jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Mengze Li | Shuran Li | Yu Tian | Yihan Fu | Yanliang Pei | Weidong Zhu | Yinglin Ke
Source: Materials & Design (article, 2023-02-24)
Field: Materials Science — Materials Chemistry

A deep learning convolutional neural network and multi-layer perceptron hybrid fusion model for predicting the mechanical properties of carbon fiber Recently, deep learning methods have become one of the hottest topics in predicting material properties, however, one bottleneck in current research is the simultaneous analysis of heterogeneous data. In this study, a deep learning fusion model is developed for the first time to predict the material properties of carbon fiber monofilament using textual (macroscopic properties of composites and matrix) and visual (two-point statistics of microstructures) data. For this, 1200 stochastic microstructures are generated using the greedy-based generation (GBG) algorithm. Then, the statistical representations of microstructures are determined using two-point statistics and the macroscopic properties are calculated based on a micro-scale finite element (FE) simulation. Finally, the visual and textual data are fed into the convolutional neural network (CNN) and multi-layer perceptron (MLP) fusion model for predicting the mechanical properties of carbon fibers. The developed hybrid CNN-MLP fusion model achieves encouraging average testing R2 of longitudinal modulus, transverse modulus, in-plane shear modulus, major Poisson’s ratio, and out-of-plane shear modulus of carbon fibers with values of 0.991, 0.969, 0.984, 0.903, and 0.955, respectively. Thus, the proposed strategy provides a promising framework for predicting material properties via multisource heterogeneous data and is expected to accelerate the smart design and optimization of materials. Materials science ; Perceptron ; Convolutional neural network ; Artificial neural network ; Artificial intelligence ; Computer science Machine Learning in Materials Science ; Fiber-reinforced polymer composites ; Hydrogen embrittlement and corrosion behaviors in metals
Authors: Andrew J. Lew | Markus J. Buehler
Source: Materials Today (article, 2023-04-01)
Field: Materials Science — Materials Chemistry

Single-shot forward and inverse hierarchical architected materials design for nonlinear mechanical properties using an Attention-Diffusion model Nonlinear system ; Computer science ; Hierarchy ; Deformation (meteorology) ; Inverse ; Diffusion ; Smart material ; Materials science ; Nanotechnology ; Mathematics ; Physics ; Geometry Machine Learning in Materials Science ; Block Copolymer Self-Assembly ; Calcium Carbonate Crystallization and Inhibition
Authors: Yining Du | Mingyang Wang | Xiaoling Ye | Benqing Liu | Lei Han | Hassan Jafri | Wencheng Liu | Xiaoxiao Zheng | Yafei Ning | Hu Li
Source: Crystals (article, 2023-06-04)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Advances in the Field of Graphene-Based Composites for Energy–Storage Applications To meet the growing demand in energy, great efforts have been devoted to improving the performances of energy–storages. Graphene, a remarkable two-dimensional (2D) material, holds immense potential for improving energy–storage performance owing to its exceptional properties, such as a large-specific surface area, remarkable thermal conductivity, excellent mechanical strength, and high-electronic mobility. This review provides a comprehensive summary of recent research advancements in the application of graphene for energy–storage. Initially, the fundamental properties of graphene are introduced. Subsequently, the latest developments in graphene-based energy–storage, encompassing lithium-ion batteries, sodium-ion batteries, supercapacitors, potassium-ion batteries and aluminum-ion batteries, are summarized. Finally, the challenges associated with graphene-based energy–storage applications are discussed, and the development prospects for this field are outlined. Graphene ; Supercapacitor ; Energy storage ; Materials science ; Nanotechnology ; Lithium (medication) ; Chemistry ; Physics ; Electrochemistry ; Electrode Supercapacitor Materials and Fabrication ; Advancements in Battery Materials ; Advanced Battery Technologies Research
Authors: Wei Zhou | Zhien Liu | Wan Chen | Xianzhong Sun | Maji Luo | Xiaohu Zhang | Chen Li | Yabin An | Shuang Song | Kai Wang | Xiong Zhang
Source: Batteries (review, 2023-02-10)
Field: Materials Science — Electronic, Optical and Magnetic Materials

A Review on Thermal Behaviors and Thermal Management Systems for Supercapacitors As a representative electrochemical energy storage device, supercapacitors (SCs) feature higher energy density than traditional capacitors and better power density and cycle life compared to lithium-ion batteries, which explains why they are extensively applied in the field of energy storage. While the available reviews are mainly concerned with component materials, state estimation, and industrial applications, there is a shortage of understanding of thermal behaviors and thermal management systems of SCs, which makes this review a timely aide for fulfilling this gap. This review introduces the energy storage mechanisms of SCs, followed by descriptions of current investigations of thermal behaviors. This covers the aspects of heat generation rates for electric double-layer capacitors (EDLCs) and hybrid supercapacitors (HSCs), together with reviewing existing experimental methods to measure and estimate heat generation rates, as well as comparative assessments of multiple heat generation rate models and research on thermal runaway. In addition, there are also overviews of current efforts by researchers in air cooling systems, liquid cooling systems, phase change material cooling systems, and heat pipe cooling systems. Finally, an in-depth discussion is provided regarding the challenges and future work directions for SCs in thermal behaviors and thermal management systems. Supercapacitor ; Thermal energy storage ; Energy storage ; Heat generation ; Process engineering ; Capacitor ; Thermal ; Work (physics) ; Thermal energy ; Materials science ; Environmental science ; Computer cooling ; Water cooling ; Computer science ; Nuclear engineering ; Mechanical engineering ; Thermal management of electronic devices and systems ; Power (physics) ; Electrical engineering ; Engineering ; Thermodynamics ; Capacitance ; Voltage Supercapacitor Materials and Fabrication ; Advanced Battery Materials and Technologies ; Advanced battery technologies research
Authors: Shuya Guo | Xiaoshan Huang | Yizhen Situ | Qiuhong Huang | Kexin Guan | Jiaxin Huang | Wei Wang | Xiangning Bai | Zili Liu | Yufang Wu | Zhiwei Qiao
Source: Advanced Science (article, 2023-05-11)
Field: Chemistry — Inorganic Chemistry

Interpretable Machine‐Learning and Big Data Mining to Predict Gas Diffusivity in Metal‐Organic Frameworks For gas separation and catalysis by metal-organic frameworks (MOFs), gas diffusion has a substantial impact on the process' overall rate, so it is necessary to determine the molecular diffusion behavior within the MOFs. In this study, an interpretable machine learing (ML) model, light gradient boosting machine (LGBM), is trained to predict the molecular diffusivity and selectivity of 9 gases (Kr, Xe, CH<sub>4</sub> , N<sub>2</sub> , H<sub>2</sub> S, O<sub>2</sub> , CO<sub>2</sub> , H<sub>2</sub> , and He). For these 9 gases, LGBM displays high accuracy (average R<sup>2</sup> = 0.962) and superior extrapolation for the diffusivity of C<sub>2</sub> H<sub>6</sub> . And this model calculation is five orders of magnitude faster than molecular dynamics (MD) simulations. Subsequently, using the trained LGBM model, an interactive desktop application is developed that can help researchers quickly and accurately calculate the diffusion of molecules in porous crystal materials. Finally, the authors find the difference in the molecular polarizability (ΔPol) is the key factor governing the diffusion selectivity by combining the trained LGBM model with the Shapley additive explanation (SHAP). By the calculation of interpretable ML, the optimal MOFs are selected for separating binary gas mixtures and CO<sub>2</sub> methanation. This work provides a new direction for exploring the structure-property relationships of MOFs and realizing the rapid calculation of molecular diffusivity. Thermal diffusivity ; Metal-organic framework ; Big data ; Computer science ; Artificial intelligence ; Data mining ; Materials science ; Machine learning ; Data science ; Thermodynamics ; Chemistry ; Physical chemistry ; Physics Metal-Organic Frameworks: Synthesis and Applications ; Machine Learning in Materials Science ; Enhanced Oil Recovery Techniques
Authors: Davide Campi | Nicolas Mounet | Marco Gibertini | Giovanni Pizzi | Nicola Marzari
Source: ACS Nano (article, 2023-06-13)
Field: Materials Science — Materials Chemistry

Expansion of the Materials Cloud 2D Database Two-dimensional (2D) materials are among the most promising candidates for beyond-silicon electronic, optoelectronic, and quantum computing applications. Recently, their recognized importance sparked a push to discover and characterize novel 2D materials. Within a few years, the number of experimentally exfoliated or synthesized 2D materials went from a few to more than a hundred, with the number of theoretically predicted compounds reaching a few thousand. In 2018 we first contributed to this effort with the identification of 1825 compounds that are either easily (1036) or potentially (789) exfoliable from experimentally known 3D compounds. Here, we report on a major expansion of this 2D portfolio thanks to the extension of the screening protocol to an additional experimental database (MPDS) as well as the updated versions of the two databases (ICSD and COD) used in our previous work. This expansion leads to the discovery of an additional 1252 monolayers, bringing the total to 3077 compounds and, notably, almost doubling the number of easily exfoliable materials to 2004. We optimize the structural properties of all these monolayers and explore their electronic structure with a particular emphasis on those rare large-bandgap 2D materials that could be precious in isolating 2D field-effect-transistor channels. Finally, for each material containing up to 6 atoms per unit cell, we identify the best candidates to form commensurate heterostructures, balancing requirements on supercell size and minimal strain. Monolayer ; Materials science ; Heterojunction ; Band gap ; Nanotechnology ; Computer science ; Database ; Optoelectronics 2D Materials and Applications ; MXene and MAX Phase Materials ; Electronic and Structural Properties of Oxides
Authors: Jian Wei You | Qian Ma | Lei Zhang | Che Liu | Jianan Zhang | Shuo Liu | Tie Jun Cui
Source: Electromagnetic Science (article, 2023-03-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Electromagnetic Metamaterials: From Classical to Quantum Electromagnetic (EM) metamaterials are artificially engineered materials with extraordinary EM properties beyond the limit of existing natural materials; thus, they have been widely used to manipulate the amplitude, phase, polarization, frequency, wave vector, waveform, and other degrees of freedom of EM waves in many practical applications. In this review, we will summarize recent advances in this flourishing field of EM metamaterials, first from the perspectives of the classical regime and then the quantum regime. More specifically, in the classical regime, traditional EM metamaterials are based on effective medium theory, and they have limitations of fixed functionalities and an inability to control EM waves in real time. To overcome these restrictions, information metamaterials, including digital coding and field-programmable metamaterials, have recently been proposed to enable real-time manipulation of EM waves based on the theory of information science. By taking advantage of information metamaterials and artificial intelligence, another crucial milestone of intelligent metamaterials has been achieved in the development of classical metamaterials. After overviewing EM metamaterials in the classical regime, we discuss cutting-edge studies of EM metamaterials in the quantum regime, namely, topological metamaterials and quantum metamaterials. These nonclassical metamaterials show excellent ability to flexibly manipulate the quantum states, and they extend the classical information metamaterials into the field of quantum information science. At the end of this review, we will give some conclusions and perspectives on this fast-evolving field. Metamaterial ; Quantum ; Physics ; Metamaterial cloaking ; Quantum mechanics ; Theoretical physics ; Metamaterial absorber ; Tunable metamaterials Metamaterials and Metasurfaces Applications ; Quantum Mechanics and Non-Hermitian Physics ; Plasmonic and Surface Plasmon Research
Authors: Katie Reilly | Laura‐Jayne A. Ellis | Hossein Hayat Davoudi | Suffeiya Supian | Marcella Torres Maia | Gabriela H. Silva | Zhiling Guo | Diego Stéfani T. Martinez | Iseult Lynch
Source: Frontiers in Toxicology (review, 2023-04-14)
Field: Materials Science — Materials Chemistry

Daphnia as a model organism to probe biological responses to nanomaterials—from individual to population effects via adverse outcome pathways The importance of the cladoceran <i>Daphnia</i> as a model organism for ecotoxicity testing has been well-established since the 1980s. <i>Daphnia</i> have been increasingly used in standardised testing of chemicals as they are well characterised and show sensitivity to pollutants, making them an essential indicator species for environmental stress. The mapping of the genomes of <i>D. pulex</i> in 2012 and <i>D. magna</i> in 2017 further consolidated their utility for ecotoxicity testing, including demonstrating the responsiveness of the <i>Daphnia</i> genome to environmental stressors. The short lifecycle and parthenogenetic reproduction make <i>Daphnia</i> useful for assessment of developmental toxicity and adaption to stress. The emergence of nanomaterials (NMs) and their safety assessment has introduced some challenges to the use of standard toxicity tests which were developed for soluble chemicals. NMs have enormous reactive surface areas resulting in dynamic interactions with dissolved organic carbon, proteins and other biomolecules in their surroundings leading to a myriad of physical, chemical, biological, and macromolecular transformations of the NMs and thus changes in their bioavailability to, and impacts on, daphnids. However, NM safety assessments are also driving innovations in our approaches to toxicity testing, for both chemicals and other emerging contaminants such as microplastics (MPs). These advances include establishing more realistic environmental exposures via medium composition tuning including pre-conditioning by the organisms to provide relevant biomolecules as background, development of microfluidics approaches to mimic environmental flow conditions typical in streams, utilisation of field daphnids cultured in the lab to assess adaption and impacts of pre-exposure to pollution gradients, and of course development of mechanistic insights to connect the first encounter with NMs or MPs to an adverse outcome, via the key events in an adverse outcome pathway. Insights into these developments are presented below to inspire further advances and utilisation of these important organisms as part of an overall environmental risk assessment of NMs and MPs impacts, including in mixture exposure scenarios. Adverse Outcome Pathway ; Organism ; Daphnia ; Population ; Model organism ; Outcome (game theory) ; Population model ; Biology ; Neuroscience ; Ecology ; Medicine ; Environmental health ; Computational biology ; Genetics ; Mathematics Nanoparticles: synthesis and applications
Authors: Fan Yang | Mikhail Y. Shalaginov | Hung‐I Lin | Sensong An | Anu Agarwal | Hualiang Zhang | Clara Rivero‐Baleine | Tian Gu | Juejun Hu
Source: Advanced Photonics (article, 2023-05-23)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Wide field-of-view metalens: a tutorial Wide field-of-view (FOV) optics are essential components in many optical systems, with applications spanning imaging, display, sensing, and beam steering. Conventional refractive wide FOV optics often involve multiple stacked lenses, resulting in large size and weight as well as high cost. Metasurface lenses or metalenses promise a viable solution to realizing wide FOV optics without complex lens assembly. We review the various architectures of wide FOV metalenses, elucidate their fundamental operating principles and design trade-offs, and quantitatively evaluate and contrast their imaging performances. Emerging applications enabled by wide FOV metasurface optics are also discussed. Optics ; Lens (geology) ; Field of view ; Beam steering ; Computer science ; Physics ; Beam (structure) Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Optical Coatings and Gratings
Authors: Guowei Kang | Daniel A. Strassfeld | Tao Sheng | Chia-Yu Chen | Jin‐Quan Yu
Source: Nature (article, 2023-05-31)
Field: Chemistry — Organic Chemistry

Transannular C–H functionalization of cycloalkane carboxylic acids Chemistry ; Cycloalkane ; Cyclooctane ; Cyclobutane ; Combinatorial chemistry ; Regioselectivity ; Molecule ; Ring (chemistry) ; Stereochemistry ; Organic chemistry ; Cyclohexane ; Catalysis Catalytic C–H Functionalization Methods ; Synthesis and Catalytic Reactions ; Radical Photochemical Reactions
Authors: Adewale George Adeniyi | Kingsley O. Iwuozor | Ebuka Chizitere Emenike | Patience A. Sagboye | Kehinde Temitope Micheal | Taiwo Temitayo Micheal | Oluwaseyi D. Saliu | R. Kermode James
Source: Journal of Cleaner Production (review, 2023-09-06)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Biomass-derived activated carbon monoliths: A review of production routes, performance, and commercialization potential Commercialization ; Biomass (ecology) ; Activated carbon ; Carbonization ; Raw material ; Environmental science ; Monolith ; Process engineering ; Waste management ; Materials science ; Business ; Engineering ; Adsorption ; Catalysis ; Chemistry Supercapacitor Materials and Fabrication ; Catalysis for Biomass Conversion ; Electrocatalysts for Energy Conversion
Authors: Madhukiran R. Dhondale | Pradip Thakor | Amritha G. Nambiar | Maan Singh | Ashish Kumar Agrawal | Nalini R. Shastri | Dinesh Kumar
Source: Pharmaceutics (review, 2023-01-05)
Field: Chemistry — Organic Chemistry

Co-Crystallization Approach to Enhance the Stability of Moisture-Sensitive Drugs Stability is an essential quality attribute of any pharmaceutical formulation. Poor stability can change the color and physical appearance of a drug, directly impacting the patient's perception. Unstable drug products may also face loss of active pharmaceutical ingredients (APIs) and degradation, making the medicine ineffective and toxic. Moisture content is known to be the leading cause of the degradation of nearly 50% of medicinal products, leading to impurities in solid dose formulations. The polarity of the atoms in an API and the surface chemistry of API particles majorly influence the affinity towards water molecules. Moisture induces chemical reactions, including free water that has also been identified as an important factor in determining drug product stability. Among the various approaches, crystal engineering and specifically co-crystals, have a proven ability to increase the stability of moisture-sensitive APIs. Other approaches, such as changing the salt form, can lead to solubility issues, thus making the co-crystal approach more suited to enhancing hygroscopic stability. There are many reported studies where co-crystals have exhibited reduced hygroscopicity compared to pure API, thereby improving the product's stability. In this review, the authors focus on recent updates and trends in these studies related to improving the hygroscopic stability of compounds, discuss the reasons behind the enhanced stability, and briefly discuss the screening of co-formers for moisture-sensitive drugs. Crystallization ; Moisture ; Chemistry ; Chemical engineering ; Nanotechnology ; Materials science ; Engineering ; Organic chemistry Chemical Thermodynamics and Molecular Structure ; Crystallization and Solubility Studies ; Crystallography and molecular interactions
Authors: Saša Kovačević | Wahaaj Ali | Emilio Martínez‐Pañeda | Javier LLorca
Source: Acta Biomaterialia (article, 2023-04-15)
Field: Materials Science — Biomaterials

Phase-field modeling of pitting and mechanically-assisted corrosion of Mg alloys for biomedical applications A phase-field model is developed to simulate the corrosion of Mg alloys in body fluids. The model incorporates both Mg dissolution and the transport of Mg ions in solution, naturally predicting the transition from activation-controlled to diffusion-controlled bio-corrosion. In addition to uniform corrosion, the presented framework captures pitting corrosion and accounts for the synergistic effect of aggressive environments and mechanical loading in accelerating corrosion kinetics. The model applies to arbitrary 2D and 3D geometries with no special treatment for the evolution of the corrosion front, which is described using a diffuse interface approach. Experiments are conducted to validate the model and a good agreement is attained against in vitro measurements on Mg wires. The potential of the model to capture mechano-chemical effects during corrosion is demonstrated in case studies considering Mg wires in tension and bioabsorbable coronary Mg stents subjected to mechanical loading. The proposed methodology can be used to assess the in vitro and in vivo service life of Mg-based biomedical devices and optimize the design taking into account the effect of mechanical deformation on the corrosion rate. The model has the potential to advocate further development of Mg alloys as a biodegradable implant material for biomedical applications. STATEMENT OF SIGNIFICANCE: A physically-based model is developed to simulate the corrosion of bioabsorbable metals in environments that resemble biological fluids. The model captures pitting corrosion and incorporates the role of mechanical fields in enhancing the corrosion of bioabsorbable metals. Model predictions are validated against dedicated in vitro corrosion experiments on Mg wires. The potential of the model to capture mechano-chemical effects is demonstrated in representative examples. The simulations show that the presence of mechanical fields leads to the formation of cracks accelerating the failure of Mg wires, whereas pitting severely compromises the structural integrity of coronary Mg stents. This work extends phase-field modeling to bioengineering and provides a mechanistic tool for assessing the service life of bioabsorbable metallic biomedical devices. Corrosion ; Materials science ; Pitting corrosion ; Dissolution ; Diffusion ; Metallurgy ; Composite material ; Chemical engineering ; Thermodynamics Magnesium Alloys: Properties and Applications ; Aluminum Alloy Microstructure Properties ; Aluminum Alloys Composites Properties