jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Jianying Zhao | Xiaoguang Zhang | Feihua Yang | Yonghong Ai | You-Sheng Chen | Dean Pan
Source: ACS Omega (article, 2024-01-29)
Field: Materials Science — Materials Chemistry

Strategy and Technical Progress of Recycling of Spent Vanadium–Titanium-Based Selective Catalytic Reduction Catalysts Selective catalytic reduction denitration technology, abbreviated as SCR, is essential for the removal of nitrogen oxide from the flue gas of coal-fired power stations and has been widely used. Due to the strong demand for energy and the requirements for environmental protection, a large amount of SCR catalyst waste is produced. The spent SCR catalyst contains high-grade valuable metals, and proper disposal or treatment of the SCR catalyst can protect the environment and realize resource recycling. This review focuses on the two main routes of regeneration and recycling of spent vanadium-titanium SCR catalysts that are currently most widely commercially used and summarizes in detail the technologies of recycling, high-efficiency recycling, and recycling of valuable components of spent vanadium-titanium SCR catalysts. This review also discusses in depth the future development direction of recycling spent vanadium-titanium SCR catalysts. It provides a reference for promoting recycling, which is crucial for resource recovery and green and low-carbon development. Vanadium ; Selective catalytic reduction ; Waste management ; Catalysis ; Flue gas ; Titanium ; Environmental science ; Materials science ; Chemistry ; Engineering ; Metallurgy Catalytic Processes in Materials Science ; Extraction and Separation Processes ; Advancements in Battery Materials
Authors: Bankole I. Oladapo | Mattew A. Olawumi | Francis T. Omigbodun
Source: Batteries (article, 2024-10-30)
Field: Materials Science — Biomaterials

Revolutionizing Battery Longevity by Optimising Magnesium Alloy Anodes Performance This research explores the enhancement of electrochemical performance in magnesium batteries by optimising magnesium alloy anodes, explicitly focusing on Mg-Al and Mg-Ag alloys. The study’s objective was to determine the impact of alloy composition on anode voltage stability and overall battery efficiency, particularly under extended cycling conditions. The research assessed the anodes’ voltage behaviour and internal resistance across magnesium bis(trifluoromethanesulfonyl)imide (Mg(TFSI)2) electrolyte formulations using a systematic setup involving cyclic voltammetry on the anode and electrochemical impedance spectroscopy. The Mg-Al alloy demonstrated superior performance, with minimal voltage drop and lower resistance increase than the Mg-Ag alloy. The results showed that the Mg-Al alloy maintained over 85% energy efficiency after 100 cycles, significantly outperforming the Mg-Ag alloy, which exhibited increased degradation and efficiency reduction to approximately 80%. These findings confirm that incorporating aluminium into magnesium anodes stabilises the anode voltage and enhances the overall battery efficiency by mitigating degradation mechanisms. Consequently, the Mg-Al alloy is identified as an up-and-coming candidate for use in advanced battery technologies, offering energy density and cycle life improvements. This study lays the groundwork for future research to refine magnesium alloy compositions further to boost battery performance. Longevity ; Battery (electricity) ; Anode ; Magnesium ; Alloy ; Materials science ; Metallurgy ; Computer science ; Medicine ; Power (physics) ; Chemistry ; Gerontology ; Electrode Magnesium Alloys: Properties and Applications ; Advancements in Battery Materials ; Hydrogen Storage and Materials
Authors: Oliver Schilter | Philippe Schwaller | Teodoro Laino
Source: Green Chemistry (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Balancing computational chemistry's potential with its environmental impact Digital chemistry methods accelerated discoveries of sustainable processes but require assessing and minimizing their carbon footprint caused by the required computing power. Carbon footprint ; Chemistry ; Biochemical engineering ; Computer science ; Green chemistry ; Environmental chemistry ; Nanotechnology ; Organic chemistry ; Greenhouse gas ; Ecology ; Catalysis ; Engineering ; Materials science ; Reaction mechanism Machine Learning in Materials Science ; Green IT and Sustainability ; Chemistry and Chemical Engineering
Authors: Rafał Roszak | Louis Gadina | Agnieszka Wołos | Ahmad Makkawi | Barbara Mikulak-Klucznik | Yasemin Bilgi | Karol Molga | Patrycja Gołębiowska | Oskar Popik | Tomasz Klucznik | Sara Szymkuć | Martyna Moskal | Sebastian Baś | Rafał Frydrych | Jacek Młynarski | Olena Vakuliuk | Daniel T. Gryko | Bartosz A. Grzybowski
Source: Nature Communications (article, 2024-11-27)
Field: Chemistry — Organic Chemistry

Systematic, computational discovery of multicomponent and one-pot reactions Discovery of new types of reactions is essential to organic chemistry because it expands the scope of accessible molecular scaffolds and can enable more economical syntheses of existing structures. In this context, the so-called multicomponent reactions, MCRs, are of particular interest because they can build complex scaffolds from multiple starting materials in just one step, without purification of intermediates. However, for over a century of active research, MCRs have been discovered rather than designed, and their number remains limited to only several hundred. This work demonstrates that computers taught the essential knowledge of reaction mechanisms and rules of physical-organic chemistry can design - completely autonomously and in large numbers - mechanistically distinct MCRs. Moreover, when supplemented by models to approximate kinetic rates, the algorithm can predict reaction yields and identify reactions that have potential for organocatalysis. These predictions are validated by experiments spanning different modes of reactivity and diverse product scaffolds. Context (archaeology) ; Organic synthesis ; Computer science ; Chemistry ; Reactivity (psychology) ; Scope (computer science) ; Organic reaction ; Biochemical engineering ; Combinatorial chemistry ; Nanotechnology ; Catalysis ; Organic chemistry ; Materials science Multicomponent Synthesis of Heterocycles ; Chemical Synthesis and Analysis ; Machine Learning in Materials Science
Authors: Jung Hwan Park | Srinivas Pattipaka | Geon‐Tae Hwang | Minok Park | Yu Mi Woo | Young Bin Kim | Han Eol Lee | Chang Kyu Jeong | Tiandong Zhang | Yuho Min | Kwi‐Il Park | Keon Jae Lee | Jungho Ryu
Source: Nano-Micro Letters (review, 2024-08-26)
Field: Materials Science — Polymers and Plastics

Light–Material Interactions Using Laser and Flash Sources for Energy Conversion and Storage Applications This review provides a comprehensive overview of the progress in light-material interactions (LMIs), focusing on lasers and flash lights for energy conversion and storage applications. We discuss intricate LMI parameters such as light sources, interaction time, and fluence to elucidate their importance in material processing. In addition, this study covers various light-induced photothermal and photochemical processes ranging from melting, crystallization, and ablation to doping and synthesis, which are essential for developing energy materials and devices. Finally, we present extensive energy conversion and storage applications demonstrated by LMI technologies, including energy harvesters, sensors, capacitors, and batteries. Despite the several challenges associated with LMIs, such as complex mechanisms, and high-degrees of freedom, we believe that substantial contributions and potential for the commercialization of future energy systems can be achieved by advancing optical technologies through comprehensive academic research and multidisciplinary collaborations. Flash (photography) ; Energy storage ; Energy transformation ; Commercialization ; Materials science ; Nanotechnology ; Laser ; Computer data storage ; Optical storage ; Computer science ; Light energy ; Process engineering ; Engineering physics ; Optoelectronics ; Engineering ; Physics ; Optics ; Computer hardware Transition Metal Oxide Nanomaterials ; Gas Sensing Nanomaterials and Sensors ; Perovskite Materials and Applications
Authors: Chao Tan | Haijuan Wu | Lei Yang | Zegao Wang
Source: Advanced Materials Technologies (article, 2024-03-08)
Field: Materials Science — Materials Chemistry

Cutting Edge High‐Throughput Synthesis and Characterization Techniques in Combinatorial Materials Science Abstract The Materials Genome Initiative is expected to accelerate the materials discovery and design by fundamentally changing the trial‐and‐error research paradigm. However, mass data from high‐throughput experiments is still essential for the revelation of rules and verification of theories. In fact, the development of combinatorial materials science is always on the strength of the upgrade and evolution of high‐throughput techniques in each stage, especially high‐throughput materials synthesis and characterization. Herein, this review summarizes the high‐throughput synthesis methods for combinatorial materials libraries, especially the co‐deposition and masking techniques of thin‐film fabrication; and details the high‐throughput characterization methods for specific material properties and typical material categories, which comes down to the spectroscopy and microscopy techniques. It is considered that high‐throughput concepts will be the predominant lab experimentation in the future, along with advanced experimental techniques and convenient data processing procedures. Before that, more cooperation between multiple researchers from different fields should be conducted to complete the combinatorial materials research, since the high‐throughput technology covers multiple disciplines with a huge span. Throughput ; Characterization (materials science) ; Computer science ; Combinatorial synthesis ; Upgrade ; Nanotechnology ; Biochemical engineering ; Computer architecture ; Materials science ; Engineering ; Chemistry ; Combinatorial chemistry Electronic and Structural Properties of Oxides ; Machine Learning in Materials Science ; Quantum Dots Synthesis And Properties
Authors: Flynn Walsh | Mingwei Zhang | Robert O. Ritchie | Mark Asta | Andrew M. Minor
Source: Science Advances (article, 2024-08-02)
Field: Materials Science — Materials Chemistry

Multiple origins of extra electron diffractions in fcc metals Diffuse intensities in the electron diffraction patterns of concentrated face-centered cubic solid solutions have been widely attributed to chemical short-range order, although this connection has been recently questioned. This article explores the many nonordering origins of commonly reported features using a combination of experimental electron microscopy and multislice diffraction simulations, which suggest that diffuse intensities largely represent thermal and static displacement scattering. A number of observations may reflect additional contributions from planar defects, surface terminations incommensurate with bulk periodicity, or weaker dynamical effects. Diffraction ; Electron diffraction ; Electron ; Scattering ; Planar ; Electron microscope ; Materials science ; Condensed matter physics ; Thermal ; Molecular physics ; Physics ; Chemical physics ; Crystallography ; Optics ; Chemistry ; Quantum mechanics ; Thermodynamics Microstructure and mechanical properties ; X-ray Diffraction in Crystallography ; Hydrogen embrittlement and corrosion behaviors in metals
Authors: Shubhajit Das | Rubén Laplaza | J. Terence Blaskovits | Clémence Corminbœuf
Source: Journal of the American Chemical Society (article, 2024-05-30)
Field: Chemistry — Organic Chemistry

Engineering Frustrated Lewis Pair Active Sites in Porous Organic Scaffolds for Catalytic CO <sub>2</sub> Hydrogenation Frustrated Lewis pairs (FLPs), featuring reactive combinations of Lewis acids and Lewis bases, have been utilized for myriad metal-free homogeneous catalytic processes. Immobilizing the active Lewis sites to a solid support, especially to porous scaffolds, has shown great potential to ameliorate FLP catalysis by circumventing some of its inherent drawbacks, such as poor product separation and catalyst recyclability. Nevertheless, designing immobilized Lewis pair active sites (LPASs) is challenging due to the requirement of placing the donor and acceptor centers in appropriate geometric arrangements while maintaining the necessary chemical environment to perform catalysis, and clear design rules have not yet been established. In this work, we formulate simple guidelines to build highly active LPASs for direct catalytic hydrogenation of CO2 through a large-scale screening of a diverse library of 25,000 immobilized FLPs. The library is built by introducing boron-containing acidic sites in the vicinity of the existing basic nitrogen sites of the organic linkers of metal–organic frameworks collected in a “top-down” fashion from the CoRE MOF 2019 database. The chemical and geometrical appropriateness of these LPASs for CO2 hydrogenation is determined by evaluating a series of simple descriptors representing the intrinsic strength (acidity and basicity) of the components and their spatial arrangement in the active sites. Analysis of the leading candidates enables the formulation of pragmatic and experimentally relevant design principles which constitute the starting point for further exploration of FLP-based catalysts for the reduction of CO2. Frustrated Lewis pair ; Chemistry ; Catalysis ; Lewis acids and bases ; Combinatorial chemistry ; Active site ; Homogeneous ; Nanotechnology ; Organic chemistry ; Materials science Organoboron and organosilicon chemistry ; Carbon dioxide utilization in catalysis ; Covalent Organic Framework Applications
Authors: Sharmi Ganguly | Joydip Sengupta
Source: Discover Nano (review, 2024-07-02)
Field: Materials Science — Materials Chemistry

Graphene-based nanotechnology in the Internet of Things: a mini review Graphene, a 2D nanomaterial, has garnered significant attention in recent years due to its exceptional properties, offering immense potential for revolutionizing various technological applications. In the context of the Internet of Things (IoT), which demands seamless connectivity and efficient data processing, graphene's unique attributes have positioned it as a promising candidate to prevail over challenges and optimize IoT systems. This review paper aims to provide a brief sketch of the diverse applications of graphene in IoT, highlighting its contributions to sensors, communication systems, and energy storage devices. Additionally, it discusses potential challenges and prospects for the integration of graphene in the rapidly evolving IoT landscape. Graphene ; Internet of Things ; Context (archaeology) ; Sketch ; Nanotechnology ; Computer science ; Data science ; Systems engineering ; Engineering ; World Wide Web ; Materials science Graphene research and applications ; Graphene and Nanomaterials Applications ; 2D Materials and Applications
Authors: Yuhao Lu | Xiuxiu Dong | Guanya Ji | Xuejing Wang | Tao Wang | Chengshun Tang | Oluwafunmilola Ola | Hongwei Duan | Qian Liu | Qijian Niu
Source: Sensors and Actuators B Chemical (article, 2024-11-02)
Field: Materials Science — Materials Chemistry

Anchor carbon dots inside NH2-MIL-88B via ship-in-a-bottle strategy for dual signal enhancement in colorimetric-fluorescent sensors Fluorescence ; Bottle ; SIGNAL (programming language) ; Dual (grammatical number) ; Carbon fibers ; Materials science ; Optoelectronics ; Nanotechnology ; Computer science ; Optics ; Composite material ; Physics ; Art Advanced Nanomaterials in Catalysis ; Advanced biosensing and bioanalysis techniques ; Electrochemical sensors and biosensors
Authors: Liangchun Li | Renlin Zheng | Rongqin Sun
Source: Journal of Advanced Research (review, 2024-04-01)
Field: Materials Science — Biomaterials

Understanding multicomponent low molecular weight gels from gelators to networks This review is focused on three key concepts. Firstly, understanding the complicated multicomponent gels systems requires a systems perspective on MLMWGs. Secondly, several protocols can be applied to control self-sorting and co-assembly behaviors in those multicomponent gels system, including the certain complementary structures, chirality inducing and dynamic control. Thirdly, the discussion is anchored in challenges and strategies of understanding MLMWGs, and some examples are provided for the understanding of multicomponent gels constructed from small natural products and subtle designed short peptides. Sorting ; Computer science ; Nanotechnology ; Biochemical engineering ; Process (computing) ; Materials science ; Engineering Supramolecular Self-Assembly in Materials ; Polydiacetylene-based materials and applications ; Photoreceptor and optogenetics research
Authors: Joseph H. Montoya | Carolyn Grimley | Muratahan Aykol | Colin Ophus | Hadas Sternlicht | Benjamin H. Savitzky | Andrew M. Minor | Steven B. Torrisi | Jackson Goedjen | Ching‐Chang Chung | Andrew H. Comstock | Shijing Sun
Source: Chemical Science (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

How the AI-assisted discovery and synthesis of a ternary oxide highlights capability gaps in materials science Exploratory synthesis has been the main generator of new inorganic materials for decades. However, our Edisonian and bias-prone processes of synthetic exploration alone are no longer sufficient in an age that demands rapid advances in materials development. In this work, we demonstrate an end-to-end attempt towards systematic, computer-aided discovery and laboratory synthesis of inorganic crystalline compounds as a modern alternative to purely exploratory synthesis. Our approach initializes materials discovery campaigns by autonomously mapping the synthetic feasibility of a chemical system using density functional theory with AI feedback. Following expert-driven down-selection of newly generated phases, we use solid-state synthesis and <i>in situ</i> characterization <i>via</i> hot-stage X-ray diffraction in order to realize new ternary oxide phases experimentally. We applied this strategy in six ternary transition-metal oxide chemistries previously considered well-explored, one of which culminated in the discovery of two novel phases of calcium ruthenates. Detailed characterization using room temperature X-ray powder diffraction, 4D-STEM and SQUID measurements identifies the structure and composition and confirms distinct properties, including distinct defect concentrations, of one of the new phases formed in our experimental campaigns. While the discovery of a new material guided by AI and DFT theory represents a milestone, our procedure and results also highlight a number of critical gaps in the process that can inform future efforts towards the improvement of AI-coupled methodologies. Ternary operation ; Nanotechnology ; Materials science ; Oxide ; Combinatorial chemistry ; Chemistry ; Computer science ; Metallurgy Machine Learning in Materials Science ; Electronic and Structural Properties of Oxides ; Catalysis and Oxidation Reactions
Authors: Dingyun Huang | Jacqueline M. Cole
Source: Scientific Data (article, 2024-01-17)
Field: Materials Science — Materials Chemistry

A database of thermally activated delayed fluorescent molecules auto-generated from scientific literature with ChemDataExtractor Abstract A database of thermally activated delayed fluorescent (TADF) molecules was automatically generated from the scientific literature. It consists of 25,482 data records with an overall precision of 82%. Among these, 5,349 records have chemical names in the form of SMILES strings which are represented with 91% accuracy; these are grouped in a subsidiary database. Each data record contains one of the following four properties: maximum emission wavelength ( λ EM ), photoluminescence quantum yield (PLQY), singlet-triplet energy splitting (Δ E ST ), and delayed lifetime ( τ D ). The databases were created through text mining using ChemDataExtractor, a chemistry-aware natural-language-processing toolkit, which has been adapted for TADF research. The text-mined corpus consisted of 2,733 papers from the Royal Society of Chemistry and Elsevier. To the best of our knowledge, these databases are the first databases that have been auto-generated for TADF molecules from existing publications. The databases have been publicly released for experimental and computational applications in the TADF research field. Fluorescence ; Chemistry ; Database ; Computer science ; Physics Machine Learning in Materials Science ; Innovative Microfluidic and Catalytic Techniques Innovation ; Computational Drug Discovery Methods
Authors: Suyang Sun | Xiaozhe Wang | Yihui Jiang | Yibo Lei | Siyu Zhang | Sanjay Kumar | Junying Zhang | E. Ma | Riccardo Mazzarello | Jiangjing Wang | Wei Zhang
Source: npj Computational Materials (article, 2024-08-25)
Field: Materials Science — Materials Chemistry

High-throughput screening to identify two-dimensional layered phase-change chalcogenides for embedded memory applications Chalcogenide phase-change materials (PCMs) are showing versatile possibilities in cutting-edge applications, including non-volatile memory, neuromorphic computing, and nano-photonics. However, for embedded phase-change memory applications, conventional PCMs suffer from insufficient thermal stability because of their relatively low crystallization temperatures (Tx). Although doping with additional alloying elements could improve the amorphous stability, it also increases the tendency towards compositional partitioning and phase separation. Recently, a two-dimensional (2D) layered compound CrGeTe3 (CrGT) was developed as a PCM, showing a high Tx ~ 276 °C with an inverse change in resistive-switching character upon phase transition. Here, we report a high-throughput materials screening for 2D layered phase-change chalcogenides. We aim to clarify whether the high Tx and the inverse electrical resistance contrast are intrinsic features of 2D PCMs. In total, twenty-five 2D chalcogenides with CrGT trilayer structures have been identified from a large database. We then focused on selected layered tellurides by performing thorough ab initio simulations and experimental investigations and confirming that their amorphous phase indeed has a much higher Tx than conventional PCMs. We attribute this enhanced amorphous stability to the structurally complex nuclei required to render crystallization possible. Overall, we regard InGeTe3 as a balanced 2D PCM with both high thermal stability and large electrical contrast for embedded memory applications. Phase-change memory ; Throughput ; Computer science ; Materials science ; Phase change ; Phase (matter) ; Computer architecture ; Nanotechnology ; Parallel computing ; Physics ; Engineering physics ; Telecommunications ; Wireless ; Layer (electronics) Phase-change materials and chalcogenides ; Chalcogenide Semiconductor Thin Films ; Advanced Memory and Neural Computing