jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Xiang He
Source: Nano-Micro Letters (review, 2023-06-07)
Field: Chemistry — Inorganic Chemistry

Fundamental Perspectives on the Electrochemical Water Applications of Metal–Organic Frameworks The recent development and implementation of metal-organic frameworks (MOFs) and MOF-based materials in electrochemical water applications are reviewed. The critical factors that affect the performances of MOFs in the electrochemical reactions, sensing, and separations are highlighted. Advanced tools, such as pair distribution function analysis, are playing critical roles in unraveling the functioning mechanisms, including local structures and nanoconfined interactions. Metal-organic frameworks (MOFs), a family of highly porous materials possessing huge surface areas and feasible chemical tunability, are emerging as critical functional materials to solve the growing challenges associated with energy-water systems, such as water scarcity issues. In this contribution, the roles of MOFs are highlighted in electrochemical-based water applications (i.e., reactions, sensing, and separations), where MOF-based functional materials exhibit outstanding performances in detecting/removing pollutants, recovering resources, and harvesting energies from different water sources. Compared with the pristine MOFs, the efficiency and/or selectivity can be further enhanced via rational structural modulation of MOFs (e.g., partial metal substitution) or integration of MOFs with other functional materials (e.g., metal clusters and reduced graphene oxide). Several key factors/properties that affect the performances of MOF-based materials are also reviewed, including electronic structures, nanoconfined effects, stability, conductivity, and atomic structures. The advancement in the fundamental understanding of these key factors is expected to shed light on the functioning mechanisms of MOFs (e.g., charge transfer pathways and guest-host interactions), which will subsequently accelerate the integration of precisely designed MOFs into electrochemical architectures to achieve highly effective water remediation with optimized selectivity and long-term stability. Metal-organic framework ; Electrochemistry ; Nanotechnology ; Materials science ; Environmental science ; Chemistry ; Electrode ; Adsorption Metal-Organic Frameworks: Synthesis and Applications ; Electrochemical Analysis and Applications ; Metal Extraction and Bioleaching
Authors: Ke Li | Nam V. Tran | Yuqing Pan | Sheng Wang | Zhicheng Jin | Guoliang Chen | Shuzhou Li | Jianwei Zheng | Xian Jun Loh | Zibiao Li
Source: Advanced Science (review, 2023-12-07)
Field: Materials Science — Polymers and Plastics

Next‐Generation Vitrimers Design through Theoretical Understanding and Computational Simulations Vitrimers are an innovative class of polymers that boast a remarkable fusion of mechanical and dynamic features, complemented by the added benefit of end-of-life recyclability. This extraordinary blend of properties makes them highly attractive for a variety of applications, such as the automotive sector, soft robotics, and the aerospace industry. At their core, vitrimer materials consist of crosslinked covalent networks that have the ability to dynamically reorganize in response to external factors, including temperature changes, pressure variations, or shifts in pH levels. In this review, the aim is to delve into the latest advancements in the theoretical understanding and computational design of vitrimers. The review begins by offering an overview of the fundamental principles that underlie the behavior of these materials, encompassing their structures, dynamic behavior, and reaction mechanisms. Subsequently, recent progress in the computational design of vitrimers is explored, with a focus on the employment of molecular dynamics (MD)/Monte Carlo (MC) simulations and density functional theory (DFT) calculations. Last, the existing challenges and prospective directions for this field are critically analyzed, emphasizing the necessity for additional theoretical and computational advancements, coupled with experimental validation. Aerospace ; Computational simulation ; Computer science ; Variety (cybernetics) ; Computational model ; Biochemical engineering ; Nanotechnology ; Automotive industry ; Field (mathematics) ; Systems engineering ; Mechanical engineering ; Statistical physics ; Artificial intelligence ; Materials science ; Computational science ; Aerospace engineering ; Engineering ; Physics ; Mathematics Polymer composites and self-healing ; Photochromic and Fluorescence Chemistry ; Advanced Polymer Synthesis and Characterization
Authors: Bowen Ma | Xiao Wu | Chunlin Zhao | Cong Lin | Min Gao | Baisheng Sa | Zhimei Sun
Source: npj Computational Materials (article, 2023-12-22)
Field: Materials Science — Materials Chemistry

An interpretable machine learning strategy for pursuing high piezoelectric coefficients in (K0.5Na0.5)NbO3-based ceramics Abstract Perovskite-type lead-free piezoelectric ceramics allow access to illustrious piezoelectric coefficients ( d 33 ) through intricate composition design and experimental modulation. Developing a swift and accurate technology for identifying (K, Na)NbO 3 (KNN)-based ceramic compositions with high d 33 in exceedingly large “compositional” space will establish an innovative research paradigm surpassing the traditional empirical trial-and-error method. Herein, we demonstrate an interpretable machine learning (ML) framework for quick evaluation of KNN-based ceramics with high d 33 based on data from published literature. Specifically, a thorough feature construction was carried out from the global and local dimensions to establish tree regression models with d 33 as the target property. Subsequently, the feature-property mapping rules of KNN-based piezoelectric ceramics are further optimized through feature screening. To intuitively understand the correlation mechanisms between ML regression targets and features, the sure independence screening and sparsifying operator (SISSO) method was employed to extract the essential descriptors to explain d 33 . A straightforward descriptor, $${\text{e}}^{({{NM}}_{\text{B}}-{{MV}}_{\text{B}})}\cdot {ST}/{(I{D}_{\text{A}})}^{2}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msup> <mml:mrow> <mml:mtext>e</mml:mtext> </mml:mrow> <mml:mrow> <mml:mo>(</mml:mo> <mml:msub> <mml:mrow> <mml:mi>NM</mml:mi> </mml:mrow> <mml:mrow> <mml:mtext>B</mml:mtext> </mml:mrow> </mml:msub> <mml:mo>−</mml:mo> <mml:msub> <mml:mrow> <mml:mi>MV</mml:mi> </mml:mrow> <mml:mrow> <mml:mtext>B</mml:mtext> </mml:mrow> </mml:msub> <mml:mo>)</mml:mo> </mml:mrow> </mml:msup> <mml:mo>⋅</mml:mo> <mml:mi>ST</mml:mi> <mml:mo>/</mml:mo> <mml:msup> <mml:mrow> <mml:mo>(</mml:mo> <mml:mi>I</mml:mi> <mml:msub> <mml:mrow> <mml:mi>D</mml:mi> </mml:mrow> <mml:mrow> <mml:mtext>A</mml:mtext> </mml:mrow> </mml:msub> <mml:mo>)</mml:mo> </mml:mrow> <mml:mrow> <mml:mn>2</mml:mn> </mml:mrow> </mml:msup> </mml:mrow> </mml:math> , consisting of only four easily accessible parameters, can accelerate the evaluation of a series of novel KNN-based ceramics with high d 33 while exhibiting strong theoretical interpretability. This work not only provides a tool for the rapid discovery of high piezoelectric performance in KNN-based ceramics but also offers a data-driven route for the design of property descriptors in perovskites. Artificial intelligence ; Computer science ; Algorithm ; Machine learning ; Ceramic ; Materials science Ferroelectric and Piezoelectric Materials ; Multiferroics and related materials ; Microwave Dielectric Ceramics Synthesis
Authors: Ziqi Guo | Prabudhya Roy Chowdhury | Zherui Han | Yixuan Sun | Dudong Feng | Guang Lin | Xiulin Ruan
Source: npj Computational Materials (article, 2023-06-02)
Field: Materials Science — Materials Chemistry

Fast and accurate machine learning prediction of phonon scattering rates and lattice thermal conductivity Abstract Lattice thermal conductivity is important for many applications, but experimental measurements or first principles calculations including three-phonon and four-phonon scattering are expensive or even unaffordable. Machine learning approaches that can achieve similar accuracy have been a long-standing open question. Despite recent progress, machine learning models using structural information as descriptors fall short of experimental or first principles accuracy. This study presents a machine learning approach that predicts phonon scattering rates and thermal conductivity with experimental and first principles accuracy. The success of our approach is enabled by mitigating computational challenges associated with the high skewness of phonon scattering rates and their complex contributions to the total thermal resistance. Transfer learning between different orders of phonon scattering can further improve the model performance. Our surrogates offer up to two orders of magnitude acceleration compared to first principles calculations and would enable large-scale thermal transport informatics. Phonon ; Thermal conductivity ; Phonon scattering ; Scattering ; Machine learning ; Artificial intelligence ; Computer science ; Condensed matter physics ; Materials science ; Statistical physics ; Physics ; Optics ; Thermodynamics Thermal properties of materials ; Advanced Thermoelectric Materials and Devices ; Thermal Expansion and Ionic Conductivity
Authors: Ian Campbell | Meng-Yen Lin | Hareesh Iyer | Mallory Parker | Jeremy L. Fredricks | Kuotian Liao | Andrew M. Jimenez | Paul Grandgeorge | Eleftheria Roumeli
Source: Annual Review of Materials Research (article, 2023-03-31)
Field: Materials Science — Biomaterials

Progress in Sustainable Polymers from Biological Matter The increasing consumption of nonrenewable materials urgently calls for the design and fabrication of sustainable alternatives. New generations of materials should be derived from renewable sources, processed using environmentally friendly methods, and designed considering their full life cycle, especially their end-of-life fate. Here, we review recent advances in developing sustainable polymers from biological matter (biomatter), including progress in the extraction and utilization of bioderived monomers and polymers, as well as the emergence of polymers produced directly from unprocessed biomatter (entire cells or tissues). We also discuss applications of sustainable polymers in bioplastics, biocomposites, and cementitious biomaterials, with emphasis on relating their performance to underlying fundamental mechanisms. Finally, we provide a future outlook for sustainable material development, highlighting the need for more accurate and accessible tools for assessing life-cycle impacts and socioeconomic challenges as this field advances. Biochemical engineering ; Renewable energy ; Environmentally friendly ; Life-cycle assessment ; Sustainable development ; Bioplastic ; Nanotechnology ; Sustainable energy ; Environmental science ; Materials science ; Engineering ; Production (economics) ; Waste management ; Economics ; Ecology biodegradable polymer synthesis and properties ; Microplastics and Plastic Pollution ; Additive Manufacturing and 3D Printing Technologies
Authors: Han Wang | Jason C. Mills | Boran Sun | Honggang Cui
Source: Progress in Polymer Science (article, 2023-12-02)
Field: Materials Science — Biomaterials

Therapeutic supramolecular polymers: Designs and applications Supramolecular chemistry ; Nanotechnology ; Supramolecular polymers ; Self-healing hydrogels ; Design elements and principles ; Materials science ; Chemistry ; Computer science ; Molecule Supramolecular Self-Assembly in Materials ; Supramolecular Chemistry and Complexes ; Nanoplatforms for cancer theranostics
Authors: Saphia A. L. Matthew | F. Philipp Seib
Source: ACS Biomaterials Science & Engineering (review, 2023-01-27)
Field: Materials Science — Biomaterials

Silk Bioconjugates: From Chemistry and Concept to Application Medical silks have captured global interest. While silk sutures have a long track record in humans, silk bioconjugates are still in preclinical development. This perspective examines key advances in silk bioconjugation, including the fabrication of silk-protein conjugates, bioconjugated silk particles, and bioconjugated substrates to enhance cell-material interactions in two and three dimensions. Many of these systems rely on chemical modification of the silk biopolymer, often using carbodiimide and reactive ester chemistries. However, recent progress in enzyme-mediated and click chemistries has expanded the molecular toolbox to enable biorthogonal, site-specific conjugation in a single step when combined with recombinant silk fibroin tagged with noncanonical amino acids. This perspective outlines key strategies available for chemical modification, compares the resulting silk conjugates to clinical benchmarks, and outlines open questions and areas that require more work. Overall, this assessment highlights a domain of new sunrise capabilities and development opportunities for silk bioconjugates that may ultimately offer new ways of delivering improved healthcare. SILK ; Bioconjugation ; Nanotechnology ; Fibroin ; Chemistry ; Polymer science ; Biopolymer ; Materials science ; Polymer ; Organic chemistry Silk-based biomaterials and applications ; Antimicrobial Peptides and Activities ; Biochemical and Structural Characterization
Authors: Frédéric Dumur
Source: European Polymer Journal (article, 2023-02-11)
Field: Chemistry — Organic Chemistry

The future of visible light photoinitiators of polymerization for photocrosslinking applications Photopolymer ; Polymerization ; Visible spectrum ; Nanotechnology ; Polymer ; Materials science ; Photochemistry ; Chemistry ; Optoelectronics Photopolymerization techniques and applications ; Advanced Polymer Synthesis and Characterization ; Photochromic and Fluorescence Chemistry
Authors: Maxime Van Haeverbeke | Bernard De Baets | Michiel Stock
Source: Computers and Electronics in Agriculture (article, 2023-09-22)
Field: Chemistry — Electrochemistry

Evaluating the potential of Distribution of Relaxation Times analysis for plant agriculture Dielectric spectroscopy ; Relaxation (psychology) ; Electrical impedance ; Computer science ; Agriculture ; Work (physics) ; Biological system ; Biochemical engineering ; Engineering ; Electrochemistry ; Electrical engineering ; Mechanical engineering ; Chemistry ; Biology ; Ecology Electrochemical Analysis and Applications ; Advanced Chemical Sensor Technologies
Authors: Ahmed H. Bakheit | Mohamed W. Attwa | Adnan A. Kadi | Hazem A. Ghabbour | Hamad M. Alkahtani
Source: Crystals (article, 2023-06-27)
Field: Chemistry — Organic Chemistry

Exploring the Chemical Reactivity, Molecular Docking, Molecular Dynamic Simulation and ADMET Properties of a Tetrahydrothienopyridine Derivative Using Computational Methods This study investigates the crystal structure, physicochemical properties, and pharmacokinetic profile of Ethyl 2-amino-6-methyl-4,5,6,7-tetrahydrothieno[2,3-c]pyridine-3-carboxylate (EAMT) as a potential therapeutic agent. The crystal structure was analyzed using Hirshfeld surface analysis in conjunction with the quantum theory of atoms in molecules (QT-AIM). Non-covalent interactions were evaluated through reduced-density gradient reduction, revealing that the EAMT crystal is stabilized by hydrogen bonds between EAMT molecules in the crystal and between EAMT molecules and water molecules. The molecular electrostatic nature of interactions was examined using MESP, while global and local descriptors were calculated to assess the compound’s reactivity. Molecular docking with the Adenosine A1 receptor was performed and validated through a 50 ns molecular dynamics simulation (MDS). Results suggest that EAMT influences protein structure, potentially stabilizing specific secondary structure elements. The compactness analysis showed a slightly more compact protein conformation and a marginally increased solvent exposure in the presence of the EAMT ligand, as indicated by Rg and SASA values. The total binding free energy (ΔG total) was determined to be −114.56 kcal/mol. ADMET predictions demonstrated EAMT’s compliance with Lipinski’s and Pfizer’s rule of five, indicating good oral availability. The compound may exhibit low-potency endocrine activity. In conclusion, EAMT presents potential as a therapeutic candidate, warranting further exploration of its molecular interactions, pharmacokinetics, and potential safety concerns. Chemistry ; Molecular dynamics ; Lipinski's rule of five ; Hydrogen bond ; Molecule ; Computational chemistry ; Density functional theory ; Docking (animal) ; Protein Data Bank (RCSB PDB) ; Molecular model ; Stereochemistry ; Organic chemistry ; In silico ; Biochemistry Chemical Reaction Mechanisms ; Synthesis and Biological Evaluation ; Synthesis and Characterization of Heterocyclic Compounds
Authors: Zahra Ebrahim Nataj | Youming Xu | Dylan Wright | Jonas Brown | Jivtesh Garg | Xi Chen | Fariborz Kargar | Alexander A. Balandin
Source: Nature Communications (article, 2023-06-02)
Field: Materials Science — Materials Chemistry

Cryogenic characteristics of graphene composites—evolution from thermal conductors to thermal insulators The development of cryogenic semiconductor electronics and superconducting quantum computing requires composite materials that can provide both thermal conduction and thermal insulation. We demonstrated that at cryogenic temperatures, the thermal conductivity of graphene composites can be both higher and lower than that of the reference pristine epoxy, depending on the graphene filler loading and temperature. There exists a well-defined cross-over temperature-above it, the thermal conductivity of composites increases with the addition of graphene; below it, the thermal conductivity decreases with the addition of graphene. The counter-intuitive trend was explained by the specificity of heat conduction at low temperatures: graphene fillers can serve as, both, the scattering centers for phonons in the matrix material and as the conduits of heat. We offer a physical model that explains the experimental trends by the increasing effect of the thermal boundary resistance at cryogenic temperatures and the anomalous thermal percolation threshold, which becomes temperature dependent. The obtained results suggest the possibility of using graphene composites for, both, removing the heat and thermally insulating components at cryogenic temperatures-a capability important for quantum computing and cryogenically cooled conventional electronics. Graphene ; Materials science ; Thermal conductivity ; Thermal conduction ; Composite material ; Interfacial thermal resistance ; Epoxy ; Thermal ; Percolation threshold ; Cryogenics ; Electronics ; Thermal resistance ; Superconductivity ; Thermal insulation ; Condensed matter physics ; Electrical resistivity and conductivity ; Nanotechnology ; Thermodynamics ; Chemistry Thermal properties of materials ; Graphene research and applications ; Thermal Radiation and Cooling Technologies
Authors: Jiaqi Wang | Zihan Liu | Shuang Zhao | Tengyan Xu | Huaimin Wang | Stan Z. Li | Wenbin Li
Source: Advanced Science (article, 2023-09-25)
Field: Materials Science — Biomaterials

Deep Learning Empowers the Discovery of Self‐Assembling Peptides with Over 10 Trillion Sequences Self-assembling of peptides is essential for a variety of biological and medical applications. However, it is challenging to investigate the self-assembling properties of peptides within the complete sequence space due to the enormous sequence quantities. Here, it is demonstrated that a transformer-based deep learning model is effective in predicting the aggregation propensity (AP) of peptide systems, even for decapeptide and mixed-pentapeptide systems with over 10 trillion sequence quantities. Based on the predicted AP values, not only the aggregation laws for designing self-assembling peptides are derived, but the transferability relation among the APs of pentapeptides, decapeptides, and mixed pentapeptides is also revealed, leading to discoveries of self-assembling peptides by concatenating or mixing, as consolidated by experiments. This deep learning approach enables speedy, accurate, and thorough search and design of self-assembling peptides within the complete sequence space of oligopeptides, advancing peptide science by inspiring new biological and medical applications. Pentapeptide repeat ; Peptide ; Sequence (biology) ; Computational biology ; Oligopeptide ; Deep learning ; Chemistry ; Homogeneous ; Computer science ; Combinatorial chemistry ; Nanotechnology ; Artificial intelligence ; Biology ; Biochemistry ; Materials science ; Physics Supramolecular Self-Assembly in Materials ; Chemical Synthesis and Analysis ; Antimicrobial Peptides and Activities
Authors: Ting Tang | Qing Luo | Yang Liu | Changlun Gao | Caijin Ling | Weibin Wu
Source: Foods (article, 2023-12-20)
Field: Chemistry — Analytical Chemistry

Research Review on Quality Detection of Fresh Tea Leaves Based on Spectral Technology As the raw material for tea making, the quality of tea leaves directly affects the quality of finished tea. The quality of fresh tea leaves is mainly assessed by manual judgment or physical and chemical testing of the content of internal components. Physical and chemical methods are more mature, and the test results are more accurate and objective, but traditional chemical methods for measuring the biochemical indexes of tea leaves are time-consuming, labor-costly, complicated, and destructive. With the rapid development of imaging and spectroscopic technology, spectroscopic technology as an emerging technology has been widely used in rapid non-destructive testing of the quality and safety of agricultural products. Due to the existence of spectral information with a low signal-to-noise ratio, high information redundancy, and strong autocorrelation, scholars have conducted a series of studies on spectral data preprocessing. The correlation between spectral data and target data is improved by smoothing noise reduction, correction, extraction of feature bands, and so on, to construct a stable, highly accurate estimation or discrimination model with strong generalization ability. There have been more research papers published on spectroscopic techniques to detect the quality of tea fresh leaves. This study summarizes the principles, analytical methods, and applications of Hyperspectral imaging (HSI) in the nondestructive testing of the quality and safety of fresh tea leaves for the purpose of tracking the latest research advances at home and abroad. At the same time, the principles and applications of other spectroscopic techniques including Near-infrared spectroscopy (NIRS), Mid-infrared spectroscopy (MIRS), Raman spectroscopy (RS), and other spectroscopic techniques for non-destructive testing of quality and safety of fresh tea leaves are also briefly introduced. Finally, in terms of technical obstacles and practical applications, the challenges and development trends of spectral analysis technology in the nondestructive assessment of tea leaf quality are examined. Hyperspectral imaging ; Computer science ; Preprocessor ; Smoothing ; Quality (philosophy) ; Artificial intelligence ; Near-infrared spectroscopy ; Remote sensing ; Pattern recognition (psychology) ; Biological system ; Environmental science ; Mathematics ; Computer vision ; Optics ; Physics ; Geography Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Remote Sensing in Agriculture