jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Chi Chen | Dan Thien Nguyen | Shannon Lee | Nathan Baker | Ajay Karakoti | Linda Lauw | Craig Owen | Karl T. Mueller | Brian A. Bilodeau | Vijayakumar Murugesan | Matthias Troyer
Source: arXiv (Cornell University) (preprint, 2024-01-08)
Field: Materials Science — Materials Chemistry

Accelerating computational materials discovery with artificial intelligence and cloud high-performance computing: from large-scale screening to experimental validation High-throughput computational materials discovery has promised significant acceleration of the design and discovery of new materials for many years. Despite a surge in interest and activity, the constraints imposed by large-scale computational resources present a significant bottleneck. Furthermore, examples of large-scale computational discovery carried through experimental validation remain scarce, especially for materials with product applicability. Here we demonstrate how this vision became reality by first combining state-of-the-art artificial intelligence (AI) models and traditional physics-based models on cloud high-performance computing (HPC) resources to quickly navigate through more than 32 million candidates and predict around half a million potentially stable materials. By focusing on solid-state electrolytes for battery applications, our discovery pipeline further identified 18 promising candidates with new compositions and rediscovered a decade's worth of collective knowledge in the field as a byproduct. By employing around one thousand virtual machines (VMs) in the cloud, this process took less than 80 hours. We then synthesized and experimentally characterized the structures and conductivities of our top candidates, the Na$_x$Li$_{3-x}$YCl$_6$ ($0 &lt; x &lt; 3$) series, demonstrating the potential of these compounds to serve as solid electrolytes. Additional candidate materials that are currently under experimental investigation could offer more examples of the computational discovery of new phases of Li- and Na-conducting solid electrolytes. We believe that this unprecedented approach of synergistically integrating AI models and cloud HPC not only accelerates materials discovery but also showcases the potency of AI-guided experimentation in unlocking transformative scientific breakthroughs with real-world applications. Bottleneck ; Cloud computing ; Computer science ; Drug discovery ; Computational model ; Scale (ratio) ; Supercomputer ; Artificial intelligence ; Data science ; Bioinformatics ; Physics ; Embedded system Machine Learning in Materials Science ; Inorganic Chemistry and Materials ; Advanced Photocatalysis Techniques
Authors: Habtamu Fekadu Etefa | Aster Aberra Tessema | F.B. Dejene
Source: Preprints.org (review, 2024-04-03)
Field: Materials Science — Materials Chemistry

Carbon Dots for Future Prospects: Synthesis, Characterizations and Recent Applications: A Review (2019–2023) Nanotechnology sparks discussions and concerns about the impacts of new nanomaterials on health and the environment. It holds importance in various domains due to its unique struc-tures. Carbon dots (C-dots) are versatile nanomaterials with applications in bioimaging, sensing, catalysis, polymers, solar cells, and more. They offer desirable characteristics such as stability, cost-effectiveness, biocompatibility, and high photoluminescent quantum yield. C-dots have the potential to replace expensive fluorophores in solar cells. They are catego-rized as carbon quantum dots, graphene quantum dots, and carbonized polymer dots. C-dots have outstanding optical and photoelectric properties with low toxicity. Bottom-up and top-down approaches are used for the synthesis of carbon dots (CDs), with each method im-pacting their physicochemical characteristics. The choice of synthesis method depends on de-sired properties and application requirements. Researchers combine these methods and ex-plore new approaches to enhance synthesis efficiency and tailor CD properties. CDs have di-verse chemical structures with modified oxygen, polymer-based, or amino groups on their surface. Various characterization methods such as HRTEM, XPS, and optical analysis (PL, UV) are used to determine CD structure. Carbon dots (CDs) are cutting-edge fluorescent nano-materials with remarkable qualities such as biocompatibility, low toxicity, environmental friendliness, high water solubility, and photo-stability. They are easily adjustable in terms of their optical properties, making them highly versatile in various fields. CDs find applications in bio-imaging, nanomedicine, drug delivery, solar cells, LEDs, photo-catalysis, elec-tro-catalysis, and other related areas. Nanotechnology ; Carbon fibers ; Business ; Materials science Carbon and Quantum Dots Applications ; Graphene and Nanomaterials Applications ; Graphene research and applications
Authors: Sraddha Agrawal | David Casanova | Dhara J. Trivedi | Oleg V. Prezhdo
Source: The Journal of Physical Chemistry Letters (article, 2024-02-19)
Field: Materials Science — Materials Chemistry

Enhanced Charge Separation in Single Atom Cobalt Based Graphitic Carbon Nitride: Time Domain <i>Ab Initio</i> Analysis In recent years, single atom catalysts have been at the forefront of energy conversion research, particularly in the field of catalysis. Carbon nitrides offer great potential as hosts for stabilizing metal atoms due to their unique electronic structure. We use <i>ab initio</i> nonadiabatic molecular dynamics to study photoexcitation dynamics in single atom cobalt based graphitic carbon nitride. The results elucidate the positive effect of the doped cobalt atom on the electronic structure of GCN. Cobalt doping produces filled midgap states that serve as oxidation centers, advantageous for various redox reactions. The presence of midgap states enables the harvesting of longer wavelength photons, thereby extending the absorption range of solar light. Although doping accelerates charge relaxation overall, charge recombination is significantly slower than charge separation, creating beneficial conditions for catalysis applications. The simulations reveal the detailed microscopic mechanism underlying the improved performance of the doped system due to atomic defects and demonstrate an effective charge separation strategy to construct highly efficient and stable photocatalytic two-dimensional materials. Ab initio ; Cobalt ; Materials science ; Charge (physics) ; Atom (system on chip) ; Nitride ; Graphitic carbon nitride ; Ab initio quantum chemistry methods ; SIESTA (computer program) ; Carbon nitride ; Computational chemistry ; Chemical physics ; Analytical Chemistry (journal) ; Chemistry ; Nanotechnology ; Physics ; Quantum mechanics ; Molecule ; Metallurgy ; Computer science ; Parallel computing ; Organic chemistry ; Catalysis Graphene research and applications ; Semiconductor materials and devices ; 2D Materials and Applications
Authors: Qiaoling Zhang | Guodong Li | Fen Qiao
Source: Journal of Advanced Research (review, 2024-02-13)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Recent advances in integrated solar cell/supercapacitor devices: Fabrication, strategy and perspectives Here, the structures and preparation methods of various types of integrated SCSD were introduced. Then, the strategies for improving the overall performance of integrated devices were evaluated. Finally, the key objectives of reducing the cost of materials, increasing the stability and sustainability of devices were highlighted. Better matching of different functional units of devices was also prospected. Supercapacitor ; Solar cell ; Process (computing) ; Computer science ; Nanotechnology ; Fabrication ; Photovoltaic system ; Materials science ; Key (lock) ; Process integration ; Process engineering ; Systems engineering ; Electrode ; Electrical engineering ; Capacitance ; Optoelectronics ; Engineering Supercapacitor Materials and Fabrication ; Advanced battery technologies research ; Electrocatalysts for Energy Conversion
Authors: H.-Q. Jin | Kenneth M. Merz
Source: Journal of Chemical Theory and Computation (article, 2024-03-05)
Field: Materials Science — Materials Chemistry

Modeling Fe(II) Complexes Using Neural Networks We report a Fe(II) data set of more than 23000 conformers in both low-spin (LS) and high-spin (HS) states. This data set was generated to develop a neural network model that is capable of predicting the energy and the energy splitting as a function of the conformation of a Fe(II) organometallic complex. In order to achieve this, we propose a type of scaled electronic embedding to cover the long-range interactions implicitly in our neural network describing the Fe(II) organometallic complexes. For the total energy prediction, the lowest MAE is 0.037 eV, while the lowest MAE of the splitting energy is 0.030 eV. Compared to baseline models, which only incorporate short-range interactions, our scaled electronic embeddings improve the accuracy by over 70% for the prediction of the total energy and the splitting energy. With regard to semiempirical methods, our proposed models reduce the MAE, with respect to these methods, by 2 orders of magnitude. Artificial neural network ; Energy (signal processing) ; Embedding ; Range (aeronautics) ; Set (abstract data type) ; Computer science ; Electronic structure ; Cover (algebra) ; Total energy ; Spin (aerodynamics) ; Function (biology) ; Data set ; Statistical physics ; Biological system ; Physics ; Materials science ; Chemistry ; Computational chemistry ; Artificial intelligence ; Thermodynamics ; Quantum mechanics Machine Learning in Materials Science ; CO2 Reduction Techniques and Catalysts ; Catalysis and Oxidation Reactions
Authors: Ningqing Lv | Rongshan Wu | Ruonan Guo | Linlin Wu | Heng Zhang | Changsheng Guo | Jian Xu
Source: Ultrasonics Sonochemistry (article, 2024-11-25)
Field: Materials Science — Materials Chemistry

Exploring the progress and challenges of ultrasonic technology in environmental remediation Amidst escalating environmental pollution due to accelerated industrialization and urbanization, there is an acute demand for effective and sustainable environmental remediation strategies. Ultrasonic technology, recognized for its green and efficient characteristics, has gained significant prominence in mitigating environmental pollution in aquatic, soil, and atmospheric ecosystems. The review provides a comprehensive analysis of the role of ultrasonic treatment in wastewater treatment, air quality improvement, and soil remediation. We systematically evaluate existing research to assess the effectiveness of ultrasonic technology in degrading pollutants and its potential for large-scale deployment. The review also examines the challenges associated with ultrasonic remediation, including optimizing operational parameters, enhancing energy transfer efficiency, and understanding the unique degradation mechanisms for various pollutants. Furthermore, we discuss environmental and safety considerations, along with the economic implications related to equipment costs and energy consumption. This review aims to contribute to the advancement of ultrasonic technology in environmental remediation by presenting a forward-looking perspective, aligning with the goals of environmental protection and sustainable development. Environmental remediation ; Environmental science ; Sonochemistry ; Ultrasonic sensor ; Nanotechnology ; Environmental chemistry ; Materials science ; Chemistry ; Acoustics ; Ecology ; Contamination ; Physics ; Biology Ultrasound and Cavitation Phenomena
Authors: Anna N. Matveyeva | Shamil O. Omarov
Source: Transactions of Tianjin University (article, 2024-08-01)
Field: Materials Science — Materials Chemistry

Comparison of Perovskite Systems Based on AFeO3 (A = Ce, La, Y) in CO2 Hydrogenation to CO Abstract CO 2 is the most cost-effective and abundant carbon resource, while the reverse water–gas reaction (rWGS) is one of the most effective methods of CO 2 utilization. This work presents a comparative study of rWGS activity for perovskite systems based on AFeO 3 (where A = Ce, La, Y). These systems were synthesized by solution combustion synthesis (SCS) with different ratios of fuel (glycine) and oxidizer ( φ ), different amounts of NH 4 NO 3 , and the addition of alumina or silica as supports. Various techniques, including X-ray diffraction analysis, thermogravimetric analysis, Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy, energy-dispersive X-ray spectroscopy, N 2 -physisorption, H 2 temperature-programmed reduction, temperature-programmed desorption of H 2 and CO 2 , Raman spectroscopy, and in situ FTIR, were used to relate the physicochemical properties with the catalytic performance of the obtained composites. Each specific perovskite-containing system (either bulk or supported) has its own optimal φ and NH 4 NO 3 amount to achieve the highest yield and dispersion of the perovskite phase. Among all synthesized systems, bulk SCS-derived La–Fe–O systems showed the highest resistance to reducing environments and the easiest hydrogen desorption, outperforming La–Fe–O produced by solgel combustion (SGC). CO 2 conversion into CO at 600 °C for bulk ferrite systems, depending on the A-cation type and preparation method, follows the order La (SGC) &lt; Y &lt; Ce &lt; La (SCS). The differences in properties between La–Fe–O obtained by the SCS and SGC methods can be attributed to different ratios of oxygen and lanthanum vacancy contributions, hydroxyl coverage, morphology, and free iron oxide presence. In situ FTIR data revealed that CO 2 hydrogenation occurs through formates generated under reaction conditions on the bulk system based on La–Fe–O, obtained by the SCS method. γ -Al 2 O 3 improves the dispersion of CeFeO 3 and LaFeO 3 phases, the specific surface area, and the quantity of adsorbed H 2 and CO 2 . This led to a significant increase in CO 2 conversion for supported CeFeO 3 but not for the La-based system compared to bulk and SiO 2 -supported perovskite catalysts. However, adding alumina increased the activity per mass for both Ce- and La-based perovskite systems, reducing the amount of rare-earth components in the catalyst and thereby lowering the cost without substantially compromising stability. Perovskite (structure) ; Materials science ; Chemical engineering ; Environmental science ; Business ; Engineering Catalytic Processes in Materials Science ; Catalysis and Oxidation Reactions ; Catalysts for Methane Reforming
Authors: Shamili Bandaru | Deepshika Arora | Kalathur Mohan Ganesh | Saurabh Umrao | Sabu Thomas | Seemesh Bhaskar | Sabyasachi Chakrabortty
Source: Nanomaterials (review, 2024-08-26)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Recent Advances in Research from Nanoparticle to Nano-Assembly: A Review The careful arrangement of nanomaterials (NMs) holds promise for revolutionizing various fields, from electronics and biosensing to medicine and optics. This review delves into the intricacies of nano-assembly (NA) techniques, focusing on oriented-assembly methodologies and stimuli-dependent approaches. The introduction provides a comprehensive overview of the significance and potential applications of NA, setting the stage for review. The oriented-assembly section elucidates methodologies for the precise alignment and organization of NMs, crucial for achieving desired functionalities. The subsequent section delves into stimuli-dependent techniques, categorizing them into chemical and physical stimuli-based approaches. Chemical stimuli-based self-assembly methods, including solvent, acid-base, biomolecule, metal ion, and gas-induced assembly, are discussed in detail by presenting examples. Additionally, physical stimuli such as light, magnetic fields, electric fields, and temperature are examined for their role in driving self-assembly processes. Looking ahead, the review outlines futuristic scopes and perspectives in NA, highlighting emerging trends and potential breakthroughs. Finally, concluding remarks summarize key findings and underscore the significance of NA in shaping future technologies. This comprehensive review serves as a valuable resource for researchers and practitioners, offering insights into the diverse methodologies and potential applications of NA in interdisciplinary research fields. Nanotechnology ; Computer science ; Resource (disambiguation) ; Materials science Gold and Silver Nanoparticles Synthesis and Applications ; Quantum Dots Synthesis And Properties ; Nanocluster Synthesis and Applications
Authors: Qian Wang | Xinyi He | Jian Mao | Junxia Wang | Liangliang Wang | Zhongchi Zhang | Yongfei Li | Fenglin Huang | Bin Zhao | Gang Chen | Hua He
Source: Molecules (article, 2024-09-05)
Field: Materials Science — Materials Chemistry

Carbon Dots: A Versatile Platform for Cu2+ Detection, Anti-Counterfeiting, and Bioimaging Carbon dots (CDs) have garnered extensive interest in basic physical chemistry as well as in biomedical applications due to their low cost, good biocompatibility, and great aqueous solubility. However, the synthesis of multi-functional carbon dots has always been a challenge for researchers. Here, we synthesized novel CDs with a high quantum yield of 28.2% through the straightforward hydrothermal method using Diaminomaleonitrile and Boc-D-2, 3-diaminopropionic acid. The size, chemical functional group, and photophysical properties of the CDs were characterized by TEM, FTIR, XPS, UV, and fluorescence. It was demonstrated in this study that the prepared CDs have a high quantum yield, excellent photostability, and low cytotoxicity. Regarding the highly water-soluble property of CDs, they were proven to possess selective and sensitive behavior against Cu<sup>2+</sup> ions (linear range = 0-9 μM and limit of detection = 1.34 μM). Moreover, the CDs were utilized in fluorescent ink in anti-counterfeiting measures. Because of their low cytotoxicity and good biocompatibility, the CDs were also successfully utilized in cell imaging. Therefore, the as-prepared CDs have great potential in fluorescence sensing, anti-counterfeiting, and bioimaging. Biocompatibility ; Quantum yield ; Fluorescence ; Aqueous solution ; Carbon fibers ; Nanotechnology ; Detection limit ; Quantum dot ; Materials science ; Biological imaging ; Carbon quantum dots ; X-ray photoelectron spectroscopy ; Chemistry ; Fourier transform infrared spectroscopy ; Chemical engineering ; Organic chemistry ; Composite number ; Chromatography Carbon and Quantum Dots Applications ; Nanocluster Synthesis and Applications ; Mercury impact and mitigation studies
Authors: Nathan J. Szymanski | Young‐Woon Byeon | Yingzhi Sun | Yan Zeng | Jianming Bai | Martin Kunz | Dong‐Min Kim | Brett A. Helms | Christopher J. Bartel | Haegyeom Kim | Gerbrand Ceder
Source: Science Advances (article, 2024-07-03)
Field: Materials Science — Materials Chemistry

Quantifying the regime of thermodynamic control for solid-state reactions during ternary metal oxide synthesis The success of solid-state synthesis often hinges on the first intermediate phase that forms, which determines the remaining driving force to produce the desired target material. Recent work suggests that when reaction energies are large, thermodynamics primarily dictates the initial product formed, regardless of reactant stoichiometry. Here, we validate this principle and quantify its constraints by performing in situ characterization on 37 pairs of reactants. These experiments reveal a threshold for thermodynamic control in solid-state reactions, whereby initial product formation can be predicted when its driving force exceeds that of all other competing phases by ≥60 milli-electron volt per atom. In contrast, when multiple phases have a comparable driving force to form, the initial product is more often determined by kinetic factors. Analysis of the Materials Project data shows that 15% of possible reactions fall within the regime of thermodynamic control, highlighting the opportunity to predict synthesis pathways from first principles. Work (physics) ; Ternary operation ; Thermodynamics ; Stoichiometry ; Oxide ; Phase (matter) ; Characterization (materials science) ; Kinetic energy ; Materials science ; Atom (system on chip) ; Thermodynamic equilibrium ; Chemical physics ; Chemistry ; Nanotechnology ; Physical chemistry ; Physics ; Computer science ; Classical mechanics ; Metallurgy Machine Learning in Materials Science ; Electronic and Structural Properties of Oxides ; Advanced Materials Characterization Techniques
Authors: Yao Shi | Joshua S. Derasp | Tristan Maschmeyer | Jason E. Hein
Source: Nature Communications (article, 2024-06-27)
Field: Chemistry — Organic Chemistry

Phase transfer catalysts shift the pathway to transmetalation in biphasic Suzuki-Miyaura cross-couplings The Suzuki-Miyaura coupling is a widely used C-C bond forming reaction. Numerous mechanistic studies have enabled the use of low catalyst loadings and broad functional group tolerance. However, the dominant mode of transmetalation remains controversial and likely depends on the conditions employed. Herein we detail a mechanistic study of the palladium-catalyzed Suzuki-Miyaura coupling under biphasic conditions. The use of phase transfer catalysts results in a remarkable 12-fold rate enhancement in the targeted system. A shift from an oxo-palladium based transmetalation to a boronate-based pathway lies at the root of this activity. Furthermore, a study of the impact of different water loadings reveals reducing the proportion of the aqueous phase increases the reaction rate, contrary to reaction conditions typically employed in the literature. The importance of these findings is highlighted by achieving an exceptionally broad substrate scope with benzylic electrophiles using a 10-fold reduction in catalyst loading relative to literature precedent. Transmetalation ; Catalysis ; Palladium ; Chemistry ; Electrophile ; Phase (matter) ; Combinatorial chemistry ; Substrate (aquarium) ; Coupling reaction ; Aqueous two-phase system ; Organic chemistry ; Biology Catalytic Cross-Coupling Reactions ; Organoboron and organosilicon chemistry ; Sulfur-Based Synthesis Techniques