jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Jieke Shi | Junda He | Zhou Yang | Chengran Yang | Mykhailo V. Klymenko | Thong Hoang | Xiwei | Xu | Zhenchang Xing | David Lo
Source: arXiv (Cornell University) (article, 2026-03-31)
Field: Materials Science — Materials Chemistry

Compiling Code LLMs into Lightweight Executables The demand for better prediction accuracy and higher execution performance in neural networks continues to grow. The emergence and success of Large Language Models (LLMs) have led to the development of many cloud-based tools for software engineering tasks such as code suggestion. While effective, cloud deployment raises concerns over privacy, latency, and reliance on connectivity. Running LLMs locally on personal devices such as laptops would address these issues by enabling offline use and reducing response time. However, local deployment is challenging: commodity devices lack high-performance accelerators like GPUs and are constrained by limited memory and compute capacity, making it difficult to execute large models efficiently. We present Ditto, a novel method for optimizing both the model size of Code LLMs and their inference programs, particularly for statically-typed programming languages such as C. Our approach integrates two key components: (1) a model compression technique inspired by product quantization, which clusters model parameters into codebooks and quantizes them to lower bit widths while ensuring that outputs remain within a bounded error, as well as synthesizing the inference program for the quantized model; and (2) a compilation pass integrated into LLVM that automatically detects and replaces unoptimized General Matrix-Vector Multiplication (GEMV) operations with implementations from Basic Linear Algebra Subprograms (BLAS) libraries, which are highly optimized for runtime performance. The output of Ditto is an optimized and compiled executable for running selected Code LLMs. We evaluate Ditto on three popular Code LLMs, achieving up to 10.5$\times$ faster inference and 6.4$\times$ lower memory usage compared with their original inference pipeline, while maintaining accuracy close to that of the full-precision models (with an average loss of only 0.27% in pass@1). Executable ; Key (lock) ; Inference ; Code (set theory) ; Code generation ; Software deployment ; Inference engine ; Implementation Machine Learning in Materials Science ; Natural Language Processing Techniques ; Topic Modeling
Authors: Jake Hill | Yelyzaveta Pulnova | Elke De Zitter | Helen M. Ginn | Briony A. Yorke
Source: FEBS Open Bio (article, 2026-03-11)
Field: Materials Science — Materials Chemistry

Analysing the significance of small conformational changes and low occupancy states in serial crystallographic data The interpretation of electron density maps from time-resolved serial diffraction experiments is often hindered by incomplete initiation and mixtures of states. Additionally, it can be challenging to determine the significance of small conformational changes. Here, we present a protocol that exploits the inherent oversampling of serial crystallographic data through batch resampling and principal component analysis (PCA). This approach provides insight into the significance of small conformational changes in proteins along a reaction time course. When combined with extrapolation of structure factor amplitudes, the method further helps in the identification of low-occupancy intermediates. In this protocol report, we describe a practical workflow for batch resampling, scaling and clustering, and provide guidance for the effective use of open-source software including RoPE and Xtrapol8. Extrapolation ; Workflow ; Protocol (science) ; Identification (biology) ; Resampling ; Oversampling ; Software ; Scaling ; Ab initio Enzyme Structure and Function ; Protein Structure and Dynamics ; Advanced Electron Microscopy Techniques and Applications
Authors: mohamed Elshahat Mahmoud Mousa | Leif Bauer | Utkarsh Singh | Ziyi Yang | Angshuman Deka | Zubin Jacob
Source: ArXiv.org (article, 2026-01-26)
Field: Materials Science — Polymers and Plastics

Uncooled Poisson Bolometer for High-Speed Event-Based Long-wave Thermal Imaging Event-based vision provides high-speed, energy-efficient sensing for applications such as autonomous navigation and motion tracking. However, implementing this technology in the long-wave infrared remains a significant challenge. Traditional infrared sensors are hindered by slow thermal response times or the heavy power requirements of cryogenic cooling. Here, we introduce the first event-based infrared detector operating in a Poisson-counting regime. This is realized with a spintronic Poisson bolometer capable of broadband detection from 0.8-14$μ\text{m}$. In this regime, infrared signals are detected through statistically resolvable changes in stochastic switching events. This approach enables room-temperature operation with high timing resolution. Our device achieves a maximum event rate of 1,250 Hz, surpassing the temporal resolution of conventional uncooled microbolometers by a factor of 4. Power consumption is kept low at 0.2$μ$W per pixel. This work establishes an operating principle for infrared sensing and demonstrates a pathway toward high-speed, energy-efficient, event-driven thermal imaging. Bolometer ; Infrared ; Detector ; Infrared detector ; Broadband ; Thermography ; Power (physics) ; Thermal ; Microbolometer Transition Metal Oxide Nanomaterials ; Advanced Memory and Neural Computing ; Advanced Sensor and Energy Harvesting Materials
Authors: H. D. Supreetha Gowda | Hemaraju | V. G. Pradeep Kumar | B. Suresha | C. R. Rachana | Subraya Krishna Bhat
Source: Scientific Reports (article, 2026-03-10)
Field: Materials Science — Polymers and Plastics

Optimizing abrasive wear in sustainable MCC reinforced hemp bamboo epoxy composites for tribological applications This study investigates the two-body abrasive wear characteristics of hybrid hemp and bamboo fibers in woven form epoxy (H/B F-Ep) composites reinforced with micro-crystalline cellulose (MCC) using a response surface methodology (RSM) framework and microstructural analysis. The effects of MCC content, emery paper grit, load, and abrading distance, on weight loss, coefficient of friction (CoF), and surface roughness (Ra) were assessed using four factors and three levels using Box–Behnken design. Analysis of variance (ANOVA) was used to develop and statistically validate quadratic regression models, which demonstrated strong predictive ability, a non-significant lack-of-fit, and high coefficients of determination (R² = 95.84–97.06%). Emery paper grit and abrading distance dominate wear loss, MCC content controls frictional response, and both MCC and grit have a substantial impact on surface roughness, according to an ANOVA. Strong nonlinear wear behavior under severe abrasion is indicated by significant interaction and quadratic terms, especially grit2 and filler–grit coupling. Optimized MCC loading reduces micro-cutting and stabilizes tribo-layer development, as indicated by main-effects and interaction plots. The statistical results were supported by SEM measurements, which showed a shift from severe micro-ploughing and fiber pull-out in unfilled composites to moderate abrasion and compacted tribo-films at the optimal MCC content. To minimize wear loss (0.0385 g), CoF (0.27), and Ra (1.62 μm), with an overall desirability of 0.96, multi-response desirability optimization determined that 3 wt% MCC, 400-grit abrasive, 150 m abrading distance, and 10 N load were the optimal settings. A strong framework for customizing natural fiber hybrid composites for tribological applications is provided by the combined RSM–SEM technique. Abrasive ; Tribology ; Abrasion (mechanical) ; Epoxy ; Response surface methodology ; Composite number ; Surface roughness ; Fiber Natural Fiber Reinforced Composites ; Tribology and Wear Analysis ; Aluminum Alloys Composites Properties
Authors: Jianlin Hu | Jie Yang | Peiyu Qin | Xi Jiang | Wentao Luo
Source: Sensors (article, 2026-03-25)
Field: Materials Science — Materials Chemistry

An Evaluation Method for Partial Discharge in Generator Stator Bar Insulation Based on Fiber-Optic Acoustic Detection Partial-discharge (PD) monitoring is essential for assessing the insulation condition of generator stator bars. Conventional methods are susceptible to electromagnetic interference and are difficult to deploy in confined stator geometries. Fiber-optic acoustic detection technology offers strong immunity to electromagnetic interference and is suitable for the narrow and high-interference environment of stator bars, but it cannot directly provide discharge magnitude information. Therefore, in this study, fiber-optic acoustic detection technology was employed to acquire partial discharge acoustic signals from stator bars, and a mandrel-type fiber-optic acoustic sensor was developed, with PD tests performed on full-scale stator bars with internal defects. Meanwhile, considering the complex temporal characteristics of PD acoustic signals, a hybrid neural network—Transformer–convolutional neural network–long short-term memory (Transformer–CNN–LSTM)—was constructed for long-term time-series modeling to establish the mapping between acoustic signals and discharge magnitude intervals. The results indicate that fiber-optic acoustic detection enables sensitive and stable detection of weak PD acoustic signals. Phase-resolved PD (PRPD) patterns from the proposed system align with the discharge characteristics of internal defects, with the acoustic signal showing a phase lag relative to the electrical PD signal. The hybrid model achieved an overall interval estimation accuracy of 96.6%, outperforming CNN and CNN-LSTM models, with accuracies of 100% and 99.4% for discharge magnitude intervals below 100 pC and above 2000 pC, respectively. Stator ; Partial discharge ; Acoustic emission ; Bar (unit) ; Generator (circuit theory) ; Interference (communication) ; SIGNAL (programming language) ; Electric generator High voltage insulation and dielectric phenomena ; Advanced Fiber Optic Sensors ; Power Transformer Diagnostics and Insulation
Authors: Bupesh Kumar K | B M Rajaprakash
Source: Journal of Emerging Technologies and Innovative Research (article, 2026-01-01)
Field: Materials Science — Ceramics and Composites

Application of Multi Response Performance Index for Optimization of Kevlar/Epoxy Composites strengthened with Hybrid SiC-ZnO Nanofillers Fibre Reinforced Polymer Composites (FRPCs) have been described as the materials of the future due to their limitless applications. They have been found to exhibit enhanced mechanical properties on addition of nanofillers. Recent research has also used hybrid nanofillers to synergistically enhance their mechanical properties. In this present research, an attempt has been made to study the effect of hybrid Silicon Carbide (SiC) – Zinc Oxide (ZnO) nanofillers on the mechanical properties of Kevlar/Epoxy composite specimens. Multi Response Performance Index (MRPI) technique has been employed in this current research for optimisation of influencing important process parameters for enhanced tensile strength, flexural strength, inter laminar shear strength and energy absorbed. Confirmatory tests have also been performed for repeatability and validity. Silicon carbide ; Ultimate tensile strength ; Composite number ; Flexural strength ; Shear (geology) ; Shear strength (soil) ; Polymer Advanced ceramic materials synthesis ; Polymer Nanocomposites and Properties ; Epoxy Resin Curing Processes
Authors: J. Seeyangnok | U. Pinsook | Graeme John Ackland
Source: ArXiv.org (article, 2026-01-06)
Field: Materials Science — Materials Chemistry

Charge Density Wave Order and Superconductivity in Janus MoXH Monolayers Two-dimensional Janus hydrogenated transition metal chalcogenides provide an unusual platform where lattice instabilities, electron-phonon coupling, and superconductivity are strongly intertwined. Using first-principles calculations, we demonstrate that Janus 2H and 1T MoXH (X = S, Se) monolayers host an intrinsic, commensurate charge density wave (CDW) ground state originating from soft phonon modes at the Brillouin zone M point. Real-space supercell optimizations confirm that the CDW reconstruction lowers the total energy and fully stabilizes the lattice, eliminating the imaginary phonon modes present in the high-symmetry metallic structures. Analysis of the electronic susceptibility shows that the CDW instability is not driven by Fermi surface nesting, but instead arises from strong electron-phonon coupling. We further reveal a material-dependent interplay between CDW order and superconductivity. In 1T MoSH, CDW formation enhances low-energy phonon contributions and strengthens electron-phonon coupling, leading to an increased superconducting transition temperature. In contrast, for 1T MoSeH and 2H MoSeH, the CDW phase suppresses electron-phonon coupling and reduces superconductivity. Finally, we show that thermal fluctuations, compressive strain, and carrier doping can selectively suppress CDW order and restore superconductivity. These results establish Janus MoXH monolayers as a tunable two-dimensional system for exploring lattice-driven charge ordering and its competition with superconductivity. Charge density wave ; Superconductivity ; Phonon ; Janus ; Monolayer ; Brillouin zone ; Doping ; Charge density ; Instability ; Phase transition 2D Materials and Applications ; Organic and Molecular Conductors Research ; Topological Materials and Phenomena
Authors: K. Chandra Sekhar | R. Umamaheswara Singh | G. Nagaraju | R. Nagaraju | Md. Shareefuddin
Source: Springer Link (Chiba Institute of Technology) (article, 2026-03-05)
Field: Materials Science — Materials Chemistry

Investigation of Lead borate glasses doped with Mn Lead oxide (PbO) is a crucial component of borate glasses despite its toxicity because its presence significantly enhances their characteristics for specific uses, like radiation shielding and optical devices. The present work deals with the radiation shielding features of the borate glasses containing high density chemicals (PbO & PbCl2). The glasses with composition xPbCl2-(30 − x)PbO−69.5B2O3−0.5MnO2 with 5 ≤ x ≤ 25 mol% were prepared using melt quenching method. To obtain the shielding characteristic of samples like MAC, LAC, Zeff, etc., the well-known and reputable Phy-X/PSD online tool is utilized. The data flattened on the higher energy side (CE and PP) and showed increased MAC and LAC in the lower energy (PE) region. Lower concentrations of PbCl2 demonstrated better LAC and MAC since sample density diminished as PbCl2 increased. Boron ; Electromagnetic shielding ; Lead oxide ; Borate glass ; Quenching (fluorescence) ; Oxide ; Radiation shielding ; Doping Radiation Shielding Materials Analysis ; Glass properties and applications ; Luminescence Properties of Advanced Materials
Authors: Hongbing Li | Zhangjie Gu | Yaling Zhu | Zhaoyang Jiao | Jinya Tian | Yi Li | Y.B. Chai | Xiaodong Chi
Source: Nature Communications (article, 2026-03-30)
Field: Materials Science — Materials Chemistry

Synergistic dual anion regulation unlocks giant thermopower and power density in hydrogel Harvesting low-grade heat from the environment and converting it into electricity holds the potential to power devices independent of cables or batteries. However, their effectiveness is limited by weak ion selectivity and insufficient concentration gradients. Here, we introduce the use of a calix[4]pyrrole as effective anion traps to selectively capture Fe(CN)<sub>6</sub><sup>4-</sup> and Cl<sup>-</sup> anions, enabling simultaneous modulation of redox ion distribution and suppression of anion mobility under a temperature gradient. This strategy combines desolvation-induced entropy gain with thermodiffusion enhancement arising from the mobility asymmetry between cations and anions. This leads to a synergistic boost in thermopower to an impressive 8.1 mV K<sup>-1</sup>, and results in a 20-fold increase in output power compared to the PVA/Fe(CN)<sub>6</sub><sup>3-/4-</sup> system. Demonstrated through a proof-of-concept wearable device with 36 unipolar elements, our system generated nearly 3 volts under ambient conditions. This strategy offers a promising route toward thermoelectric materials with enhanced thermopower for efficient harvesting low-grade thermal energy. Seebeck coefficient ; Ion ; Power density ; Thermoelectric effect ; Thermal ; Thermal conduction ; Power (physics) ; Redox Advanced Thermoelectric Materials and Devices ; Advanced battery technologies research ; Supercapacitor Materials and Fabrication
Authors: Changle Li | Xugang Wang | Chengdong Gu | Zhanmin Zhang | Yupeng Zheng | Liu Liu
Source: Energies (article, 2026-03-25)
Field: Materials Science — Materials Chemistry

Combustion and Power Generation Characteristics of a Thermoelectric Generator Fueled by Hydrogen-Enriched Compressed Natural Gas (HCNG) Hydrogen-enriched compressed natural gas (HCNG) is a promising transitional fuel for residential-scale distributed power, yet its impacts on direct-combustion thermoelectric generator (TEG) systems remain insufficiently quantified. In this study, a micro-scale TEG integrated with a commercially available self-aspirating household burner was experimentally investigated under thermal inputs of 700–2500 W and hydrogen blending ratios of 0–20 vol%, using open-loop water cooling to maximize heat rejection. The hot- and cold-side temperatures exhibited negligible variation with a hydrogen addition, and the maximum electrical output was essentially preserved across all blending ratios; at 2500 W the system delivered 75.8 W with a system efficiency of 3.03%. In contrast, hydrogen blending substantially reduced pollutant emissions: at 2500 W, CO decreased from 52.7 to 1 mg/m3 and CO2 from 6.73% to 5.36% as the hydrogen fraction increased from 0 to 20 vol%. Meanwhile, combustion stability improved, indicated by a reduced coefficient of variation (0.77% → 0.49%). These results demonstrate that up to 20 vol% hydrogen blending can achieve significant emissions mitigation without compromising TEG power performance, supporting HCNG-fueled TEGs as a practical option for residential backup power. Thermoelectric generator ; Compressed hydrogen ; Combustion ; Natural gas ; Combustor ; Electricity generation ; Compressed natural gas ; Hydrogen ; Hydrogen fuel enhancement Advanced Thermoelectric Materials and Devices ; Hybrid Renewable Energy Systems ; Integrated Energy Systems Optimization
Authors: K. Chandra Sekhar | R. Umamaheswara Singh | G. Nagaraju | R. Nagaraju | Md. Shareefuddin
Source: EPJ Web of Conferences (article, 2026-01-01)
Field: Materials Science — Materials Chemistry

Investigation of Lead borate glasses doped with Mn <sup>2+</sup> : Comprehensive analysis of radiation shielding properties Lead oxide (PbO) is a crucial component of borate glasses despite its toxicity because its presence significantly enhances their characteristics for specific uses, like radiation shielding and optical devices. The present work deals with the radiation shielding features of the borate glasses containing high density chemicals (PbO &amp; PbCl 2 ). The glasses with composition xPbCl 2 -(30 − x)PbO−69.5B 2 O 3 −0.5MnO 2 with 5 ≤ x ≤ 25 mol% were prepared using melt quenching method. To obtain the shielding characteristic of samples like MAC, LAC, Z eff , etc., the well-known and reputable Phy-X/PSD online tool is utilized. The data flattened on the higher energy side (CE and PP) and showed increased MAC and LAC in the lower energy (PE) region. Lower concentrations of PbCl 2 demonstrated better LAC and MAC since sample density diminished as PbCl 2 increased. Electromagnetic shielding ; Boron ; Radiation shielding ; Radiation ; Analytical Chemistry (journal) ; Oxide ; Lead oxide ; Borate glass ; Quenching (fluorescence) Radiation Shielding Materials Analysis ; Glass properties and applications ; Graphite, nuclear technology, radiation studies
Authors: Aikaterini-Artemis Agiomavriti | Olympiada Saharidi | Aikaterini Vasilaki | Stavroula Koulouvakou | Efstratios Nikolaou | Theodora Papadimitriou | Thomas Bartzanas | Nikos Chorianopoulos | Athanasios Gelasakis
Source: Spectroscopy Journal (article, 2026-01-30)
Field: Chemistry — Analytical Chemistry

Exploring the Use of Spectral Technologies in Ovine Milk Analysis: A Preliminary Study The purpose of this study was to examine the use of portable spectroscopy technologies for rapid milk composition and hygiene quality assessment in ovine milk. Two portable analyzers, namely SmartAnalysis (UV/Vis absorbance) and SpectraPod (NIR transmittance), were used to obtain spectral data of raw milk samples. Additionally, reference values of the milk’s compositional, physical, and hygienic traits were measured. Machine learning algorithms were used to explore the correlations between spectral data and milk traits. The initial results indicated a promising potential of utilizing spectral technologies to predict milk quality and hygienic parameters. Regression models presented a moderate predictive accuracy, with R2 values between 0.55 and 0.34, respectively, regarding fat (RF-NIR) and protein (LR-UV/Vis). Classification models indicated high accuracy for hygienic parameters, with the highest accuracy and AUC values up to 0.87 and 0.83, respectively, predicting increased levels of total bacterial count (TBC), while somatic cell count (SCC) level was less accurately predicted by the model, with AUC values lower than 0.70. The results demonstrate the applicability potential of UV/Vis and NIR portable devices in milk quality assessment, enabling its rapid evaluation, including milk composition and hygiene parameters at the point of service. Raw milk ; Somatic cell count ; Predictive modelling ; Quality (philosophy) ; Regression analysis ; Dairy industry ; Data quality ; Chemometrics Spectroscopy and Chemometric Analyses ; Milk Quality and Mastitis in Dairy Cows ; Listeria monocytogenes in Food Safety
Authors: Jiale Dong | Ting Guo | Yi Huang | Yangchun Ma | Weijin Chen | Jie Xue | Jun Jiang | Enhui Dong | Yue Kong | Hang Ding | Wenlong Zhang | Shutao Ma
Source: Advanced Science (article, 2026-01-09)
Field: Chemistry — Organic Chemistry

Dipiperazine‐Phenyl Derivatives Based on Convergent Molecular Platforms Can Reverse Multidrug Resistance in Gram‐Negative Bacteria by Inhibiting Efflux and Permeabilizing Cell Membranes With the global surge of infections caused by multidrug-resistant (MDR) Gram-negative bacteria, there is an urgent need for breakthrough therapeutic approaches. To overcome the intrinsic resistance mechanisms of bacteria, End-alkyl-modified dipiperazine-phenyl derivatives are designed via convergent molecular platforms (CMPs)-guided multi-target directed ligand (MTDL) strategy. These dual-functional compounds not only inhibit the AcrB-TolC efflux pump system but also enhance bacterial membrane permeability and display a distinctive activity profile across a broad concentration range. Through integrated evaluation combining in vitro activity screening and computational ADMET (absorption, distribution, metabolism, excretion, toxicity) profiling, compound C5 is identified as a promising lead candidate. This compound achieved three notable breakthroughs. First, it reduces biofilm formation by 80% at 1/64 minimum inhibitory concentration (MIC) when combined with antibiotics. Second, unlike conventional antibiotic adjuvants that typically display potentiation within a narrow concentration window (1/4 MIC), C5 maintained robust and consistent synergistic activity across a broad range from 1/64 MIC to 1/4 MIC. Third, C5 markedly enhanced the therapeutic efficacy of antibiotics such as minocycline by over 1000-fold in in vivo infection models, without causing detectable acute toxicity or cytotoxicity. The established MTDL-CMPs integrated platform pioneers a novel "pump-membrane dual blockade" therapeutic paradigm against MDR Enterobacteriaceae infections. Efflux ; In vitro ; In vivo ; Antibiotics ; Minocycline ; Bacteria ; Minimum inhibitory concentration ; Multiple drug resistance ; Biofilm ; Therapeutic window Antimicrobial agents and applications ; Cancer therapeutics and mechanisms ; Nanoplatforms for cancer theranostics