jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Dong‐Il Yeom | Y. Ko | Young-Kyu Ko | Heungsoon Im | Jungi Song | Yongwook Seok | Hanbyeol Jang | Jaeha Hwang | Sen Jin | Kenji Watanabe | Takashi Taniguchi | Kayoung Lee
Source: Advanced Functional Materials (article, 2025-04-03)
Field: Materials Science — Materials Chemistry

Ternary Transistors With Reconfigurable Polarities Abstract The recent surge in interest in ultra‐power‐saving electronic systems has highlighted multi‐valued logic circuitry as a promising technology that can simultaneously reduce circuit area, complexity, and power consumption compared to conventional binary logic. Nevertheless, the development of both p ‐type and n ‐type multi‐valued transistors with stable intermediate states is rare, particularly without CMOS‐incompatible heterostructures. Here, polarity‐reconfigurable ternary transistors are introduced fabricated using few‐layer black phosphorus (BP) homojunction. The ternary transistors feature asymmetric contacts and control gates, which determine carrier polarity and injection levels. The control gates allow the conversion from a conventional ambipolar operation to a p ‐type ternary operation, with a ≈50‐fold improvement in the on–off ratio and a well‐defined intermediate state. The intermediate state is established by a weakly gate‐dependent injection of minority carriers. The operational characteristics are discussed in relation to the applied control gate, drain bias, BP thickness, and contact metal, along with the ternary‐to‐binary transition. Notably, the devices also exhibit electrical switching to an n ‐type ternary operation, with its intermediate state matching that of the p ‐type ternary operation thanks to the antisymmetric device architecture. Materials science ; Ternary operation ; Transistor ; Nanotechnology ; Business ; Engineering physics ; Electrical engineering ; Computer science ; Engineering 2D Materials and Applications ; Graphene research and applications ; Advanced Memory and Neural Computing
Authors: Somar Khalil | Jenny T.C Ho | Michel Plisnier
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2025-08-02)
Field: Chemistry — Spectroscopy

Definitive benchmarking of DDA and DIA for host cell protein analysis on the Orbitrap Astral in a regulatory-aligned framework Host cell proteins (HCPs) are critical quality attributes in biotherapeutics and require accurate, protein-resolved quantification beyond the coverage limits of immunoassays. The Orbitrap Astral mass spectrometer was evaluated for label-free HCP analysis through a direct comparison of data-dependent acquisition (DDA, Top80) and data-independent acquisition (DIA, 4 m/z windows). Deterministic protein inference was implemented to ensure invariant protein grouping across datasets and software versions. Quantification was anchored using a whole-proteome stable isotope–labeled HCP standard, with identification error controlled through empirical false discovery proportion estimation. Both acquisition modes quantified total HCP content with high linearity (R 2 &gt; 0.99) and total error within ±30% acceptance limits across a seven-point spike-in series. DIA achieved greater analytical depth, identifying 45% more proteins and 68% more peptides than DDA, with substantially reduced missingness. Protein-level fold-change behavior was evaluated using hierarchical Bayesian regression, with slopes centered near unity for DIA and systematic compression observed for DDA. Abundance-stratified resampling analysis demonstrated trueness and precision across the dynamic range and defined lower limits of quantification of approximately 0.6 ppm for DIA and 1.6 ppm for DDA. Both acquisition strategies accurately report global HCP content, while DIA provides improved coverage, fold-change fidelity, and sensitivity for low-abundance impurities. This study demonstrates that untargeted MS-based HCP measurements can be analytically qualified for use in regulated biopharmaceutical settings. Benchmarking ; Host (biology) ; Computer science ; Business ; Biology ; Genetics Advanced Proteomics Techniques and Applications ; Viral Infectious Diseases and Gene Expression in Insects ; Mass Spectrometry Techniques and Applications
Authors: Fenghui Zhu | Yinghuan Liu | Zhining Sun | Jiping Ni | Ying Jiang
Source: Angewandte Chemie International Edition (article, 2025-04-04)
Field: Materials Science — Polymers and Plastics

Aptamer‐Based Galvanic Potentiometric Sensor for Real‐Time Monitoring of Serotonin Signaling Under Psychosocial Stress Psychosocial stress, a pervasive factor in mental health disorders, is tightly linked to serotonin (5-HT) dysregulation. Real-time electrochemical monitoring of 5-HT in vivo is challenged by interference from vitamin C (Vc) and biofouling, requiring invasive pretreatments. We present a self-powered aptamer-engineered galvanic sensor (aptGRP<sub>5-HT</sub>) that integrates phosphorothioate aptamers with a redox potentiometric mechanism, achieving 21.5-fold higher selectivity and 98.3-fold enhanced sensitivity against Vc over conventional sensors while resisting electrochemical biofouling. The aptGRP<sub>5-HT</sub> operates in complex biological environments without pretreatment, enabling direct monitoring in a rodent psychosocial stress model. Using this tool, we uncover a neurochemical signature of social hierarchy: high-ranking mice exhibit elevated 5-HT release in the medial prefrontal cortex (mPFC) and dorsal raphe nucleus (DRN), with region-specific correlations to neuronal activity-reduced spontaneous firing in the mPFC and increased activity in the DRN. This work resolves long-standing challenges in neurochemical sensing and establishes aptGRP<sub>5-HT</sub> as a transformative platform for probing brain function and stress-related disorders. Neurochemical ; Aptamer ; Dorsal raphe nucleus ; Prefrontal cortex ; Neuroscience ; Serotonin ; Chemistry ; Psychology ; Serotonergic ; Biology ; Receptor ; Biochemistry ; Cognition ; Molecular biology Conducting polymers and applications ; Biotin and Related Studies ; Electrochemical Analysis and Applications
Authors: Emilio J. Estrada | Juan Manuel Márquez | Diego Portillo-Sánchez | Pablo Roig
Source: Physical review. D/Physical review. D. (article, 2025-05-27)
Field: Materials Science — Materials Chemistry

Proton-box contribution to <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msubsup><mml:mrow><mml:mi>a</mml:mi></mml:mrow><mml:mrow><mml:mi>μ</mml:mi></mml:mrow><mml:mrow><mml:mtext>HLbL</mml:mtext></mml:mrow></mml:msubsup></mml:mrow></mml:math> We analyze the proton-box contribution to the hadronic light-by-light part of the muon’s anomalous magnetic moment, which is the first reported baryonic contribution to this piece. We follow the quark-loop analysis, incorporating the relevant data-driven and lattice proton form factors. Although the heavy mass expansion would yield a contribution of <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline"><a:mi mathvariant="script">O</a:mi><a:mo stretchy="false">(</a:mo><a:msup><a:mn>10</a:mn><a:mrow><a:mo>−</a:mo><a:mn>10</a:mn></a:mrow></a:msup><a:mo stretchy="false">)</a:mo></a:math>, the damping of the form factors in the regions where the kernel peaks explains our finding <f:math xmlns:f="http://www.w3.org/1998/Math/MathML" display="inline"><f:mrow><f:msubsup><f:mrow><f:mi>a</f:mi></f:mrow><f:mrow><f:mi>μ</f:mi></f:mrow><f:mrow><f:mi mathvariant="normal">p</f:mi><f:mo>−</f:mo><f:mtext>box</f:mtext></f:mrow></f:msubsup><f:mo>=</f:mo><f:mn>1.82</f:mn><f:mo stretchy="false">(</f:mo><f:mn>7</f:mn><f:mo stretchy="false">)</f:mo><f:mo>×</f:mo><f:msup><f:mrow><f:mn>10</f:mn></f:mrow><f:mrow><f:mo>−</f:mo><f:mn>12</f:mn></f:mrow></f:msup></f:mrow></f:math>, 2 orders of magnitude smaller than the forthcoming uncertainty on the <k:math xmlns:k="http://www.w3.org/1998/Math/MathML" display="inline"><k:msub><k:mi>a</k:mi><k:mi>μ</k:mi></k:msub></k:math> measurement and on its Standard Model prediction. Algorithm ; Mathematics Lanthanide and Transition Metal Complexes ; Magnetism in coordination complexes ; Medical Imaging Techniques and Applications
Authors: Y. Z. Song | Sheng Wang | Jia‐Ning Hou | Zhaopeng Yu | Yan Liu | Zhongqiang Zhang
Source: Advanced Functional Materials (article, 2025-11-04)
Field: Materials Science — Surfaces, Coatings and Films

Phase Replacement Enables Self‐Detectable and High‐Efficiency Oil‐Adsorbing Bioinspired Coupled Structure Abstract Real‐time self‐detection of micro‐oil droplet positions and trajectories is critical for the timely identification of oil leaks from subsea crude oil pipelines and equipments. Traditional detection methods exhibit inherent latency, often resulting in significant environmental damage by the time leaks are discovered. This work pioneers an electrified system composed of a bioinspired coupled conical microcolumn structure (BCCM) for real‐time self‐detection and collection of underwater micro‐oil droplets via a stable gas film. The design of mushroom‐shaped structures enhances the gas film thickness (273 µm) and stability (5.76 m s −1 ), enabling the ultra‐fast transport of micro‐oil droplets by gas film induction (135 mm s −1 ). This shift in the motion interface from oil‐water to oil‐gas significantly reduces resistance. Through phase replacement, like a “fluid‐controlled gate,” the on/off switch is activated by absorbing oil and ethanol. The fluid‐controlled gate enables waterproof‐free operation by regulating switch states, facilitating underwater applications ranging from dynamic light displays to naval alert systems and environmental monitoring. This work builds an integrated system capable of oil adsorption, transport, and self‐detection with highly efficient oil pollution cleaning, recovery, and precise detection. Subsea ; Pipeline transport ; Underwater ; Work (physics) ; Conical surface ; Microelectromechanical systems ; Phase (matter) ; Fossil fuel Surface Modification and Superhydrophobicity ; Electrowetting and Microfluidic Technologies ; Advanced Sensor and Energy Harvesting Materials
Authors: Kerstin Fiebig | Thomas Jourdan | Martin H Kock | Karolina Krehl | Roswitha Merle | Christa Thöne‐Reineke
Source: Journal of the American Association for Laboratory Animal Science (article, 2025-01-01)
Field: Chemistry — Physical and Theoretical Chemistry

Infrared Thermography for Temperature Measurement in Adult Female C57BL/6NCrl Mice: A Comparison with Rectal Probe and Subcutaneous Transponder Body temperature is an easily measured clinical parameter that provides important information about an animal's health and welfare. In the context of animal experiments, temperature monitoring provides relevant data needed to manage animal care and has been embraced as a means of assessing humane endpoints. At the same time, temperature measurement in the sense of the 3Rs (Replacement, Refinement, and Reduction) should not cause any additional pain or distress to the animals. Therefore, the use of noninvasive, accurate, and cost-effective methods for temperature monitoring is of great importance in research laboratories. The purpose of this study was to determine the accuracy and consistency of different temperature measurement methods in black-haired C57BL/6NCrl mice. Body surface temperature measured by noninvasive infrared thermography was compared with established methods: subcutaneous and rectal temperature measurements. The study was conducted on 50 adult female mice, and measurements were taken for 5 d. Temperatures were measured using previously implanted subcutaneous temperature transponders, followed by infrared thermometry and rectal probes. The analyzed data showed that mouse temperature measurement using an infrared camera is an adequate method for noncontact and noninvasive temperature assessment in female C57BL/6NCrl mice and promotes laboratory animal welfare refinement. Thermography ; Transponder (aeronautics) ; Rectal temperature ; Context (archaeology) ; Temperature measurement ; Animal welfare ; Medicine ; Infrared ; Infrared thermometer ; Biomedical engineering ; Consistency (knowledge bases) ; Materials science ; Biology ; Computer science ; Anesthesia ; Optics ; Artificial intelligence ; Physics thermodynamics and calorimetric analyses ; Meat and Animal Product Quality ; Animal Behavior and Welfare Studies
Authors: Morena Raiola | Isaac Esteban | Kenzo Ivanovitch | Miquel Sendra | Miguel Torres
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2025-06-28)
Field: Materials Science — Biomaterials

A method for analysing tissue motion and deformation during mammalian organogenesis SUMMARY Understanding tissue morphogenesis is an important goal in developmental biology and tissue engineering. Accurately describing tissue deformation processes and how cell rearrangements contribute to these is a challenging task. Live analysis of morphogenesis in 3D is frequently used to obtain source data that allow to extract such features from developing organs. However, several limitations are encountered when applying these methodologies to mammalian embryos. The mouse embryo is the most frequently used model, but most studies use a very limited number of specimens and present only individual acquisitions due to constraints imposed by embryo culture and imaging. Here we used data from live analysis of embryonic heart development to develop methodologies that allow to 1) deduce tissue deformation and cell movements from image intensity flows, 2) stage and register data from several specimens/acquisitions to a dynamic consensus model of heart development, 3) statistically calculate and map to the model tissue growth and anisotropy and 4) generate a digital model of heart development that allows in-silico pseudo-cell fate mapping. Our methodology will greatly facilitate the understanding of morphogenetic processes underlying mammalian organogenesis. Organogenesis ; Deformation (meteorology) ; Motion (physics) ; Computer science ; Cell biology ; Biology ; Computational biology ; Computer vision ; Geology ; Genetics Collagen: Extraction and Characterization
Authors: Sherif Abdulkader Tawfik | Julian Berk | Tiffany R. Walsh | Santu Rana | Svetha Venkatesh
Source: The Journal of Physical Chemistry C (article, 2025-03-20)
Field: Materials Science — Materials Chemistry

Accelerated Discovery of Solid-State Electrolytes Using Bayesian Optimization Current lithium batteries do not fully meet the longevity and safety requirements of electric vehicles. Novel solid-state lithium-ion batteries could be a compelling solution to these problems. In this work, we unravel some of these new materials with potentially high lithium conductivity by using a Bayesian optimization approach. This involves exploring the material space for new solid-state electrolyte materials with the objective of maximizing lithium diffusivity. The materials selected by the Bayesian optimization algorithm are then examined using ab initio molecular dynamics to estimate their diffusion energy barrier. We establish that the materials are electronic insulators, a requirement in electrolyte materials, by computing the electronic bandgaps of each of the selected materials using a hybrid exchange method and then examine the stability of the materials at the lithium metal anode interface by computing the crystal decomposition energies. Out of the selected materials, we find that Li3YBr6 has a reasonably low diffusion barrier, a high bandgap, and is potentially the most stable material at the lithium metal interface. In addition to introducing stable and high-diffusivity solid-state electrolyte materials, our work presents a material discovery method that can be applied to a broad range of applications. Bayesian optimization ; Bayesian probability ; Electrolyte ; Computer science ; State (computer science) ; Solid-state ; Materials science ; Artificial intelligence ; Chemistry ; Algorithm ; Physical chemistry Machine Learning in Materials Science ; Process Optimization and Integration ; Catalysis and Oxidation Reactions
Authors: José Mancias | Brent Vela | Juan Flórez-Coronel | Rouhollah Tavakoli | Douglas Allaire | Raymundo Arróyave | D. Tourret
Source: Acta Materialia (article, 2025-07-29)
Field: Materials Science — Materials Chemistry

Mapping of microstructure transitions during rapid alloy solidification using Bayesian-guided phase-field simulations Materials science ; Microstructure ; Alloy ; Phase (matter) ; Phase field models ; Phase transition ; Metallurgy ; Field (mathematics) ; Thermodynamics Solidification and crystal growth phenomena ; Metallurgy and Material Forming ; Aluminum Alloy Microstructure Properties
Authors: N.P. Kartashov | Nikolaos N. Vlassis
Source: Computer Methods in Applied Mechanics and Engineering (article, 2025-01-25)
Field: Materials Science — Materials Chemistry

A large language model and denoising diffusion framework for targeted design of microstructures with commands in natural language Microstructure plays a critical role in determining the macroscopic properties of materials, with applications spanning alloy design, MEMS devices, and tissue engineering, among many others. Computational frameworks have been developed to capture the complex relationship between microstructure and material behavior. However, despite these advancements, the steep learning curve associated with domain-specific knowledge and complex algorithms restricts the broader application of these tools. To lower this barrier, we propose a framework that integrates Natural Language Processing (NLP), Large Language Models (LLMs), and Denoising Diffusion Probabilistic Models (DDPMs) to enable microstructure design using intuitive natural language commands. Our framework employs contextual data augmentation, driven by a pretrained LLM, to generate and expand a diverse dataset of microstructure descriptors. A retrained Named Entity Recognition (NER) model extracts relevant microstructure descriptors from user-provided natural language inputs, which are then used by the DDPM to generate microstructures with targeted mechanical properties and topological features. The NLP and DDPM components of the framework are modular, allowing for separate training and validation, which ensures flexibility in adapting the framework to different datasets and use cases. A surrogate model system is employed to rank and filter generated samples based on their alignment with target properties. This work introduces a comprehensive framework that bridges natural language processing and mechanics, addressing key challenges such as the lack of training data, syntax invariance in textual descriptors, and precision in text embeddings. Demonstrated on a database of nonlinear hyperelastic microstructures, this framework serves as a prototype for accessible inverse design of microstructures, starting from intuitive natural language commands. Natural (archaeology) ; Computer science ; Diffusion ; Microstructure ; Natural language ; Programming language ; Artificial intelligence ; Geology ; Materials science ; Physics ; Composite material ; Thermodynamics Machine Learning in Materials Science ; Composite Material Mechanics ; Topology Optimization in Engineering
Authors: Han Yan | Yubo Zhao | Shanyong Xuan | Hailong Yang | Chunhe Miao | Xuefeng Yao
Source: Composite Structures (article, 2025-03-15)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Optimization design of structural parameters for honeycomb microwave absorbing repair structure based on surrogate models Surrogate model ; Honeycomb ; Structural integrity ; Materials science ; Microwave ; Structural engineering ; Honeycomb structure ; Composite material ; Engineering ; Mathematical optimization ; Mathematics Electromagnetic wave absorption materials ; Cellular and Composite Structures ; Advanced Antenna and Metasurface Technologies
Authors: Xinyu Lin | Weike Su | Qihong Zhang
Source: Carbohydrate Polymers (article, 2025-08-06)
Field: Materials Science — Biomaterials

Bayesian-assisted mechanochemical synthesis of carboxylated cellulose nanocrystals and its application in Pickering emulsion Pickering emulsion ; Cellulose ; Emulsion ; Nanocrystal ; Chemical engineering ; Materials science ; Polymer science ; Chemistry ; Polymer chemistry ; Organic chemistry ; Nanotechnology ; Engineering Advanced Cellulose Research Studies ; Pickering emulsions and particle stabilization ; biodegradable polymer synthesis and properties
Authors: H CHOI | Hyeonmin Yang | Junhyeok Woo | Jihun Mun | Tae‐Hyun Bae
Source: Korean Journal of Chemical Engineering (article, 2025-08-10)
Field: Chemistry — Inorganic Chemistry

Upcycling PET Waste into High-Performance Metal–Organic Frameworks: Sustainable Synthesis of MIL-53(Al) for Gas Separation and Storage Abstract This study investigates the potential of upcycling polyethylene terephthalate (PET) waste into high-valuable functional materials, specifically focusing on the synthesis of metal–organic frameworks (MOFs). Terephthalic acid (TPA), obtained through acidic hydrolysis of post-consumer PET waste, was utilized as an organic linker to synthesize MIL-53(Al)-R, a well-known aluminum-based MOF. The synthesized MIL-53(Al)-R exhibits the same crystal structure, morphology, and porosity as conventional MIL-53(Al)-C, with gas adsorption performance comparable to existing literature values. These findings validate the feasibility of using recycled PET as a viable feedstock for MOF production and highlight the potential of waste-derived MIL-53(Al)-R as an eco-friendly adsorbent for gas separation and storage applications. The study not only underscores the functional performance of MIL-53(Al)-R but also promotes a sustainable strategy for plastic waste valorization. By transforming environmental pollutants into high-performance materials, this work supports green chemistry initiatives and contributes to the development of circular economy approaches in materials science and chemical engineering. Metal-organic framework ; Sustainable society ; Materials science ; Waste management ; Gas separation ; Process engineering ; Environmental science ; Chemical engineering ; Chemistry ; Organic chemistry ; Adsorption ; Engineering ; Sustainability Metal-Organic Frameworks: Synthesis and Applications ; Magnesium Oxide Properties and Applications ; MXene and MAX Phase Materials
Authors: Jianzhao Zhou | Jingzheng Ren | Chang He
Source: Green Chemistry (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Turning sewage sludge and medical waste into energy: sustainable process synthesis <i>via</i> surrogate-based superstructure optimization Waste-to-energy (WtE) conversion offers a promising solution for sustainable waste management, but identifying economically viable and environmentally sustainable pathways remains a significant challenge. Superstructure ; Waste management ; Process (computing) ; Sewage sludge ; Environmental science ; Sustainable energy ; Process engineering ; Sewage treatment ; Engineering ; Computer science ; Renewable energy Graphite, nuclear technology, radiation studies