jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Sitaram Meduri | Jalaiah Nandanavanam
Source: Energy and AI (article, 2023-01-13)
Field: Chemistry — Inorganic Chemistry

Prediction of hydrogen uptake of metal organic frameworks using explainable machine learning Metal organic frameworks (MOFs) are considered as potential materials for hydrogen storage. The hydrogen uptake is influenced by several parameters (e.g., temperature, pressure, isosteric heat of adsorption, BET surface area). Of late, machine learning (ML) technique is used to assess the role of input features on the prediction. In the present study, a few ML models are selected, trained, and evaluated. The best and least performing models are tuned for hyperparameters. The results show that hyperparameter tuning (HPT) significantly increases the coefficient of determination (R2) of the least-performing model, the support vector regression (SVR). In contrast, the improvement in R2 with HPT is marginal for the best-performing model, the extra tree (ET), with a mean absolute error (MAE) of 0.088 wt% and R2 of 0.9945. The predictions made by the hyperparameter tuned extra tree model are explained using the Shapley additive explanations (SHAP) and contours together. The order of importance of input features in predicting the hydrogen uptake is identified as follows: temperature, pressure, isosteric heat of adsorption, and BET surface area. The SHAP dependence plots suggest that pressure is the common interactive feature among the input features in predicting hydrogen uptake. The present study helped understand the role of input features collectively in predicting the hydrogen uptake of MOFs. Hyperparameter ; Hydrogen ; Adsorption ; Mean squared error ; Support vector machine ; Artificial intelligence ; Feature (linguistics) ; Regression ; Mean absolute error ; Chemistry ; Machine learning ; Computer science ; Thermodynamics ; Biological system ; Mathematics ; Materials science ; Statistics ; Physical chemistry ; Physics ; Organic chemistry ; Biology Metal-Organic Frameworks: Synthesis and Applications ; Hydrogen Storage and Materials ; Covalent Organic Framework Applications
Authors: Sijia Liu | Fujia Dong | Jie Hao | Lu Qiao | Jianhong Guo | Songlei Wang | Ruiming Luo | Yu Lv | Jiarui Cui
Source: Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy (article, 2023-01-09)
Field: Chemistry — Analytical Chemistry

Combination of hyperspectral imaging and entropy weight method for the comprehensive assessment of antioxidant enzyme activity in Tan mutton Chemistry ; Hyperspectral imaging ; Antioxidant ; Enzyme ; Entropy (arrow of time) ; Environmental chemistry ; Biochemistry ; Remote sensing ; Thermodynamics Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality ; Phytochemicals and Antioxidant Activities
Authors: Zichao Xu | Yuhua Wang | Yue Li | Yitong Wang | Bo Peng | Kenneth Davey | Liang Sun | Guanjie Li | Shilin Zhang | Zaiping Guo
Source: Advanced Energy Materials (article, 2023-10-27)
Field: Chemistry — Organic Chemistry

C<sub>60</sub> and Derivatives Boost Electrocatalysis and Photocatalysis: Electron Buffers to Heterojunctions Abstract Buckminsterfullerene (C 60 ) and derivatives are significant in the synthesis of efficient electrocatalysts and photocatalysts. This is because of electron acceptor properties and distinctive heterostructure(s) and physicochemical characteristics. High‐performance electrocatalysts and photocatalysts are important therefore in conversions for clean energy. Here a critical assessment of advances in use of C 60 and derivatives as heterostructures and “electron buffers” in catalysts are reported. Methodologies for preparing C 60 composite catalysts are assessed and categorized and microscopic mechanisms for boosting catalytic performance through C 60 and derivatives in important catalytic materials including, semiconductors, carbon‐based metal‐free materials, metal nanoclusters, single atoms, and metal–organic skeletons are established. Important characterizations used with C 60 and derivative composites are contrasted and assessed and practical challenges to development are determined. A prospective on future directions and likely outcomes in development of high efficiency electrocatalysts and photocatalysts is provided. It is concluded that C 60 and derivatives are advantageous for advanced electrocatalysts and photocatalysts with high structural integrity and boosted electron transport. The findings are expected to be of interest and benefit to researchers and manufacturers for formation of heterostructures and electron buffer areas for significantly boosted catalytic performance. Materials science ; Heterojunction ; Nanoclusters ; Catalysis ; Photocatalysis ; Electrocatalyst ; Nanotechnology ; Metal ; Chemical engineering ; Optoelectronics ; Chemistry ; Physical chemistry ; Organic chemistry ; Metallurgy ; Electrochemistry Fullerene Chemistry and Applications ; Electrocatalysts for Energy Conversion ; Graphene research and applications
Authors: Shusheel Kumar | Aneela Tahira | Adeel Liaquat Bhatti | Muhammad Ali Bhatti | Zaheer Ahmed Ujjan | Umair Aftab | Sooraj Kumar | Abdullah A. Al‐Kahtani | Ayman Nafady | Elmuez A. Dawi | Mélanie Emo | Brigitte Vigolo | Antonia Infantes‐Molina | Zafar Hussain Ibupoto
Source: Journal of Energy Storage (article, 2023-12-11)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Oxygen vacancies and tailored redox activity encountered with NiCo2O4 nanostructures for promising applications in supercapacitor and water oxidation Tafel equation ; Supercapacitor ; Electrochemistry ; Materials science ; Chemical engineering ; Oxygen evolution ; Cobalt ; Overpotential ; Nanostructure ; Bimetallic strip ; Cobalt hydroxide ; Redox ; Cobalt oxide ; Oxide ; Electrode ; Nanotechnology ; Chemistry ; Metal ; Metallurgy ; Physical chemistry Supercapacitor Materials and Fabrication ; Electrocatalysts for Energy Conversion ; Advanced battery technologies research
Authors: Jize Liu | Federica Recupido | Giuseppe Cesare Lama | Maria Oliviero | Letizia Verdolotti | Marino Lavorgna
Source: Collagen and Leather (article, 2023-03-09)
Field: Materials Science — Polymers and Plastics

Recent advances concerning polyurethane in leather applications: an overview of conventional and greener solutions Polyurethane ; Environmentally friendly ; Sustainable design ; Engineering ; Construction engineering ; Biochemical engineering ; Manufacturing engineering ; Nanotechnology ; Architectural engineering ; Sustainability ; Materials science ; Composite material Polymer composites and self-healing ; Microplastics and Plastic Pollution ; Marine Biology and Environmental Chemistry
Authors: Zaid Alhulaybi | Ibrahim Dubdub
Source: Polymers (article, 2023-07-11)
Field: Materials Science — Materials Chemistry

Comprehensive Kinetic Study of PET Pyrolysis Using TGA The pyrolysis of polyethylene terephthalate (PET) is a well-known process for producing high fuel value. This paper aims to study the kinetics of PET pyrolysis reactions at 4 different heating rates (2, 5, 10, and 20 K min<sup>-1</sup>) using thermogravimetric analysis (TGA) data. TGA data show only one kinetic reaction within the temperature ranges of 650 to 750 K. Five different model-free models, namely, the Freidman (FR), Flynn-Wall-Qzawa (FWO), Kissinger-Akahira-Sunose (KAS), Starink (STK), and distributed activation energy model (DAEM), were fitted to the experimental data to obtain the activation energy (<i>E<sub>a</sub></i>) and the pre-exponential factor (<i>A</i><sub>0</sub>) of the reaction kinetics. The Coats-Redfern (CR) model equation was fitted with the help of master plot (Criado's) to identify the most convenient reaction mechanism for this system. <i>E<sub>a</sub></i>'s values were determined by the application of the five aforementioned models and were found to possess an average value of 212 kJ mol<sup>-1</sup>. The mechanism of PET pyrolysis reaction was best described by first-order reaction kinetics; this was confirmed by the compensation. Further thermodynamic parameter analysis indicated that the reaction was endothermic in nature. Activation energy ; Thermogravimetric analysis ; Pyrolysis ; Kinetics ; Endothermic process ; Order of reaction ; Materials science ; Thermodynamics ; Kinetic energy ; Chemical kinetics ; Reaction mechanism ; Physical chemistry ; Chemistry ; Reaction rate constant ; Organic chemistry ; Catalysis ; Physics Thermal and Kinetic Analysis ; Thermochemical Biomass Conversion Processes ; Polymer crystallization and properties
Authors: Ksenija Radotić | Mira Stanković | Dragana Bartolić | Maja Natić
Source: Foods (review, 2023-08-11)
Field: Chemistry — Analytical Chemistry

Intrinsic Fluorescence Markers for Food Characteristics, Shelf Life, and Safety Estimation: Advanced Analytical Approach Food is a complex matrix of proteins, fats, minerals, vitamins, and other components. Various analytical methods are currently used for food testing. However, most of the used methods require sample preprocessing and expensive chemicals. New analytical methods are needed for quick and economic measurement of food quality and safety. Fluorescence spectroscopy is a simple and quick method to measure food quality, without sample preprocessing. This technique has been developed for food samples due to the application of a front-face measuring setup. Fluorescent compounds-fluorophores in the food samples are highly sensitive to their environment. Information about molecular structure and changes in food samples is obtained by the measurement of excitation-emission matrices of the endogenous fluorophores and by applying multivariate chemometric tools. Synchronous fluorescence spectroscopy is an advantageous screening mode used in food analysis. The fluorescent markers in food are amino acids tryptophan and tyrosine; the structural proteins collagen and elastin; the enzymes and co-enzymes NADH and FAD; vitamins; lipids; porphyrins; and mycotoxins in certain food types. The review provides information on the principles of the fluorescence measurements of food samples and the advantages of this method over the others. An analysis of the fluorescence spectroscopy applications in screening the various food types is provided. Fluorescence spectroscopy ; Fluorescence ; Food quality ; Chemistry ; Biological system ; Sample preparation ; Fluorometer ; Analyte ; Tryptophan ; Food science ; Chromatography ; Biochemistry ; Biology ; Amino acid Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality ; Advanced Chemical Sensor Technologies
Authors: Siheun Lee | Hung M. Vu | Jung‐Hyun Lee | Heejin Lim | Min‐Sik Kim
Source: Biology (review, 2023-03-02)
Field: Chemistry — Spectroscopy

Advances in Mass Spectrometry-Based Single Cell Analysis Technological developments and improvements in single-cell isolation and analytical platforms allow for advanced molecular profiling at the single-cell level, which reveals cell-to-cell variation within the admixture cells in complex biological or clinical systems. This helps to understand the cellular heterogeneity of normal or diseased tissues and organs. However, most studies focused on the analysis of nucleic acids (e.g., DNA and RNA) and mass spectrometry (MS)-based analysis for proteins and metabolites of a single cell lagged until recently. Undoubtedly, MS-based single-cell analysis will provide a deeper insight into cellular mechanisms related to health and disease. This review summarizes recent advances in MS-based single-cell analysis methods and their applications in biology and medicine. Biology ; Computational biology ; Cell ; Single-cell analysis ; Nucleic acid ; Proteomics ; RNA ; Systems biology ; Mass spectrometry ; DNA ; Cell biology ; Bioinformatics ; Genetics ; Gene ; Chemistry ; Chromatography Mass Spectrometry Techniques and Applications ; Single-cell and spatial transcriptomics ; Advanced Proteomics Techniques and Applications
Authors: Wei Chen | Yuyang Li | Yineng Liu | Yuan Gao | Yiming Yan | Zhaogang Dong | Jinfeng Zhu
Source: Advanced Optical Materials (article, 2023-10-27)
Field: Materials Science — Electronic, Optical and Magnetic Materials

All‐Dielectric SERS Metasurface with Strong Coupling Quasi‐BIC Energized by Transformer‐Based Deep Learning Abstract Researchers have paid great attention to pursuing metal‐free nanostructures as alternatives to metallic counterparts in the field of surface‐enhanced Raman scattering (SERS) for label‐free sensing. However, these metal‐free investigations are hindered by the tiny enhancement factor of the local near field. Here, the design of all‐dielectric SERS metasurfaces is proposed with quasi‐bound states in the continuum (Q‐BIC), inspired by transformer‐based deep learning. By manipulating the incident angle, the mechanism of strong coupling Q‐BIC is introduced with a large Rabi splitting of ≈105 meV, which opens a bandgap and forms an anti‐crossing behavior. Compared to conventional approaches, the strong coupling Q‐BIC scheme not only boosts an extraordinary SERS enhancement factor of ≈10 7 but also extends the field‐enhancing scale up to ten‐fold. The theoretical optimization implies overwhelming dominance versus the conventional metallic nanostructure design for SERS. The study denotes an approach to utilize the strong coupling effects of Q‐BIC in all‐dielectric SERS metasurfaces and will provide essential design guides for more powerful sensing applications based on SERS. Raman scattering ; Dielectric ; Materials science ; Nanostructure ; Coupling (piping) ; Optoelectronics ; Raman spectroscopy ; Transformer ; Nanotechnology ; Optics ; Physics ; Quantum mechanics ; Voltage Gold and Silver Nanoparticles Synthesis and Applications ; Metamaterials and Metasurfaces Applications ; Plasmonic and Surface Plasmon Research
Authors: Xiaohong Wu | Shupeng Zeng | Haijun Fu | Bin Wu | Haoxiang Zhou | Chunxia Dai
Source: Food Chemistry X (article, 2023-03-30)
Field: Chemistry — Analytical Chemistry

Determination of corn protein content using near-infrared spectroscopy combined with A-CARS-PLS In order to quickly and accurately determine the protein content of corn, a new characteristic wavelength selection algorithm called anchor competitive adaptive reweighted sampling (A-CARS) was proposed in this paper. This method first lets Monte Carlo synergy interval PLS (MC-siPLS) to select the sub-intervals where the characteristic variables exist and then uses CARS to screen the variables further. A-CARS-PLS was compared with 6 methods, including 3 feature variable selection methods (GA-PLS, random frog PLS, and CARS-PLS) and 2 interval partial least squares methods (siPLS and MWPLS). The results showed that A-CARS-PLS was significantly better than other methods with the results: RMSECV = 0.0336, R<sup>2</sup> <sub>c</sub> = 0.9951 in the calibration set; RMSEP = 0.0688, R<sup>2</sup> <sub>p</sub> = 0.9820 in the prediction set. Furthermore, A-CARS reduced the original 700-dimensional variable to 23 variables. The results showed that A-CARS-PLS was better than some wavelength selection methods, and it has great application potential in the non-destructive detection of protein content in corn. Partial least squares regression ; Feature selection ; Calibration ; Content (measure theory) ; Near-infrared spectroscopy ; Variable elimination ; Monte Carlo method ; Set (abstract data type) ; Selection (genetic algorithm) ; Interval (graph theory) ; Artificial intelligence ; Mathematics ; Pattern recognition (psychology) ; Chemistry ; Statistics ; Computer science ; Physics Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Advanced Chemical Sensor Technologies
Authors: Bo Wen | Bing Zhang
Source: Nature Communications (article, 2023-04-18)
Field: Chemistry — Spectroscopy

PepQuery2 democratizes public MS proteomics data for rapid peptide searching We present PepQuery2, which leverages a new tandem mass spectrometry (MS/MS) data indexing approach to enable ultrafast, targeted identification of novel and known peptides in any local or publicly available MS proteomics datasets. The stand-alone version of PepQuery2 allows directly searching more than one billion indexed MS/MS spectra in the PepQueryDB or any public datasets from PRIDE, MassIVE, iProX, or jPOSTrepo, whereas the web version enables users to search datasets in PepQueryDB with a user-friendly interface. We demonstrate the utilities of PepQuery2 in a wide range of applications including detecting proteomic evidence for genomically predicted novel peptides, validating novel and known peptides identified using spectrum-centric database searching, prioritizing tumor-specific antigens, identifying missing proteins, and selecting proteotypic peptides for targeted proteomics experiments. By putting public MS proteomics data directly into the hands of scientists, PepQuery2 opens many new ways to transform these data into useful information for the broad research community. Proteomics ; Computational biology ; Peptide ; Computer science ; Chemistry ; Biology ; Biochemistry ; Gene Advanced Proteomics Techniques and Applications ; Machine Learning in Bioinformatics ; vaccines and immunoinformatics approaches
Authors: Benoît Baillif | Jason C. Cole | Patrick McCabe | Andreas Bender
Source: Current Opinion in Structural Biology (review, 2023-03-29)
Field: Materials Science — Materials Chemistry

Deep generative models for 3D molecular structure Deep generative models have gained recent popularity for chemical design. Many of these models have historically operated in 2D space; however, more recently explicit 3D molecular generative models have become of interest, which are the topic of this article. Dozens of published models have been developed in the last few years to generate molecules directly in 3D, outputting both the atom types and coordinates, either in one-shot or adding atoms or fragments step-by-step. These 3D generative models can also be guided by structural information such as a binding pocket representation to successfully generate molecules with docking score ranges similar to known actives, but still showing lower computational efficiency and generation throughput than 1D/2D generative models and sometimes producing unrealistic conformations. We advocate for a unified benchmark of metrics to evaluate generation and propose perspectives to be addressed in next implementations. Generative grammar ; Computer science ; Benchmark (surveying) ; Generative model ; Chemical space ; Representation (politics) ; Generative adversarial network ; Artificial intelligence ; Popularity ; Theoretical computer science ; Machine learning ; Deep learning ; Drug discovery ; Biology ; Bioinformatics Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Chemistry and Chemical Engineering
Authors: Megan Stanley | Marwin Segler
Source: Current Opinion in Structural Biology (review, 2023-07-18)
Field: Materials Science — Materials Chemistry

Fake it until you make it? Generative de novo design and virtual screening of synthesizable molecules Expediting ; Virtual screening ; Computer science ; Workflow ; Generative grammar ; Perspective (graphical) ; Data science ; Computational biology ; Artificial intelligence ; Drug discovery ; Bioinformatics ; Systems engineering ; Engineering ; Biology Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Scientific Computing and Data Management
Authors: Alina Ghilan | Raluca Nicu | Diana Ciolacu | Florin Ciolacu
Source: Materials (review, 2023-06-17)
Field: Materials Science — Biomaterials

Insight into the Latest Medical Applications of Nanocellulose Nanocelluloses (NCs) are appealing nanomaterials that have experienced rapid development in recent years, with great potential in the biomedical field. This trend aligns with the increasing demand for sustainable materials, which will contribute both to an improvement in wellbeing and an extension of human life, and with the demand to keep up with advances in medical technology. In recent years, due to the diversity of their physical and biological properties and the possibility of tuning them according to the desired goal, these nanomaterials represent a point of maximum interest in the medical field. Applications such as tissue engineering, drug delivery, wound dressing, medical implants or those in cardiovascular health are some of the applications in which NCs have been successfully used. This review presents insight into the latest medical applications of NCs, in the forms of cellulose nanocrystals (CNCs), cellulose nanofibers (CNFs) and bacterial nanocellulose (BNC), with an emphasis on the domains that have recently experienced remarkable growth, namely wound dressing, tissue engineering and drug delivery. In order to highlight only the most recent achievements, the presented information is focused on studies from the last 3 years. Approaches to the preparation of NCs are discussed either by top-down (chemical or mechanical degradation) or by bottom-up (biosynthesis) techniques, along with their morphological characterization and unique properties, such as mechanical and biological properties. Finally, the main challenges, limitations and future research directions of NCs are identified in a sustained effort to identify their effective use in biomedical fields. Nanocellulose ; Nanotechnology ; Drug delivery ; Nanofiber ; Medical device ; Human health ; Nanomaterials ; Cellulose ; Biochemical engineering ; Materials science ; Biomedical engineering ; Medicine ; Engineering Advanced Cellulose Research Studies ; Electrospun Nanofibers in Biomedical Applications ; Nanocomposite Films for Food Packaging
Authors: Wei Wang | Zilong Peng | Zhenping Ma | Lei Zhang | Xianzhen Wang | Ziming Xu | Yongbao Feng | Chenglong Liu | Dewei Liang | Qiulong Li
Source: ACS Applied Materials & Interfaces (article, 2023-10-02)
Field: Materials Science — Electronic, Optical and Magnetic Materials

High-Efficiency Electromagnetic Interference Shielding from Highly Aligned MXene Porous Composites via Controlled Directional Freezing Lightweight porous composite materials (PCMs) with outstanding electromagnetic interference (EMI) shielding performances are ideal for aerospace, artificial intelligence, military, and other fields. Herein, a three-dimensional Ti<sub>3</sub>C<sub>2</sub>T<sub><i>x</i></sub> MXene/sodium alginate (SA)/carbon nanotubes (CNTs) (MSC) PCMs was prepared by a controlled directional freezing process. This method constructs a directionally ordered porous structure, which can make the incident electromagnetic waves reflect and scattered several times in the PCMs. The introduction of CNTs into the MSC PCMs can form three-dimensional conductive networks with MXene, thus improving the conductivity and further improving the electromagnetic shielding performance. Furthermore, the SA with abundant hydrogen bonding can strengthen the interlayer interaction between MXene and CNTs. Profiting from the controlled directional freezing and highly aligned porous structure, the MSC PCMs with 75 wt % CNTs exhibit ultrahigh conductivity of 1630 S m<sup>-1</sup>, an ultrahigh EMI shielding effectiveness of 48.0 dB in X-band for electromagnetic waves incident perpendicular to the hole growth direction, and compressive strength of 72.3 kPa. The as-prepared MSC PCMs show excellent EMI shielding and mechanical properties and have significant applications in the preparation of an entirely novel type of EMI shielding materials with an absorption-based mechanism. Materials science ; Electromagnetic shielding ; Composite material ; EMI ; Electromagnetic interference ; Carbon nanotube ; Porosity ; Composite number ; Electrical conductor ; Perpendicular ; MXenes ; Electromagnetic radiation ; Nanotechnology ; Electronic engineering ; Optics Electromagnetic wave absorption materials ; Advanced Antenna and Metasurface Technologies ; MXene and MAX Phase Materials