jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Lê Văn Cường | Hyeonseok Yoon
Source: International Journal of Molecular Sciences (article, 2024-01-26)
Field: Materials Science — Polymers and Plastics

Advances in the Use of Conducting Polymers for Healthcare Monitoring Conducting polymers (CPs) are an innovative class of materials recognized for their high flexibility and biocompatibility, making them an ideal choice for health monitoring applications that require flexibility. They are active in their design. Advances in fabrication technology allow the incorporation of CPs at various levels, by combining diverse CPs monomers with metal particles, 2D materials, carbon nanomaterials, and copolymers through the process of polymerization and mixing. This method produces materials with unique physicochemical properties and is highly customizable. In particular, the development of CPs with expanded surface area and high conductivity has significantly improved the performance of the sensors, providing high sensitivity and flexibility and expanding the range of available options. However, due to the morphological diversity of new materials and thus the variety of characteristics that can be synthesized by combining CPs and other types of functionalities, choosing the right combination for a sensor application is difficult but becomes important. This review focuses on classifying the role of CP and highlights recent advances in sensor design, especially in the field of healthcare monitoring. It also synthesizes the sensing mechanisms and evaluates the performance of CPs on electrochemical surfaces and in the sensor design. Furthermore, the applications that can be revolutionized by CPs will be discussed in detail. Flexibility (engineering) ; Nanotechnology ; Computer science ; Materials science ; Systems engineering ; Engineering Conducting polymers and applications ; Advanced Sensor and Energy Harvesting Materials ; Analytical Chemistry and Sensors
Authors: Mengyao Sun | Yanjun Chen | Xiaoqiang Fan | Dong Li | Jiaxin Song | Ke Yu | Zhen Zhao
Source: Nature Communications (article, 2024-11-15)
Field: Materials Science — Materials Chemistry

Electronic asymmetry of lattice oxygen sites in ZnO promotes the photocatalytic oxidative coupling of methane Photocatalytic oxidative coupling of methane with oxygen is promising to obtain valuable muti-carbon products, yet suffering low reactivity. Here, we apply cerium modifications on zinc oxide-supported gold catalysts based on the electronic asymmetry design of lattice oxygen to improve the coupling activity. The methane conversion rate exceeds 16000 μmol g<sup>-1</sup> h<sup>-1</sup> with muti-carbon selectivity of 94.9% and catalytic durability of 3 days, and it can increase to 34000 μmol g<sup>-1</sup> h<sup>-1</sup> under more thermal assistance, with a turnover frequency of 507 h<sup>-1</sup> for ethane and an apparent quantum efficiency of 33.7% at 350 nm. According to systematic characterizations and theoretical analysis, cerium dopants not only can boost the formation of reactive oxygen species but also intervene in the vivacity of lattice oxygen by manipulating metal-oxygen bond strength, thereby leading to favorable methyl desorption to form ethane and quick water release. This work provides insight into the rational design of efficient photocatalysts for aerobic methane-to-ethane conversion. Photocatalysis ; Methane ; Oxidative coupling of methane ; Oxygen ; Asymmetry ; Oxidative phosphorylation ; Lattice (music) ; Materials science ; Coupling (piping) ; Photochemistry ; Chemistry ; Physics ; Catalysis ; Biochemistry Catalytic Processes in Materials Science ; Catalysis and Oxidation Reactions ; Advanced Photocatalysis Techniques
Authors: Suman Kumari | Jasvir Dalal | Anand Kumar | Rishi Pal | Ritu Chahal | Anil Ohlan
Source: RSC Advances (article, 2024-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Enhanced microwave absorption properties of conducting polymer@graphene composite to counteract electromagnetic radiation pollution: green EMI shielding Conducting polymers have been thoroughly investigated and found to have extensive applications in the fields of microwave absorption and electromagnetic (EM) shielding owing to their distinctive characteristics and adaptability. In the present work, conducting polymer (PEDOT and polyaniline) and graphene composites were prepared <i>via</i> an <i>in situ</i> chemical polymerization technique. Further, these composite materials were characterized to determine their potential to address the issue of EM radiation pollution in the microwave frequency (12.4 GHz to 18 GHz). The PEDOT/graphene composites exhibited significant shielding effectiveness of up to 46.53 dB, achieving a green index (<i>g</i><sub>s</sub>) of 1.17. Also, absorption was observed to be the dominant shielding mechanism in all the samples owing to significant dielectric losses (<i>ε</i>''/<i>ε</i>' ≈ 1.9-3.1) and microwave conductivity (<i>σ</i><sub>s</sub> = 19.9-73.6 S m<sup>-1</sup>) in the samples at 18 GHz. Both dielectric loss and conduction loss occurred because of the strong interactions involving polarization, charge propagation, and the creation of conductive routes through the incorporation of graphene in the polymer matrix. These properties/shielding results indicate the potential of the composites to be used as lightweight EM shielding materials. These materials are suitable shield materials for electronic devices to protect them from harmful electromagnetic radiation, making them vital in various applications. Electromagnetic shielding ; Microwave ; EMI ; Materials science ; Graphene ; Electromagnetic interference ; Absorption (acoustics) ; Electromagnetic radiation ; Composite number ; Optoelectronics ; Composite material ; Nanotechnology ; Optics ; Physics ; Telecommunications ; Computer science Electromagnetic wave absorption materials ; Advanced Antenna and Metasurface Technologies
Authors: Fugang Hu | Ningfeng Gong | Jinsong Zeng | Pengfei Li | Tianguang Wang | Jinpeng Li | Bin Wang | Kefu Chen
Source: Advanced Functional Materials (article, 2024-04-30)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Aramid Nanofiber‐Based Artificial Nacre‐Supported Graphene/Silver Nanowire Nanopapers for Electromagnetic Interference Shielding and Thermal Management Abstract The development of next‐generation flexible electronics hinges on the creation of materials that are not only mechanically robust but also multifunctional. Herein, a novel approach is presented to fabricate an aramid nanofibers/cellulose nanocrystals/montmorillonite nanoplates (ACM) composite substrate with a robust “brick and mortar” microstructure. This substrate is seamlessly integrated with a high‐performance graphene/silver nanowire (G/Ag) composite conductive layer, resulting in the creation of ACM&amp;G/Ag nanopapers. The resulting nanopapers achieve remarkable tensile strength (δ c ) (543.82 MPa), tensile modulus (E c ) (10.93 GPa), and toughness (U c ) (95.18 MJ m −3 ). Notably, when normalized by weight, the specific tensile strength of these nanopapers surpasses that of commercial titanium alloy, reaching 399.87 MPa g −1 cm 3 , compared to titanium alloy's 257.00 MPa g −1 cm 3 . With a high conductivity of 1398.08 S cm −1 , ACM&amp;G/Ag nanopapers exhibit impressive electromagnetic interference shielding effectiveness (EMI SE) of 39.59 dB and EMI SE/t of 16359.26 dB cm −1 . Moreover, ACM&amp;G/Ag nanopapers exhibit exceptional thermal management performance, featuring high electrical heating temperature (280 °C), rapid response time (&lt;6 s), enduring heating stability, deicing capacity, and reliable heating performance even in humid environments. These results underscore the substantial potential of these high‐performance nanopapers in diverse applications such as wearable devices, electromagnetic compatibility, thermal management, human health, and aerospace. Materials science ; Composite material ; Electromagnetic shielding ; Ultimate tensile strength ; Nanofiber ; Graphene ; Composite number ; Nanocomposite ; Aramid ; Nanotechnology ; Fiber Electromagnetic wave absorption materials ; Advanced Sensor and Energy Harvesting Materials ; MXene and MAX Phase Materials
Authors: S. N. Yurchenko | A. Owens | Kyriaki Kefala | Jonathan Tennyson
Source: Monthly Notices of the Royal Astronomical Society (article, 2024-01-13)
Field: Chemistry — Spectroscopy

ExoMol line lists – LVII. High accuracy ro-vibrational line list for methane (CH4) ABSTRACT The MM ro-vibrational line list for methane (12CH4) is presented; MM covers wavelengths λ &amp;gt; 0.83 μm (wavenumbers up to 12 000 cm−1) and contains over 50 billion transitions between 9155 208 states with total angular momentum J ≤ 60. MM was generated through solution of the nuclear motion Schrödinger equation using variational program trove for an empirically derived potential energy surface (PES) and a new high-level ab initio dipole moment surface. The PES was constructed by fitting the ro-vibrational energies of CH4 to a set of highly accurate, experimentally derived energies. Molecular states are classified using the Td(M) symmetry group and are fully assigned with rotation and vibration quantum numbers. The MM line list is adapted to high-resolution applications by replacing the calculated ro-vibrational energies with the experimentally derived values where available, namely for 23 208 states with J ≤ 27 below 9986 cm−1. Doing so leads to over 1000 000 experimentally derived CH4 lines compared to approximately $330\, 000$ lines of 12CH4 in the HITRAN data base. The MM line list is shown to be more complete than the recent HITEMP methane line list. Methane spectra computed using MM across a broad range of temperatures and wavenumbers show excellent agreement with experiment. The MM line list supersedes the previous ExoMol methane line lists 10to10 and 30to10 both in terms of accuracy and coverage. Together with the pre-computed ExoMolOP molecular atmospheric opacity tables, it is now the recommended CH4 data set in the ExoMol data base (www.exomol.com). Physics ; Line (geometry) ; Methane ; Astrophysics ; Astronomy Spectroscopy and Laser Applications ; Atmospheric Ozone and Climate ; Atmospheric and Environmental Gas Dynamics
Authors: Jiatong Han | Donghui Xu | Yanyan Huang | Yuwei Hua | Xin Ding | Zhihao Lin | Jie Zhou | Lin Huan | Ge Chen | Jing Wang | Xiaomin Xu | Jia Liu | Guangyang Liu
Source: Chemical Engineering Journal (article, 2024-08-02)
Field: Chemistry — Inorganic Chemistry

Developing fine-tuned MOF membranes for highly efficient separation and adsorption of chemical pollutant in water Adsorption ; Separation (statistics) ; Membrane ; Pollutant ; Chemical engineering ; Chemistry ; Water pollutants ; Water treatment ; Environmental chemistry ; Environmental science ; Environmental engineering ; Organic chemistry ; Computer science ; Engineering Metal-Organic Frameworks: Synthesis and Applications ; Gas Sensing Nanomaterials and Sensors ; Extraction and Separation Processes
Authors: Akhil Ranjan Borah | Pallabi Hazarika | Runjun Duarah | Rajiv Goswami | Swapnali Hazarika
Source: ACS Omega (article, 2024-02-29)
Field: Materials Science — Biomaterials

Biodegradable Electrospun Membranes for Sustainable Industrial Applications [Image: see text] The escalating demand for sustainable industrial practices has driven the exploration of innovative materials, prominently exemplified by biodegradable electrospun membranes (BEMs). This review elucidates the pivotal role of these membranes across diverse industrial applications, addressing the imperative for sustainability. Furthermore, a comprehensive overview of biodegradable materials underscores their significance in electrospinning and their role in minimizing the environmental impact through biodegradability. The application of BEMs in various industrial sectors, including water treatment, food packaging, and biomedical applications, are extensively discussed. The environmental impact and sustainability analysis traverse the lifecycle of BEMs, evaluating their production to disposal and emphasizing reduced waste and resource conservation. This review demonstrates the research about BEMs toward an eco-conscious industrial landscape for a sustainable future. Sustainability ; Traverse ; Business ; Engineering ; Ecology Electrospun Nanofibers in Biomedical Applications ; Membrane Separation Technologies ; biodegradable polymer synthesis and properties
Authors: Mumtahina Mim | Khairul Habib | Sazratul Nayeem Farabi | Syed Awais Ali | MA Zaed | Mohammad Younas | R. Saidur
Source: ACS Omega (review, 2024-07-18)
Field: Materials Science — Materials Chemistry

MXene: A Roadmap to Sustainable Energy Management, Synthesis Routes, Stabilization, and Economic Assessment MXenes with their wide range of tunability and good surface chemistry provide unique and distinctive characteristics offering potential employment in various aspects of energy management applications. These high-performance materials have attracted considerable attention in recent decades due to their outstanding characteristics. In the literature, most of the work is related to specific methods for the preparation of MXenes. In this Review, we present a detailed discussion on the synthesis of MXenes through different etching routes involving acids, such as hydrochloric acid, hydrofluoric acid, and lithium fluoride, and non-acidic alkaline solution, electrochemical, and molten salt methods. Furthermore, a concise overview of the different structural, optical, electronic, and magnetic properties of MXenes is provided corresponding to their role in supporting high thermal, chemical, mechanical, environmental, and electrochemical stability. Additionally, the role of MXenes in maintaining the thermal management performance of photovoltaic thermal systems (PV/T), wearable light heaters, solar water desalination, batteries, and supercapacitors is also briefly discussed. A techno-economic and life cycle analysis of MXenes is provided to analyze their sustainability, scalability, and commercialization to facilitate a comprehensive array of energy management systems. Lastly, the technology readiness level of MXenes is defined, and future recommendations for MXenes are provided for their further utilization in niche applications. The present work strives to link the chemistry of MXenes to process economics for energy management applications. MXenes ; Nanotechnology ; Supercapacitor ; Sustainability ; Materials science ; Computer science ; Chemistry ; Electrochemistry ; Ecology MXene and MAX Phase Materials ; Advanced Photocatalysis Techniques ; Supercapacitor Materials and Fabrication
Authors: Yao Yang | Jihan Zhou | Zipeng Zhao | Geng Sun | Saman Moniri | Colin Ophus | Yongsoo Yang | Ziyang Wei | Yakun Yuan | Cheng Zhu | Yang Liu | Qiang Sun | Qingying Jia | Hendrik Heinz | Jim Ciston | Peter Ercius | Philippe Sautet | Yu Huang | Jianwei Miao
Source: Nature Catalysis (article, 2024-07-08)
Field: Materials Science — Materials Chemistry

Atomic-scale identification of active sites of oxygen reduction nanocatalysts Nanomaterial-based catalyst ; Identification (biology) ; Atomic units ; Reduction (mathematics) ; Scale (ratio) ; Active oxygen ; Oxygen ; Oxygen reduction reaction ; Environmental science ; Environmental chemistry ; Chemistry ; Materials science ; Chemical engineering ; Nanotechnology ; Biology ; Physical chemistry ; Engineering ; Physics ; Ecology ; Mathematics ; Nanoparticle Machine Learning in Materials Science ; Electron and X-Ray Spectroscopy Techniques ; Electrocatalysts for Energy Conversion
Authors: He Li | Zechen Tang | Jingheng Fu | Wen-Han Dong | Nianlong Zou | Xiaoxun Gong | Wenhui Duan | Yong Xu
Source: Physical Review Letters (preprint, 2024-02-28)
Field: Materials Science — Materials Chemistry

Deep-Learning Density Functional Perturbation Theory Calculating perturbation response properties of materials from first principles provides a vital link between theory and experiment, but is bottlenecked by the high computational cost. Here, a general framework is proposed to perform density functional perturbation theory (DFPT) calculations by neural networks, greatly improving the computational efficiency. Automatic differentiation is applied on neural networks, facilitating accurate computation of derivatives. High efficiency and good accuracy of the approach are demonstrated by studying electron-phonon coupling and related physical quantities. This work brings deep-learning density functional theory and DFPT into a unified framework, creating opportunities for developing ab initio artificial intelligence. Perturbation theory (quantum mechanics) ; Computation ; Density functional theory ; Computer science ; Artificial neural network ; Functional theory ; Perturbation (astronomy) ; Ab initio ; Artificial intelligence ; Statistical physics ; Theoretical computer science ; Physics ; Algorithm ; Quantum mechanics Machine Learning in Materials Science ; Electronic and Structural Properties of Oxides ; Semiconductor materials and devices
Authors: Junkil Park | Honghui Kim | Yeonghun Kang | Yunsung Lim | Jihan Kim
Source: JACS Au (review, 2024-09-12)
Field: Materials Science — Materials Chemistry

From Data to Discovery: Recent Trends of Machine Learning in Metal–Organic Frameworks Renowned for their high porosity and structural diversity, metal-organic frameworks (MOFs) are a promising class of materials for a wide range of applications. In recent decades, with the development of large-scale databases, the MOF community has witnessed innovations brought by data-driven machine learning methods, which have enabled a deeper understanding of the chemical nature of MOFs and led to the development of novel structures. Notably, machine learning is continuously and rapidly advancing as new methodologies, architectures, and data representations are actively being investigated, and their implementation in materials discovery is vigorously pursued. Under these circumstances, it is important to closely monitor recent research trends and identify the technologies that are being introduced. In this Perspective, we focus on emerging trends of machine learning within the field of MOFs, the challenges they face, and the future directions of their development. Data science ; Computer science ; Artificial intelligence Machine Learning in Materials Science ; Computational Drug Discovery Methods ; X-ray Diffraction in Crystallography
Authors: Omar Abou El Kheir | Leo H. Bonati | Michele Parrinello | Marco Bernasconi
Source: npj Computational Materials (article, 2024-02-10)
Field: Materials Science — Materials Chemistry

Unraveling the crystallization kinetics of the Ge2Sb2Te5 phase change compound with a machine-learned interatomic potential Abstract The phase change compound Ge 2 Sb 2 Te 5 (GST225) is exploited in advanced non-volatile electronic memories and in neuromorphic devices which both rely on a fast and reversible transition between the crystalline and amorphous phases induced by Joule heating. The crystallization kinetics of GST225 is a key functional feature for the operation of these devices. We report here on the development of a machine-learned interatomic potential for GST225 that allowed us to perform large scale molecular dynamics simulations (over 10,000 atoms for over 100 ns) to uncover the details of the crystallization kinetics in a wide range of temperatures of interest for the programming of the devices. The potential is obtained by fitting with a deep neural network (NN) scheme a large quantum-mechanical database generated within density functional theory. The availability of a highly efficient and yet highly accurate NN potential opens the possibility to simulate phase change materials at the length and time scales of the real devices. Crystallization ; Germanium compounds ; Kinetics ; Phase change ; Materials science ; Phase (matter) ; Chemical physics ; Crystallography ; Thermodynamics ; Chemistry ; Physics ; Optoelectronics ; Germanium ; Silicon ; Classical mechanics Phase-change materials and chalcogenides ; Machine Learning in Materials Science ; Chalcogenide Semiconductor Thin Films
Authors: Dimitar Georgiev | Simon Vilms Pedersen | Ruoxiao Xie | A. Fernandez-Galiana | Molly M. Stevens | Mauricio Barahona
Source: Analytical Chemistry (article, 2024-05-15)
Field: Chemistry — Analytical Chemistry

RamanSPy: An Open-Source Python Package for Integrative Raman Spectroscopy Data Analysis Raman spectroscopy is a nondestructive and label-free chemical analysis technique, which plays a key role in the analysis and discovery cycle of various branches of science. Nonetheless, progress in Raman spectroscopic analysis is still impeded by the lack of software, methodological and data standardization, and the ensuing fragmentation and lack of reproducibility of analysis workflows thereof. To address these issues, we introduce <i>RamanSPy</i>, an open-source Python package for Raman spectroscopic research and analysis. <i>RamanSPy</i> provides a comprehensive library of tools for spectroscopic analysis that supports day-to-day tasks, integrative analyses, the development of methods and protocols, and the integration of advanced data analytics. <i>RamanSPy</i> is modular and open source, not tied to a particular technology or data format, and can be readily interfaced with the burgeoning ecosystem for data science, statistical analysis, and machine learning in Python. <i>RamanSPy</i> is hosted at https://github.com/barahona-research-group/RamanSPy, supplemented with extended online documentation, available at https://ramanspy.readthedocs.io, that includes tutorials, example applications, and details about the real-world research applications presented in this paper. Python (programming language) ; Workflow ; Documentation ; Computer science ; Standardization ; Raman spectroscopy ; Data science ; Data analysis ; Software ; Analytics ; Software engineering ; Open source ; World Wide Web ; Chemistry ; Programming language ; Database ; Data mining ; Operating system Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Advanced Chemical Sensor Technologies