jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Bing Zhu | Xinyao Jiang | Songjun Li | Maiyong Zhu
Source: Polymers (article, 2024-04-30)
Field: Materials Science — Polymers and Plastics

An Overview of Recycling Phenolic Resin Over a century ago, phenolic formaldehyde (PF) resin was developed and continues to increase in yield due to its diverse applications. However, PF resin is a thermosetting plastic lacking fluidity and moldability, which are nondegradable in natural environments, leading to severe threats to fossil resources as well as global environmental crises. As a result, recycling PF resin is extremely important. In this review, we provide the recent advances in the recycling of PF resin, which includes mechanical recycling, chemical recycling, and utilization of carbon-based materials. The advantages and disadvantages of each strategy are evaluated from a green chemistry perspective. This article aims to attract interest in PF resin design, synthesizing, application and recycling, offering useful suggestions. Thermosetting polymer ; Materials science ; Carbon fibers ; Yield (engineering) ; Waste management ; Fossil fuel ; Environmental science ; Forensic engineering ; Organic chemistry ; Chemistry ; Composite material ; Engineering Polymer composites and self-healing ; Epoxy Resin Curing Processes ; Carbon dioxide utilization in catalysis
Authors: E Shaw | Ashleigh M. Chester | Georgina P. Robertson | Celia Castillo‐Blas | Thomas D. Bennett
Source: Chemical Science (review, 2024-01-01)
Field: Chemistry — Inorganic Chemistry

Synthetic and analytical considerations for the preparation of amorphous metal–organic frameworks Metal-organic frameworks (MOFs) are hybrid porous materials presenting several tuneable properties, allowing them to be utilised for a wide range of applications. To date, focus has been on the preparation of novel crystalline MOFs for specific applications. Recently, interest in amorphous MOFs (aMOFs), defined by their lack of correlated long-range order, is growing. This is due to their potential favourable properties compared to their crystalline equivalents, including increased defect concentration, improved processability and gas separation ability. Direct synthesis of these disordered materials presents an alternative method of preparation to post-synthetic amorphisation of a crystalline framework, potentially allowing for the preparation of aMOFs with varying compositions and structures, and very different properties to crystalline MOFs. This perspective summarises current literature on directly synthesised aMOFs, and proposes methods that could be utilised to modify existing syntheses for crystalline MOFs to form their amorphous counterparts. It outlines parameters that could discourage the ordering of crystalline MOFs, before examining the potential properties that could emerge. Methodologies of structural characterisation are discussed, in addition to the necessary analyses required to define a topologically amorphous structure. Amorphous solid ; Metal-organic framework ; Nanotechnology ; Materials science ; Perspective (graphical) ; Amorphous metal ; Computer science ; Chemistry ; Organic chemistry ; Artificial intelligence ; Adsorption Metal-Organic Frameworks: Synthesis and Applications ; Magnetism in coordination complexes ; Advanced Nanomaterials in Catalysis
Authors: Nicolas Joly | Sylvain Gaillard | Albert Poater | Jean‐Luc Renaud
Source: Organic Chemistry Frontiers (article, 2024-01-01)
Field: Chemistry — Inorganic Chemistry

Hydrogen autotransfer with alcohols for alkylations Iron/ruthenium complexes, akin to Knölker catalysts, for bond reduction and sustainable alkylation using alcohols are included in this review, along with advances in dehydrogenative coupling, hydrogen borrowing, and light-assisted catalysis. Chemistry ; Atom economy ; Hydrogen atom ; Hydrogen ; Organic chemistry ; Combinatorial chemistry ; Catalysis ; Group (periodic table) Asymmetric Hydrogenation and Catalysis ; Catalysis and Hydrodesulfurization Studies ; Hydrogen Storage and Materials
Authors: Jesús Rafael González Parra | Francesca Di Turo
Source: Sustainability (article, 2024-02-24)
Field: Materials Science — Materials Chemistry

The Use of Plant Extracts as Sustainable Corrosion Inhibitors for Cultural Heritage Alloys: A Mini-Review Corrosion inhibitors have traditionally been utilised to protect copper alloy sculptures from corrosion despite the recognised environmental and human health risks. Knowing the associated toxicity, ongoing extensive research seeks alternative substances for corrosion reduction, giving rise to the emergence of green inhibitors. In this pursuit, plant extract inhibitors have gained attention, particularly in the heritage field. This review discusses recent advancements in synthesising sustainable and eco-friendly products designed to preserve metallic heritage from corrosion. We discuss the key findings on plant extracts used for corrosion control in metal alloys, taking into account the extraction methods to ensure the comprehensive coverage of relevant details. The use of plant extracts as corrosion inhibitors for metallic materials in cultural heritage (CH) is a highly promising and valuable research area. This review highlights recent advancements in the field, providing utility for conservators, conservation scientists, and restorers in identifying the most effective, eco-friendly, and safe compounds for material application. Corrosion ; Cultural heritage ; Environmentally friendly ; Human health ; Engineering ; Environmental science ; Construction engineering ; Materials science ; Metallurgy ; Geography ; Archaeology ; Ecology ; Medicine Corrosion Behavior and Inhibition ; Concrete Corrosion and Durability ; Conservation Techniques and Studies
Authors: Luciellen da Costa Ferreira | Ian Carlos Bispo Carvalho | Lúcio André de Castro Jorge | A. M. Quezado‐Duval | Maurício Rossato
Source: Frontiers in Plant Science (article, 2024-04-11)
Field: Chemistry — Analytical Chemistry

Hyperspectral imaging for the detection of plant pathogens in seeds: recent developments and challenges Food security, a critical concern amid global population growth, faces challenges in sustainable agricultural production due to significant yield losses caused by plant diseases, with a multitude of them caused by seedborne plant pathogen. With the expansion of the international seed market with global movement of this propagative plant material, and considering that about 90% of economically important crops grown from seeds, seed pathology emerged as an important discipline. Seed health testing is presently part of quality analysis and carried out by seed enterprises and governmental institutions looking forward to exclude a new pathogen in a country or site. The development of seedborne pathogens detection methods has been following the plant pathogen detection and diagnosis advances, from the use of cultivation on semi-selective media, to antibodies and DNA-based techniques. Hyperspectral imaging (HSI) associated with artificial intelligence can be considered the new frontier for seedborne pathogen detection with high accuracy in discriminating infected from healthy seeds. The development of the process consists of standardization of methods and protocols with the validation of spectral signatures for presence and incidence of contamined seeds. Concurrently, epidemiological studies correlating this information with disease outbreaks would help in determining the acceptable thresholds of seed contamination. Despite the high costs of equipment and the necessity for interdisciplinary collaboration, it is anticipated that health seed certifying programs and seed suppliers will benefit from the adoption of HSI techniques in the near future. Hyperspectral imaging ; Biotechnology ; Standardization ; Population ; Agriculture ; Biology ; Geography ; Remote sensing ; Environmental health ; Computer science ; Medicine ; Ecology Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Remote Sensing in Agriculture
Authors: Hangwei Jia | Xueling Hou | Shilie Pan
Source: Inorganic Chemistry Frontiers (article, 2024-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Research progress in optical materials with cationic organic planar π-conjugated groups containing CN bonds The calculated polarizability anisotropy, hyperpolarizability and HOMO–LUMO gap of optically active groups. Conjugated system ; Cationic polymerization ; Planar ; Materials science ; Chemistry ; Polymer chemistry ; Organic chemistry ; Polymer ; Computer science Crystal Structures and Properties ; Organometallic Compounds Synthesis and Characterization ; Crystal structures of chemical compounds
Authors: Xueji Wang | Todd Van Mechelen | Sathwik Bharadwaj | M. Roknuzzaman | Fanglin Bao | Rajib Rahman | Zubin Jacob
Source: eLight (article, 2024-12-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Exploiting universal nonlocal dispersion in optically active materials for spectro-polarimetric computational imaging Abstract Recent years have seen significant advancements in exploring novel light-matter interactions such as hyperbolic dispersion within natural crystals. However, current studies have predominantly concentrated on local optical response of materials characterized by a dielectric tensor without spatial dispersion. Here, we investigate the nonlocal response in optically-active crystals with screw symmetries, revealing their lossless, super-dispersive properties compared to traditional optical response functions. We leverage this universal nonlocal dispersion, i.e. the dispersion of optical rotatory power, to explore a novel spectral de-multiplexing scheme compared to conventional gratings, prisms and metasurfaces. We design and demonstrate an ‘Nonlocal-Cam’ - a camera that exploits nonlocal dispersion through sampling of polarized spectral states and the application of computational spectral reconstruction algorithms. The Nonlocal-Cam captures information in both laboratory and outdoor field experiments which is unavailable to traditional intensity cameras - the spectral texture of polarization. Merging the fields of nonlocal electrodynamics and computational imaging, our work paves the way for exploiting nonlocal optics of optically active materials in a variety of applications, from biological microscopy to physics-driven machine vision and remote sensing. Polarimetry ; Dispersion (optics) ; Polarization (electrochemistry) ; Optics ; Lossless compression ; Physics ; Computer science ; Scattering ; Computer vision ; Data compression ; Chemistry Metamaterials and Metasurfaces Applications ; Plasmonic and Surface Plasmon Research ; Mechanical and Optical Resonators
Authors: Wenyang Jia | Alessandro Ferragina | Ruth M. Hamill | Anastasios Koidis
Source: Talanta (article, 2024-05-03)
Field: Chemistry — Analytical Chemistry

Modelling and numerical methods for identifying low-level adulteration in ground beef using near-infrared hyperspectral imaging (NIR-HSI) Owing to the inherent characteristics of ground beef, adulteration presents a substantial risk for suppliers and consumers alike. This study developed a robust and novel method for identifying replacement fraud in ground beef with beef liver, beef heart, and pork using Near Infrared-Hyperspectral Imaging (NIR-HSI) coupled with chemometric and other statistical methods. More specifically, NIR-HSI provided an efficient and accurate means of identifying each type of adulteration using the classification model Genetic Algorithm (GA) - Backpropagation Artificial Neural Network (BPANN), showing perfect sensitivity and specificity (a value of 1.00) for the calibration and the validation sets for all types of adulteration. As an alternative to chemometric analysis, Hyperspectral Imaging-Root Mean Square (HSI-RMS) value, based on the RMS<sub>cut-off</sub> calculation, was determined to discriminate types of adulterations without the need of resource-intensive modelling. This HSI-RMS approach provides a simple-to-use method that avoids the complexity of HSI data processing and aims to directly understand the similarity between different spectra of one sample in the pixel level. Different types of adulteration show noticeable differences reflected in the HSI-RMS value (varying from 55 to 1439), which demonstrate the potential of HSI-RMS concept as a novel and valuable alternative for assessing the HSI data and facilitating the identification of adulterants. Hyperspectral imaging ; Pattern recognition (psychology) ; Artificial intelligence ; Artificial neural network ; Near-infrared spectroscopy ; Backpropagation ; Root mean square ; Partial least squares regression ; Remote sensing ; Biological system ; Computer science ; Machine learning ; Engineering Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Meat and Animal Product Quality
Authors: Shi-Wen Lv | Yuang Zhang | Wentao Wang | Shufen Zhang | Bingtao Tang
Source: Smart Molecules (review, 2024-12-01)
Field: Materials Science — Materials Chemistry

Visible light‐responsive azo‐based smart materials: Design, performance, and applications in energy storage Azobenzene and its derivatives are the most extensively investigated and applied molecular photoswitches, which can undergo reversible transformation between <i>trans</i> and <i>cis</i> isomers upon irradiation with light at specific wavelengths. Through structural geometry transformation, the property alterations can be integrated into smart materials to meet diverse application requirements. Most azo-based photoswitches require UV light for activation. However, complete activation within the visible or even near-infrared light range could offer several benefits for photoswitch applications, including improved biocompatibility, better light penetration, and enhanced solar light utilization efficiency. This review presents an overview of the development of visible-light responsive azo-based materials, covering molecular design strategies and their applications in energy storage. Recent efforts aimed at enhancing the performance of azo-based energy storage materials are highlighted. According to the different strategies for improving energy storage properties, these materials are categorized as those that directly increase isomerization energy and those that introduce phase transition energy. Furthermore, we discuss the challenges and opportunities in this field with a view to inspire further exploration. Photoswitch ; Azobenzene ; Materials science ; Light energy ; Energy storage ; Nanotechnology ; Energy transformation ; Visible spectrum ; Computer science ; Optoelectronics ; Photochemistry ; Chemistry ; Optics ; Polymer ; Physics Photochromic and Fluorescence Chemistry ; Supramolecular Self-Assembly in Materials ; Photoreceptor and optogenetics research
Authors: Denis V. Petrovskiy | Kirill S. Nikolsky | Liudmila I. Kulikova | Vladimir R. Rudnev | Tatiana V. Butkova | Kristina A. Malsagova | Arthur T. Kopylov | Anna L. Kaysheva
Source: Scientific Reports (article, 2024-07-01)
Field: Chemistry — Spectroscopy

PowerNovo: de novo peptide sequencing via tandem mass spectrometry using an ensemble of transformer and BERT models The primary objective of analyzing the data obtained in a mass spectrometry-based proteomic experiment is peptide and protein identification, or correct assignment of the tandem mass spectrum to one amino acid sequence. Comparison of empirical fragment spectra with the theoretical predicted one or matching with the collected spectra library are commonly accepted strategies of proteins identification and defining of their amino acid sequences. Although these approaches are widely used and are appreciably efficient for the well-characterized model organisms or measured proteins, they cannot detect novel peptide sequences that have not been previously annotated or are rare. This study presents PowerNovo tool for de novo sequencing of proteins using tandem mass spectra acquired in a variety of types of mass analyzers and different fragmentation techniques. PowerNovo involves an ensemble of models for peptide sequencing: model for detecting regularities in tandem mass spectra, precursors, and fragment ions and a natural language processing model, which has a function of peptide sequence quality assessment and helps with reconstruction of noisy sequences. The results of testing showed that the performance of PowerNovo is comparable and even better than widely utilized PointNovo, DeepNovo, Casanovo, and Novor packages. Also, PowerNovo provides complete cycle of processing (pipeline) of mass spectrometry data and, along with predicting the peptide sequence, involves the peptide assembly and protein inference blocks. Tandem mass spectrometry ; Peptide ; Tandem mass tag ; Computational biology ; Peptide sequence ; Mass spectrometry ; Isobaric labeling ; Peptide mass fingerprinting ; Protein sequencing ; Mass spectrum ; Computer science ; Protein mass spectrometry ; Chemistry ; Proteomics ; Biology ; Quantitative proteomics ; Chromatography ; Biochemistry ; Gene Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Identification and Quantification in Food
Authors: Sohail M. A. Khan | Ajay Kumar
Source: Polymer Composites (review, 2024-11-04)
Field: Materials Science — Materials Chemistry

Failure analysis in advance cylindrical composite pressure vessel under pressure &amp; temperature for hydrogen storage: A comprehensive review Abstract Low‐thickness/diameter cylindrical storage pressure vessels with composite overwrapping fail at diverse internal and external pressure circumstances, causing several faults that must be included and minimized to retain effectiveness and working capability. The bursting effect is caused by hoop (internal) stresses and can be reduced by composite lamination alignment and internal pressure resistance. Pressure vessel bursting faults vary with internal tensions and can induce fiber reinforced polymer fracture and composite cylinder failure under many failure criteria. Micro‐mechanical nondestructive testing uses independent failure criteria associated to modes like Tsai‐Wu, Tsai‐Hill, Azzi‐Tsai, Hoffman, and Chamis. Micro‐cracking of composite layers generates delamination in composite pressure vessels, causing porosity. Pressure vessel micro‐cracking was assessed using classical laminate theory. Composite material strain‐rate failures in mobile applications like hydrogen storage cars with composite pressure vessels are examined due to their widespread use. Finally, Polar, Helical, and Hoop winding sequences are consistently focused to optimize the design and analyze the parameters for the overall impact of different failure aspects as bursting behavior in cylindrical composite pressure vessels. Type‐IV composite pressure vessels have the best results due to their lightest weight but complexity of winding over the polar head geodesic and non‐geodesic curvatures overwrapped carbon include all these internal composite and liner geometry faults and optimize them to reduce failure issues to fix composite overwrapped pressure vessels (COPV's) design. Liner‐less composite pressure vessels ( Type‐V ) need more design and production study for high‐pressure and temperature applications. Highlights Failure deals with the internal and external pressures exerted on composite pressure vessels. Failures like bursting of the pressure vessel, due to like micro‐cracking, delamination's and strain‐rate failures of composites. Failures detection through NDT inspection for polymer composite materials for composite pressure vessels. (COPV) perfect lamina sequence, liner materials and fiber winding angles must be considered for designing state of the art liner‐less Type‐V pressure vessels. Independent Failure criteria like (Tsai‐Wu &amp; Hashin). Materials science ; Composite number ; Pressure vessel ; Composite material ; Hydrogen storage ; Hydrogen ; Chemistry Hydrogen Storage and Materials ; Mechanical Failure Analysis and Simulation ; Spacecraft and Cryogenic Technologies
Authors: Xin Yang | Chi Ho Chan | Shanshan Yao | Hang Yin Chu | Minchuan Lyu | Ziqi Chen | Huan Xiao | Yuan Ma | Sifan Yu | Fangfei Li | Jin Liu | Luyao Wang | Zongkang Zhang | Bao‐Ting Zhang | Lu Zhang | Aiping Lü | Yaofeng Wang | Ge Zhang | Yuanyuan Yu
Source: Molecular Therapy — Nucleic Acids (article, 2024-12-21)
Field: Materials Science — Materials Chemistry

DeepAptamer: Advancing high-affinity aptamer discovery with a hybrid deep learning model Oligonucleotide aptamers are typically identified through a rigorous and time-consuming process known as systematic evolution of ligands by exponential enrichment (SELEX), which requires 20 to 30 iterative rounds to eliminate non/weak binding sequences and enrich tight binding sequences with high affinity. Moreover, inherent experimental biases and non-specific interactions within SELEX could inadvertently exclude high-affinity candidates, leading to a high failure rate. To address these challenges, we proposed DeepAptamer for identifying high-affinity sequences from unenriched early SELEX rounds. As a hybrid neural network model combining convolutional neural networks and bidirectional long short-term memory, DeepAptamer integrated sequence composition and structural features to predict aptamer binding affinities and potential binding motifs. Trained on comprehensive SELEX data, DeepAptamer outperformed existing models in accuracy as substantiated by experimental evidence. More importantly, DeepAptamer effectively identified key nucleotides for target binding. DeepAptamer can efficiently identify high-affinity aptamers against various targets, enhancing its potential to discover promising sequences in initial screening stages and obviating the 20-30 iterative selection rounds required for full enrichment of selection pools. This represented a notable leap forward in aptamer technology, with broad implications for its application across a spectrum of selection targets. Aptamer ; Deep learning ; Drug discovery ; Computational biology ; Computer science ; Nanotechnology ; Artificial intelligence ; Data science ; Biology ; Materials science ; Bioinformatics ; Molecular biology Machine Learning in Materials Science ; RNA and protein synthesis mechanisms ; Machine Learning and Algorithms
Authors: Zhiyi Wu | David Dotson | Irfan Alibay | Bryce K. Allen | Mohammad Soroush Barhaghi | Jérôme Hénin | Thomas T. Joseph | Ian M. Kenney | Hyungro Lee | Haoxi Li | Victoria T. Lim | Shuai Liu | Domenico Marson | Pascal T. Merz | Alexander Schlaich | David L. Mobley | Michael R. Shirts | Oliver Beckstein
Source: The Journal of Open Source Software (article, 2024-09-26)
Field: Chemistry — Physical and Theoretical Chemistry

alchemlyb: the simple alchemistry library <i>alchemlyb</i> is an open-source Python software package for the analysis of alchemical free energy calculations, an important method in computational chemistry and biology, most notably in the field of drug discovery (Merz et al., 2010). Its functionality contains individual composable building blocks for all aspects of a full typical free energy analysis workflow, starting with the extraction of raw data from the output of diverse molecular simulation packages, moving on to data preprocessing tasks such as decorrelation of time series, using various estimators to derive free energy estimates from simulation samples, and finally providing quality analysis tools for data convergence checking and visualization. <i>alchemlyb</i> also contains high-level end-to-end workflows that combine multiple building blocks into a user-friendly analysis pipeline from the initial data input stage to the final results. This workflow functionality enhances accessibility by enabling researchers from diverse scientific backgrounds, and not solely computational chemistry specialists, to use <i>alchemlyb</i> effectively. Simple (philosophy) ; Computer science ; Mathematics ; Philosophy Various Chemistry Research Topics ; Computational Drug Discovery Methods ; Protein Structure and Dynamics