jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Darlington Eze Ekechukwu | Gideon Oluseyi Daramola | Omowonuola Ireoluwapo Kehinde Olanrewaju
Source: GSC Advanced Research and Reviews (review, 2024-06-24)
Field: Materials Science — Materials Chemistry

Advancements in catalysts for zero-carbon synthetic fuel production: A comprehensive review The quest for sustainable and environmentally friendly energy sources has intensified the focus on zero-carbon synthetic fuel production. Catalysts play a pivotal role in this process, enhancing the efficiency and feasibility of transforming renewable energy sources into synthetic fuels. This comprehensive review delves into recent advancements in catalyst development for zero-carbon synthetic fuel production. It examines the innovative materials and techniques that have emerged to optimize catalytic performance, including nanostructured catalysts, hybrid materials, and biomimetic approaches. The review highlights the significant progress made in understanding and manipulating catalyst properties to achieve higher activity, selectivity, and stability under various reaction conditions. It also explores the integration of advanced characterization techniques and computational modeling in catalyst design, providing insights into the molecular-level interactions and mechanisms driving catalytic processes. Special attention is given to the development of catalysts for key reactions such as water splitting, carbon dioxide reduction, and hydrogenation. The review discusses the challenges associated with scaling up these technologies and the potential environmental impacts, offering a balanced perspective on the feasibility of widespread adoption. Furthermore, the review addresses the synergistic effects of combining different catalytic materials and the potential of using earth-abundant elements to reduce costs and enhance sustainability. The role of electrochemical and photochemical catalysts in driving efficient energy conversion processes is also explored, showcasing the versatility and potential of these technologies in achieving zero-carbon fuel production. In conclusion, this review underscores the transformative potential of advanced catalysts in the quest for sustainable synthetic fuels. It provides a roadmap for future research and development, emphasizing the need for interdisciplinary approaches and collaborative efforts to overcome existing challenges and accelerate the transition to a zero-carbon energy landscape. The advancements in catalyst technology not only promise to revolutionize synthetic fuel production but also contribute significantly to global efforts in mitigating climate change and reducing reliance on fossil fuels. Carbon fibers ; Production (economics) ; Catalysis ; Environmental science ; Biochemical engineering ; Waste management ; Materials science ; Process engineering ; Chemistry ; Engineering ; Economics ; Organic chemistry ; Composite material Catalytic Processes in Materials Science ; Catalysts for Methane Reforming ; Catalysis and Hydrodesulfurization Studies
Authors: Georges Dubourg | Zoran Pavlović | Branimir Bajac | Manil Kukkar | Nina Finčur | Zorica Novaković | Marko Radović
Source: The Science of The Total Environment (article, 2024-04-04)
Field: Materials Science — Materials Chemistry

Advancement of metal oxide nanomaterials on agri-food fronts Agrochemical ; MOX fuel ; Agriculture ; Food packaging ; Food safety ; Business ; Food industry ; Food security ; Environmental science ; Risk analysis (engineering) ; Environmental planning ; Engineering ; Medicine ; Chemistry Nanoparticles: synthesis and applications ; Advanced Nanomaterials in Catalysis
Authors: Zhuoran Wang | Yaxin Hou | Guoheng Tang | Yucong Li | Yue Zhao | Yixin Yu | Guannan Wang | Xiyun Yan | Kelong Fan
Source: Fundamental Research (review, 2024-12-03)
Field: Materials Science — Materials Chemistry

Intelligent nanozymes: Biomimetic design, mechanisms and biomedical applications Nanozymes are a unique class of nanomaterials that possess intrinsic enzymatic properties, exhibiting similar reaction kinetics to natural enzymes. As enzyme substitutes in various biomedical applications, nanozymes offer numerous advantages, including low cost, tunable catalytic activity, and exceptional stability. However, their catalytic activities are typically lower than those of natural enzymes, and the lack of precise control over their functional modulation limits their therapeutic potential. To address these challenges, the biomimetic and intelligent design of nanozymes has been introduced as a critical concept for enhancing their functionality. In this review, we will explore the importance of biomimetic design in the development of intelligent nanozymes. We will first introduce the foundational principles and strategies for their targeted design, followed by an overview of recent advances in the regulatory mechanisms and biomedical applications of intelligent nanozymes. Lastly, we will highlight the current limitations in this research field and propose future directions. With continued progress in biomimetic and intelligent design, nanozymes are poised to accelerate their clinical translation and large-scale commercialization, further expanding their potential in therapeutic applications. Nanotechnology ; Biomimetics ; Computer science ; Systems engineering ; Human–computer interaction ; Engineering ; Materials science Advanced Nanomaterials in Catalysis ; Nanoplatforms for cancer theranostics ; Advanced biosensing and bioanalysis techniques
Authors: Xinyu Peng | Jiaojiao Liang | Kuo Wang | Xiaojie Zhao | Zhiyan Peng | Zhennan Li | Jinhui Zeng | Lan Zheng | Min Lei | Di Huang
Source: npj Computational Materials (article, 2024-09-11)
Field: Materials Science — Materials Chemistry

Construction frontier molecular orbital prediction model with transfer learning for organic materials The frontier molecular orbitals of organic semiconductor materials play a crucial role in the performance of photoelectric devices, including organic photovoltaics (OPVs), organic light-emitting diodes (OLEDs), and organic photodetectors (OPDs). In this work, a model for predicting frontier molecular orbital of organic materials, including HOMO and LUMO levels, is established with the extreme gradient boosting algorithm and Klekota-Roth fingerprints. The correlation coefficients of HOMO or LUMO energy levels in the testing set are 0.75 and 0.84 in the transfer model from 11,626 DFT data in Harvard Energy database to 1198 experimental data in literature. The difference between the ML predicted value and the experimental value is smaller than the difference between ML prediction and DFT calculation, always less than 10%. Moreover, based on correlation and SHAP interpretability analysis, 13 key structural fragments influencing energy levels are selected to further verify the effective regulation of the frontier molecular orbital by the key structural fragments in practical applications. Considering the completely opposite regulatory functions of key structural fragments on HOMO and LUMO energy levels, four new Y6 derivatives, Y-PCP, Y-P6F, Y-PCF, and Y-P4FC, are designed to flexibly modify the HOMO and LUMO energy levels. The prediction trends of ML align closely with the computational trends from DFT. It is worth noting that the accuracy of LUMO energy level prediction by the prediction model makes up for the instability of DFT calculation on LUMO energy level. This work offers a cost-effective method to accelerate the acquisition of electronic properties of organic materials. Frontier ; Transfer of learning ; Molecular orbital ; Computer science ; Chemistry ; Artificial intelligence ; Geography ; Organic chemistry ; Molecule Machine Learning in Materials Science ; Crystallography and molecular interactions ; Computational Drug Discovery Methods
Authors: Peter A. Dykeman-Bermingham | Matthew P. Bogen | Supraja S. Chittari | Savannah F. Grizzard | Abigail Knight
Source: Journal of the American Chemical Society (article, 2024-03-12)
Field: Materials Science — Biomaterials

Tailoring Hierarchical Structure and Rare Earth Affinity of Compositionally Identical Polymers via Sequence Control Macromolecule sequence, structure, and function are inherently intertwined. While well-established relationships exist in proteins, they are more challenging to define for synthetic polymer nanoparticles due to their molecular weight, sequence, and conformational dispersities. To explore the impact of sequence on nanoparticle structure, we synthesized a set of 16 compositionally identical, sequence-controlled polymers with distinct monomer patterning of dimethyl acrylamide and a bioinspired, structure-driving di(phenylalanine) acrylamide (FF). Sequence control was achieved through multiblock polymerizations, yielding unique ensembles of polymer sequences which were simulated by kinetic Monte Carlo simulations. Systematic analysis of the global (tertiary- and quaternary-like) structure in this amphiphilic copolymer series revealed the effect of multiple sequence descriptors: the number of domains, the hydropathy of terminal domains, and the patchiness (density) of FF within a domain, each of which impacted both chain collapse and the distribution of single- and multichain assemblies. Furthermore, both the conformational freedom of chain segments and local-scale, β-sheet-like interactions were sensitive to the patchiness of FF. To connect sequence, structure, and target function, we evaluated an additional series of nine sequence-controlled copolymers as sequestrants for rare earth elements (REEs) by incorporating a functional acrylic acid monomer into select polymer scaffolds. We identified key sequence variables that influence the binding affinity, capacity, and selectivity of the polymers for REEs. Collectively, these results highlight the potential of and boundaries of sequence control via multiblock polymerizations to drive primary sequence ensembles hierarchical structures, and ultimately the functionality of compositionally identical polymeric materials. Sequence (biology) ; Chemistry ; Polymer ; Copolymer ; Monomer ; Amphiphile ; Macromolecule ; Organic chemistry ; Biochemistry biodegradable polymer synthesis and properties ; Advanced Polymer Synthesis and Characterization ; Supramolecular Self-Assembly in Materials
Authors: Xinjuan Liu | Hongchao Luo
Source: ACS Omega (article, 2024-01-04)
Field: Materials Science — Materials Chemistry

Preparation of Coal-Based Graphene by Flash Joule Heating This study explores the production of flash graphene (AC-FG) from anthracite coal by using the flash Joule heating (FJH) method. This study demonstrates that AC-FG can be derived from anthracite coal by precisely controlling the system parameters, specifically the pulse voltage. The FJH process requires no catalyst. The produced material was characterized by using Raman, XRD, XPS, TG, SEM, TEM, and XPS techniques. The results reveal that the degree of graphitization of coal reaches its peak at 190 V. From an energy perspective, FJH provides a straightforward and cost-effective method for graphene preparation, offering a substantial avenue for the efficient utilization of coal resources and the cost-effective application of graphene. Anthracite ; Graphene ; Flash (photography) ; Joule heating ; Coal ; Materials science ; Joule (programming language) ; Raman spectroscopy ; X-ray photoelectron spectroscopy ; Carbon nanotube ; Nanotechnology ; Chemical engineering ; Process engineering ; Composite material ; Efficient energy use ; Waste management ; Electrical engineering ; Engineering ; Physics ; Optics Graphene research and applications ; Graphene and Nanomaterials Applications ; Supercapacitor Materials and Fabrication
Authors: Michael Scherbela | Leon Gerard | Philipp Grohs
Source: Nature Communications (article, 2024-01-02)
Field: Materials Science — Materials Chemistry

Towards a transferable fermionic neural wavefunction for molecules Deep neural networks have become a highly accurate and powerful wavefunction ansatz in combination with variational Monte Carlo methods for solving the electronic Schrödinger equation. However, despite their success and favorable scaling, these methods are still computationally too costly for wide adoption. A significant obstacle is the requirement to optimize the wavefunction from scratch for each new system, thus requiring long optimization. In this work, we propose a neural network ansatz, which effectively maps uncorrelated, computationally cheap Hartree-Fock orbitals, to correlated, high-accuracy neural network orbitals. This ansatz is inherently capable of learning a single wavefunction across multiple compounds and geometries, as we demonstrate by successfully transferring a wavefunction model pre-trained on smaller fragments to larger compounds. Furthermore, we provide ample experimental evidence to support the idea that extensive pre-training of such a generalized wavefunction model across different compounds and geometries could lead to a foundation wavefunction model. Such a model could yield high-accuracy ab-initio energies using only minimal computational effort for fine-tuning and evaluation of observables. Ansatz ; Wave function ; Atomic orbital ; Physics ; Observable ; Quantum mechanics ; Artificial neural network ; Scaling ; Statistical physics ; Computer science ; Artificial intelligence ; Mathematics ; Geometry Machine Learning in Materials Science ; Spectroscopy and Quantum Chemical Studies ; Advanced Chemical Physics Studies
Authors: Simuck F. Yuk | Irmak Sargin | Noah Meyer | Jaron T. Krogel | Scott P. Beckman | Valentino R. Cooper
Source: Scientific Reports (article, 2024-08-30)
Field: Materials Science — Materials Chemistry

Putting error bars on density functional theory Predicting the error in density functional theory (DFT) calculations due to the choice of exchange-correlation (XC) functional is crucial to the success of DFT, but currently, there are limited options to estimate this a priori. This is particularly important for high-throughput screening of new materials. In this work, the structure and elastic properties of binary and ternary oxides are computed using four XC functionals: LDA, PBE-GGA, PBEsol, and vdW-DF with C09 exchange. To analyze the systemic errors inherent to each XC functional, we employed materials informatics methods to predict the expected errors. The predicted errors were also used to better the DFT-predicted lattice parameters. Our results emphasize the link between the computed errors and the electron density and hybridization errors of a functional. In essence, these results provide "error bars" for choosing a functional for the creation of high-accuracy, high-throughput datasets as well as avenues for the development of XC functionals with enhanced performance, thereby enabling the accelerated discovery and design of new materials. Computer science ; Density functional theory ; Physics ; Quantum mechanics Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Catalysis and Oxidation Reactions
Authors: Yachao Zhu | Siraprapha Deebansok | Jie Deng | Xuanze Wang | Thierry Brousse | Frèdéric Favier | Olivier Fontaine
Source: Advanced Energy Materials (article, 2024-04-10)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Electron Delocalization and Electrochemical Potential Distribution Phenomena in Faradaic Electrode Materials for Understanding Electrochemical Behavior Abstract Electrochemical energy storage devices are built upon the foudations of batteries and supercapacitors. In the past decade, new pseudocapacitor‐like electrodes are intensively developed to obtain superior energy storage performance. Pseudocapacitive matarials store charge through Faradaic processes, while the electrochemical signal remains like electrochemical double‐layer capacitors (EDLCs). To address this controversy, an analytical model is introduced for evaluating the voltammograms of electrode materials. Given this, the work focuses on understanding the origin of the pseudocapacitive phenomena in the cyclic voltammetry (CV) electrochemical signal. Based on electron transfer mechanism and tunnelling effect within the atomic structure, pseudocapacitive matarials possess a high electron delocalization possibility related to the redox centers number and initiates the electrochemical potential distribution among neighboring redox sites, which is consequently observed in the electrochemical signal as the plateau feature in CV, like EDLC. First, the determination of the capacitive tendency of various electrode materials is proposed, which turns out to be relative to the redox centers number (n) and total charge (Z). Here, when this number is large, electron hopping will very likely happen. The developed model is versatile to predict rate/potential regimes for the maximum faradaic storage, and then well differentiates the pseudocapacitive and battery materials. Pseudocapacitor ; Materials science ; Supercapacitor ; Electrochemistry ; Redox ; Faraday efficiency ; Cyclic voltammetry ; Electrode ; Delocalized electron ; Nanotechnology ; Electron transfer ; Energy storage ; Chemical physics ; Chemical engineering ; Chemistry ; Power (physics) ; Thermodynamics ; Photochemistry ; Physical chemistry Supercapacitor Materials and Fabrication ; Conducting polymers and applications ; Advanced battery technologies research
Authors: Pasquale Mastella | Biagio Todaro | Stefano Luin
Source: Nanomaterials (review, 2024-08-01)
Field: Materials Science — Biomaterials

Nanogels: Recent Advances in Synthesis and Biomedical Applications In the context of advanced nanomaterials research, nanogels (NGs) have recently gained broad attention for their versatility and promising biomedical applications. To date, a significant number of NGs have been developed to meet the growing demands in various fields of biomedical research. Summarizing preparation methods, physicochemical and biological properties, and recent applications of NGs may be useful to help explore new directions for their development. This article presents a comprehensive overview of the latest NG synthesis methodologies, highlighting advances in formulation with different types of hydrophilic or amphiphilic polymers. It also underlines recent biomedical applications of NGs in drug delivery and imaging, with a short section dedicated to biosafety considerations of these innovative nanomaterials. In conclusion, this article summarizes recent innovations in NG synthesis and their numerous applications, highlighting their considerable potential in the biomedical field. Nanotechnology ; Context (archaeology) ; Computer science ; Biosafety ; Biochemical engineering ; Data science ; Engineering ; Materials science ; Biotechnology ; Biology Nanoparticle-Based Drug Delivery ; Innovative Microfluidic and Catalytic Techniques Innovation ; Nanoplatforms for cancer theranostics
Authors: Maria‐Tsampika Manoli | A. Gargantilla Becerra | Carlos del Cerro | Virginia Rivero‐Buceta | M. Auxiliadora Prieto | Juan Nogales
Source: Cell Reports (article, 2024-03-22)
Field: Materials Science — Biomaterials

A model-driven approach to upcycling recalcitrant feedstocks in Pseudomonas putida by decoupling PHA production from nutrient limitation Bacterial polyhydroxyalkanoates (PHAs) have emerged as promising eco-friendly alternatives to petroleum-based plastics since they are synthesized from renewable resources and offer exceptional properties. However, their production is limited to the stationary growth phase under nutrient-limited conditions, requiring customized strategies and costly two-phase bioprocesses. In this study, we tackle these challenges by employing a model-driven approach to reroute carbon flux and remove regulatory constraints using synthetic biology. We construct a collection of Pseudomonas putida-overproducing strains at the expense of plastics and lignin-related compounds using growth-coupling approaches. PHA production was successfully achieved during growth phase, resulting in the production of up to 46% PHA/cell dry weight while maintaining a balanced carbon-to-nitrogen ratio. Our strains are additionally validated under an upcycling scenario using enzymatically hydrolyzed polyethylene terephthalate as a feedstock. These findings have the potential to revolutionize PHA production and address the global plastic crisis by overcoming the complexities of traditional PHA production bioprocesses. Polyhydroxyalkanoates ; Pseudomonas putida ; Biochemical engineering ; Metabolic flux analysis ; Raw material ; Production (economics) ; Biorefinery ; Bioprocess ; Synthetic biology ; Carbon source ; Pulp and paper industry ; Chemistry ; Biotechnology ; Biochemistry ; Organic chemistry ; Chemical engineering ; Biology ; Bacteria ; Metabolism ; Computational biology ; Engineering ; Economics biodegradable polymer synthesis and properties ; Microbial Metabolic Engineering and Bioproduction ; Biofuel production and bioconversion
Authors: Mingfei Pan | Tao Shui | Ziqian Zhao | Li Xiang | Bin Yan | Ning Gu | Hongbo Zeng
Source: National Science Review (review, 2024-09-09)
Field: Materials Science — Surfaces, Coatings and Films

Engineered Janus hydrogels: biomimetic surface engineering and biomedical applications Hydrogel bioadhesives, when applied to dysfunctional tissues substituting the epidermis or endothelium, exhibit compelling characteristics that enable revolutionary diagnostic and therapeutic procedures. Despite their demonstrated efficacy, these hydrogels as soft implants are still limited by improper symmetric surface functions, leading to postoperative complications and disorders. Janus hydrogel bioadhesives with unique asymmetric surface designs have thus been proposed as a reliable and biocompatible hydrogel interface, mimicking the structural characteristics of natural biological barriers. In this comprehensive review, we provide guidelines for the rational design of Janus hydrogel bioadhesives, covering methods for hydrogel surface chemistry and microstructure engineering. The engineering of Janus hydrogels is highlighted, specifically in tuning the basal surface to facilitate instant and robust hydrogel-tissue integration and modulating the apical surface as the anti-adhesion, anti-fouling, and anti-wear barrier. These asymmetric designs hold great potential in clinical translation, supporting applications including hemostasis/tissue sealing, chronic wound management, and regenerative medicine. By shedding light on the potential of Janus hydrogels as bioactive interfaces, this review paper aims to inspire further research and overcome current obstacles for advancing soft matter in next-generation healthcare. Self-healing hydrogels ; Janus ; Nanotechnology ; Materials science ; Tissue engineering ; Surface (topology) ; Biomedical engineering ; Polymer science ; Engineering ; Polymer chemistry ; Mathematics Polymer Surface Interaction Studies ; Electrospun Nanofibers in Biomedical Applications ; 3D Printing in Biomedical Research