jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Phillip Hillen | Feras El Yaakobi | Nolan Miller
Source:  (article, 2026-03-06)
Field: Materials Science — Materials Chemistry

“Using Design of Experiments to Advance Corrosion Inhibitor Technology in Oil and Gas Systems” Abstract This study applies the Design of Experiments (DOE) methodology to optimize corrosion inhibitor formulations used in oil and gas production. These chemical inhibitors are multicomponent blends, and their effectiveness is influenced by several variables. One such variable is the ratio of active ingredients, a factor that has received limited attention in prior research. Using DOE, a two-dimensional simplex lattice design was generated to test the ratios of three common active ingredients and evaluate their performance in a statistically optimal way given the present constraints. To reflect real-world application, the study also considered inhibitor effectiveness under varying conditions, including sweet versus sour gas environments and brine-only versus brine-oil partitioned systems. Performance metrics included general corrosion rates and localized corrosion characteristics. Results revealed overlapping optimal mixture regions across conditions and highlighted the minimal impact of partitioning compared to environmental factors. This work demonstrates the power of DOE in chemical formulation, providing a robust foundation for making data-driven decisions regarding corrosion inhibitor product development. Corrosion ; Corrosion inhibitor ; Fossil fuel ; Work (physics) ; Design of experiments ; Amine gas treating Corrosion Behavior and Inhibition ; Material Selection and Properties ; Process Optimization and Integration
Authors: Xingpeng Liu | Guiquan Fan | Zhihong Liu | Yunxiao Zhu | Faqi Liang | Qiaowen Lei | Na Liao | Yujie Zhu | Yixin Su | Xuechun Chen | Yan Luo | Liming Wang | Qitong Huang | Shuisheng Hu | Hanqiang Zhang | Xiaofeng Lin
Source: Chinese Chemical Letters (article, 2026-03-01)
Field: Chemistry — Organic Chemistry

Antibiotic-CDs: Exploration of antibacterial activity, mechanistic insights, and future directions Drug discovery ; Mechanism (biology) ; Antibacterial activity ; Key (lock) Antimicrobial agents and applications ; Antimicrobial Peptides and Activities ; Bacterial biofilms and quorum sensing
Authors: Kawen Li | Hangjin Cho | Richard Norte | Dongil Shin
Source: arXiv (Cornell University) (preprint, 2026-04-08)
Field: Materials Science — Materials Chemistry

Quasicrystal Architected Nanomechanical Resonators via Data-Driven Design From butterfly wings to remnants of nuclear detonation, aperiodic order repeatedly emerges in nature, often exhibiting reduced sensitivity to boundaries and symmetry constraints. Inspired by this principle, a paradigm shift is introduced in nanomechanical resonator design from periodic to aperiodic structures, focusing on a special class: quasicrystals (QCs). Although soft clamping enabled by phononic stopbands has become a central strategy for achieving high-$Q_m$ nanomechanical resonators, its practical realization has been largely confined to periodic phononic crystals, where band structure engineering is well established. The potential of aperiodic architectures, however, has remained largely unexplored, owing to their intrinsic complexity and the lack of systematic approaches to identifying and exploiting stopband behavior. Here we demonstrate that soft clamping can be realized in quasicrystal architectures and that high-$Q_m$ nanomechanical resonators can be systematically achieved through a data-driven design framework. As a representative demonstration, the 12-fold QC-based resonator exhibits a quality factor $Q_m \sim 10^7$ and an effective mass of sub-nanograms at MHz frequencies, corresponding to an exceptional force sensitivity of $26.4$~aN/$\sqrt{\text{Hz}}$ compared to previous 2D phononic crystals. These results establish QCs as a robust platform for next-generation nanomechanical resonators and open a new design regime beyond periodic order. Aperiodic graph ; Resonator ; Quasicrystal ; Clamping ; Stopband ; Sensitivity (control systems) ; Optomechanics ; String (physics) ; Realization (probability) Quasicrystal Structures and Properties ; Acoustic Wave Phenomena Research ; Cellular and Composite Structures
Authors: Lucas Svensson | Babak Sadigh | Christine Wu | Paul Erhart
Source: arXiv (Cornell University) (preprint, 2026-03-10)
Field: Materials Science — Materials Chemistry

Efficient method for calculation of low-temperature phase boundaries Understanding phase stability and phase transformations is central to predicting material behavior under varying thermodynamic conditions. One of the earliest and most influential applications of density functional theory in materials science has been the prediction of pressure-induced phase transitions at 0 K. Extending these calculations to finite temperatures, however, requires accounting for thermal, quantum, and anharmonic contributions to the free energy, often at significant computational cost. In this work, we present a general and efficient framework for calculating low-temperature phase boundaries by combining the Clausius-Clapeyron equation with the quasi-harmonic approximation. This methodology requires a minimal number of calculations, while naturally incorporating internal degrees of freedom and allowing for the inclusion of quantum and low-order anharmonic effects. We illustrate the accuracy and efficiency of the approach by constructing the phase diagram of silica in the pressure range from -2 to 12 GPa and temperatures up to 1750 K. To this end, we employ both density functional theory and a machine-learned interatomic potential, enabling well-converged free energy estimates and a rigorous comparison between first-principles and data-driven models. Anharmonicity ; Degrees of freedom (physics and chemistry) ; Stability (learning theory) ; Density functional theory ; Phase diagram ; Range (aeronautics) ; Phase (matter) ; Thermodynamic integration Machine Learning in Materials Science ; High-pressure geophysics and materials ; Phase Equilibria and Thermodynamics
Authors: Yue Wang | Donglei Zhou | Ruoxi Wang | Wei Li | Ruixin Song | Wen Xu | Xue Bai | Yu Zhang | Yang chen | Pengjia Qi | Tingting Zhou | Tong Zhang | Hongwei Song
Source: Nature Communications (article, 2026-03-17)
Field: Materials Science — Materials Chemistry

Submicrowatt-driven near-infrared luminescence from perovskite-fluoride quantum-cutting heterostructures for gas sensing The pursuit of wideband tunable near-infrared (NIR) light sources has reached fever pitch due to advances in photonic chips, optical communications, and molecular trace detection. Lanthanide ions (Ln<sup>3+</sup>), renowned for their characteristic NIR luminescence, have nevertheless been stymied by the challenges of an extremely low molar extinction coefficient and linear absorption. Herein, a senitization methodology is presented that capitalizes on the quantum cutting-engineered heterostructure nanoparticles (CsPbX<sub>3</sub>: Yb<sup>3+</sup>-NaYF<sub>4</sub>: Yb<sup>3+</sup>, Ln<sup>3+</sup>), to achieve multi-wavelength NIR luminescence spanning the 900-2200 nm spectrum. The designed heterostructure exhibits an unprecedented absorption bandwidth (200-690 nm) across the UV-visible spectrum, with an exceptionally low stimulation threshold at the sub-microwatt level (50 µW cm<sup>-2</sup>). The NIR luminescent wavelengths can be precisely modulated by meticulously adjusting the dopant Ln<sup>3+</sup> ions leveraging Yb<sup>3+</sup>-mediated quantum cutting processes. Spectroscopic analysis reveals a directed energy transfer pathway at the perovskite-fluoride heterogeneous interface: perovskite host→Yb<sup>3+</sup> (perovskite) →Yb<sup>3+</sup> (NaYF<sub>4</sub>) → Ln<sup>3+</sup>. This architecture demonstrates multiplexed gas detection capabilities under AI-assisted analysis, facilitating the simultaneous identification and monitoring of multiple marker gases in complex environments. Our work provides a scalable strategy for constructing ultra-broadband NIR light sources, with implications for high-throughput spectroscopic sensing. Luminescence ; Heterojunction ; Photoluminescence ; Quantum dot Luminescence Properties of Advanced Materials ; Perovskite Materials and Applications ; Solid State Laser Technologies
Authors: Kulmani Mehar | Deepak Kumar | Shakti Prakash Jena | Keerti Rai | Mahit Jain | Sandeep G M | Vasanthaseelan S | Ritesh Prathap Singh
Source: Journal of Hazardous Materials Advances (article, 2026-02-01)
Field: Materials Science — Materials Chemistry

Next-generation nuclear waste management: Geological repositories, emerging technologies, and global pathways • Global nuclear waste exceeds 370,000 tons, projected to 400,000 tons by 2035 • Geological repositories analyzed: Onkalo (5,500 t) and WIPP (175,000 m³) • Emerging solutions: borehole disposal, transmutation, vitrification, Synroc • Risk models show <1% failure probability with IAEA and EPA compliance • Future innovations: graphene barriers, robotics, and AI-enabled monitoring • Integrated strategies support safe, adaptive, and net-zero aligned disposal The safe management of nuclear waste remains a central challenge for sustaining nuclear energy in the low-carbon transition, with a global inventory exceeding 370,000 metric tons and increasing by 10,000 tons annually. This review synthesizes advances in waste classification, repository design, emerging disposal technologies, environmental safeguards, and future directions. Nuclear waste is categorized into low-level (90% volume, <1% radioactivity), intermediate-level (7% volume, 4% radioactivity), and high-level wastes (2% volume, >95% radioactivity), alongside highly radioactive spent fuel (10¹⁰–10¹⁴ Bq/g). Current strategies emphasize geological repositories such as Onkalo (5,500 tons, 400–500 m depth) and WIPP (175,000 m³, 655 m depth), which employ multi-barrier systems but face challenges including high heat output (10–20 kW/ton) and material durability (10⁻⁵/year corrosion). Complementary approaches deep borehole disposal (3–5 km depth, 1–2 billion USD), partitioning and transmutation (>90% toxicity reduction), and immobilization via vitrification (leach rate ∼10⁻⁶ g/m²/day) are advancing the safety and sustainability of disposal. Risk assessments, supported by IAEA safety standards, demonstrate <1% failure probability over 10,000 years, while future innovations in advanced materials (e.g., graphene by 2030), robotics (RADBOT deployment by 2028), and AI-driven monitoring (20% predictive improvement by 2035) could reduce long-term risks by 30% by 2040. The findings underscore the critical role of geological repositories, enhanced by emerging technologies, and highlight the need for interdisciplinary collaboration to ensure secure, sustainable nuclear waste disposal aligned with global net-zero goals by 2050. By strengthening the scientific basis for next-generation disposal technologies, this study contributes on responsible management of hazardous materials Radioactive waste ; Sustainability ; Spent nuclear fuel ; Borehole ; Software deployment ; Waste disposal ; Nuclear transmutation ; Vitrification Nuclear materials and radiation effects ; Graphite, nuclear technology, radiation studies ; Radioactive element chemistry and processing
Authors: Chi Yu | Kunjun Zhuang | Hengfeng Zhao | Jianhua Guo | Xinghua Jiang
Source: Journal of Alloys and Compounds (article, 2026-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Intelligent algorithm-driven trilayer graded aerogel composites enable full-band microwave absorption from 2 to 18 GHz Microwave ; Aerogel ; Permittivity ; Absorption (acoustics) ; Electromagnetic shielding ; Attenuation ; Radar ; Cloaking ; Graphene Electromagnetic wave absorption materials ; Advanced Antenna and Metasurface Technologies ; Metamaterials and Metasurfaces Applications
Authors: Seong‐Hoon Jang | Shin Kiyohara | Hitoshi Takamura | Yu Kumagai
Source: ArXiv.org (article, 2026-01-23)
Field: Materials Science — Materials Chemistry

Charting the Landscape of Oxygen Ion Conductors: A 60-Year Dataset with Interpretable Regression Models Oxygen ion conductors are indispensable materials for such as solid oxide fuel cells, sensors, and membranes. Despite extensive research across diverse structural families, systematic data enabling comparative analysis remain scarce. Here, we present a curated dataset of oxygen ion conductors compiled from $84$ experimental reports spanning $60$ years, covering $483$ materials. Each record includes activation energy ($E_a$) and prefactor ($A$) derived from Arrhenius plots, alongside detailed metadata on structure, composition, measurement method, and data source. When the original papers derive these using an erroneous Arrhenius equation $σ_T=A\exp{\left(-\frac{E_a}{RT}\right)}$, where ($σ_T$ is the oxygen ion conductivity at temperature $T$ and $R$ is the gas constant), we replotted these using the correct one, $σ_{T}T=A\exp{\left(-\frac{E_a}{RT}\right)}$. To illustrate how the database can be used, we constructed interpretable regression models for predicting oxygen ionic conductivity. Two symbolic regression models for E_a and A suggest that oxygen ion transport is primarily governed by local coordination environment and the electrostatic interactions, respectively. This dataset establishes a reliable foundation for data-driven discovery and predictive modeling of next-generation oxygen ion conductors. Arrhenius equation ; Oxygen ; Regression analysis ; Ion ; Regression ; Conductivity ; Metadata ; Ionic bonding Machine Learning in Materials Science ; Advancements in Solid Oxide Fuel Cells ; Electrocatalysts for Energy Conversion
Authors: Harkirat Singh | Mayank Raj | Kaushik Bhattacharya
Source: Journal of the Mechanics and Physics of Solids (article, 2026-03-10)
Field: Materials Science — Materials Chemistry

Effective behavior of heterogeneous media governed by strain gradient elasticity Elasticity (physics) ; Strain (injury) ; Nonlinear elasticity ; Plasticity ; Finite strain theory Nonlocal and gradient elasticity in micro/nano structures ; Thermoelastic and Magnetoelastic Phenomena ; Elasticity and Material Modeling
Authors: Seong‐Hoon Jang | Shin Kiyohara | Hitoshi Takamura | Yu Kumagai
Source: arXiv (Cornell University) (preprint, 2026-01-23)
Field: Materials Science — Materials Chemistry

Charting the Landscape of Oxygen Ion Conductors: A 60-Year Dataset with Interpretable Regression Models Oxygen ion conductors are indispensable materials for such as solid oxide fuel cells, sensors, and membranes. Despite extensive research across diverse structural families, systematic data enabling comparative analysis remain scarce. Here, we present a curated dataset of oxygen ion conductors compiled from $84$ experimental reports spanning $60$ years, covering $483$ materials. Each record includes activation energy ($E_a$) and prefactor ($A$) derived from Arrhenius plots, alongside detailed metadata on structure, composition, measurement method, and data source. When the original papers derive these using an erroneous Arrhenius equation $σ_T=A\exp{\left(-\frac{E_a}{RT}\right)}$, where ($σ_T$ is the oxygen ion conductivity at temperature $T$ and $R$ is the gas constant), we replotted these using the correct one, $σ_{T}T=A\exp{\left(-\frac{E_a}{RT}\right)}$. To illustrate how the database can be used, we constructed interpretable regression models for predicting oxygen ionic conductivity. Two symbolic regression models for E_a and A suggest that oxygen ion transport is primarily governed by local coordination environment and the electrostatic interactions, respectively. This dataset establishes a reliable foundation for data-driven discovery and predictive modeling of next-generation oxygen ion conductors. Arrhenius equation ; Oxygen ; Regression analysis ; Ion ; Regression ; Conductivity ; Metadata ; Ionic bonding Machine Learning in Materials Science ; Advancements in Solid Oxide Fuel Cells ; Electrocatalysts for Energy Conversion
Authors: Yi Shao | Qianghui Xu | Junyu Yang | Maoyuan Li | Sudong Ji | Fuchao Hao | Jun Shen
Source: SSRN Electronic Journal (preprint, 2026-01-01)
Field: Chemistry — Spectroscopy

Efficient data-driven prediction of effective thermal conductivity in porous phenolic resins from SEM images Thermal conductivity ; Porosity ; Particle (ecology) ; Thermal ; Characterization (materials science) ; Consistency (knowledge bases) ; Particle size ; Workflow Aerogels and thermal insulation ; Thermal properties of materials ; Advanced ceramic materials synthesis
Authors: Ilia Toli
Source: Zenodo (CERN European Organization for Nuclear Research) (preprint, 2026-04-07)
Field: Materials Science — Materials Chemistry

447 Terabytes per Square Centimetre at Zero Retention Energy: Non-Volatile Memory at the Atomic Scale on Fluorographane The memory wall — the widening gap between processor throughput and memory bandwidth — has become the defining hardware constraint of the artificial intelligence era, now compounded by a structural NAND flash supply crisis driven by AI demand. We propose a post-transistor, pre-quantum memory architecture built on single-layer fluorographane (CF), in which the bistable covalent orientation of each fluorine atom relative to the sp³-hybridized carbon scaffold constitutes an intrinsic, radiation-hard binary degree of freedom. The C–F inversion barrier of ~4.6 eV (B3LYP-D3BJ/def2-TZVP, this work; verified transition state with one imaginary frequency; confirmed at 4.8 eV by DLPNO-CCSD(T)/def2-TZVP; rigorous lower bound from the fluorophenalane molecular model) yields a thermal bit-flip rate of ~10⁻⁶⁵ s⁻¹ and a quantum tunneling rate of ~10⁻⁷⁶ s⁻¹ at 300 K, simultaneously eliminating both spontaneous bit-loss mechanisms. The barrier lies below the C–F bond dissociation energy (5.6 eV) at both levels of theory, so the covalent bond remains intact throughout the inversion. A single 1 cm² sheet encodes 447 TB of non-volatile information at zero retention energy. Volumetric nanotape architectures extend this to 0.4–9 ZB/cm³. We present a tiered read-write architecture progressing from scanning-probe validation (Tier 1, achievable with existing instrumentation) through near-field mid-infrared arrays (Tier 2) to a dual-face parallel configuration governed by a central controller, with a projected aggregate throughput of 25 PB/s at full Tier 2 array scale. A scanning-probe prototype already constitutes a functional non-volatile memory device with areal density exceeding all existing technologies by more than five orders of magnitude. Throughput ; Quantum entanglement ; Resistive random-access memory ; Binary number ; Flash memory ; Non-volatile memory ; Memory architecture ; Quantum tunnelling ; Atom (system on chip) ; Atomic units ; Terabyte 2D Materials and Applications ; Graphene research and applications ; Semiconductor materials and devices
Authors: Ji Yang | Qian Gao | Qianxu Yang | Hui Jiang | Wei Zhang | Shiyun Tang | Ze Liu | Aiming Chen | Zhongda Zeng
Source: Journal of Analytical and Applied Pyrolysis (article, 2026-01-12)
Field: Chemistry — Analytical Chemistry

Data-driven discovery of tobacco leaf blending rules for new replacement through integration of thermogravimetric, near-infrared, and attribute-encoded fingerprinting data Feature selection ; Raw data ; Complementarity (molecular biology) ; Feature (linguistics) ; Selection (genetic algorithm) ; Pattern recognition (psychology) ; Process (computing) ; Variation (astronomy) Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Food Drying and Modeling
Authors: Ashok Vaseashta | Sedef Salel | N. Bölgen
Source: Materials (article, 2026-04-03)
Field: Materials Science — Biomaterials

Biopolymer-Based Electrospun Nanofibers for Wound Healing, Regeneration, and Therapeutics The management of complex acute and chronic wounds remains a formidable challenge in modern medicine, underscoring the urgent need for advanced therapeutic strategies that accelerate healing, prevent infection, and promote functional tissue regeneration. Electrospun nanofibers have attracted considerable attention in the biomedical field due to their extracellular matrix-like architecture, high surface area, interconnected porosity, and tunable physicochemical composition, which drive advances in wound regeneration, tissue engineering, and biopolymer-based therapeutics. In wound healing, nanofibrous dressings composed of natural polymers such as chitosan, gelatin, collagen, and cellulose promote cell attachment and proliferation, support angiogenesis, and enable infection control while delivering bioactive agents, thereby addressing significant challenges related to inflammation, biocompatibility, and antimicrobial resistance. In tissue engineering, aligned and hierarchically organized scaffolds fabricated from biopolymers such as collagen, gelatin, chitosan, and cellulose enhance the guided orientation of cells, differentiation, and functional regeneration of neural, musculoskeletal, vascular, and skin tissues. In addition to their conventional regenerative applications, recent studies have demonstrated that electrospun biopolymer nanofibers can be used in multifunctional biomedical platforms, including smart and stimuli-responsive systems for drug delivery, biosensing, regenerative interfaces, and wearable medical technologies. The integrated constructs that incorporate diagnostic or therapeutic functionalities, hybrid fabrication approaches that combine 3D printing with electrospinning, and intelligent biopolymer frameworks that enable telemedicine, real-time physiological monitoring, and personalized regenerative therapies offer new opportunities for developing improved biomedical systems. Overall, these advances position electrospun nanofiber systems as promising biomaterials for next-generation biomedical innovation. This review summarizes recent progress in tissue-engineered scaffolds, wound dressings, fabrication strategies for integrative therapeutics, and wearable devices with transformative potential for biomedical applications. Finally, the review addresses significant challenges related to scalability and clinical translation. It offers perspectives on future directions, including the integration of artificial intelligence and the regeneration of complex skin appendages, which will shape the next generation of nanofiber-based wound-healing therapies. Regenerative medicine ; Nanofiber ; Regeneration (biology) ; Tissue engineering ; Bacterial cellulose ; Scaffold ; Biopolymer ; Wearable computer ; Flexibility (engineering) Electrospun Nanofibers in Biomedical Applications ; Wound Healing and Treatments ; Tissue Engineering and Regenerative Medicine
Authors: Sihui Li | Wantian Zhang | Li-Dong Zhao | Yao Lu
Source: Science China Materials (article, 2026-01-13)
Field: Materials Science — Materials Chemistry

Multifunctional flexible thermoelectric devices for next-generation wearable and integrated systems Wearable computer ; Thermal management of electronic devices and systems ; Thermoelectric materials ; Electricity ; Wearable technology ; Compatibility (geochemistry) ; Efficient energy use ; Key (lock) ; System integration Advanced Thermoelectric Materials and Devices ; Advanced Sensor and Energy Harvesting Materials ; Innovative Energy Harvesting Technologies