jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Zhenzhao Zhang | Yunpeng Guo | Chunran Wu | Tingbo Wang | Ming Huang | Wei Li | Chen Xingyu | Haijun Mao | Kaijun Wang | Wenjian Guo | Fenglin Wang | Zhuofeng Liu
Source: Materials Genome Engineering Advances (article, 2026-02-25)
Field: Materials Science — Materials Chemistry

A Dynamic‐Weighted Deep Transfer Learning Framework for Thermal Conductivity Prediction and Analysis ABSTRACT To overcome the limitations of small‐sample data in establishing microstructure–property linkages, this study introduces a deep transfer learning framework with a dynamic weighting mechanism. By transferring the perceptual capabilities of the ResNet‐18 model and adaptively fusing them with material domain knowledge, the model effectively captures complex features such as phase distribution. Using silicon nitride ceramics as the primary research object, the framework achieves an average cross‐validation prediction accuracy ( R 2 ) of 0.73, representing a 104.3% relative improvement compared to the traditional CNN framework, and the optimal model reaches an accuracy of R 2 = 0.89. Furthermore, this framework also demonstrates exceptional predictive accuracy on silicon carbide ceramics ( R 2 = 0.84) and sintered nano silver ( R 2 = 0.93), indicating its strong generalization capabilities. By employing multilevel gradient‐weighted class activation mapping (Grad‐CAM) and sliding occlusion analysis, the decision‐making process of the model is elucidated, thereby validating the logical soundness of its predictions. Additionally, symbolic regression is utilized to identify the influence of different microstructural features on thermal conductivity and to establish their quantitative relationships. This research holds broad application prospects in the rapid development and design of thermal management materials, analysis of material microstructure images, and the establishment of structure–performance relationships between microstructural features and macroscopic properties. Thermal conductivity ; Weighting ; Silicon carbide ; Transfer of learning ; Process (computing) ; Ceramic ; Artificial neural network ; Silicon nitride ; Phase (matter) Thermal properties of materials ; Machine Learning in Materials Science ; Thermography and Photoacoustic Techniques
Authors: Joy He-Yueya | Anikait Singh | Ge Gao | Michael Y. Li | Sherry Yang | Chelsea Finn | Emma Brunskill | Noah D. Goodman
Source: arXiv (Cornell University) (preprint, 2026-04-10)
Field: Materials Science — Materials Chemistry

GIANTS: Generative Insight Anticipation from Scientific Literature Scientific breakthroughs often emerge from synthesizing prior ideas into novel contributions. While language models (LMs) show promise in scientific discovery, their ability to perform this targeted, literature-grounded synthesis remains underexplored. We introduce insight anticipation, a generation task in which a model predicts a downstream paper's core insight from its foundational parent papers. To evaluate this capability, we develop GiantsBench, a benchmark of 17k examples across eight scientific domains, where each example consists of a set of parent papers paired with the core insight of a downstream paper. We evaluate models using an LM judge that scores similarity between generated and ground-truth insights, and show that these similarity scores correlate with expert human ratings. Finally, we present GIANTS-4B, an LM trained via reinforcement learning (RL) to optimize insight anticipation using these similarity scores as a proxy reward. Despite its smaller open-source architecture, GIANTS-4B outperforms proprietary baselines and generalizes to unseen domains, achieving a 34% relative improvement in similarity score over gemini-3-pro. Human evaluations further show that GIANTS-4B produces insights that are more conceptually clear than those of the base model. In addition, SciJudge-30B, a third-party model trained to compare research abstracts by likely citation impact, predicts that insights generated by GIANTS-4B are more likely to lead to higher citations, preferring them over the base model in 68% of pairwise comparisons. We release our code, benchmark, and model to support future research in automated scientific discovery. Similarity (geometry) ; Anticipation (artificial intelligence) ; Pairwise comparison ; Set (abstract data type) ; Generative grammar ; Scientific modelling ; Benchmark (surveying) ; Generative model Machine Learning in Materials Science ; Topic Modeling ; Artificial Intelligence in Healthcare and Education
Authors: Gan Zhang | Xu Zhang | Hui Li | Jinhui Zhao | Yao Qin | Qinghui Zhang | Mingxing Li | Yu Yang
Source: Infrared Physics & Technology (article, 2026-01-30)
Field: Chemistry — Analytical Chemistry

Instrument-invariant near-infrared spectroscopy via domain adaptation for robust quantitative analysis of barley protein content Adaptation (eye) ; Transfer of learning ; Domain (mathematical analysis) ; Near-infrared spectroscopy ; Spectroscopy ; Principal component analysis ; Pattern recognition (psychology) ; Domain adaptation Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Md. Abdul Karim | Antor Saha | Md. Jubayer Hossain | Md. Shahin Kabir | Md. Omar Faruk | Mahmuda Khatun | Md. Riad Khan | Dayal Chandra Roy
Source: Scientific Reports (article, 2026-03-04)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Role of oxygen vacancies on the structural, electronic, optical, and photocatalytic properties of Ba2CeMO6 (M = Bi, Sb) double perovskites: a DFT study Oxygen vacancies are known to critically influence the crystal structure, electronic properties, as well as photocatalytic performance of double perovskites. In this study, we employ first-principles density functional theory (DFT) with generalized gradient approximation (GGA) and Hubbard U corrections to systematically investigate the effects of oxygen vacancies on Ba2CeMO6 (M = Bi, Sb) double perovskites. The introduction of vacancies significantly modifies the band structure, generating intermediate electronic states that reduce the band gap energy and enhance photocatalytic performance, as evidenced by band edge potential analysis. Effective mass calculation supported the results and displayed lighter mass of charge carriers in the reduction potential. Structural relaxations reveal local distortions around the vacancy sites and exhibit vacancy-mediated phase transition phenomenon. The experimental zero band gap of Ba2CeBiO6 is rationalized by the oxygen vacancy-induced semiconducting to metallic electronic configuration. Thermodynamic calculations indicated high Debye temperature and melting point with minimum thermal conductivity. Furthermore, optical property analysis suggests improved light absorption in the visible range, highlighting the potential of defect-engineered Ba2CeMO6 (M = Bi, Sb) for efficient photocatalytic applications. These results provide fundamental insights into defect-mediated property tuning in perovskite semiconductors, offering to design for next-generation functional materials. Photocatalysis ; Oxygen ; Density functional theory ; Visible spectrum Magnetic and transport properties of perovskites and related materials ; Heusler alloys: electronic and magnetic properties ; Advancements in Solid Oxide Fuel Cells
Authors: Yao Fu | Zhen Li | Yi-Zhou Tong | Kai-Ran Duan | Boru Men | Qing Lü | Xi Lu
Source: Research Square (preprint, 2026-01-12)
Field: Chemistry — Inorganic Chemistry

Diastereodivergent Synthesis of Multi-Substituted Cyclohexanes via Alkene Hydroamidation Cyclohexanes ; Cyclohexane ; Steric effects ; Alkene ; Substituent ; Catalysis ; Stereoselectivity ; Cycloalkane ; Electronic effect Asymmetric Hydrogenation and Catalysis ; Catalytic C–H Functionalization Methods ; Catalytic Cross-Coupling Reactions
Authors: Siti Hasnah Kamarudin | Nur Maisarah Suhaimi | Nurul Alis Syamimi Abd Manap | Silvi Ikawati | Ummi Hani Abdullah | Mohd Salahuddin Mohd Basri | Luqman Chuah Abdullah | Mohd Rozi Ahmad
Source: Research Square (preprint, 2026-02-16)
Field: Materials Science — Polymers and Plastics

Enhancing Mechanical and Morphological Performance of Recycled Polypropylene Bamboo Fiber Composites Using Palm Stearin Biohybrid Resin Palm stearin ; Ultimate tensile strength ; Polypropylene ; Izod impact strength test ; Composite number ; Scanning electron microscope ; Flexural strength ; Bamboo charcoal Natural Fiber Reinforced Composites ; Bamboo properties and applications ; Fiber-reinforced polymer composites
Authors: Haifeng Wang | Jian Zhang | Xiaoyi Wang | T Wang | Zhi-Qiang Shen | Jingjie Pan | Haigui Yang | Zhen Liu
Source: Coatings (article, 2026-02-03)
Field: Materials Science — Surfaces, Coatings and Films

High-Uniformity Ultra-Broadband Composite Coatings for Large-Aperture Space Telescopes Using Dual-Ring Co-Evaporation In addressing the key technical challenges of achieving ultra-broadband and high film-thickness uniformity for meter-class large-aperture space telescopes, this study utilized a self-developed 4 m-class large-aperture thin-film deposition system. By employing plasma-assisted electron-beam evaporation technology and a co-evaporation method with inner and outer dual-ring multi-evaporation sources, precise control of film-thickness uniformity within a 2 m range was achieved. A composite film structure combining a metal reflective layer and an ultraviolet-enhanced dielectric layer was adopted to realize high reflectivity across an ultra-broad spectrum from ultraviolet to long-wave infrared. Experimental results show that the average reflectance of the composite film reaches 91.52% in the 0.25~0.38 μm spectral band and 99.40% in the 0.38~12 μm spectral band. The thickness uniformity of ZrO2 and MgF2 films within the 2 m aperture area was controlled at 1.37% and 3.12%, respectively, meeting the requirements for high uniformity in large-aperture space applications. Radiation testing confirmed that the change in film reflectance is less than 1% under a total irradiation dose of 3.66 × 108 rad(Si), satisfying the demands for operation in harsh space environments. This research provides an innovative solution for thin-film technology in large-aperture, ultra-broad-spectrum space optical systems and holds significant value for engineering applications. Composite number ; Layer (electronics) ; Reflectivity ; Ultraviolet ; Aperture (computer memory) ; Radiation ; Optical coating ; Deposition (geology) Optical Coatings and Gratings ; Silicone and Siloxane Chemistry ; Advanced optical system design
Authors: Susanna Wood | Fiona Gordon | Robin S. Stein | Mark Howard | John Parkinson
Source: Strathprints: The University of Strathclyde institutional repository (University of Strathclyde) (article, 2026-01-12)
Field: Chemistry — Spectroscopy

Efficient logP determination by automated, spatially encoded 19 F NMR Spectroscopy We report a straightforward method for direct determination of logP by slice-selective 19F NMR spectroscopy utilising a single NMR sample. Our technique uses a partitioned NMR sample of n-octanol/water containing the compound of interest, a modern NMR spectrometer equipped with 19F-observation and Z-axis pulsed-field gradient capabilities in addition to automation programs to measure solute distribution between solvent layers. The approach is validated using a range of fluorinated compounds with known experimental logP values. Details of our experimental method development and implementation processes are reported in supporting data and the benefits of using this approach for experimental logP determination are highlighted. Nuclear magnetic resonance spectroscopy ; Measure (data warehouse) ; Spectrometer ; Spectroscopy ; Analytical Chemistry (journal) ; Two-dimensional nuclear magnetic resonance spectroscopy ; Automation ; Fluorine-19 NMR Advanced NMR Techniques and Applications ; NMR spectroscopy and applications ; Metabolomics and Mass Spectrometry Studies
Authors: Susanna Wood | Fiona Gordon | Robin S. Stein | Mark J. Howard | John A Parkinson
Source: RSC Medicinal Chemistry (article, 2026-01-01)
Field: Chemistry — Spectroscopy

Efficient log <i>P</i> determination by automated, spatially encoded <sup>19</sup> F NMR spectroscopy We report a straightforward method for direct determination of log <i>P</i> by slice-selective <sup>19</sup>F NMR spectroscopy utilising a single NMR sample. Our technique uses a partitioned NMR sample of <i>n</i>-octanol/water containing the compound of interest, a modern NMR spectrometer equipped with <sup>19</sup>F-observation and <i>Z</i>-axis pulsed-field gradient capabilities in addition to automation programs to measure solute distribution between solvent layers. The approach is validated using a range of fluorinated compounds with known experimental log <i>P</i> values. Details of our experimental method development and implementation processes are reported in supporting data and the benefits of using this approach for experimental log <i>P</i> determination are highlighted. Nuclear magnetic resonance spectroscopy ; Measure (data warehouse) ; Spectrometer ; Analytical Chemistry (journal) ; Spectroscopy ; Range (aeronautics) Advanced NMR Techniques and Applications ; NMR spectroscopy and applications ; Metabolomics and Mass Spectrometry Studies
Authors: Zhankun Yang
Source: Applied and Computational Engineering (article, 2026-04-13)
Field: Materials Science — Materials Chemistry

Overview of the System Engineering for Lightweighting of Automotive Structures Automotive lightweighting represents a core technical pathway for realizing energy conservation, emission reduction, and extending the driving range of new energy vehicles. From the systematic perspective of "materials-processes", this paper comprehensively reviews the application progress and development status of lightweight materials including high-strength steel, aluminum alloy, magnesium alloy and composite materials, as well as advanced manufacturing technologies such as conventional die casting, rheological die casting and integrated die casting. The study indicates that the future development of automotive lightweighting should focus on multi-material collaborative design and the upgrading of manufacturing processes. Nevertheless, the large-scale application of lightweight technologies is still confronted with severe challenges. Firstly, the profitable production of lightweight materials and the establishment of a recycling system covering the entire life cycle are not yet sufficiently developed. Secondly, advanced manufacturing processes are constrained by high equipment investments and industrialization challenges. This article aims to provide a theoretical reference for overcoming the aforementioned bottlenecks and accelerating the widespread dissemination and application of lightweight automotive technologies. Automotive industry ; Casting ; Production (economics) ; Focus (optics) ; Die casting ; Advanced manufacturing ; Energy consumption ; Process (computing) Material Selection and Properties ; Engineering and Materials Science Studies ; Aluminum Alloys Composites Properties
Authors: Yinqi Chen | Cheng Xu | Yang Zhang | Constantin Schrade
Source: Nature Communications (article, 2026-01-07)
Field: Materials Science — Materials Chemistry

Finite-momentum superconductivity from chiral bands in twisted MoTe2 A recent experiment has reported unconventional superconductivity in twisted bilayer MoTe<sub>2</sub>, emerging from a normal state that exhibits a finite anomalous Hall effect - a signature of intrinsic chirality. Motivated by this discovery, we construct a continuum model for twisted MoTe<sub>2</sub> constrained by lattice symmetries from first-principles calculations that captures the moiré-induced inversion symmetry breaking even in the absence of a displacement field. Building on this model, we show that overscreening of the nominally repulsive Coulomb interaction gives rise to finite-momentum superconductivity in this chiral moiré system. Remarkably, the finite-momentum superconducting state can arise solely from internal symmetry breaking of the moiré superlattice, differentiating it from previously studied cases that require external fields. It further features a nonreciprocal quasiparticle dispersion and an intrinsic superconducting diode effect. Our results highlight a novel route to unconventional superconducting states in twisted transition metal dichalcogenides moiré systems, driven entirely by intrinsic symmetry-breaking effects. Superconductivity ; Quasiparticle ; Coulomb ; Lattice (music) ; Symmetry breaking ; Symmetry (geometry) ; Point reflection ; Homogeneous space 2D Materials and Applications ; Topological Materials and Phenomena ; Iron-based superconductors research
Authors: Zhenyi Xu | Xianbiao Jiang | Q. Chen | Pumo Cai
Source: RSC Advances (article, 2026-01-01)
Field: Chemistry — Analytical Chemistry

Detection of polyphenols-to-amino acids ratio in Wuyi Rock Tea <i>via</i> CARS-PLSR processing of near infrared spectroscopy The total polyphenols (TP), free amino acids (FAA), and the polyphenols-to-amino acids ratio (TP/FAA) serve as crucial indicators of the taste quality of tea. Traditional detection methods, however, often suffer from limitations such as prolonged analysis time, complex procedures, and the potential for reagent contamination. To expedite the determination and analysis of the TP/FAA in Wuyi Rock Tea, this study employed three wavelength selection methods: Uninformative Variable Elimination (UVE), Successive Projections Algorithm (SPA), and Competitive Adaptive Reweighted Sampling (CARS). These approaches were integrated with Partial Least Squares Regression (PLSR) and Principal Component Regression (PCR) to develop a quantitative analysis model for the polyphenols-to-amino acids ratio in Wuyi Rock Tea. Results revealed that after applying Standard Normal Variate (SNV) combined with Savitzky-Golay Derivative (SD) preprocessing to the near-infrared (NIR) spectra, all three methods improved model performance to varying extents, with the CARS-PLSR wavelength selection method demonstrating the most significant optimization. The coefficients of determination for both calibration and prediction sets of the TP/FAA ratio reached 0.9897 and 0.9812, respectively, while the root mean square error of calibration (RMSEC) and prediction (RMSEP) were 0.1854 and 0.1434, respectively. The relative percent deviation (RPD) was 3.21, indicating enhanced stability and accuracy of the quantitative model. Validation results confirmed that the CARS-PLSR method effectively extracted essential NIR spectral variables while concurrently eliminating redundant spectral noise. This study presents a novel framework for rapid tea quality assessment using NIR spectroscopy. Near-infrared spectroscopy ; Calibration ; Partial least squares regression ; Feature selection ; Principal component analysis ; Matrix (chemical analysis) ; Regression ; Standard deviation ; Relative standard deviation ; Regression analysis Spectroscopy and Chemometric Analyses ; Tea Polyphenols and Effects ; Traditional Chinese Medicine Analysis
Authors: Ruoqian Gao | Xinran Su | Pengtao Hu | Kai Wu | Yingge Cong | Junlin Li | Mingfeng Ge | Xiaoyi Liu | Wenfei Dong
Source: Research Square (preprint, 2026-03-04)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Independent blazed diffraction in a polarization insensitive dual waveband metagrating Diffraction ; Wavefront ; Planar ; Diffraction grating ; Wavelength ; Diffraction efficiency ; Blazed grating ; Polarization (electrochemistry) Metamaterials and Metasurfaces Applications ; Plasmonic and Surface Plasmon Research ; Orbital Angular Momentum in Optics