jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: S. M. Shatil Shahriar | Alec McCarthy | Syed Muntazir Andrabi | Yajuan Su | Navatha Shree Polavoram | Johnson V. John | Mitchell P. Matis | Wuqiang Zhu | Jingwei Xie
Source: Nature Communications (article, 2024-02-05)
Field: Materials Science — Biomaterials

Mechanically resilient hybrid aerogels containing fibers of dual-scale sizes and knotty networks for tissue regeneration The structure and design flexibility of aerogels make them promising for soft tissue engineering, though they tend to come with brittleness and low elasticity. While increasing crosslinking density may improve mechanics, it also imparts brittleness. In soft tissue engineering, resilience against mechanical loads from mobile tissues is paramount. We report a hybrid aerogel that consists of self-reinforcing networks of micro- and nanofibers. Nanofiber segments physically entangle microfiber pillars, allowing efficient stress distribution through the intertwined fiber networks. We show that optimized hybrid aerogels have high specific tensile moduli (~1961.3 MPa cm<sup>3</sup> g<sup>-1</sup>) and fracture energies (~7448.8 J m<sup>-2</sup>), while exhibiting super-elastic properties with rapid shape recovery (~1.8 s). We demonstrate that these aerogels induce rapid tissue ingrowth, extracellular matrix deposition, and neovascularization after subcutaneous implants in rats. Furthermore, we can apply them for engineering soft tissues via minimally invasive procedures, and hybrid aerogels can extend their versatility to become magnetically responsive or electrically conductive, enabling pressure sensing and actuation. Regeneration (biology) ; Dual (grammatical number) ; Scale (ratio) ; Materials science ; Cell biology ; Biology ; Physics Electrospun Nanofibers in Biomedical Applications ; Aerogels and thermal insulation ; Advanced Sensor and Energy Harvesting Materials
Authors: Nasuha Ahmad | Mohd Idzat Idris | Azimah Hussin | Julia Abdul Karim | N.M. Azreen | Rafidah Zainon
Source: Scientific Reports (article, 2024-10-29)
Field: Materials Science — Materials Chemistry

Enhancing shielding efficiency of ordinary and barite concrete in radiation shielding utilizations Concrete has been widely utilized as a radiation shielding material due to its properties and structural integrity. This study aims to evaluate the efficiency of ordinary concrete versus barite concrete as radiation shielding materials, focusing on the physical aspects and changes in crystal size lattice parameters after neutron irradiation. Specifically, the research investigates the shielding effectiveness of these materials across different grades (M15, M25, M35, and M45) against gamma-ray sources Cobalt-60 and Caesium-137. The methodology involves measuring the linear attenuation coefficient (μ), half value layer (HVL), tenth value layer (TVL), and mean free path (MFP). Additionally, X-ray diffraction (XRD) was employed to assess crystallite size and lattice parameter changes post-irradiation for neutron irradiation. Results indicate that incorporating barite as an aggregate significantly enhances the density and crystallite macroscopic properties of the concrete. Irradiation with Cobalt-60 and Cesium 137 revealed that ordinary concrete has a lower linear attenuation (μ) ranging from 0.172 to 0.195 cm<sup>-1</sup>, with consistent mass attenuation across all grades at 0.81 cm<sup>2</sup>/g. XRD analysis demonstrated a rightward shift in the SiO₂ and BaSO₄ peaks post-irradiation, signifying crystalline expansion. In terms of lattice parameters, the d-value showed a notable decrease of 0.10 after 48 h of irradiation in grade 25, while the most significant increase of 0.02 occurred after 24 h of irradiation in grades 15 and 45. In conclusion, barite concrete proves to be more effective for radiation shielding in nuclear facilities, whereas ordinary concrete is suitable for medical shielding, or facilities exposed to lower radiation doses. Electromagnetic shielding ; Radiation shielding ; Radiation ; Nuclear engineering ; Computer science ; Materials science ; Composite material ; Engineering ; Physics ; Nuclear physics Radiation Shielding Materials Analysis ; Graphite, nuclear technology, radiation studies ; Nuclear materials and radiation effects
Authors: Jérôme Sol | Hugo Prod’homme | Luc Le Magoarou | Philipp del Hougne
Source: Nature Communications (article, 2024-04-02)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Experimentally realized physical-model-based frugal wave control in metasurface-programmable complex media Metasurface-programmable radio environments are considered a key ingredient of next-generation wireless networks. Yet, identifying a metasurface configuration that yields a desired wireless functionality in an unknown complex environment was so far only achieved with closed-loop iterative feedback schemes. Here, we introduce open-loop wave control in metasurface-programmable complex media by estimating the parameters of a compact physics-based forward model. Our experiments demonstrate orders-of-magnitude advantages over deep-learning-based digital-twin benchmarks in terms of accuracy, compactness and required calibration examples. Strikingly, our parameter estimation also works without phase information and without providing measurements for all considered scattering coefficients. These unique generalization capabilities of our pure-physics model unlock unforeseen and previously inaccessible frugal wave control protocols that significantly alleviate the measurement complexity. For instance, we achieve coherent wave control (focusing or perfect absorption) and phase-shift-keying backscatter communications in metasurface-programmable complex media with intensity-only measurements. Our approach is also directly relevant to dynamic metasurface antennas, microwave-based signal processors and emerging in situ reconfigurable nanophotonic, optical and room-acoustical systems. Computer science ; Wireless ; Electronic engineering ; Key (lock) ; Microwave ; Telecommunications Metamaterials and Metasurfaces Applications ; Indoor and Outdoor Localization Technologies ; Antenna Design and Analysis
Authors: Samuel Peña‐Díaz | William P. Olsen | Huabing Wang | Daniel E. Otzen
Source: Advanced Materials (article, 2024-02-02)
Field: Materials Science — Biomaterials

Functional Amyloids: The Biomaterials of Tomorrow? Functional amyloid (FAs), particularly the bacterial proteins CsgA and FapC, have many useful properties as biomaterials: high stability, efficient, and controllable formation of a single type of amyloid, easy availability as extracellular material in bacterial biofilm and flexible engineering to introduce new properties. CsgA in particular has already demonstrated its worth in hydrogels for stable gastrointestinal colonization and regenerative tissue engineering, cell-specific drug release, water-purification filters, and different biosensors. It also holds promise as catalytic amyloid; existing weak and unspecific activity can undoubtedly be improved by targeted engineering and benefit from the repetitive display of active sites on a surface. Unfortunately, FapC remains largely unexplored and no application is described so far. Since FapC shares many common features with CsgA, this opens the window to its development as a functional scaffold. The multiple imperfect repeats in CsgA and FapC form a platform to introduce novel properties, e.g., in connecting linkers of variable lengths. While exploitation of this potential is still at an early stage, particularly for FapC, a thorough understanding of their molecular properties will pave the way for multifunctional fibrils which can contribute toward solving many different societal challenges, ranging from CO<sub>2</sub> fixation to hydrolysis of plastic nanoparticles. Materials science ; Nanotechnology ; Polymer science ; Engineering ethics ; Engineering Supramolecular Self-Assembly in Materials ; Hydrogels: synthesis, properties, applications ; Advanced Drug Delivery Systems
Authors: Yuan Gao | Wei Chen | Fajun Li | Mingyong Zhuang | Yiming Yan | Jun Wang | Xiang Wang | Zhaogang Dong | Wei Ma | Jinfeng Zhu
Source: Advanced Science (article, 2024-09-09)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Meta‐Attention Deep Learning for Smart Development of Metasurface Sensors Optical metasurfaces with pronounced spectral characteristics are promising for sensor applications. Currently, deep learning (DL) offers a rapid manner to design various metasurfaces. However, conventional DL models are usually assumed as black boxes, which is difficult to explain how a DL model learns physical features, and they usually predict optical responses of metasurfaces in a fuzzy way. This makes them incapable of capturing critical spectral features precisely, such as high quality (Q) resonances, and hinders their use in designing metasurface sensors. Here, a transformer-based explainable DL model named Metaformer for the high-intelligence design, which adopts a spectrum-splitting scheme to elevate 99% prediction accuracy through reducing 99% training parameters, is established. Based on the Metaformer, all-dielectric metasurfaces based on quasi-bound states in the continuum (Q-BIC) for high-performance metasensing are designed, and fabrication experiments are guided potently. The explainable learning relies on spectral position encoding and multi-head attention of meta-optics features, which overwhelms traditional black-box models dramatically. The meta-attention mechanism provides deep physics insights on metasurface sensors, and will inspire more powerful DL design applications on other optical devices. Computer science ; Deep learning ; Artificial intelligence ; Transformer ; Electrical engineering ; Engineering Metamaterials and Metasurfaces Applications ; Animal Vocal Communication and Behavior ; Plasmonic and Surface Plasmon Research
Authors: Corneliu Toader | Adrian Dumitru | Lucian Eva | Matei Șerban | Răzvan-Adrian Covache-Busuioc | Alexandru Vlad Ciurea
Source: International Journal of Molecular Sciences (review, 2024-12-11)
Field: Materials Science — Biomaterials

Nanoparticle Strategies for Treating CNS Disorders: A Comprehensive Review of Drug Delivery and Theranostic Applications This review aims to address the significant challenges of treating central nervous system (CNS) disorders such as neurodegenerative diseases, strokes, spinal cord injuries, and brain tumors. These disorders are difficult to manage due to the complexity of disease mechanisms and the protective blood-brain barrier (BBB), which restricts drug delivery. Recent advancements in nanoparticle (NP) technologies offer promising solutions, with potential applications in drug delivery, neuroprotection, and neuroregeneration. By examining current research, we explore how NPs can cross the BBB, deliver medications directly to targeted CNS regions, and enhance both diagnostics and treatment. Key NP strategies, such as passive targeting, receptor-mediated transport, and stimuli-responsive systems, demonstrate encouraging results. Studies show that NPs may improve drug delivery, minimize side effects, and increase therapeutic effectiveness in models of Alzheimer's, Parkinson's, stroke, and glioblastoma. NP technologies thus represent a promising approach for CNS disorder management, combining drug delivery and diagnostic capabilities to enable more precise and effective treatments that could significantly benefit patient outcomes. Drug delivery ; Medicine ; Drug ; Neuroprotection ; Targeted drug delivery ; Disease ; Neuroregeneration ; Neuroscience ; Drug delivery to the brain ; Central nervous system ; Blood–brain barrier ; Pharmacology ; Nanotechnology ; Pathology ; Biology ; Internal medicine Nanoparticle-Based Drug Delivery ; Advanced Drug Delivery Systems ; RNA Interference and Gene Delivery
Authors: Ethan Cisneros | Brinkley Morse | Ani Savk | K.M.A. Malik | Nicholas A. Peppas | Olivia L. Lanier
Source: Journal of Nanobiotechnology (review, 2024-11-15)
Field: Materials Science — Biomaterials

The role of patient-specific variables in protein corona formation and therapeutic efficacy in nanomedicine Despite their potential, the adoption of nanotechnology in therapeutics remains limited, with only around eighty nanomedicines approved in the past 30 years. This disparity is partly due to the "one-size-fits-all" approach in medical design, which often overlooks patient-specific variables such as biological sex, genetic ancestry, disease state, environment, and age that influence nanoparticle behavior. Nanoparticles (NPs) must be transported through systemic, microenvironmental, and cellular barriers that vary across heterogeneous patient populations. Key patient-dependent properties impacting NP delivery include blood flow rates, body fat distribution, reproductive organ vascularization, hormone and protein levels, immune responses, and chromosomal differences. Understanding these variables is crucial for developing effective, patient-specific nanotechnologies. The formation of a protein corona around NPs upon exposure to biological fluids significantly alters NP properties, affecting biodistribution, pharmacokinetics, cytotoxicity, and organ targeting. The dynamics of the protein corona, such as time-dependent composition and formation of soft and hard coronas, depend on NP characteristics and patient-specific serum components. This review highlights the importance of understanding protein corona formation across different patient backgrounds and its implications for NP design, including sex, ancestry, age, environment, and disease state. By exploring these variables, we aim to advance the development of personalized nanomedicine, improving therapeutic efficacy and patient outcomes. Nanomedicine ; Corona (planetary geology) ; Nanotechnology ; Medicine ; Chemistry ; Materials science ; Physics ; Nanoparticle Nanoparticle-Based Drug Delivery ; Iron Metabolism and Disorders ; Cancer Research and Treatment
Authors: Daniele Cangialosi
Source: Journal of Polymer Science (article, 2024-02-10)
Field: Materials Science — Materials Chemistry

Physical aging and vitrification in polymers and other glasses: Complex behavior and size effects Abstract The paradigmatic view on the transformation of a supercooled liquid into a glass, so‐called vitrification or glass transition, and the subsequent time evolution of the non‐equilibrium glass, addressed as physical aging, relies on the exclusive role of the main relaxation with super‐Arrhenius temperature dependence. The aim of the present review is to carefully scrutinize the wealth of recent experimental results, above all in polymeric glasses, showing the relevance of other relaxational mechanisms in both vitrification and physical aging. While the relaxation bears dominant role in both phenomena in proximity of the glass transition temperature, , a broad view on a much wider temperature range indicates that vitrification and physical aging are mediated by non‐ mechanisms of equilibration. This review also shows that a reduction of the typical time scale of equilibration can be achieved in glasses with large free interface, namely with reduced sample size. In this way, fast non‐ mechanisms of equilibration can be exploited to convey glasses to low energy states in experimentally feasible time scales, thereby attaining information on the existence of the so‐called “ideal glass” in small sized samples. Vitrification ; Glass transition ; Supercooling ; Relaxation (psychology) ; Materials science ; Arrhenius equation ; Thermodynamics ; Polymer ; Chemical physics ; Activation energy ; Physical chemistry ; Chemistry ; Composite material ; Physics Material Dynamics and Properties ; Liquid Crystal Research Advancements ; Glass properties and applications
Authors: Yeonhong Kim | Yangwon Jeon | Minyoung Na | Soon‐Jin Hwang | Youngdae Yoon
Source: Sensors (review, 2024-01-10)
Field: Chemistry — Electrochemistry

Recent Trends in Chemical Sensors for Detecting Toxic Materials Industrial development has led to the widespread production of toxic materials, including carcinogenic, mutagenic, and toxic chemicals. Even with strict management and control measures, such materials still pose threats to human health. Therefore, convenient chemical sensors are required for toxic chemical monitoring, such as optical, electrochemical, nanomaterial-based, and biological-system-based sensors. Many existing and new chemical sensors have been developed, as well as new methods based on novel technologies for detecting toxic materials. The emergence of material sciences and advanced technologies for fabrication and signal-transducing processes has led to substantial improvements in the sensing elements for target recognition and signal-transducing elements for reporting interactions between targets and sensing elements. Many excellent reviews have effectively summarized the general principles and applications of different types of chemical sensors. Therefore, this review focuses on chemical sensor advancements in terms of the sensing and signal-transducing elements, as well as more recent achievements in chemical sensors for toxic material detection. We also discuss recent trends in biosensors for the detection of toxic materials. Chemical sensor ; Nanotechnology ; Environmental monitoring ; Computer science ; Human health ; Biochemical engineering ; Environmental science ; Materials science ; Engineering ; Chemistry Electrochemical Analysis and Applications ; Advanced biosensing and bioanalysis techniques ; Electrochemical sensors and biosensors
Authors: Tian Qin | Haoyi Yang | Lei Wang | Weiran Xue | Nan Yao | Quan Li | Xiang Chen | Xiukang Yang | Xiqian Yu | Qiang Zhang | Hong Li
Source: Angewandte Chemie International Edition (article, 2024-06-27)
Field: Materials Science — Materials Chemistry

Molecule Design for Non‐Aqueous Wide‐Temperature Electrolytes via the Intelligentized Screening Method Operating a lithium-ion battery (LIB) in a wide temperature range is essential for ensuring a stable electricity supply amidst fluctuating temperatures caused by climate or terrain changes. Electrolyte plays a pivotal role in determining the temperature durability of batteries. However, specialized electrolytes designed for either low or high temperatures typically possess distinct features. Therefore, wide-temperature electrolytes (WTEs) are necessary as they encompass a combination of diverse properties, which complicates the clear instruction of WTE design. Here we represent an artificial intelligence (Al)-assisted workflow of WTE design through stepwise parameterizations and calculations. Linear mono-nitriles are identified as ideal wide-liquidus-range solvents that can "softly" solvate lithium ions by weak interactions. In addition, the explainable modules revealed the halogenoid similarity of cyanide as fluorine on the electrolyte properties (e.g. boiling point and dielectric constant). With the further introduction of an ether bond, 3-methoxypropionitrile (MPN) has been eventually determined as a main electrolyte solvent, enabling the battery operation from -60 to 120 °C. Particularly, a LiCoO<sub>2</sub>/Li cell using the proposed WTE can realize stable cycling with capacity retention reaching 72.3 % after 50 cycles under a high temperature of 100 °C. Aqueous solution ; Electrolyte ; Computer science ; Chemistry ; Organic chemistry ; Physical chemistry Machine Learning in Materials Science ; Fuel Cells and Related Materials ; Various Chemistry Research Topics
Authors: Fankai Xie | Tenglong Lu | Sheng Meng | Miao Liu
Source: Science Bulletin (article, 2024-09-01)
Field: Materials Science — Materials Chemistry

GPTFF: A high-accuracy out-of-the-box universal AI force field for arbitrary inorganic materials This study introduces a novel artificial intelligence (AI) force field, namely a graph-based pre-trained transformer force field (GPTFF), which can simulate arbitrary inorganic systems with good precision and generalizability. Harnessing a large trove of the data and the attention mechanism of transformer algorithms, the model can accurately predict energy, atomic force, and stress with mean absolute error (MAE) values of 32 meV/atom, 71 meV/Å, and 0.365 GPa, respectively. The dataset used to train the model includes 37.8 million single-point energies, 11.7 billion force pairs, and 340.2 million stresses. We also demonstrated that the GPTFF can be universally used to simulate various physical systems, such as crystal structure optimization, phase transition simulations, and mass transport. The model is publicly released with this paper, enabling anyone to use it immediately without needing to train it. Generalizability theory ; Force field (fiction) ; Computer science ; Transformer ; Algorithm ; Simulation ; Artificial intelligence ; Engineering ; Electrical engineering ; Voltage ; Mathematics Machine Learning in Materials Science ; Fuel Cells and Related Materials ; Electron and X-Ray Spectroscopy Techniques
Authors: S. Maekawa | Takehiro Seshimo | Takahiro Dazai | Kazufumi Sato | Kan Hatakeyama‐Sato | Yuta Nabae | Teruaki Hayakawa
Source: Nature Communications (article, 2024-07-06)
Field: Materials Science — Materials Chemistry

Chemically tailored block copolymers for highly reliable sub-10-nm patterns by directed self-assembly While block copolymer (BCP) lithography is theoretically capable of printing features smaller than 10 nm, developing practical BCPs for this purpose remains challenging. Herein, we report the creation of a chemically tailored, highly reliable, and practically applicable block copolymer and sub-10-nm line patterns by directed self-assembly. Polystyrene-block-[poly(glycidyl methacrylate)-random-poly(methyl methacrylate)] (PS-b-(PGMA-r-PMMA) or PS-b-PGM), which is based on PS-b-PMMA with an appropriate amount of introduced PGMA (10-33 mol%) is quantitatively post-functionalized with thiols. The use of 2,2,2-trifluoroethanethiol leads to polymers (PS-b-PG<sub>F</sub>Ms) with Flory-Huggins interaction parameters (χ) that are 3.5-4.6-times higher than that of PS-b-PMMA and well-defined higher-order structures with domain spacings of less than 20 nm. This study leads to the smallest perpendicular lamellar domain size of 12.3 nm. Furthermore, thin-film lamellar domain alignment and vertical orientation are highly reliably and reproducibly obtained by directed self-assembly to yield line patterns that correspond to a 7.6 nm half-pitch size. Copolymer ; Lamellar structure ; Materials science ; Glycidyl methacrylate ; Polystyrene ; Lithography ; Methyl methacrylate ; Polymer ; Self-assembly ; Methacrylate ; Polymer chemistry ; Chemical engineering ; Nanotechnology ; Optoelectronics ; Composite material Block Copolymer Self-Assembly ; Advanced Polymer Synthesis and Characterization ; Polymer Surface Interaction Studies