jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Xin Sun | Jindi Yang | Xiangkang Zeng | Lijun Guo | Chuanbiao Bie | Zhuyuan Wang | Kaige Sun | Aloka Kumar Sahu | Mike Tebyetekerwa | Thomas E. Rufford | Xiwang Zhang
Source: Angewandte Chemie International Edition (review, 2024-09-23)
Field: Materials Science — Materials Chemistry

Pairing Oxygen Reduction and Water Oxidation for Dual‐Pathway H<sub>2</sub>O<sub>2</sub> Production Hydrogen peroxide (H<sub>2</sub>O<sub>2</sub>) is a crucial chemical applied in various industry sectors. However, the current industrial anthraquinone process for H<sub>2</sub>O<sub>2</sub> synthesis is carbon-intensive. With sunlight and renewable electricity as energy inputs, photocatalysis and electrocatalysis have great potential for green H<sub>2</sub>O<sub>2</sub> production from oxygen (O<sub>2</sub>) and water (H<sub>2</sub>O). Herein, we review the advances in pairing two-electron O<sub>2</sub> reduction and two-electron H<sub>2</sub>O oxidation reactions for dual-pathway H<sub>2</sub>O<sub>2</sub> synthesis. The basic principles, paired redox reactions, and catalytic device configurations are introduced initially. Aligning with the energy input, the latest photocatalysts, electrocatalysts, and photo-electrocatalysts for dual-pathway H<sub>2</sub>O<sub>2</sub> production are discussed afterward. Finally, we outlook the research opportunities in the future. This minireview aims to provide insights and guidelines for the broad community who are interested in catalyst design and innovative technology for on-site H<sub>2</sub>O<sub>2</sub> synthesis. Pairing ; Dual (grammatical number) ; Reduction (mathematics) ; Production (economics) ; Oxygen ; Chemistry ; Mathematics ; Art ; Physics ; Economics ; Organic chemistry Catalytic Processes in Materials Science ; Water Quality Monitoring and Analysis ; Advanced oxidation water treatment
Authors: Yuting Li | Qifei Guo | Zhao Ding | Han Jiang | Hang Yang | Wenjia Du | Yang Zheng | Kaifu Huo | Leon L. Shaw
Source: Chemical Engineering Journal (article, 2024-02-15)
Field: Chemistry — Inorganic Chemistry

MOFs-Based Materials for Solid-State Hydrogen Storage: Strategies and Perspectives Hydrogen storage ; Nanotechnology ; Metal-organic framework ; Physisorption ; Materials science ; Scope (computer science) ; Hydrogen ; Process engineering ; Adsorption ; Biochemical engineering ; Computer science ; Chemistry ; Engineering Metal-Organic Frameworks: Synthesis and Applications ; Hydrogen Storage and Materials ; Carbon dioxide utilization in catalysis
Authors: Vimukthi Dananjaya | Sathish Marimuthu | Chunhui Yang | Andrews Nirmala Grace | Chamil Abeykoon
Source: Progress in Materials Science (article, 2024-03-12)
Field: Materials Science — Materials Chemistry

Synthesis, properties, applications, 3D printing and machine learning of graphene quantum dots in polymer nanocomposites This comprehensive review discusses the recent progress in synthesis, properties, applications, 3D printing and machine learning of graphene quantum dots (GQDs) in polymer composites. It explores various synthesis methods, highlighting the size control and surface functionalization of GQDs. The unique electronic structure, tunable bandgap, and optical properties of GQDs are examined. Strategies for incorporating GQDs into polymer matrices and their effects on mechanical, electrical, thermal, and optical properties are discussed. Applications of GQD-based polymer composites in optoelectronics, energy storage, sensors, and biomedical devices are also reviewed. The challenges and future prospects of GQD-based composites are also explored, aiming to provide researchers with a comprehensive understanding of further advancements that should be possible in related fields. Moreover, this article explores new developments in 3D printing technology that can benefit from the promise of composite materials loaded with graphene quantum dots, a promising class of materials with a wide range of potential applications. In addition to discussing the synthesis and properties of GQDs, this review delves into the emerging role of machine learning techniques in optimising GQD-polymer composite materials. Furthermore, it explores how artificial intelligence and data-driven approaches are revolutionising the design and characterisation of these nanocomposites, enabling researchers to navigate the vast parameter space efficiently to achieve the desired properties. The overall aim of this review is to build up a common platform connecting individual subsections of synthesis, properties, applications, 3D printing and machine learning of GQD in polymer nanocomposites together to generate a comprehensive review for the readers. Materials science ; Quantum dot ; Nanotechnology ; Graphene ; Nanocomposite ; Graphene quantum dot ; Surface modification ; Polymer nanocomposite ; 3D printing ; Polymer ; Mechanical engineering ; Composite material ; Engineering Carbon and Quantum Dots Applications ; Luminescence and Fluorescent Materials ; Quantum Dots Synthesis And Properties
Authors: Bin Ouyang | Yan Zeng
Source: Nature Communications (article, 2024-02-01)
Field: Materials Science — Materials Chemistry

The rise of high-entropy battery materials The emergence of high-entropy materials has inspired the exploration of novel materials in diverse technologies. In electrochemical energy storage, high-entropy design has shown advantageous impacts on battery materials such as suppressing undesired short-range order, frustrating energy landscape, decreasing volumetric change and reducing the reliance on critical metals. This comment addresses the definition and potential improper use of the term “high entropy” in the context of battery materials design, highlights the unique properties of high-entropy materials in battery applications, and outlines the remaining challenges in the synthesis, characterization, and computational modeling of high-entropy battery materials. Electrochemical energy storage ; Entropy (arrow of time) ; Computer science ; Battery (electricity) ; High entropy alloys ; Energy storage ; Materials science ; Nanotechnology ; Electrochemistry ; Thermodynamics ; Chemistry ; Physics ; Metallurgy ; Electrode ; Physical chemistry Thermal Expansion and Ionic Conductivity ; Hydrogen Storage and Materials ; Advancements in Battery Materials
Authors: Máté Czagány | Szabolcs Hompoth | Anup Kumar Keshri | Niranjan Pandit | Imre Galambos | Zoltán Gácsi | Péter Baumli
Source: Materials (article, 2024-02-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Supercapacitors: An Efficient Way for Energy Storage Application To date, batteries are the most widely used energy storage devices, fulfilling the requirements of different industrial and consumer applications. However, the efficient use of renewable energy sources and the emergence of wearable electronics has created the need for new requirements such as high-speed energy delivery, faster charge–discharge speeds, longer lifetimes, and reusability. This leads to the need for supercapacitors, which can be a good complement to batteries. However, one of their drawbacks is their lower energy storage capability, which has triggered worldwide research efforts to increase their energy density. With the introduction of novel nanostructured materials, hierarchical pore structures, hybrid devices combining these materials, and unconventional electrolytes, significant developments have been reported in the literature. This paper reviews the short history of the evolution of supercapacitors and the fundamental aspects of supercapacitors, positioning them among other energy-storage systems. The main electrochemical measurement methods used to characterize their energy storage features are discussed with a focus on their specific characteristics and limitations. High importance is given to the integral components of the supercapacitor cell, particularly to the electrode materials and the different types of electrolytes that determine the performance of the supercapacitor device (e.g., storage capability, power output, cycling stability). Current directions in the development of electrode materials, including carbonaceous forms, transition metal-based compounds, conducting polymers, and novel materials are discussed. The synergy between the electrode material and the current collector is a key factor, as well as the fine-tuning of the electrode material and electrolyte. Supercapacitor ; Energy storage ; Materials science ; Nanotechnology ; Renewable energy ; Electronics ; Computer science ; Capacitance ; Electrode ; Process engineering ; Electrical engineering ; Power (physics) ; Engineering Supercapacitor Materials and Fabrication ; Conducting polymers and applications ; Advanced battery technologies research
Authors: Yongyao Yin | Qiang Jiang | Hongbo Wang | Jianghong Liu | Yiyang Xie | Qiuhua Wang | Yongtian Wang | Lingling Huang
Source: Advanced Materials (article, 2024-02-19)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Multi‐Dimensional Multiplexed Metasurface Holography by Inverse Design Multi-dimensional multiplexed metasurface holography extends holographic information capacity and promises revolutionary advancements for vivid imaging, information storage, and encryption. However, achieving multifunctional metasurface holography by forward design method is still difficult because it relies heavily on Jones matrix engineering, which places high demands on physical knowledge and processing technology. To break these limitations and simplify the design process, here, an end-to-end inverse design framework is proposed. By directly linking the metasurface to the reconstructed images and employing a loss function to guide the update of metasurface, the calculation of hologram can be omitted; thus, greatly simplifying the design process. In addition, the requirements on the completeness of meta-library can also be significantly reduced, allowing multi-channel hologram to be achieved using meta-atoms with only two degrees of freedom, which is very friendly to processing. By exploiting the proposed method, metasurface hologram containing up to 12 channels of multi-wavelength, multi-plane, and multi-polarization is designed and experimentally demonstrated, which exhibits the state-of-the-art information multiplexing capacity of the metasurface composed of simple meta-atoms. This method is conducive to promoting the intelligent design of multifunctional meta-devices, and it is expected to eventually accelerate the application of meta-devices in colorful display, imaging, storage and other fields. Materials science ; Holography ; Inverse ; Multiplexing ; Optics ; Inverse problem ; Optoelectronics ; Physics ; Computer science ; Geometry ; Telecommunications Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: Bibhu Prasad Nanda | Priyanka Rani | Priyanka Paul | Aman | Subrahmanya S. Ganti | Rohit Bhatia
Source: Journal of Pharmaceutical Analysis (review, 2024-02-28)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Recent trends and impact of localized surface plasmon resonance (LSPR) and surface-enhanced Raman spectroscopy (SERS) in modern analysis An optical biosensor is a specialized analytical device that utilizes the principles of optics and light in bimolecular processes. Localized surface plasmon resonance (LSPR) is a phenomenon in the realm of nanophotonics that occurs when metallic nanoparticles (NPs) or nanostructures interact with incident light. Conversely, surface-enhanced Raman spectroscopy (SERS) is an influential analytical technique based on Raman scattering, wherein it amplifies the Raman signals of molecules when they are situated near specific and specially designed nanostructures. A detailed exploration of the recent ground-breaking developments in optical biosensors employing LSPR and SERS technologies has been thoroughly discussed along with their underlying principles and the working mechanisms. A biosensor chip has been created, featuring a high-density deposition of gold nanoparticles (AuNPs) under varying ligand concentration and reaction duration on the substrate. An ordinary description, along with a visual illustration, has been thoroughly provided for concepts such as a sensogram, refractive index shift, surface plasmon resonance (SPR), and the evanescent field, Rayleigh scattering, Raman scattering, as well as the electromagnetic enhancement and chemical enhancement. LSPR and SERS both have advantages and disadvantages, but widely used SERS has some advantages over LSPR, like chemical specificity, high sensitivity, multiplexing, and versatility in different fields. This review confirms and elucidates the significance of different disease biomarker identification. LSPR and SERS both play a vital role in the detection of various types of cancer, such as cervical cancer, ovarian cancer, endometrial cancer, prostate cancer, colorectal cancer, and brain tumors. This proposed optical biosensor offers potential applications for early diagnosis and monitoring of viral disease, bacterial infectious diseases, fungal diseases, diabetes, and cardiac disease biosensing. LSPR and SERS provide a new direction for environmental monitoring, food safety, refining impurities from water samples, and lead detection. The understanding of these biosensors is still limited and challenging. Chemistry ; Surface plasmon resonance ; Surface-enhanced Raman spectroscopy ; Raman spectroscopy ; Resonance Raman spectroscopy ; Plasmon ; Spectroscopy ; Nanotechnology ; Surface (topology) ; Surface plasmon ; Resonance (particle physics) ; Raman scattering ; Optoelectronics ; Nanoparticle ; Optics ; Atomic physics ; Materials science Gold and Silver Nanoparticles Synthesis and Applications ; Spectroscopy Techniques in Biomedical and Chemical Research ; Advanced biosensing and bioanalysis techniques
Authors: Yuming Jiang | Rex Devasahayam Arokia Balaya | Dina Schuster | Benjamin A. Neely | Germán L. Rosano | Norbert Volkmar | Amanda Momenzadeh | Trenton M. Peters-Clarke | Susan Egbert | Simion Kreimer | Emma H. Doud | Oliver M. Crook | Amit Kumar Yadav | Muralidharan Vanuopadath | Adrian D. Hegeman | Martín L. Mayta | Anna G. Duboff | Nicholas M. Riley | Robert L. Moritz | Jesse G. Meyer
Source: ACS Measurement Science Au (review, 2024-06-04)
Field: Chemistry — Spectroscopy

Comprehensive Overview of Bottom-Up Proteomics Using Mass Spectrometry Proteomics is the large scale study of protein structure and function from biological systems through protein identification and quantification. "Shotgun proteomics" or "bottom-up proteomics" is the prevailing strategy, in which proteins are hydrolyzed into peptides that are analyzed by mass spectrometry. Proteomics studies can be applied to diverse studies ranging from simple protein identification to studies of proteoforms, protein-protein interactions, protein structural alterations, absolute and relative protein quantification, post-translational modifications, and protein stability. To enable this range of different experiments, there are diverse strategies for proteome analysis. The nuances of how proteomic workflows differ may be challenging to understand for new practitioners. Here, we provide a comprehensive overview of different proteomics methods. We cover from biochemistry basics and protein extraction to biological interpretation and orthogonal validation. We expect this Review will serve as a handbook for researchers who are new to the field of bottom-up proteomics. Mass spectrometry ; Proteomics ; Top-down proteomics ; Chemistry ; Computer science ; Chromatography ; Protein mass spectrometry ; Tandem mass spectrometry Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Protein purification and stability
Authors: Helen Park | Hongtao He | Yan Xu | Xu Liu | Nigel S. Scrutton | Guo‐Qiang Chen
Source: Biotechnology Advances (article, 2024-01-23)
Field: Materials Science — Biomaterials

PHA is not just a bioplastic! Bioplastic ; Polyhydroxyalkanoates ; Biochemical engineering ; Supply chain ; Business ; Nanotechnology ; Materials science ; Waste management ; Engineering biodegradable polymer synthesis and properties ; Microplastics and Plastic Pollution ; Additive Manufacturing and 3D Printing Technologies
Authors: Jesse B. Hopkins
Source: Journal of Applied Crystallography (article, 2024-01-15)
Field: Materials Science — Materials Chemistry

<i>BioXTAS RAW 2</i> : new developments for a free open-source program for small-angle scattering data reduction and analysis <i>BioXTAS RAW</i> is a free open-source program for reduction, analysis and modelling of biological small-angle scattering data. Here, the new developments in <i>RAW</i> version 2 are described. These include improved data reduction using <i>pyFAI</i>; updated automated Guinier fitting and <i>D</i> <sub>max</sub> finding algorithms; automated series (<i>e.g.</i> size-exclusion chromatography coupled small-angle X-ray scattering or SEC-SAXS) buffer- and sample-region finding algorithms; linear and integral baseline correction for series; deconvolution of series data using regularized alternating least squares (<i>REGALS</i>); creation of electron-density reconstructions using electron density via solution scattering (<i>DENSS</i>); a comparison window showing residuals, ratios and statistical comparisons between profiles; and generation of PDF reports with summary plots and tables for all analysis. Furthermore, there is now a <i>RAW</i> API, which can be used without the graphical user interface (GUI), providing full access to all of the functionality found in the GUI. In addition to these new capabilities, <i>RAW</i> has undergone significant technical updates, such as adding Python 3 compatibility, and has entirely new documentation available both online and in the program. Python (programming language) ; Deconvolution ; Scattering ; Raw data ; Data reduction ; Graphical user interface ; Computer science ; Reduction (mathematics) ; Computational science ; Small-angle scattering ; Small-angle X-ray scattering ; Mac OS ; Algorithm ; Software ; Data mining ; Optics ; Mathematics ; Physics ; Geometry Enzyme Structure and Function ; Protein Structure and Dynamics ; X-ray Spectroscopy and Fluorescence Analysis
Authors: Daying Zheng | Kaijie Liu | Zeshu Zhang | Qi Fu | Mengyao Bian | Xinyu Han | Xin Shen | Xiaohui Chen | Haijiao Xie | Xiao Wang | Xiangguang Yang | Yibo Zhang | Shuyan Song
Source: Nature Communications (article, 2024-08-06)
Field: Materials Science — Materials Chemistry

Essential features of weak current for excellent enhancement of NOx reduction over monoatomic V-based catalyst Human society is facing increasingly serious problems of environmental pollution and energy shortage, and up to now, achieving high NH<sub>3</sub>-SCR activity at ultra-low temperatures (<150 °C) remains challenging for the V-based catalysts with V content below 2%. In this study, the monoatomic V-based catalyst under the weak current-assisted strategy can completely convert NO<sub>x</sub> into N<sub>2</sub> at ultra-low temperature with V content of 1.36%, which shows the preeminent turnover frequencies (TOF<sub>145 °C</sub> = 1.97×10<sup>-3 </sup>s<sup>-1</sup>). The improvement of catalytic performance is mainly attributed to the enhancement catalysis of weak current (ECWC) rather than electric field, which significantly reduce the energy consumption of the catalytic system by more than 90%. The further mechanism research for the ECWC based on a series of weak current-assisted characterization means and DFT calculations confirms that migrated electrons mainly concentrate around the V single atoms and increase the proportion of antibonding orbitals, which make the V-O chemical bond weaker (electron scissors effect) and thus accelerate oxygen circulation. The novel current-assisted catalysis in the present work can potentially apply to other environmental and energy fields. Catalysis ; Antibonding molecular orbital ; Selective catalytic reduction ; NOx ; Chemistry ; Monatomic gas ; Current (fluid) ; Chemical physics ; Electron ; Nanotechnology ; Materials science ; Chemical engineering ; Atomic orbital ; Physics ; Physical chemistry ; Thermodynamics ; Organic chemistry Catalytic Processes in Materials Science ; Ammonia Synthesis and Nitrogen Reduction ; Advanced Photocatalysis Techniques
Authors: Bohayra Mortazavi
Source: Advanced Energy Materials (article, 2024-12-10)
Field: Materials Science — Materials Chemistry

Recent Advances in Machine Learning‐Assisted Multiscale Design of Energy Materials Abstract This review highlights recent advances in machine learning (ML)‐assisted design of energy materials. Initially, ML algorithms were successfully applied to screen materials databases by establishing complex relationships between atomic structures and their resulting properties, thus accelerating the identification of candidates with desirable properties. Recently, the development of highly accurate ML interatomic potentials and generative models has not only improved the robust prediction of physical properties, but also significantly accelerated the discovery of materials. In the past couple of years, ML methods have enabled high‐precision first‐principles predictions of electronic and optical properties for large systems, providing unprecedented opportunities in materials science. Furthermore, ML‐assisted microstructure reconstruction and physics‐informed solutions for partial differential equations have facilitated the understanding of microstructure–property relationships. Most recently, the seamless integration of various ML platforms has led to the emergence of autonomous laboratories that combine quantum mechanical calculations, large language models, and experimental validations, fundamentally transforming the traditional approach to novel materials synthesis. While highlighting the aforementioned recent advances, existing challenges are also discussed. Ultimately, ML is expected to fully integrate atomic‐scale simulations, reverse engineering, process optimization, and device fabrication, empowering autonomous and generative energy system design. This will drive transformative innovations in energy conversion, storage, and harvesting technologies. Generative grammar ; Transformative learning ; Computer science ; Process (computing) ; Nanotechnology ; Materials science ; Scale (ratio) ; Artificial intelligence ; Systems engineering ; Industrial engineering ; Mechanical engineering ; Physics Machine Learning in Materials Science ; Electronic and Structural Properties of Oxides ; X-ray Diffraction in Crystallography