelligent algorithms, and multimodal synergistic sensing. Recent studies demonstrate that these techniques have attained trace-level identification of target ions regarding analytical efficacy, with detection limits generally conforming to or beyond applicable environmental and health safety regulations. Moreover, pertinent research has enhanced detection linear ranges, anti-interference properties, and adaptability for point-of-care testing (POCT), validating the usefulness and developmental prospects of this technology for analysis in complicated matrices. Raman scattering ; Surface plasmon resonance ; Metal ions in aqueous solution ; Nanomaterials ; Nanoparticle ; Plasmon ; Fabrication ; Metal ; Field (mathematics) Gold and Silver Nanoparticles Synthesis and Applications ; Advanced Nanomaterials in Catalysis ; Nanocluster Synthesis and Applications
Source: International Journal of Corrosion and Scale Inhibition (article, 2026-04-01)
Field: Materials Science — Materials Chemistry

Corrosion inhibition of mild steel in 1 M HCl solution by N-(4-methoxyphenyl)piperazine-1-acetamide: potentiodynamic polarization, weight loss, SEM analysis, and DFT computational studies This study investigates the corrosion inhibition performance of N-PAP (N-(4methoxyphenyl)piperazine-1-acetamide) for mild steel protection in 1.0 M hydrochloric acid solution through an integrated experimental and theoretical approach.Potentiodynamic polarization measurements revealed that N-PAP functions as a mixed-type corrosion inhibitor, achieving a maximum inhibition efficiency of 80.3% at 0.5 mM concentration.The compound systematically reduced corrosion current density from 117.4 Acm 2 (blank solution) to 23.1 Acm 2 and decreased the corrosion rate from 56.3 mpy to 10.3 mpy, representing an 82% reduction in material loss.Gravimetric studies confirmed enhanced protection with extended exposure time and elevated temperatures, reaching 97.4% efficiency at 333 K and 1.0 mM concentration.The inhibitor adsorption followed the Langmuir isotherm model with excellent correlation (R 2 = 0.9956), indicating monolayer formation through predominantly physisorption mechanisms.The calculated standard free energy of adsorption ( 0 ads G =-13.06 kJ/mol) confirmed spontaneous adsorption.Scanning electron microscopy analysis demonstrated significant surface protection, showing smooth, intact morphology in inhibited samples compared to severe corrosion damage in uninhibited specimens.Density functional theory calculations provided molecular-level insights, revealing favorable electronic properties including HOMO energy (-7.873 eV), LUMO energy (0.533 eV), and optimal electron transfer fraction (N = 0.397) that support strong metal-inhibitor interactions.The proposed inhibition mechanism involves coordinate bond formation through nitrogen atoms in the piperazine ring and additional anchoring via the para-methoxy group, creating a protective organic film that blocks both anodic metal dissolution and cathodic hydrogen evolution reactions.These findings establish N-PAP as an effective, environmentally compatible corrosion inhibitor with practical applicability for mild steel protection in aggressive acidic environments. Corrosion ; Physisorption ; Langmuir adsorption model ; Adsorption ; Density functional theory ; Hydrochloric acid ; Dissolution ; Corrosion inhibitor ; Passivation ; Cathodic protection Corrosion Behavior and Inhibition ; Hydrogen embrittlement and corrosion behaviors in metals ; Concrete Corrosion and Durability
Authors: Hanjui Chang | Fei Long | Jiaquan Li
Source: Scientific Reports (article, 2026-02-14)
Field: Materials Science — Polymers and Plastics

Fusion of NSGA-II and Latin hypercube sampling for optimizing node displacement in thin-film IME molding In the high-risk environment of firefighting operations, the safety of firefighters depends on the performance of advanced protective equipment. This paper proposes a magnetic levitation shield that combines thin-film in-mold electronic (IME) forming technology and magnetic levitation control as protective equipment. Its non-contact and high strength characteristics ensure the safety of firefighters. However, the execution of the shield's protective function is inseparable from the precise control of the magnetic levitation system, so the defects in the circuits formed by the IME need to be controlled to minimize the loss of current and power as much as possible, thereby improving the stability of the shield. Since the degree of defect in the IME circuit has a greater correlation with the node displacement of the product itself, the main objective of this study is to minimize the node displacement of the product by setting different injection molding parameters. Therefore, this paper innovatively combines the non-dominated sorting genetic algorithm II (NSGA-II) with Latin Hypercube sampling (LHS), and combines Moldex 3D to optimize and obtain different Palatto solutions, and finally selects the eligible combination of process parameters based on the research purpose. Through research and discussion, it was found that the synergistic effect of the two led to an optimization rate of 65.7-89.7% for node displacement. Finally, through the analysis of the impact of different degrees of circuit damage caused by different degrees of node displacement on current loss and power loss, the effectiveness of the method was demonstrated in multiple aspects, providing effective safety guarantee for workers in high-risk environments. The research results not only provide a technical solution and theoretical basis for the design, manufacture and maintenance of magnetic levitation shields for firefighters, but also promote the cross-application of in-mold electronic technology and intelligent optimization algorithms, opening up a new path for improving the safety protection level of firefighters in high-risk environments. Node (physics) ; Magnetic levitation ; Displacement (psychology) ; Levitation ; Sorting ; Latin hypercube sampling ; Power (physics) Polymer composites and self-healing ; Advanced Sensor and Energy Harvesting Materials ; Mechanical Behavior of Composites