jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Adib Bin Rashid | Mahima Haque | S M Mohaimenul Islam | K. M. Rafi Uddin Labib
Source: Heliyon (review, 2024-01-01)
Field: Materials Science — Polymers and Plastics

RETRACTED: Nanotechnology-enhanced fiber-reinforced polymer composites: Recent advancements on processing techniques and applications Incorporating nanoparticles can significantly improve the performance and functionality of fiber-reinforced polymer (FRP) composites. Different techniques exist for processing, testing, and implementing nanocomposites in various industries. Depending on these factors, these materials can be tailored to suit the specific applications of the automotive and aerospace industries, defence industries, biomedical and energy sectors etc. Nanotechnology offers several potential benefits for composites, including improved mechanical properties, surface modification, and sensing capabilities. This paper discusses the different types of nanoparticles, nanofibers, and nano-coating that can be used for reinforcement, surface modification, and property enhancement in FRP composites. It also examines the challenges associated with incorporating nanotechnology into composites and provides recommendations for potential opportunities in future work. This study is intended to offer a comprehensive understanding of the current research on using nanotechnology in FRP composites and its potential impact on the composites industry. Materials science ; Nanofiber ; Composite material ; Coating ; Nanocomposite ; Fibre-reinforced plastic ; Aerospace ; Automotive industry ; Advanced composite materials ; Nanoparticle ; Surface modification ; Nanotechnology ; Fiber-reinforced composite ; Polymer nanocomposite ; Fiber ; Composite number ; Mechanical engineering ; Engineering ; Aerospace engineering Polymer Nanocomposites and Properties ; Polymer Nanocomposite Synthesis and Irradiation ; Innovative concrete reinforcement materials
Authors: Yahui Liu | Shunda Qiao | Chao Fang | Ying He | Haiyue Sun | Jian Liu | Yufei Ma
Source: Opto-Electronic Advances (article, 2024-01-01)
Field: Chemistry — Spectroscopy

A highly sensitive LITES sensor based on a multi-pass cell with dense spot pattern and a novel quartz tuning fork with low frequency A highly sensitive light-induced thermoelectric spectroscopy (LITES) sensor based on a multi-pass cell (MPC) with dense spot pattern and a novel quartz tuning fork (QTF) with low resonance frequency is reported in this manuscript. An erbium-doped fiber amplifier (EDFA) was employed to amplify the output optical power so that the signal level was further enhanced. The optical path length (OPL) and the ratio of optical path length to volume (RLV) of the MPC is 37.7 m and 13.8 cm<sup>-2</sup>, respectively. A commercial QTF and a self-designed trapezoidal-tip QTF with low frequency of 9461.83 Hz were used as the detectors of the sensor, respectively. The target gas selected to test the performance of the system was acetylene (C<sub>2</sub>H<sub>2</sub>). When the optical power was constant at 1000 mW, the minimum detection limit (MDL) of the C<sub>2</sub>H<sub>2</sub>-LITES sensor can be achieved 48.3 ppb when using the commercial QTF and 24.6 ppb when using the trapezoidal-tip QTF. An improvement of the detection performance by a factor of 1.96 was achieved after replacing the commercial QTF with the trapezoidal-tip QTF. Detection limit ; Materials science ; Analytical Chemistry (journal) ; Optics ; Optoelectronics ; Physics ; Chemistry Spectroscopy and Laser Applications ; Gas Sensing Nanomaterials and Sensors ; Atmospheric Ozone and Climate
Authors: Ulises H. Guzmán | Ana Martínez‐Val | Zilu Ye | Eugen Damoc | Tabiwang N. Arrey | Anna Pashkova | Santosh Renuse | Eduard Denisov | J. Petzoldt | Amelia C. Peterson | Florian Harking | Ole Østergaard | Rasmus Rydbirk | Susana Aznar | Hamish Stewart | Yue Xuan | Daniel Hermanson | Stevan Horning | Christian Hock | Alexander Makarov | Vlad Zabrouskov | Jesper V. Olsen
Source: Nature Biotechnology (article, 2024-02-01)
Field: Chemistry — Spectroscopy

Ultra-fast label-free quantification and comprehensive proteome coverage with narrow-window data-independent acquisition Mass spectrometry (MS)-based proteomics aims to characterize comprehensive proteomes in a fast and reproducible manner. Here we present the narrow-window data-independent acquisition (nDIA) strategy consisting of high-resolution MS1 scans with parallel tandem MS (MS/MS) scans of ~200 Hz using 2-Th isolation windows, dissolving the differences between data-dependent and -independent methods. This is achieved by pairing a quadrupole Orbitrap mass spectrometer with the asymmetric track lossless (Astral) analyzer which provides >200-Hz MS/MS scanning speed, high resolving power and sensitivity, and low-ppm mass accuracy. The nDIA strategy enables profiling of >100 full yeast proteomes per day, or 48 human proteomes per day at the depth of ~10,000 human protein groups in half-an-hour or ~7,000 proteins in 5 min, representing 3× higher coverage compared with current state-of-the-art MS. Multi-shot acquisition of offline fractionated samples provides comprehensive coverage of human proteomes in ~3 h. High quantitative precision and accuracy are demonstrated in a three-species proteome mixture, quantifying 14,000+ protein groups in a single half-an-hour run. Proteome ; Mass spectrometry ; Quantitative proteomics ; Chemistry ; Tandem mass spectrometry ; Proteomics ; Tandem mass tag ; Orbitrap ; Chromatography ; Analytical Chemistry (journal) Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Kevin Maik Jablonka | Philippe Schwaller | Andres Ortega‐Guerrero | Berend Smit
Source: Nature Machine Intelligence (article, 2024-02-06)
Field: Materials Science — Materials Chemistry

Leveraging large language models for predictive chemistry Abstract Machine learning has transformed many fields and has recently found applications in chemistry and materials science. The small datasets commonly found in chemistry sparked the development of sophisticated machine learning approaches that incorporate chemical knowledge for each application and, therefore, require specialized expertise to develop. Here we show that GPT-3, a large language model trained on vast amounts of text extracted from the Internet, can easily be adapted to solve various tasks in chemistry and materials science by fine-tuning it to answer chemical questions in natural language with the correct answer. We compared this approach with dedicated machine learning models for many applications spanning the properties of molecules and materials to the yield of chemical reactions. Surprisingly, our fine-tuned version of GPT-3 can perform comparably to or even outperform conventional machine learning techniques, in particular in the low-data limit. In addition, we can perform inverse design by simply inverting the questions. The ease of use and high performance, especially for small datasets, can impact the fundamental approach to using machine learning in the chemical and material sciences. In addition to a literature search, querying a pre-trained large language model might become a routine way to bootstrap a project by leveraging the collective knowledge encoded in these foundation models, or to provide a baseline for predictive tasks. Computer science ; Chemistry Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Topic Modeling
Authors: Junxiong Xiao | Beibei Zhan | Mukun He | Xiaosi Qi | Xiu Gong | Jingliang Yang | Yunpeng Qu | Junfei Ding | Wei Zhong | Junwei Gu
Source: Advanced Functional Materials (article, 2024-02-28)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Interfacial Polarization Loss Improvement Induced by the Hollow Engineering of Necklace‐like PAN/Carbon Nanofibers for Boosted Microwave Absorption Abstract Rational manipulation of composition and microstructure design is recognized as an effective pathway to realize multifunctional high‐performance microwave absorber. In this work, necklace‐like hollow polyacrylonitrile (PAN)/carbon nanofibers are designed and constructed through a simple continuous electrospinning‐carbonization‐etching route. Specifically, by varying the carbonization temperature, the ratio of PAN to carbon content of necklace‐like hollow PAN/carbon nanofibers can be effectively regulated, resulting in tunable electromagnetic parameters and conductive loss capacities. After that, the hollow structure is further introduced to improve the feature of lightweight, impedance‐matching characteristics, and interfacial polarization loss ability. Accordingly, the necklace‐like hollow PAN/carbon nanofibers exhibited a frequency bandwidth of 6.60 GHz and a minimum reflection loss of −44.73 dB at 1.76 mm. Both the experimental and theoretical simulation results indicated that the obtained necklace‐like hollow PAN/carbon nanofibers possessed the high chemical stability and excellent microwave absorbing performance, endowing them as the excellent candidates for microwave absorbers in the extreme conditions. Therefore, the findings not only offered a simple pathway to rationally manipulate composition and microstructure but also provided a novel technique to make the most of hollow engineering for strengthening interface polarization loss. Materials science ; Polyacrylonitrile ; Reflection loss ; Carbon nanofiber ; Microwave ; Carbonization ; Microstructure ; Electrospinning ; Nanofiber ; Composite material ; Nanotechnology ; Carbon nanotube ; Optoelectronics ; Polymer ; Composite number ; Scanning electron microscope Electromagnetic wave absorption materials ; Advanced Antenna and Metasurface Technologies ; Metamaterials and Metasurfaces Applications
Authors: Tairan Wang | Jianyu Hu | Runhai Ouyang | Y. Wang | Yi Huang | Sulei Hu | Wei‐Xue Li
Source: Science (article, 2024-11-21)
Field: Materials Science — Materials Chemistry

Nature of metal-support interaction for metal catalysts on oxide supports The metal-support interaction is one of the most important pillars in heterogeneous catalysis, but developing a fundamental theory has been challenging because of the intricate interfaces. Based on experimental ‎data, interpretable machine learning, theoretical derivation, and first-principles simulations, we established a ‎general theory of metal-oxide interactions grounded in ‎metal-metal and metal-oxygen interactions. The theory applies to metal nanoparticles and atoms on oxide supports and oxide films on metal supports. We found that for late-transition metal catalysts, metal-metal interactions dominated the oxide support effects and suboxide encapsulation over metal nanoparticles. A principle of strong metal-metal interactions for encapsulation occurrence is formulated and substantiated by extensive ‎experiments including 10 metals and 16 ‎oxides. The valuable insights revealed on (strong) metal-support interaction advance the interfacial design of supported metal catalysts. Metal ; Oxide ; Catalysis ; Suboxide ; Materials science ; Transition metal ; Nanoparticle ; Nanotechnology ; Chemistry ; Metallurgy ; Organic chemistry Catalytic Processes in Materials Science ; Machine Learning in Materials Science ; Catalysis and Oxidation Reactions
Authors: Adeleke Maradesa | Baptiste Py | Jake Huang | Yang Lu | Pietro Iurilli | Aleksander Mroziński | Ho Mei Law | Yuhao Wang | Zilong Wang | Jingwei Li | Shengjun Xu | Quentin Meyer | Jiapeng Liu | Claudio Brivio | A. G. Gavrilyuk | Kiyoshi Kobayashi | Antonio Bertei | Nicholas J. Williams | Chuan Zhao | Michael A. Danzer | Mark P. Zic | Phillip M. Wu | Ville Yrjänä | Sergei V. Pereverzyev | Yuhui Chen | André Weber | Sergei V. Kalinin | Jan Philipp Schmidt | Yoed Tsur | Bernard A. Boukamp | Qiang Zhang | Miran Gaberšček | Ryan O’Hayre | Francesco Ciucci
Source: Joule (article, 2024-06-07)
Field: Chemistry — Electrochemistry

Advancing electrochemical impedance analysis through innovations in the distribution of relaxation times method Computer science ; Electrical impedance ; Software ; Parametric statistics ; Exploratory data analysis ; Data science ; Data mining ; Electrical engineering ; Engineering ; Mathematics Electrochemical Analysis and Applications ; Fuel Cells and Related Materials ; Conducting polymers and applications
Authors: Shunda Qiao | Ying He | Haiyue Sun | Pietro Patimisco | Angelo Sampaolo | Vincenzo Spagnolo | Yufei Ma
Source: Light Science & Applications (article, 2024-05-01)
Field: Chemistry — Spectroscopy

Ultra-highly sensitive dual gases detection based on photoacoustic spectroscopy by exploiting a long-wave, high-power, wide-tunable, single-longitudinal-mode solid-state laser Photoacoustic spectroscopy (PAS) as a highly sensitive and selective trace gas detection technique has extremely broad application in many fields. However, the laser sources currently used in PAS limit the sensing performance. Compared to diode laser and quantum cascade laser, the solid-state laser has the merits of high optical power, excellent beam quality, and wide tuning range. Here we present a long-wave, high-power, wide-tunable, single-longitudinal-mode solid-state laser used as light source in a PAS sensor for trace gas detection. The self-built solid-state laser had an emission wavelength of ~2 μm with Tm:YAP crystal as the gain material, with an excellent wavelength and optical power stability as well as a high beam quality. The wide wavelength tuning range of 9.44 nm covers the absorption spectra of water and ammonia, with a maximum optical power of ~130 mW, allowing dual gas detection with a single laser source. The solid-state laser was used as light source in three different photoacoustic detection techniques: standard PAS with microphone, and external- and intra-cavity quartz-enhanced photoacoustic spectroscopy (QEPAS), proving that solid-state laser is an attractive excitation source in photoacoustic spectroscopy. Photoacoustic spectroscopy ; Materials science ; Longitudinal mode ; Laser ; Power (physics) ; Spectroscopy ; Solid-state ; Dual mode ; Photoacoustic imaging in biomedicine ; Optoelectronics ; Optics ; Wavelength ; Physics ; Electronic engineering ; Engineering physics ; Engineering Spectroscopy and Laser Applications ; Atmospheric and Environmental Gas Dynamics ; Laser Design and Applications
Authors: Mahboubeh Ahmadi Bonakdar | Denis Rodrigue
Source: Macromol—A Journal of Macromolecular Research (article, 2024-02-11)
Field: Materials Science — Biomaterials

Electrospinning: Processes, Structures, and Materials Electrospinning is a simple and affordable method of producing nanofibers, offering a large specific surface area and highly porous structures with diameters ranging from nanometers to micrometers. This process relies on an electrostatic field, providing precise control over the fiber dimensions and morphologies through parameter optimization and the use of specialized spinnerets and collectors. The paper extensively covers the electrospinning process and parameters, shedding light on the factors influencing electrospinning. It addresses the morphological and structural aspects of electrospun fibers that are used in different applications. Additionally, this paper explores various polymeric and non-polymeric materials used in electrospinning. Furthermore, it investigates the incorporation of fillers during electrospinning, using an electric field to enhance properties and functionality. The review concludes by offering insights into upscaling electrospinning production. Electrospinning ; Materials science ; Nanofiber ; Nanometre ; Porosity ; Nanotechnology ; Fiber ; Composite material ; Polymer Electrospun Nanofibers in Biomedical Applications ; Advanced Sensor and Energy Harvesting Materials ; Conducting polymers and applications
Authors: Maciej P. Polak | Dane Morgan
Source: Nature Communications (article, 2024-02-21)
Field: Materials Science — Materials Chemistry

Extracting accurate materials data from research papers with conversational language models and prompt engineering There has been a growing effort to replace manual extraction of data from research papers with automated data extraction based on natural language processing, language models, and recently, large language models (LLMs). Although these methods enable efficient extraction of data from large sets of research papers, they require a significant amount of up-front effort, expertise, and coding. In this work, we propose the ChatExtract method that can fully automate very accurate data extraction with minimal initial effort and background, using an advanced conversational LLM. ChatExtract consists of a set of engineered prompts applied to a conversational LLM that both identify sentences with data, extract that data, and assure the data's correctness through a series of follow-up questions. These follow-up questions largely overcome known issues with LLMs providing factually inaccurate responses. ChatExtract can be applied with any conversational LLMs and yields very high quality data extraction. In tests on materials data, we find precision and recall both close to 90% from the best conversational LLMs, like GPT-4. We demonstrate that the exceptional performance is enabled by the information retention in a conversational model combined with purposeful redundancy and introducing uncertainty through follow-up prompts. These results suggest that approaches similar to ChatExtract, due to their simplicity, transferability, and accuracy are likely to become powerful tools for data extraction in the near future. Finally, databases for critical cooling rates of metallic glasses and yield strengths of high entropy alloys are developed using ChatExtract. Computer science ; Natural language processing ; Data science Machine Learning in Materials Science ; Software Engineering Research ; Computational Drug Discovery Methods
Authors: Haiyang Yu | A. Díaz | Xu Lu | Binhan Sun | Yu Ding | Motomichi Koyama | Jianying He | Xiao Zhou | A. Oudriss | X. Feaugas | Zhiliang Zhang
Source: Chemical Reviews (review, 2024-05-09)
Field: Materials Science — Metals and Alloys

Hydrogen Embrittlement as a Conspicuous Material Challenge─Comprehensive Review and Future Directions Hydrogen is considered a clean and efficient energy carrier crucial for shaping the net-zero future. Large-scale production, transportation, storage, and use of green hydrogen are expected to be undertaken in the coming decades. As the smallest element in the universe, however, hydrogen can adsorb on, diffuse into, and interact with many metallic materials, degrading their mechanical properties. This multifaceted phenomenon is generically categorized as hydrogen embrittlement (HE). HE is one of the most complex material problems that arises as an outcome of the intricate interplay across specific spatial and temporal scales between the mechanical driving force and the material resistance fingerprinted by the microstructures and subsequently weakened by the presence of hydrogen. Based on recent developments in the field as well as our collective understanding, this Review is devoted to treating HE as a whole and providing a constructive and systematic discussion on hydrogen entry, diffusion, trapping, hydrogen-microstructure interaction mechanisms, and consequences of HE in steels, nickel alloys, and aluminum alloys used for energy transport and storage. HE in emerging material systems, such as high entropy alloys and additively manufactured materials, is also discussed. Priority has been particularly given to these less understood aspects. Combining perspectives of materials chemistry, materials science, mechanics, and artificial intelligence, this Review aspires to present a comprehensive and impartial viewpoint on the existing knowledge and conclude with our forecasts of various paths forward meant to fuel the exploration of future research regarding hydrogen-induced material challenges. Hydrogen embrittlement ; Hydrogen ; Hydrogen storage ; Hydrogen economy ; Embrittlement ; Nanotechnology ; Chemistry ; Hydrogen fuel ; Engineering physics ; Materials science ; Metallurgy ; Physics Hydrogen embrittlement and corrosion behaviors in metals ; Nuclear Materials and Properties ; Corrosion Behavior and Inhibition
Authors: Xue Zhang | Xuelei Tian | Na Wu | Shanyu Zhao | Yutian Qin | Fei Pan | Shengying Yue | Xinyu Ma | Jing Qiao | Wei Xu | Wei Liu | Jiurong Liu | Meiting Zhao | Kostya Ostrikov | Zhihui Zeng
Source: Science Advances (article, 2024-03-13)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Metal-organic frameworks with fine-tuned interlayer spacing for microwave absorption Designing a functional, conductive metal-organic framework (cMOF) is highly desired. Substantial efforts have been dedicated to increasing the intralayer conjugation of the cMOFs, while less dedication has been made to tuning the interlayer charge transport of the metal-organic nanosheets for the controllable dielectric property. Here, we construct a series of conductive bimetallic organic frameworks of (Zn<sub>x</sub>Cu<sub>3-x</sub>) (hexahydroxytriphenylene)<sub>2</sub> (ZnCu-HHTP) to allow for fine-tuned interlayer spacing of two-dimensional frameworks, by adjusting the ratios of Zn and Cu metal ions. This approach for atomistic interlayer design allows for the finely control of the charge transport, band structure, and dielectric properties of the cMOF. As a result, Zn3Cu1-HHTP, with an optimal dielectric property, exhibits high-efficiency absorption in the gigahertz microwave range, achieving an ultra-strong reflection loss of -81.62 decibels. This study not only advances the understanding of the microstructure-function relationships in cMOFs but also offers a generic nanotechnology-based approach to achieving controllable interlayer spacing in MOFs for the targeted applications. Materials science ; Bimetallic strip ; Microwave ; Absorption (acoustics) ; Dielectric ; Electrical conductor ; Metal-organic framework ; Metal ; Optoelectronics ; Nanotechnology ; Microstructure ; Reflection (computer programming) ; Composite material ; Computer science ; Chemistry ; Telecommunications Electromagnetic wave absorption materials ; Metal-Organic Frameworks: Synthesis and Applications ; MXene and MAX Phase Materials