jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Michael J. Lance | Mackenzie Ridley | Kenneth Kane | Bruce A. Pint
Source: Journal of the American Ceramic Society (article, 2023-05-10)
Field: Materials Science — Ceramics and Composites

Raman spectroscopic characterization of SiO <sub>2</sub> phase transformation and Si substrate stress relevant to EBC performance Abstract To accurately model the long‐term durability of environmental barrier coatings (EBCs), a more complete understanding of the phase composition and transformations of the thermally grown oxide SiO 2 (TGO) is desired. For the TGO formed during thermal cycling in steam, cristobalite formation and the subsequent β‐ to α‐cristobalite transformation has been identified as a potentially life‐limiting mechanism. In this study, Raman micro‐spectroscopy was used to quantify the cristobalite transformation on a polycrystalline Si coupon that was exposed to steam at 1350°C for 100 h. The phase transformation was mapped at 200–260°C on the TGO surface at different ramp rates using a heating stage and a micro‐positioning stage. The stress in the Si substrate was also determined using Raman spectroscopy by measuring the stress induced peak shift. The α→β phase transformation produced a 300–500 MPa tensile stress in the Si substrate, which compared well to the stress predicted from the volumetric expansion of the cristobalite. Quantifying the phase transformation and residual stress are critical tools in developing the next generation of high performance EBCs. Materials science ; Cristobalite ; Raman spectroscopy ; Thermal expansion ; Stress (linguistics) ; Residual stress ; Crystallite ; Temperature cycling ; Phase (matter) ; Substrate (aquarium) ; Composite material ; Metallurgy ; Thermal ; Optics ; Chemistry ; Thermodynamics Advanced ceramic materials synthesis ; High-Temperature Coating Behaviors ; Nuclear materials and radiation effects
Authors: L. Cupertino-Malheiros | A. Oudriss | Florian Thébault | M Piette | X. Feaugas
Source: Metallurgical and Materials Transactions A (article, 2023-02-06)
Field: Materials Science — Metals and Alloys

Hydrogen Diffusion and Trapping in Low-Alloy Tempered Martensitic Steels Abstract Structural characterization of ten low-alloy tempered martensitic steels of varied composition (C, Cr, Mo, Mn, and V contents) and tempering temperature was performed to question the impact of microstructural features on hydrogen state. Thermal desorption spectroscopy and electrochemical permeation data for each alloy were acquired and interpreted in view of hydrogen diffusion/trapping models. This large database provided precise information regarding solubility, diffusion coefficient, activation energies for diffusion and trapping, hydrogen distribution into lattice, and reversible and irreversible trap sites. The results reveal a tendency for the apparent diffusion coefficient to decrease with increasing yield strength, mainly related to the density of trap sites rather than lattice diffusion. Estimates of trapping at dislocation core could explain the irreversible trapping in the six steels with sub-surface hydrogen concentration smaller than 1.5 wppm. For the four steels with higher solubility, it was calculated the superabundant vacancies concentration necessary to justify the amount of trapping sites. The steel with the highest Mo and V contents presented superior solubility of trapped hydrogen which was related to its precipitation of few nanometers in size. It was considered irreversible trapping at carbon vacancies as well as reversible trapping at elastic strain fields around the detected MC carbides. Trapping ; Materials science ; Hydrogen ; Solubility ; Alloy ; Tempering ; Diffusion ; Martensite ; Analytical Chemistry (journal) ; Thermodynamics ; Chemical physics ; Metallurgy ; Chemistry ; Physical chemistry ; Microstructure Hydrogen embrittlement and corrosion behaviors in metals ; Microstructure and Mechanical Properties of Steels ; Corrosion Behavior and Inhibition
Authors: Kaustubh Kasture | Pravin Shende
Source: Archives of Computational Methods in Engineering (article, 2023-06-13)
Field: Materials Science — Materials Chemistry

Amalgamation of Artificial Intelligence with Nanoscience for Biomedical Applications Computer science ; Applications of artificial intelligence ; Artificial intelligence ; Big data ; Nanotechnology ; Systems engineering ; Data science ; Risk analysis (engineering) ; Engineering ; Medicine ; Data mining ; Materials science Machine Learning in Materials Science ; 3D Printing in Biomedical Research ; Computational Drug Discovery Methods
Authors: Kacey G. Ortiz | Jordan J. Dotson | Donovan J. Robinson | Matthew S. Sigman | Rashad R. Karimov
Source: Journal of the American Chemical Society (article, 2023-05-19)
Field: Chemistry — Organic Chemistry

Catalyst-Controlled Enantioselective and Regiodivergent Addition of Aryl Boron Nucleophiles to N-Alkyl Nicotinate Salts Dihydropyridines are versatile building blocks for the synthesis of pyridines, tetrahydropyridines, and piperidines. Addition of nucleophiles to activated pyridinium salts allows synthesis of 1,2-, 1,4-, or 1,6-dihydropyridines; however, this process often leads to a mixture of constitutional isomers. Catalyst-controlled regioselective addition of nucleophiles to pyridiniums has the potential to solve this problem. Herein, we report that the regioselective addition of boron-based nucleophiles to pyridinium salts can be accomplished by the choice of a Rh catalyst. Chemistry ; Nucleophile ; Pyridinium ; Regioselectivity ; Enantioselective synthesis ; Catalysis ; Aryl ; Alkyl ; Organic chemistry ; Boron ; Combinatorial chemistry ; Medicinal chemistry Catalytic C–H Functionalization Methods ; Catalytic Cross-Coupling Reactions ; Organoboron and organosilicon chemistry
Authors: Xinyu Wang | Shengnan Zhang | Jicong Zhang | Yaomin Wang | Xiaoyu Jiang | Youqi Tao | Dan Li | Chao Zhong | Cong Liu
Source: Chemical Society Reviews (review, 2023-01-01)
Field: Materials Science — Biomaterials

Rational design of functional amyloid fibrillar assemblies Amyloid fibrillar assemblies, originally identified as pathological entities in neurodegenerative diseases, have been widely adopted by various proteins to fulfill diverse biological functions in living organisms. Due to their unique features, such as hierarchical assembly, exceptional mechanical properties, environmental stability, and self-healing properties, amyloid fibrillar assemblies have been employed as functional materials in numerous applications. Recently, with the rapid advancement in synthetic biology and structural biology tools, new trends in the functional design of amyloid fibrillar assemblies have begun to emerge. In this review, we provide a comprehensive overview of the design principles for functional amyloid fibrillar assemblies from an engineering perspective, as well as through the lens of structural insights. Initially, we introduce the fundamental structural configurations of amyloid assemblies and highlight the functions of representative examples. We then focus on the underlying design principles of two prevalent strategies for the design of functional amyloid fibrillar assemblies: (1) introducing new functions <i>via</i> protein modular design and/or hybridization, with typical applications encompassing catalysis, virus disinfection, biomimetic mineralization, bio-imaging, and biotherapy; and (2) dynamically regulating living amyloid fibrillar assemblies using synthetic gene circuits, with typical applications in pattern formation, leakage repair, and pressure sensing. Next, we summarize how breakthroughs in characterization techniques have contributed to unveiling the structural polymorphism of amyloid fibrils at the atomic level, and further clarifying the highly diverse regulation mechanisms of amyloid fibrillar assembly and disassembly fine-tuned by various factors. The structural knowledge may significantly aid in the structure-guided design of amyloid fibrillar assemblies with diverse bio-activities and adjustable regulatory properties. Finally, we envision that a new trend in functional amyloid design may emerge by integrating structural tunability, synthetic biology and artificial intelligence. Rational design ; Amyloid fibril ; Amyloid (mycology) ; Perspective (graphical) ; Nanotechnology ; Neuroscience ; Amyloid β ; Chemistry ; Computer science ; Materials science ; Biology ; Medicine ; Artificial intelligence ; Pathology ; Disease Supramolecular Self-Assembly in Materials ; Alzheimer's disease research and treatments ; Polyoxometalates: Synthesis and Applications
Authors: Xi-Xi Wang | Hao‐Tian Wu | Wen-Song Wang | Yu Luo | Yuan-Jin Zheng
Source: Carbon (article, 2023-06-28)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Ti3C2 MXenes meta-film switching ultra-broadband and high-efficiency green EMI shielding MXenes ; EMI ; Electromagnetic shielding ; Electromagnetic interference ; Materials science ; Broadband ; Polarization (electrochemistry) ; Attenuation ; Optoelectronics ; Electrical engineering ; Nanotechnology ; Physics ; Optics ; Engineering ; Composite material ; Chemistry Electromagnetic wave absorption materials ; Advanced Antenna and Metasurface Technologies ; Metamaterials and Metasurfaces Applications
Authors: Daniel Martín‐Yerga | Patrick R. Unwin | Dimitrios Valavanis | Xiangdong Xu
Source: Current Opinion in Electrochemistry (article, 2023-09-30)
Field: Chemistry — Electrochemistry

Correlative co-located electrochemical multi-microscopy Correlative co-located electrochemical multi-microscopy is transforming our understanding of property-function relationships in electrode materials. By coupling scanning electrochemical cell microscopy (SECCM) with complementary characterization techniques applied to identical locations of a surface, we can now unravel the intricate interplay between various physicochemical properties of electrode materials and interfaces and their impact on electrochemical phenomena, with high spatial resolution. This review explores recent advances in this correlative approach to showcase how it can reveal major new insights into the activity of materials and interfaces. Applications span diverse electrochemical fields, including energy conversion and storage, sensing, and corrosion science. We also envision future developments that will open up new possibilities for rational materials design, accelerated mechanistic understanding, and automated materials discovery. Correlative ; Nanotechnology ; Characterization (materials science) ; Electrochemistry ; Electrode ; Materials science ; Microscopy ; Electrochemical energy conversion ; Chemistry ; Optics ; Physics Electrochemical Analysis and Applications ; Conducting polymers and applications ; Analytical Chemistry and Sensors
Authors: Robert Busch | Lirong Sun | Drake Austin | Jie Jiang | Paige Miesle | Michael A. Susner | Benjamin S. Conner | Ali M. Jawaid | Shannon T. Becks | K. Mahalingam | Michael Velez | Riccardo Torsi | Joshua A. Robinson | Rahul Rao | Nicholas R. Glavin | Richard A. Vaia | Ruth Pachter | W. Joshua Kennedy | Jonathan P. Vernon | Peter R. Stevenson
Source: npj 2D Materials and Applications (article, 2023-02-24)
Field: Materials Science — Materials Chemistry

Exfoliation procedure-dependent optical properties of solution deposited MoS2 films The development of high-precision large-area optical coatings and devices comprising low-dimensional materials hinges on scalable solution-based manufacturability with control over exfoliation procedure-dependent effects. As such, it is critical to understand the influence of technique-induced transition metal dichalcogenide (TMDC) optical properties that impact the design, performance, and integration of advanced optical coatings and devices. Here, we examine the optical properties of semiconducting MoS<sub>2</sub> films from the exfoliation formulations of four prominent approaches: solvent-mediated exfoliation, chemical exfoliation with phase reconversion, redox exfoliation, and native redox exfoliation. The resulting MoS<sub>2</sub> films exhibit distinct refractive indices (<i>n</i>), extinction coefficients (<i>k</i>), dielectric functions (ε<sub>1</sub> and ε<sub>2</sub>), and absorption coefficients (α). For example, a large index contrast of Δ<i>n</i> ≈ 2.3 is observed. These exfoliation procedures and related chemistries produce different exfoliated flake dimensions, chemical impurities, carrier doping, and lattice strain that influence the resulting optical properties. First-principles calculations further confirm the impact of lattice defects and doping characteristics on MoS<sub>2</sub> optical properties. Overall, incomplete phase reconfiguration (from 1T to mixed crystalline 2H and amorphous phases), lattice vacancies, intraflake strain, and Mo oxidation largely contribute to the observed differences in the reported MoS<sub>2</sub> optical properties. These findings highlight the need for controlled technique-induced effects as well as the opportunity for continued development of, and improvement to, liquid phase exfoliation methodologies. Such chemical and processing-induced effects present compelling routes to engineer exfoliated TMDC optical properties toward the development of next-generation high-performance mirrors, narrow bandpass filters, and wavelength-tailored absorbers. Exfoliation joint ; Materials science ; Doping ; Optoelectronics ; Amorphous solid ; Impurity ; Nanotechnology ; Chemical engineering ; Chemistry ; Crystallography ; Organic chemistry 2D Materials and Applications ; Perovskite Materials and Applications ; MXene and MAX Phase Materials
Authors: Xuzhi Zhang | Xiangyi Hou | Liangyu Ma | Yaqi Shi | Dahai Zhang | Keming Qu
Source: Journal of Nanobiotechnology (review, 2023-03-20)
Field: Materials Science — Materials Chemistry

Analytical methods for assessing antimicrobial activity of nanomaterials in complex media: advances, challenges, and perspectives Assessing the antimicrobial activity of engineered nanomaterials (ENMs), especially in realistic scenarios, is of great significance for both basic research and applications. Multiple analytical methods are available for analysis via off-line or on-line measurements. Real-world samples are often complex with inorganic and organic components, which complicates the measurements of microbial viability and/or metabolic activity. This article highlights the recent advances achieved in analytical methods including typical applications and specifics regarding their accuracy, cost, efficiency, and user-friendliness. Methodological drawbacks, technique gaps, and future perspectives are also discussed. This review aims to help researchers select suitable methods for gaining insight into antimicrobial activities of targeted ENMs in artificial and natural complex matrices. Nanomaterials ; Antimicrobial ; Nanotechnology ; Chemistry ; Engineering ethics ; Biochemical engineering ; Materials science ; Engineering Nanoparticles: synthesis and applications ; Advanced Nanomaterials in Catalysis ; Gold and Silver Nanoparticles Synthesis and Applications
Authors: D. Castro‐Reigía | A. I. Martín-García | S. Sanllorente | L.A. Sarabia | José Manuel Amigo | M.C. Ortiz
Source: Journal of Food Engineering (article, 2023-09-12)
Field: Chemistry — Analytical Chemistry

Bread fermentation monitoring through NIR spectroscopy and PLS-DA. Determining the optimal fermentation point in bread doughs Dough fermentation is a fundamental step in bread manufacturing, commonly supervised by bakery experts. This work aims to develop an efficient technology based on near infrared spectroscopy (NIR) and partial least squares-discriminant analysis (PLS-DA) to determine the fermentation state of bread loaves in the bakery industry. Knowing the fermentation state of the loaves during the manufacturing will allow to act in the production line, avoiding introducing an inadequate loaf in the oven and reducing costs. For that, a new methodology is proposed that consists in reproducing the knowledge of a Master Baker through a NIR spectrometer. Regarding the sequentiality of the objects and the real applicability of the method, three different cases were proposed using PLS-DA, getting that, in the best case, the sensitivity of the prediction set for the unfermented doughs was 88% and for the fermented and over-fermented was 86%; whereas the specificities were all greater than 86%. Fermentation ; Partial least squares regression ; Food science ; Near-infrared spectroscopy ; Chemometrics ; Chemistry ; Mathematics ; Linear discriminant analysis ; Process engineering ; Pulp and paper industry ; Engineering ; Chromatography ; Statistics ; Biology Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality ; Food composition and properties
Authors: Mayk Caldas Ramos | Shane S. Michtavy | Marc D. Porosoff | Andrew Dickson White
Source: arXiv (Cornell University) (preprint, 2023-04-11)
Field: Materials Science — Materials Chemistry

Bayesian Optimization of Catalysis With In-Context Learning Large language models (LLMs) can perform accurate classification with zero or few examples through in-context learning. We extend this capability to regression with uncertainty estimation using frozen LLMs (e.g., GPT-3.5, Gemini), enabling Bayesian optimization (BO) in natural language without explicit model training or feature engineering. We apply this to materials discovery by representing experimental catalyst synthesis and testing procedures as natural language prompts. A key challenge in materials discovery is the need to characterize suboptimal candidates, which slows progress. While BO is effective for navigating large design spaces, standard surrogate models like Gaussian processes assume smoothness and continuity, an assumption that fails in highly non-linear domains such as heterogeneous catalysis. Our task-agnostic BO workflow overcomes this by operating directly in language space, producing interpretable and actionable predictions without requiring structural or electronic descriptors. On benchmarks like aqueous solubility and oxidative coupling of methane (OCM), BO-ICL matches or outperforms Gaussian processes. In live experiments on the reverse water-gas shift (RWGS) reaction, BO-ICL identifies near-optimal multi-metallic catalysts within six iterations from a pool of 3,700 candidates. Our method redefines materials representation and accelerates discovery, with broad applications across catalysis, materials science, and AI. Code: https://github.com/ur-whitelab/BO-ICL. Computer science ; Bayesian optimization ; Artificial intelligence ; Machine learning ; Context (archaeology) ; Gaussian process ; Bayesian probability ; Lift (data mining) ; Process (computing) ; Gaussian ; Programming language Machine Learning in Materials Science ; Topic Modeling ; Machine Learning and Data Classification
Authors: Gaël Sebald | Giulia Lombardi | Gildas Coativy | Jacques Jay | Laurent Lebrun | Atsuki Komiya
Source: Applied Thermal Engineering (article, 2023-01-06)
Field: Materials Science — Materials Chemistry

High-performance polymer-based regenerative elastocaloric cooler Coefficient of performance ; Refrigeration ; Materials science ; Mechanical engineering ; Thermal conductivity ; Natural rubber ; Cooling capacity ; Evaporative cooler ; Elastomer ; Nuclear engineering ; Automotive engineering ; Process engineering ; Refrigerant ; Composite material ; Engineering ; Heat exchanger Thermal Expansion and Ionic Conductivity ; Advanced Thermoelectric Materials and Devices ; Refrigeration and Air Conditioning Technologies
Authors: Johanna Tüshaus | Amirhossein Sakhteman | Severin Lechner | Matthew The | Eike Mucha | Christoph Krisp | Jürgen Schlegel | Claire Delbridge | Bernhard Küster
Source: The EMBO Journal (article, 2023-11-02)
Field: Chemistry — Spectroscopy

A region‐resolved proteomic map of the human brain enabled by high‐throughput proteomics Proteomics ; Biology ; Computational biology ; Profiling (computer programming) ; Protein expression ; High resolution ; Human Protein Atlas ; Human brain ; Quantitative proteomics ; Neuroscience ; Computer science ; Gene ; Biochemistry Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Mass Spectrometry Techniques and Applications
Authors: Qi Wang | Xinhao Feng | Xinyou Liu
Source: Cellulose (review, 2023-08-01)
Field: Materials Science — Biomaterials

Functionalization of nanocellulose using atom transfer radical polymerization and applications: a review Nanocellulose ; Atom-transfer radical-polymerization ; Surface modification ; Materials science ; Nanotechnology ; Polymer ; Biocompatibility ; Polymerization ; Chemical engineering ; Composite material ; Cellulose Advanced Cellulose Research Studies ; Advanced Polymer Synthesis and Characterization ; biodegradable polymer synthesis and properties
Authors: Hyunsoo Park | Yeonghun Kang | Jihan Kim
Source: ACS Applied Materials & Interfaces (article, 2023-11-20)
Field: Materials Science — Materials Chemistry

Enhancing Structure–Property Relationships in Porous Materials through Transfer Learning and Cross-Material Few-Shot Learning Porous materials have emerged as promising solutions for a wide range of energy and environmental applications. However, the asymmetric development in the field of metal-organic frameworks (MOFs) has led to a data imbalance when it comes to MOFs versus other porous materials such as covalent organic frameworks (COFs), porous polymer networks (PPNs), and zeolites. To address this issue, we introduce PMTransformer (Porous Material Transformer), a multimodal Transformer model pretrained on a vast data set of 1.9 million hypothetical porous materials, including metal-organic frameworks, covalent organic frameworks, porous polymer networks, and zeolites. PMTransformer showcases remarkable transfer learning capabilities, resulting in state-of-the-art performance in predicting various porous material properties. To address the challenge of asymmetric data aggregation, we propose cross-material few-shot learning, which leverages the synergistic effect among different porous material classes to enhance the fine-tuning performance with a limited number of examples. As a proof of concept, we demonstrate its effectiveness in predicting band gap values of COFs using the available MOF data in the training set. Moreover, we established cross-material relationships in porous materials by predicting the unseen properties of other classes of porous materials. Our approach presents a new pathway for understanding the underlying relationships among various classes of porous materials, paving the way toward a more comprehensive understanding and design of porous materials. Materials science ; Property (philosophy) ; Porosity ; Porous medium ; Transfer of learning ; Nanotechnology ; Composite material ; Artificial intelligence ; Computer science Covalent Organic Framework Applications ; Metal-Organic Frameworks: Synthesis and Applications ; Rock Mechanics and Modeling