jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Peiwen Xu | Hehui Wang | Jun Liu | Xinzhen Feng | Weijie Ji | Chak‐Tong Au
Source: ACS Applied Materials & Interfaces (article, 2021-07-19)
Field: Materials Science — Materials Chemistry

High-Performance Ni<sub><i>x</i></sub>Co<sub>3-x</sub>O<sub>4</sub>/Ti<sub>3</sub>C<sub>2</sub>T<sub><i>x</i></sub>-HT Interfacial Nanohybrid for Electrochemical Overall Water Splitting This study highlights the facet structure control of regular Ni<sub><i>x</i></sub>Co<sub>3-<i>x</i></sub>O<sub>4</sub> nanoplates and interfacial modulation through elemental doping and morphologically fitted assembly of Ti<sub>3</sub>C<sub>2</sub>T<sub><i>x</i></sub> nanosheets for high performances in OER/HER and overall water splitting. Over the resulting Ni<sub>0.09</sub>Co<sub>2.91</sub>O<sub>4</sub>/Ti<sub>3</sub>C<sub>2</sub>T<sub><i>x</i></sub>-HT in a solution of 1 M KOH, the OER and HER overpotentials of 262 and 210 mV, respectively, are achievable at a current density of 10 mA cm<sup>-2</sup>. In the case of the overall water splitting by using Ni<sub>0.09</sub>Co<sub>2.91</sub>O<sub>4</sub>/Ti<sub>3</sub>C<sub>2</sub>T<sub><i>x</i></sub>-HT as anode and cathode catalysts, only a potential of 1.66 V is needed to obtain a current density of 10 mA cm<sup>-2</sup>, and the catalysts can stand for a period of 70 h, remarkably outperforming the RuO<sub>2</sub>-Pt/C-based catalyst and benefiting from the intensive association and interfacial function between the Ti<sub>3</sub>C<sub>2</sub>T<sub><i>x</i></sub> and Ni<sub><i>x</i></sub>Co<sub>3-<i>x</i></sub>O<sub>4</sub> nanosheets. Interestingly, a surface reconstruction from the (112) to (111) facet structure occurred upon the fine-tuned Ni doping of regular Ni<sub><i>x</i></sub>Co<sub>3-<i>x</i></sub>O<sub>4</sub> hexagonal nanoplates and led to a highly active catalyst surface. At <i>x</i> = 0.09, the amount of Ni<sup>3+</sup> becomes the highest, which is favorable for the generation of the critical OH intermediates on Ni<sub><i>x</i></sub>Co<sub>3-<i>x</i></sub>O<sub>4</sub>/Ti<sub>3</sub>C<sub>2</sub>T<sub><i>x</i></sub>-HT. The current study documented the significance of the well-controlled interfacial assembly of transition-metal oxide/MXenes as an effective electrocatalyst in the OER/HER and overall water splitting processes and provided the insights into the structure-performance correlation over such kinds of precious metal-free catalysts. Materials science ; Water splitting ; Catalysis ; Electrocatalyst ; Transition metal ; Cathode ; Oxide ; MXenes ; Anode ; Doping ; Current density ; Metal ; Oxygen evolution ; Chemical engineering ; Nanotechnology ; Electrode ; Physical chemistry ; Optoelectronics ; Metallurgy ; Photocatalysis ; Electrochemistry MXene and MAX Phase Materials ; Electrocatalysts for Energy Conversion ; Advanced Memory and Neural Computing
Authors: Weijin Li | Soumya Mukherjee | Baohui Ren | Rong Cao | Roland A. Fischer
Source: Advanced Energy Materials (article, 2021-04-01)
Field: Materials Science — Materials Chemistry

Open Framework Material Based Thin Films: Electrochemical Catalysis and State‐of‐the‐art Technologies Abstract Open framework materials (OFMs), such as metal‐organic frameworks and covalent organic frameworks have emerged as promising electrocatalysts to address the global energy crisis and environmental problems. Powdered non‐film forms, that is, bulk OFMs exhibit excellent catalytic activities toward electrocatalytic carbon dioxide reduction, water splitting, and the oxygen reduction reaction. However, electrode preparation using bulk solids suffers from a range of oft‐encountered difficulties, primarily limited by challenges in controlling their thickness, roughness, and particle sizes, despite early performance promises. Targeting energy sustainability, it is a matter of growing interest to directly integrate OFMs in the form of thin films onto conductive substrates. In essence, this leads to electrocatalysts with controlled features: thickness, roughness, and particle sizes. Thus far, there are only a handful of OFM thin films developed for electrocatalysis. Exploration of these understudied OFM thin films to serve electrocatalysis still lies at its infancy. This review will cover the key discoveries of OFM thin films as electrocatalysts and will critically examine the strengths, challenges, and future goals in exploring bespoke OFM thin films for electrocatalysis, under conditions that mimic real‐world applications. Electrocatalyst ; Materials science ; Thin film ; Nanotechnology ; Metal-organic framework ; Bespoke ; Electrochemistry ; Electrode ; Organic chemistry ; Chemistry Covalent Organic Framework Applications ; Metal-Organic Frameworks: Synthesis and Applications ; Advanced Photocatalysis Techniques
Authors: Yimeng Lyu | Rui Xu | Olivia C. Williams | Ziyuan Wang | Carsten Sievers
Source: Journal of Catalysis (article, 2021-10-12)
Field: Materials Science — Materials Chemistry

Reaction paths of methane activation and oxidation of surface intermediates over NiO on Ceria-Zirconia catalysts studied by In-situ FTIR spectroscopy Chemistry ; Catalysis ; Non-blocking I/O ; Cubic zirconia ; In situ ; Fourier transform infrared spectroscopy ; Methane ; Heterogeneous catalysis ; Inorganic chemistry ; Photochemistry ; Chemical engineering ; Organic chemistry Catalytic Processes in Materials Science ; Catalysis and Oxidation Reactions ; Catalysts for Methane Reforming
Authors: Xiaoyi Feng | Yuning Luo | Fangjie Li | Xueting Jian | Yang Liu
Source: Gels (review, 2021-08-04)
Field: Materials Science — Biomaterials

Development of Natural-Drugs-Based Low-Molecular-Weight Supramolecular Gels Natural small molecular drugs with excellent biocompatibility, diverse pharmacological activities, and wide sources play an increasingly important role in the development of new drug and disease treatment. In recent years, the utilization of paclitaxel, camptothecin, rhein, curcumin, and other natural small molecular drugs with unique rigid backbone structures and modifiable multiple sites as building blocks to form gels by self-assembly has attracted widespread attention. The obtained low-molecular-weight supramolecular gel not only retains the general characteristics of the gel but also overcomes the shortcomings of natural drugs, such as poor water solubility and low bioavailability. It has the advantages of high drug loading, low toxicity, and outstanding stimulus responsiveness, which is widely used in biomedical fields. Here, we provided a comprehensive review of natural-drugs-based low-molecular-weight supramolecular gels reported in recent years and summarized their assembly mechanism, gel structure, gel properties, and potential applications. It is expected to provide a reference for further research of natural-drugs-based supramolecular gels. Supramolecular chemistry ; Curcumin ; Nanotechnology ; Biocompatibility ; Drug delivery ; Drug ; Bioavailability ; Camptothecin ; Chemistry ; Materials science ; Pharmacology ; Biology ; Molecule ; Organic chemistry ; Biochemistry Supramolecular Self-Assembly in Materials ; Supramolecular Chemistry and Complexes ; Glycosylation and Glycoproteins Research
Authors: Yong Ho Lee | Elliott H. Denton | Bill Morandi
Source: Nature Chemistry (article, 2021-01-29)
Field: Chemistry — Organic Chemistry

Palladium-catalysed carboformylation of alkynes using acid chlorides as a dual carbon monoxide and carbon source Chemistry ; Electrophile ; Carbonylation ; Carbon monoxide ; Catalysis ; Aldehyde ; Palladium ; Combinatorial chemistry ; Alkyne ; Steric effects ; Hydroformylation ; Organic chemistry ; Rhodium Catalytic C–H Functionalization Methods ; Catalytic Cross-Coupling Reactions ; Organoboron and organosilicon chemistry
Authors: Vega Widya Karisma | Wei Wu | Mingxing Lei | Liu Huawen | Muhammad Nisar | Matthew D. Lloyd | Charareh Pourzand | Julia Li Zhong
Source: Frontiers in Cell and Developmental Biology (review, 2021-02-11)
Field: Materials Science — Materials Chemistry

UVA-Triggered Drug Release and Photo-Protection of Skin Light has attracted special attention as a stimulus for triggered drug delivery systems (DDS) due to its intrinsic features of being spatially and temporally tunable. Ultraviolet A (UVA) radiation has recently been used as a source of external light stimuli to control the release of drugs using a "switch on- switch off" procedure. This review discusses the promising potential of UVA radiation as the light source of choice for photo-controlled drug release from a range of photo-responsive and photolabile nanostructures <i>via</i> photo-isomerization, photo-cleavage, photo-crosslinking, and photo-induced rearrangement. In addition to its clinical use, we will also provide here an overview of the recent UVA-responsive drug release approaches that are developed for phototherapy and skin photoprotection. Photoprotection ; Drug delivery ; Drug ; Chemistry ; Ultraviolet radiation ; Nanotechnology ; Biophysics ; Materials science ; Pharmacology ; Medicine ; Biology Photochromic and Fluorescence Chemistry ; Skin Protection and Aging ; Nanoplatforms for cancer theranostics
Authors: Hyeongoo Kim | Gang Zhang | T. C. Chung | Changwoo Nam
Source: Advanced Sustainable Systems (article, 2021-10-15)
Field: Materials Science — Surfaces, Coatings and Films

A Role for Newly Developed Sorbents in Remediating Large‐Scale Oil Spills: Reviewing Recent Advances and Beyond Abstract The conservation of ocean and freshwater have been crucial issues over the past decades, and oil/water separation is a well‐known technology to restore polluted water systems. In the meantime, oil sorbents serve as a promising means of achieving water conservation to recover from oil spills, which require a multi‐factorial approach to review high selectivity, capacity, and rate of oil recovery. However, reusability is a critical component to consider in incidents with large‐scale spills. With the development of sorbent technology, some studies have progressed to explore surface engineering and material design for high oil sorption capacity and durability. Thus, this systemic review, a summary of sorbent developments, serves as a guide to understanding practical applications that can apply to large‐scale oil spills and recognize remaining issues. In this review, the oil weathering process and oil sorption mechanisms in relation to the characteristics of target pollutants are introduced. Then, this comprehensive review focuses on materials in advanced sorbents. These materials have properties including, aligned channels for fast sorption, self‐heating capabilities for viscous oil cleanup, and magnetic‐responsiveness to enhance a collection of final products. The perspective and challenges for the next generation of oil spills remediation technology‐based oil sorbents materials are finally presented in the last section. Oil spill ; Sorbent ; Environmental science ; Sorption ; Environmental remediation ; Scale (ratio) ; Petroleum engineering ; Reusability ; Process engineering ; Waste management ; Computer science ; Adsorption ; Engineering ; Environmental engineering ; Contamination ; Chemistry Surface Modification and Superhydrophobicity ; Oil Spill Detection and Mitigation ; Enhanced Oil Recovery Techniques
Authors: Xinqi Chen | Shengjie Fan | Chao Han | Tian Wu | Lianjun Wang | Wan Jiang | Wei Dai | Jianping Yang
Source: Rare Metals (article, 2021-02-28)
Field: Materials Science — Materials Chemistry

Multiscale architectures boosting thermoelectric performance of copper sulfide compound The online version of this article (10.1007/s12598-020-01698-6) contains supplementary material, which is available to authorized users. Spark plasma sintering ; Materials science ; Grain boundary ; Thermoelectric effect ; Copper ; Nanostructure ; Scattering ; Phonon scattering ; Thermoelectric materials ; Thermal conductivity ; Phonon ; Copper sulfide ; Figure of merit ; Chemical engineering ; Optoelectronics ; Nanotechnology ; Condensed matter physics ; Sintering ; Metallurgy ; Composite material ; Thermodynamics ; Optics ; Microstructure Advanced Thermoelectric Materials and Devices ; Thermal properties of materials ; Thermal Radiation and Cooling Technologies
Authors: Andreas Schweikert | Sarah Theiner | Debora Wernitznig | Anna Schoeberl | Martin Schaier | Sophie Neumayer | Bernhard K. Keppler | Gunda Koellensperger
Source: Analytical and Bioanalytical Chemistry (article, 2021-05-05)
Field: Chemistry — Spectroscopy

Micro-droplet-based calibration for quantitative elemental bioimaging by LA-ICPMS In this work, a novel standardization strategy for quantitative elemental bioimaging is evaluated. More specifically, multi-element quantification by laser ablation-inductively coupled plasma-time-of-flight mass spectrometry (LA-ICP-TOFMS) is performed by multi-point calibration using gelatin-based micro-droplet standards and validated using in-house produced reference materials. Fully automated deposition of micro-droplets by micro-spotting ensured precise standard volumes of 400 ± 5 pL resulting in droplet sizes of around 200 μm in diameter. The small dimensions of the micro-droplet standards and the use of a low-dispersion laser ablation setup reduced the analysis time required for calibration by LA-ICPMS significantly. Therefore, as a key advance, high-throughput analysis (pixel acquisition rates of more than 200 Hz) enabled to establish imaging measurement sequences with quality control- and standardization samples comparable to solution-based quantification exercises by ICP-MS. Analytical figures of merit such as limit of detection, precision, and accuracy of the calibration approach were assessed for platinum and for elements with biological key functions from the lower mass range (phosphorus, copper, and zinc). As a proof-of-concept application, the tool-set was employed to investigate the accumulation of metal-based anticancer drugs in multicellular tumor spheroid models at clinically relevant concentrations. Graphical abstract. Calibration ; Mass spectrometry ; Chemistry ; Laser ablation ; Calibration curve ; Analytical Chemistry (journal) ; Figure of merit ; Detection limit ; Materials science ; Chromatography ; Laser ; Optics ; Optoelectronics ; Physics Mass Spectrometry Techniques and Applications ; Analytical chemistry methods development ; Ion-surface interactions and analysis
Authors: Marc Vila | José H. García | Stephan Roche
Source: arXiv (Cornell University) (article, 2021-06-30)
Field: Materials Science — Materials Chemistry

Valley-Polarized Quantum Anomalous Hall Phase in Bilayer Graphene with Layer-Dependent Proximity Effects Realizations of some topological phases in two-dimensional systems rely on the challenge of jointly incorporating spin-orbit and magnetic exchange interactions. Here, we predict the formation and control of a fully valley-polarized quantum anomalous Hall effect in bilayer graphene, by separately imprinting spin-orbit and magnetic proximity effects in different layers. This results in varying spin splittings for the conduction and valence bands, which gives rise to a topological gap at a single Dirac cone. The topological phase can be controlled by a gate voltage and switched between valleys by reversing the sign of the exchange interaction. By performing quantum transport calculations in disordered systems, the chirality and resilience of the valley-polarized edge state are demonstrated. Our findings provide a promising route to engineer a topological phase that could enable low-power electronic devices and valleytronic applications. Condensed matter physics ; Bilayer graphene ; Graphene ; Physics ; Quantum anomalous Hall effect ; Quantum Hall effect ; Topology (electrical circuits) ; Quantum spin Hall effect ; Electron ; Quantum mechanics Graphene research and applications ; Topological Materials and Phenomena ; Quantum and electron transport phenomena
Authors: Yuxin Li | Rongzhi Dong | Wenhui Yang | Jianjun Hu
Source: Computational Materials Science (article, 2021-07-05)
Field: Materials Science — Materials Chemistry

Composition based crystal materials symmetry prediction using machine learning with enhanced descriptors Crystal (programming language) ; Artificial intelligence ; Benchmark (surveying) ; Machine learning ; Computer science ; Crystal structure ; Space (punctuation) ; Crystal structure prediction ; Random forest ; Algorithm ; Materials science ; Crystallography ; Chemistry ; Geology Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Crystallography and molecular interactions
Authors: Zhenze Yang | Markus J. Buehler
Source: Frontiers in Materials (article, 2021-10-06)
Field: Materials Science — Materials Chemistry

Words to Matter: De novo Architected Materials Design Using Transformer Neural Networks Transformer neural networks have become widely used in a variety of AI applications, enabling significant advances in Natural Language Processing (NLP) and computer vision. Here we demonstrate the use of transformer neural networks in the de novo design of architected materials using a unique approach based on text input that enables the design to be directed by descriptive text, such as “ a regular lattice of steel ”. Since transformer neural nets enable the conversion of data from distinct forms into one another, including text into images, such methods have the potential to be used as a natural-language-driven tool to develop complex materials designs. In this study we use the Contrastive Language-Image Pre-Training (CLIP) and VQGAN neural networks in an iterative process to generate images that reflect text prompt driven materials designs. We then use the resulting images to generate three-dimensional models that can be realized using additive manufacturing, resulting in physical samples of these text-based materials. We present several such word-to-matter examples, and analyze 3D printed material specimen through associated additional finite element analysis, especially focused on mechanical properties including mechanism design. As an emerging new field, such language-based design approaches can have profound impact, including the use of transformer neural nets to generate machine code for 3D printing, optimization of processing conditions, and other end-to-end design environments that intersect directly with human language. Transformer ; Computer science ; Artificial neural network ; Artificial intelligence ; Iterative and incremental development ; Natural language ; Natural language processing ; Engineering ; Voltage ; Electrical engineering ; Software engineering Machine Learning in Materials Science ; Material Selection and Properties ; Calcium Carbonate Crystallization and Inhibition
Authors: Jun Zhang | Yao-Kun Lei | Zhen Zhang | Xu Han | Maodong Li | Lijiang Yang | Yi Isaac Yang | Yi Qin Gao
Source: Physical Chemistry Chemical Physics (article, 2021-01-01)
Field: Materials Science — Materials Chemistry

Deep reinforcement learning of transition states Combining reinforcement learning (RL) and molecular dynamics (MD) simulations, we propose a machine-learning approach, called RL<sup>‡</sup>, to automatically unravel chemical reaction mechanisms. In RL<sup>‡</sup>, locating the transition state of a chemical reaction is formulated as a game, and two functions are optimized, one for value estimation and the other for policy making, to iteratively improve our chance of winning this game. Both functions can be approximated by deep neural networks. By virtue of RL<sup>‡</sup>, one can directly interpret the reaction mechanism according to the value function. Meanwhile, the policy function allows efficient sampling of the transition path ensemble, which can be further used to analyze reaction dynamics and kinetics. Through multiple experiments, we show that RL<sup>‡</sup> can be trained tabula rasa hence allowing us to reveal chemical reaction mechanisms with minimal subjective biases. Reinforcement learning ; Function (biology) ; State (computer science) ; Value (mathematics) ; Artificial neural network ; Path (computing) ; Bellman equation ; Q-learning Machine Learning in Materials Science ; Quantum many-body systems ; Neural Networks and Reservoir Computing
Authors: Yonglan Liu | Dong Zhang | Yijing Tang | Yanxian Zhang | Yung Chang | Jie Zheng
Source: ACS Applied Materials & Interfaces (article, 2021-02-26)
Field: Materials Science — Surfaces, Coatings and Films

Machine Learning-Enabled Design and Prediction of Protein Resistance on Self-Assembled Monolayers and Beyond The rational design of highly antifouling materials is crucial for a wide range of fundamental research and practical applications. The immense variety and complexity of the intrinsic physicochemical properties of materials (i.e., chemical structure, hydrophobicity, charge distribution, and molecular weight) and their surface coating properties (i.e., packing density, film thickness and roughness, and chain conformation) make it challenging to rationally design antifouling materials and reveal their fundamental structure-property relationships. In this work, we developed a data-driven machine learning model, a combination of factor analysis of functional group (FAFG), Pearson analysis, random forest (RF) and artificial neural network (ANN) algorithms, and Bayesian statistics, to computationally extract structure/chemical/surface features in correlation with the antifouling activity of self-assembled monolayers (SAMs) from a self-construction data set. The resultant model demonstrates the robustness of <i>Q</i><sub>CV</sub><sup>2</sup> = 0.90 and RMSE<sub>CV</sub> = 0.21 and the predictive ability of <i>Q</i><sub>ext</sub><sup>2</sup> = 0.84 and RMSE<sub>ext</sub> = 0.28, determines key descriptors and functional groups important for the antifouling activity, and enables to design original antifouling SAMs using the predicted antifouling functional groups. Three computationally designed molecules were further coated onto the surfaces in different forms of SAMs and polymer brushes. The resultant coatings with negative fouling indexes exhibited strong surface resistance to protein adsorption from undiluted blood serum and plasma, validating the model predictions. The data-driven machine learning model demonstrates their design and predictive capacity for next-generation antifouling materials and surfaces, which hopefully help to accelerate the discovery and understanding of functional materials. Biofouling ; Materials science ; Rational design ; Coating ; Machine learning ; Density functional theory ; Biological system ; Surface roughness ; Artificial intelligence ; Monolayer ; Nanotechnology ; Robustness (evolution) ; Computer science ; Composite material ; Computational chemistry ; Chemistry Polymer Surface Interaction Studies ; Marine Biology and Environmental Chemistry ; Knee injuries and reconstruction techniques