jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Shupei Liu | Yunlei Zhou | Jian Zhou | Hao Tang | Fei Gao | Decheng Zhao | Jinghui Ren | Yutong Wu | Zhoulu Wang | Yang Luo | Xiang Liu | Yi Zhang
Source: Nanophotonics (review, 2022-06-08)
Field: Materials Science — Materials Chemistry

Ti <sub>3</sub> C <sub>2</sub> T <sub> <i>x</i> </sub> MXenes‐based flexible materials for electrochemical energy storage and solar energy conversion Over the past decade, two-dimensional (2D) Ti<sub>3</sub>C<sub>2</sub>T <sub><i>x</i></sub> MXenes demonstrated attractive characteristics such as high electrical conductivity, tunable layered structure, controllable interfacial chemical composition, high optical transparency, and excellent electromagnetic wave absorption, enabling Ti<sub>3</sub>C<sub>2</sub>T <sub><i>x</i></sub> MXenes as promising electrode materials in energy storage devices. Among these devices, flexible energy storage devices have attracted wide attention and developed rapidly due to the synchronously excellent electrochemical and mechanical properties. This review summarizes the recent progress of Ti<sub>3</sub>C<sub>2</sub>T <sub><i>x</i></sub> MXenes pertaining to novel material preparation and promising applications in energy storage and conversion including batteries, supercapacitors, solar cells, and solar steam generation. This work aims to provide an in-depth and reasonable understanding of the relationship between the unique nanostructure/chemical composition of Ti<sub>3</sub>C<sub>2</sub>T <sub><i>x</i></sub> MXenes and competitive electrochemical properties, which will facilitate the development of 2D Ti<sub>3</sub>C<sub>2</sub>T <sub><i>x</i></sub> MXenes for practical energy storage and solar energy conversion devices. MXenes ; Energy transformation ; Materials science ; Energy storage ; Nanomaterials ; Electrochemical energy conversion ; Electrochemistry ; Solar energy ; Electrochemical energy storage ; Solar energy conversion ; Direct energy conversion ; Engineering physics ; Nanotechnology ; Optoelectronics ; Physics ; Supercapacitor ; Chemistry ; Electrode ; Physical chemistry ; Electrical engineering ; Thermodynamics MXene and MAX Phase Materials ; 2D Materials and Applications ; Advanced Photocatalysis Techniques
Authors: Jonathan Quinson
Source: Current Opinion in Electrochemistry (article, 2022-03-18)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Colloidal surfactant-free syntheses of precious metal nanoparticles for electrocatalysis The successful study, understanding, optimization, and ultimately scaling up of electroactive and stable electrodes strongly rely on the careful design and preparation of electrocatalytic materials. In particular, precious metal nanoparticles are key electrocatalysts for a wide range of reactions. Colloidal syntheses offer several advantages to develop precious metal nanoparticles but unfortunately often require capping agents to stabilize the nanoparticles. These ligands or surfactants often block the surface active sites and need to be removed by time and/or energy demanding steps. These extra steps potentially (unnecessarily) complicate studies, might impair reproducibility and limit a direct transfer of fundamental breakthroughs to real-life applications. Fortunately, a range of surfactant-free syntheses have been reported and are well-suited to develop electrocatalysts with improved activity. Surfactant-free syntheses also bear promising features towards high-throughput screening of multi-metallic nanomaterials to explore new concepts in electrode design. Electrocatalyst ; Nanotechnology ; Nanoparticle ; Nanomaterials ; Materials science ; Electrode ; Pulmonary surfactant ; Chemistry ; Electrochemistry Gold and Silver Nanoparticles Synthesis and Applications ; Electrochemical Analysis and Applications ; Electrocatalysts for Energy Conversion
Authors: Aditya Koneru | Rohit Batra | Sukriti Manna | Troy D. Loeffler | Henry Chan | Michael Sternberg | Anthony Avarca | Harpal Singh | Mathew J. Cherukara | Subramanian K. R. S. Sankaranarayanan
Source: The Journal of Physical Chemistry Letters (article, 2022-02-17)
Field: Materials Science — Materials Chemistry

Multi-reward Reinforcement Learning Based Bond-Order Potential to Study Strain-Assisted Phase Transitions in Phosphorene We introduce a multi-reward reinforcement learning (RL) approach to train a flexible bond-order potential (BOP) for 2D phosphorene based on ab initio training data sets. Our approach is based on a continuous action space Monte Carlo tree search algorithm that is general and scalable and presents an efficient multiobjective optimization scheme for high-dimensional materials design problems. As a proof-of-concept, we deploy this scheme to parametrize multiple structural and dynamical properties of 2D phosphorene polymorphs. Our RL-trained BOP model adequately captures the structure, energetics, transformation barriers, equation of state, elastic constants, and phonon dispersions of various 2D P polymorphs. We use this model to probe the impact of temperature and strain rate on the phase transition from black (α-P) to blue phosphorene (β-P) through molecular dynamics simulations. A decrease in critical strain for this phase transition with increase in temperature is observed, and the underlying atomistic mechanisms are discussed. Phosphorene ; Reinforcement learning ; Materials science ; Statistical physics ; Monte Carlo method ; Phase transition ; Ab initio ; Phonon ; Scalability ; Computer science ; Nanotechnology ; Thermodynamics ; Mathematics ; Physics ; Condensed matter physics ; Machine learning ; Quantum mechanics Machine Learning in Materials Science ; 2D Materials and Applications ; MXene and MAX Phase Materials
Authors: Yue Zhang | Cong Wang | Mya Soukaseum | Dionisios G. Vlachos | Hui Fang
Source: Journal of Chemical Information and Modeling (review, 2022-06-30)
Field: Materials Science — Materials Chemistry

Unleashing the Power of Knowledge Extraction from Scientific Literature in Catalysis Valuable knowledge of catalysis is often hidden in a large amount of scientific literature. There is an urgent need to extract useful knowledge to facilitate scientific discovery. This work takes the first step toward the goal in the field of catalysis. Specifically, we construct the first information extraction benchmark data set that covers the field of catalysis and also develop a general extraction framework that can accurately extract catalysis-related entities from scientific literature with 90% extraction accuracy. We further demonstrate the feasibility of leveraging the extracted knowledge to help users better access relevant information in catalysis through an entity-aware search engine and a correlation analysis system. Construct (python library) ; Benchmark (surveying) ; Computer science ; Field (mathematics) ; Knowledge extraction ; Scientific literature ; Set (abstract data type) ; Scientific field ; Information extraction ; Data science ; Information retrieval ; Work (physics) ; Knowledge management ; Data mining ; Engineering ; Mathematics Machine Learning in Materials Science ; Data Quality and Management ; Web Data Mining and Analysis
Authors: Neal Munyebvu | Esmé Lane | Enrico Grisan | Philip D. Howes
Source: Materials Advances (article, 2022-01-01)
Field: Materials Science — Materials Chemistry

Accelerating colloidal quantum dot innovation with algorithms and automation This review discusses how high-throughput experimentation and data-driven strategies, such as the use of machine learning models, are being used to enable rapid advances in colloidal quantum dot technologies. Automation ; Quantum dot ; Computer science ; Throughput ; Quantum ; Nanotechnology ; Colloid ; Algorithm ; Engineering ; Materials science ; Physics ; Mechanical engineering ; Quantum mechanics ; Telecommunications Quantum Dots Synthesis And Properties ; Gold and Silver Nanoparticles Synthesis and Applications ; Nanocluster Synthesis and Applications
Authors: Xujie Liu | Yang Wang | Jiongpeng Yuan | Xiaojing Li | Siwei Wu | Ying Bao | Zhenzhen Feng | Feilong Ou | Yan He
Source: Bioengineering (article, 2022-09-30)
Field: Chemistry — Inorganic Chemistry

Prediction of the Ibuprofen Loading Capacity of MOFs by Machine Learning Metal-organic frameworks (MOFs) have been widely researched as drug delivery systems due to their intrinsic porous structures. Herein, machine learning (ML) technologies were applied for the screening of MOFs with high drug loading capacity. To achieve this, first, a comprehensive dataset was gathered, including 40 data points from more than 100 different publications. The organic linkers, metal ions, and the functional groups, as well as the surface area and the pore volume of the investigated MOFs, were chosen as the model's inputs, and the output was the ibuprofen (IBU) loading capacity. Thereafter, various advanced and powerful machine learning algorithms, such as support vector regression (SVR), random forest (RF), adaptive boosting (AdaBoost), and categorical boosting (CatBoost), were employed to predict the ibuprofen loading capacity of MOFs. The coefficient of determination (R<sup>2</sup>) of 0.70, 0.72, 0.66, and 0.76 were obtained for the SVR, RF, AdaBoost, and CatBoost approaches, respectively. Among all the algorithms, CatBoost was the most reliable, exhibiting superior performance regarding the sparse matrices and categorical features. Shapley additive explanations (SHAP) analysis was employed to explore the impact of the eigenvalues of the model's outputs. Our initial results indicate that this methodology is a well generalized, straightforward, and cost-effective method that can be applied not only for the prediction of IBU loading capacity, but also in many other biomaterials projects. AdaBoost ; Boosting (machine learning) ; Categorical variable ; Gradient boosting ; Support vector machine ; Random forest ; Machine learning ; Artificial intelligence ; Computer science Metal-Organic Frameworks: Synthesis and Applications ; Crystallography and molecular interactions ; X-ray Diffraction in Crystallography
Authors: Kazem Adavi | Ahmadreza Amini | Mohammad Latifi | Jaber Shabanian | Jamal Chaouki
Source: Frontiers in Chemical Engineering (article, 2022-11-01)
Field: Chemistry — Organic Chemistry

Kinetic study of multiphase reactions under microwave irradiation: A mini-review Microwave (MW) heating is rapid, selective, and volumetric, and it is a compelling non-conventional heating approach for driving chemical reactions. The effect of MW irradiation on the kinetics of thermal/catalytic reactions is still under debate. A group of researchers reported that the effect of MW heating on reaction kinetics is highlighted through the non-thermal effects of MWs on kinetic parameters and reaction mechanisms in addition to the thermal effect. However, another group attributed the observations to the thermal effect only. In the present work, we summarized and critically synthesized available information in the literature on the subject. It can be concluded that MW heating has solely the thermal effect on gas-solid reactions, and the variations of kinetic parameters are related to the direct and indirect impacts of that. Temperature measurement limitations, physical structure variation, and non-uniform temperature distribution are the primary sources of the discrepancy in previous studies. In ionic liquid-solid reactions, the presence of electromagnetic fields can affect the movement of ions/polar molecules which can be considered a non-thermal effect of MWs. However, the effect of MW absorption by solid/catalyst, and the formation of hot spots must be taken into account to avoid potential discrepancy. Therefore, further theoretical/experimental studies are required to clarify the effect of MWs on liquid-solid reactions. In addition, developing reliable temperature measurement methods and isothermal reaction domain are required for an accurate kinetic study during MW irradiation. Isothermal process ; Kinetic energy ; Thermal ; Irradiation ; Chemical kinetics ; Microwave ; Thermodynamics ; Kinetics ; Chemical reaction ; Materials science ; Chemistry ; Catalysis ; Work (physics) ; Physical chemistry ; Chemical physics ; Organic chemistry Microwave-Assisted Synthesis and Applications ; Ammonia Synthesis and Nitrogen Reduction ; Catalysis and Hydrodesulfurization Studies
Authors: Priyanka Priyadarshini | Subhashree Das | D. Alagarasan | R. Ganesan | S. Varadharajaperumal | Susanta Kumar Sahoo | Ramakanta Naik
Source: RSC Advances (article, 2022-01-01)
Field: Materials Science — Materials Chemistry

The impact of fluence dependent proton ion irradiation on the structural and optical properties of Bi<sub>5</sub>In<sub>30</sub>Se<sub>65</sub> thin films for nonlinear optical devices This paper reports the effects of ion irradiation on the structural, linear, and nonlinear optical properties of thermally evaporated Bi<sub>5</sub>In<sub>30</sub>Se<sub>65</sub> thin films. The prepared films were irradiated with 30 keV proton ions with different fluences, such as 5 × 10<sup>15</sup> ions per cm<sup>2</sup>, 1 × 10<sup>16</sup> ions per cm<sup>2</sup>, and 5 × 10<sup>16</sup> ions per cm<sup>2</sup>. Structural analysis <i>via</i> X-ray diffraction (XRD) confirmed the non-crystalline nature of the film after ion irradiation with different doses. However, after the irradiation dose, the surface morphology changed, as shown by atomic force microscopy (AFM) images and field emission scanning electron microscopy (FESEM) images. The compositions of the films were obtained using energy-dispersive X-ray spectroscopy (EDX). Optical analysis <i>via</i> UV-Visible spectroscopy showed a reduction in the transmittance and an increase in the absorption in the higher wavelength region with irradiation. The optical bandgap and Tauc parameter decreased with an increase in the irradiation fluence, which is due to an increase in the irradiation-induced defects and disorder inside the system. The increases in the third order nonlinear susceptibility and the nonlinear refractive index with ion fluence are useful for nonlinear optical applications. The linear refractive index calculated from the transmittance data increased, satisfying Moss's rule. The optical parameters, such as lattice dielectric constant, optical density, skin depth, optical conductivity, real and imaginary dielectric constants, optical conductivity, loss factor, VELF, and SELF, were calculated using several empirical relationships and showed increasing behavior with the ion irradiation dose. The changes obtained in both the linear and nonlinear parameters will be useful for nonlinear optical device applications. Irradiation ; Materials science ; Fluence ; Refractive index ; Ion ; Transmittance ; Dielectric ; Analytical Chemistry (journal) ; Thin film ; Optical conductivity ; Band gap ; Spectroscopy ; Scanning electron microscope ; Optics ; Optoelectronics ; Chemistry ; Nanotechnology Phase-change materials and chalcogenides ; Chalcogenide Semiconductor Thin Films ; Nonlinear Optical Materials Studies
Authors: Fei Long | Shengli Jiang | Adeyinka Gbenga Adekunle | Ví­ctor M. Zavala | Ezra Bar‐Ziv
Source: ACS Sustainable Chemistry & Engineering (article, 2022-11-18)
Field: Chemistry — Analytical Chemistry

Online Characterization of Mixed Plastic Waste Using Machine Learning and Mid-Infrared Spectroscopy To recycle the mixed plastic wastes (MPW), it is important to obtain the compositional information online in real time. We present a sensing framework based on a convolutional neural network (CNN) and mid-infrared spectroscopy (MIR) for the rapid and accurate characterization of MPW. The MPW samples are placed on a moving platform to mimic the industrial environment. The MIR spectra are collected at the rate of 100 Hz, and the proposed CNN architecture can reach an overall prediction accuracy close to 100%. Therefore, the proposed method paves the way toward the online MPW characterization in industrial applications where high throughput is needed. Characterization (materials science) ; Convolutional neural network ; Plastic waste ; Spectroscopy ; Infrared ; Infrared spectroscopy ; Computer science ; Throughput ; Process engineering ; Environmental science ; Artificial intelligence ; Materials science ; Nanotechnology ; Waste management ; Chemistry ; Engineering ; Optics ; Telecommunications ; Organic chemistry ; Physics Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Andrea Ehrmann | Tomasz Błachowicz | Guido Ehrmann | Thomas Grethe
Source: Applied Research (article, 2022-06-22)
Field: Materials Science — Materials Chemistry

Recent developments in phase‐change memory Abstract Phase‐change memory (PCM) belongs to the nonvolatile solid‐state memory techniques. Usually, a chalcogenide is sandwiched between two conductive electrodes and data are stored by setting each cell to a low‐resistance (crystalline) or a high‐resistance (amorphous) state. Switching between these states is relatively fast, which makes phase‐change random access memories (PCRAMs) highly interesting for nonvolatile memories. Multilevel cells, which can store more than 1 bit per cell, and multilayer high‐density memory arrays have also been reported as advantages of PCRAM. Writing currents and data retention, on the other hand, still show potential for optimization. This review gives an overview of the most recent developments in new material compositions and material‐related optimization of PCM in comparison with already produced PCM. Phase-change memory ; Data retention ; Chalcogenide ; Non-volatile memory ; Materials science ; Phase change ; Amorphous solid ; Random access memory ; Computer science ; Optoelectronics ; Nanotechnology ; Engineering physics ; Computer hardware ; Engineering ; Chemistry Phase-change materials and chalcogenides ; Advanced Memory and Neural Computing ; Transition Metal Oxide Nanomaterials
Authors: Jianmin Zhou | Yixin Zhou | Weiwei Tang
Source: Crystals (article, 2022-07-14)
Field: Materials Science — Materials Chemistry

Molecular Mechanism of Organic Crystal Nucleation: A Perspective of Solution Chemistry and Polymorphism Crystal nucleation determining the formation and assembly pathway of first organic materials is the central science of various scientific disciplines such as chemical, geochemical, biological, and synthetic materials. However, our current understanding of the molecular mechanisms of nucleation remains limited. Over the past decades, the advancements of new experimental and computational techniques have renewed numerous interests in detailed molecular mechanisms of crystal nucleation, especially structure evolution and solution chemistry. These efforts bifurcate into two categories: (modified) classical nucleation theory (CNT) and non-classical nucleation mechanisms. In this review, we briefly introduce the two nucleation mechanisms and summarize current molecular understandings of crystal nucleation that are specifically applied in polymorphic crystallization systems of small organic molecules. Many important aspects of crystal nucleation including molecular association, solvation, aromatic interactions, and hierarchy in intermolecular interactions were examined and discussed for a series of organic molecular systems. The new understandings relating to molecular self-assembly in nucleating systems have suggested more complex multiple nucleation pathways that are associated with the formation and evolution of molecular aggregates in solution. Nucleation ; Chemical physics ; Solvation ; Crystal (programming language) ; Crystallization ; Chemistry ; Supramolecular chemistry ; Polymorphism (computer science) ; Intermolecular force ; Molecular dynamics ; Molecule ; Materials science ; Computational chemistry ; Organic chemistry ; Computer science Crystallization and Solubility Studies ; Crystallography and molecular interactions ; Calcium Carbonate Crystallization and Inhibition
Authors: Lu Su | Simone I. S. Hendrikse | E. W. Meijer
Source: Current Opinion in Chemical Biology (review, 2022-06-21)
Field: Chemistry — Organic Chemistry

Supramolecular glycopolymers: How carbohydrates matter in structure, dynamics, and function Supramolecular glycopolymers exhibiting inherent dynamicity, tunability, and adaptivity allow us to arrive at a deeper understanding of multivalent carbohydrate-carbohydrate interactions and carbohydrate-protein interactions, both being essential to key biological events. The impacts of the carbohydrate segments in these supramolecular glycopolymers towards their structure, dynamics, and function as biomaterials are addressed in this minireview. Bottlenecks and challenges are discussed, and we speculate about possible future directions. Supramolecular chemistry ; Carbohydrate ; Function (biology) ; Nanotechnology ; Glycopolymer ; Chemistry ; Computational biology ; Biochemistry ; Biology ; Materials science ; Molecule ; Organic chemistry ; Polymer ; Evolutionary biology ; Copolymer Carbohydrate Chemistry and Synthesis ; Glycosylation and Glycoproteins Research ; Supramolecular Self-Assembly in Materials
Authors: Panagiotis Krokidas | Stelios Karozis | Salvador Moncho | George Giannakopoulos | Edward N. Brothers | M.E. Kainourgiakis | Ioannis G. Economou | Theodore Steriotis
Source: Journal of Materials Chemistry A (article, 2022-01-01)
Field: Chemistry — Inorganic Chemistry

Data mining for predicting gas diffusivity in zeolitic-imidazolate frameworks (ZIFs) Molecular sieving is based on mobility differences of species under extreme confinement, i.e. within pores of molecular dimensions. Zeolitic imidazolate framework ; Thermal diffusivity ; Imidazolate ; Materials science ; Metal-organic framework ; Chemistry ; Thermodynamics ; Physical chemistry ; Physics ; Inorganic chemistry ; Adsorption Metal-Organic Frameworks: Synthesis and Applications ; Covalent Organic Framework Applications ; Membrane Separation and Gas Transport
Authors: Manoj Kumar Gupta | Vishesh Singhal | Nitesh Singh Rajput
Source: Evergreen (review, 2022-09-01)
Field: Materials Science — General Materials Science

Applications and Challenges of Carbon-fibres reinforced Composites: A Review Carbon-fiber reinforced polymers (CFRPs) or Carbon-fiber reinforced plastics composites is a material that has caught the interest of many industries due to its excellent properties like strength, lightweight, crashworthiness, style, looks, and many more. This paper discussed the manufacturing of carbon fibres and CFRPs. The properties of carbon fibres and carbon-fiber reinforced plastics composites are discussed in detail. The applications of Carbon-fiber reinforced plastics composites in the field of automotive and aerospace elaborated in detail. The challenges, recycling of CFRPs, and new approaches in the field of fibres reinforced plastic composites are also addressed in this paper. Composite material ; Materials science ; Carbon fibers ; Advanced composite materials ; Composite number Material Properties and Applications