jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Federico J. Hernández | Rachel Crespo‐Otero
Source: Annual Review of Physical Chemistry (review, 2023-02-16)
Field: Materials Science — Materials Chemistry

Modeling Excited States of Molecular Organic Aggregates for Optoelectronics Light-driven phenomena in organic molecular aggregates underpin several mechanisms relevant to optoelectronic applications. Modeling these processes is essential for aiding the design of new materials and optimizing optoelectronic devices. In this review, we cover the use of different atomistic models, excited-state dynamics, and transport approaches for understanding light-activated phenomena in molecular aggregates, including radiative and nonradiative decay pathways. We consider both intra- and intermolecular mechanisms and focus on the role of conical intersections as facilitators of internal conversion. We explore the use of the exciton models for Frenkel and charge transfer states and the electronic structure methods and algorithms commonly applied for excited-state dynamics. Throughout the review, we analyze the approximations employed for the simulation of internal conversion, intersystem crossing, and reverse intersystem crossing rates and analyze the molecular processes behind single fission, triplet-triplet annihilation, Dexter energy transfer, and Förster energy transfer. Intersystem crossing ; Excited state ; Exciton ; Singlet fission ; Intermolecular force ; Chemical physics ; Materials science ; Internal conversion ; Molecular dynamics ; Radiative transfer ; Physics ; Atomic physics ; Chemistry ; Triplet state ; Computational chemistry ; Molecule ; Singlet state ; Quantum mechanics Luminescence and Fluorescent Materials ; Organic Light-Emitting Diodes Research ; Photochemistry and Electron Transfer Studies
Authors: Qiuyue Yang | Emily P. Nguyen | David Panáček | Veronika Šedajová | Vítězslav Hrubý | Giulio Rosati | Cecília de Carvalho Castro Silva | Aristides Bakandritsos | Michal Otyepka | Arben Merkoçi
Source: Green Chemistry (article, 2023-01-01)
Field: Chemistry — Electrochemistry

Metal-free cysteamine-functionalized graphene alleviates mutual interferences in heavy metal electrochemical detection Heavy metal pollutants are of great concern to environmental monitoring due to their potent toxicity. Electrochemical detection, one of the main techniques, is hindered by the mutual interferences of various heavy metal ions in practical use. In particular, the sensitivity of carbon electrodes to Cd<sup>2+</sup> ions (one of the most toxic heavy metals) is often overshadowed by some heavy metals (<i>e.g.</i> Pb<sup>2+</sup> and Cu<sup>2+</sup>). To mitigate interference, metallic particles/films (<i>e.g.</i> Hg, Au, Bi, and Sn) typically need to be embedded in the carbon electrodes. However, these additional metallic materials may face issues of secondary pollution and unsustainability. In this study, a metal-free and sustainable nanomaterial, namely cysteamine covalently functionalized graphene (GSH), was found to lead to a 6-fold boost in the Cd<sup>2+</sup> sensitivity of the screen-printed carbon electrode (SPCE), while the sensitivities to Pb<sup>2+</sup> and Cu<sup>2+</sup> were not influenced in simultaneous detection. The selective enhancement could be attributed to the grafted thiols on GSH sheets with good affinity to Cd<sup>2+</sup> ions based on Pearson's hard and soft acid and base principle. More intriguingly, the GSH-modified SPCE (GSH-SPCE) featured high reusability with extended cycling times (23 times), surpassing the state-of-art SPCEs modified by non-covalently functionalized graphene derivatives. Last, the GSH-SPCE was validated in tap water. Graphene ; Cysteamine ; Electrochemistry ; Metal ; Materials science ; Inorganic chemistry ; Chemistry ; Nanotechnology ; Metallurgy ; Organic chemistry ; Electrode ; Physical chemistry Electrochemical Analysis and Applications ; Trace Elements in Health ; Molecular Sensors and Ion Detection
Authors: Asegid Belete Tegenaw | Ahmed Awol Yimer | Tamene Tadesse Beyene
Source: Heliyon (article, 2023-10-01)
Field: Materials Science — Materials Chemistry

Boosting the photocatalytic activity of ZnO-NPs through the incorporation of C-dot and preparation of nanocomposite materials Due to their applications in cosmetology, medicine, antibacterial and other fields, zinc oxide nanoparticles (ZnO-NPs) are among the nanoscale materials experiencing exponential growth. In contrast, pure ZnO-NPs have been reported to have a very large energy bandgap, a large exaction binding energy, electron-hole recombination, no visible light absorption, and poor photocatalytic activities, which limit their potential uses. ZnO-NPs can be further extended through the incorporation of trace amounts of carbon materials to engulf these problems. We investigate the photocatalytic degradation of methylene blue (MB) dye with pure ZnO-NPs infused with a limited amount of carbon dot (C-dot) materials. Consequently, adding 10% C-dot to ZnO-NPs reduced their energy bandgap from 3.1 to 2.8 eV and significantly increased their photocatalytic activity. MB was almost completely degraded (98.4%) after 60 min when 50 mg of C-dot-incorporated ZnO-NPs were added. By comparison, the nanocomposite's photocatalytic activity exceeded that of pure ZnO-NPs by more than 50%. A surface charge and stability improvement are responsible for the extraordinary photocatalytic improvement. As far as we know, this is the best-ever photocatalytic improvement achieved by incorporating a trace amount of C-dot material into pure ZnO-NPs. Photocatalysis ; Nanocomposite ; Materials science ; Band gap ; Nanotechnology ; Nanoparticle ; Zinc ; Quantum dot ; Chemical engineering ; Chemistry ; Catalysis ; Optoelectronics ; Organic chemistry ; Metallurgy Carbon and Quantum Dots Applications ; Advanced Photocatalysis Techniques ; Quantum Dots Synthesis And Properties
Authors: Pan‐Ke Zhou | Hongling Yu | Yiping Li | Hong Yu | Qian Chen | Xiong Chen
Source: Journal of Polymer Science (article, 2023-06-28)
Field: Materials Science — Materials Chemistry

Recent advances in covalent organic polymers‐based thin films as memory devices Abstract Covalent organic polymers (COPs) have emerged as a promising class of materials for memory devices due to their unique electronic properties and potential for tunability. This review highlights recent advances in the field of COPs‐based thin films for memory applications, with a focus on the synthesis and characterization of COP thin films, their electronic properties, and their performance as memory devices. The potential of COPs‐based thin films as flexible memory devices is also discussed. Overall, the recent progress in COPs‐based thin films for memory applications suggests that these materials may have a significant impact on the development of next‐generation memory technologies. Thin film ; Materials science ; Nanotechnology ; Covalent bond ; Polymer ; Characterization (materials science) ; Computer science ; Chemistry ; Organic chemistry ; Composite material Covalent Organic Framework Applications ; Advanced Memory and Neural Computing ; Conducting polymers and applications
Authors: Mohammed Abu‐Elghait | Mohamed K. Y. Soliman | Mohamed Salah Azab | Salem S. Salem
Source: Biomass Conversion and Biorefinery (article, 2023-12-23)
Field: Materials Science — Materials Chemistry

Response surface methodology: Optimization of myco-synthesized gold and silver nanoparticles by Trichoderma saturnisporum Abstract In the current study, the optimal reaction condition for fabrication of Au and Ag nanoparticles by using Trichoderma saturnisporum was developed. Optimization of fermentation conditions for extracellular AuNPs and AgNPs synthesis using response surface methodology was achieved. To accomplish the ideal reaction state, the green synthesis reaction’s effective parameters and central composite face design were used. Precursor concentrations, pH, and temperature were found to be the most effective parameters for the fabrication of Au and Ag nanomaterials. The model’s realization used a respectable foot. Normal probability plots; interaction plots, including effect plots; variance analysis (ANOVA), surface plots; contour plots; and Pareto charts were used to optimize the components. Significance threshold (5%) was used to influence all of the factors. The production process was also influenced by some of the potential connections between these factors. The recommended regression model fits the experimental data extremely well. The findings of this study looked at how much more bio-fabrication was possible with optimal fermentation conditions for the producer of AuNPs and AgNPs compared with traditional optimization techniques. Response surface methodology ; Central composite design ; Fabrication ; Silver nanoparticle ; Nanoparticle ; Trichoderma ; Thermal decomposition ; Realization (probability) ; Materials science ; Fermentation ; Nanomaterials ; Biological system ; Colloidal gold ; Nanotechnology ; Mathematics ; Computer science ; Chemistry ; Biotechnology ; Statistics ; Organic chemistry ; Biology Nanoparticles: synthesis and applications ; Graphene and Nanomaterials Applications ; Nanotechnology research and applications
Authors: Dan Li | Zheng Ouyang | Xiaoxiao Ma
Source: Molecules (review, 2023-03-17)
Field: Chemistry — Spectroscopy

Mass Spectrometry Imaging for Single-Cell or Subcellular Lipidomics: A Review of Recent Advancements and Future Development Mass Spectrometry Imaging (MSI) has emerged as a powerful imaging technique for the analysis of biological samples, providing valuable insights into the spatial distribution and structural characterization of lipids. The advancements in high-resolution MSI have made it an indispensable tool for single-cell or subcellular lipidomics. By preserving both intracellular and intercellular information, MSI enables a comprehensive analysis of lipidomics in individual cells and organelles. This enables researchers to delve deeper into the diversity of lipids within cells and to understand the role of lipids in shaping cell behavior. In this review, we aim to provide a comprehensive overview of recent advancements and future prospects of MSI for cellular/subcellular lipidomics. By keeping abreast of the cutting-edge studies in this field, we will continue to push the boundaries of the understanding of lipid metabolism and the impact of lipids on cellular behavior. Lipidomics ; Computational biology ; Mass spectrometry imaging ; Metabolomics ; STED microscopy ; Organelle ; Intracellular ; Biology ; Cell biology ; Chemistry ; Bioinformatics ; Mass spectrometry ; Computer science ; Superresolution ; Artificial intelligence Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Advanced Proteomics Techniques and Applications
Authors: Lei Zhang | Gábor Cśanyi | E. van der Giessen | Francesco Maresca
Source: npj Computational Materials (article, 2023-12-08)
Field: Materials Science — Metals and Alloys

Atomistic fracture in bcc iron revealed by active learning of Gaussian approximation potential Abstract The prediction of atomistic fracture mechanisms in body-centred cubic (bcc) iron is essential for understanding its semi-brittle nature. Existing atomistic simulations of the crack-tip under mode-I loading based on empirical interatomic potentials yield contradicting predictions and artificial mechanisms. To enable fracture prediction with quantum accuracy, we develop a Gaussian approximation potential (GAP) using an active learning strategy by extending a density functional theory (DFT) database of ferromagnetic bcc iron. We apply the active learning algorithm and obtain a Fe GAP model with a converged model uncertainty over a broad range of stress intensity factors (SIFs) and for four crack systems. The learning efficiency of the approach is analysed, and the predicted critical SIFs are compared with Griffith and Rice theories. The simulations reveal that cleavage along the original crack plane is the atomistic fracture mechanism for {100} and {110} crack planes at T = 0 K, thus settling a long-standing issue. Our work also highlights the need for a multiscale approach to predicting fracture and intrinsic ductility, whereby finite temperature, finite loading rate effects and pre-existing defects (e.g., nanovoids, dislocations) should be taken explicitly into account. Materials science ; Fracture (geology) ; Density functional theory ; Brittleness ; Gaussian ; Statistical physics ; Multiscale modeling ; Condensed matter physics ; Physics ; Composite material ; Computational chemistry ; Chemistry Hydrogen embrittlement and corrosion behaviors in metals ; Microstructure and mechanical properties ; Microstructure and Mechanical Properties of Steels
Authors: Yang Xu | Yilin Mao | Li He | Litao Sun | Shuangshuang Wang | Xiaojiang Li | Jiazhi Shen | Xinyue Yin | Kai Fan | Zhaotang Ding | Yu Wang
Source: Plant Methods (article, 2023-09-09)
Field: Chemistry — Analytical Chemistry

A deep learning model for rapid classification of tea coal disease This study revealed the classification potential of tea coal disease based on RGB and hyperspectral imaging, which can provide an accurate, non-destructive, and efficient classification method for monitoring tea coal disease. Hyperspectral imaging ; RGB color model ; Artificial intelligence ; Support vector machine ; Coal ; Pattern recognition (psychology) ; Computer science ; Deep learning ; Computer vision ; Geography Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Remote Sensing in Agriculture
Authors: Nina Gumbiowski | Κateryna Loza | Marc Heggen | Matthias Epple
Source: Nanoscale Advances (article, 2023-01-01)
Field: Materials Science — Surfaces, Coatings and Films

Automated analysis of transmission electron micrographs of metallic nanoparticles by machine learning Metallic nanoparticles were analysed with respect to size and shape by a machine learning approach. This involved a separation of particles from the background (segmentation), a separation of overlapping particles, and the identification of individual particles. An algorithm to separate overlapping particles, based on ultimate erosion of convex shapes (UECS), was implemented. Finally, particle properties like size, circularity, equivalent diameter, and Feret diameter were computed for each particle of the whole particle population. Thus, particle size distributions can be easily created based on the various parameters. However, strongly overlapping particles are difficult and sometimes impossible to separate because of an <i>a priori</i> unknown shape of a particle that is partially lying in the shadow of another particle. The program is able to extract information from a sequence of images of the same sample, thereby increasing the number of analysed nanoparticles to several thousands. The machine learning approach is well-suited to identify particles at only limited particle-to-background contrast as is demonstrated for ultrasmall gold nanoparticles (2 nm). Particle (ecology) ; Nanoparticle ; Nanoparticle tracking analysis ; Materials science ; Particle size ; Artificial intelligence ; A priori and a posteriori ; Segmentation ; Population ; Computer science ; Biological system ; Nanotechnology ; Chemistry ; Engineering ; Chemical engineering Electron and X-Ray Spectroscopy Techniques ; Enhanced Oil Recovery Techniques ; Mineral Processing and Grinding
Authors: Madhukiran R. Dhondale | Amritha G. Nambiar | Maan Singh | Abhishek R. Mali | Ashish Kumar Agrawal | Nalini R. Shastri | Pradeep Kumar | Dinesh Kumar
Source: Journal of Pharmaceutical Sciences (review, 2023-02-12)
Field: Materials Science — Materials Chemistry

Current Trends in API Co-Processing: Spherical Crystallization and Co-Precipitation Techniques Process analytical technology ; Process engineering ; Quality by Design ; Pharmaceutical manufacturing ; Granulation ; Computer science ; Robustness (evolution) ; Active ingredient ; Biochemical engineering ; Process development ; Nanotechnology ; Materials science ; New product development ; Work in process ; Engineering ; Chemistry ; Business Crystallization and Solubility Studies ; Innovative Microfluidic and Catalytic Techniques Innovation ; Drug Solubulity and Delivery Systems
Authors: P. Pathmanaban | B. K. Gnanavel | Shanmuga Sundaram Anandan | S. Sathiyamurthy
Source: Discover Food (article, 2023-12-21)
Field: Chemistry — Analytical Chemistry

Advancing post-harvest fruit handling through AI-based thermal imaging: applications, challenges, and future trends Abstract Recent advancements in imaging, electronics, and computer science have engendered significant progress in non-destructive testing and quality monitoring within the agro-food industry. This progress is particularly evident in integrating infrared thermal imaging (TI) and artificial intelligence (AI) techniques. As a non-contact method, AI-based TI holds promise in detecting various quality attributes and has found extensive applications in agriculture, food processing, and post-harvest fruit handling. This paper delves into recent applications of AI-based thermal imaging, specifically in post-harvest fruit handling. The introduction provides a comprehensive overview of the challenges faced in the post-harvest fruit handling industry while emphasizing the advantages of AI-driven thermal imaging technology. The detailed thermal imaging system encompasses both passive and active thermography techniques. This paper provides an in-depth exploration of artificial intelligence, focusing on machine learning and deep learning. It highlights the significance of convolutional neural networks (CNNs) and their architectural phases. Subsequently, critical applications of AI-based thermal imaging in post-harvest fruit quality assessment are discussed. These applications encompass bruise detection, maturity identification, condition monitoring, grading and sorting, pest and disease detection, and considerations for packaging and supply chain management. Furthermore, this paper addresses the challenges and limitations of AI-based thermal imaging in post-harvest fruit handling. In conclusion, this paper discusses future trends in AI-based thermal imaging, emphasizing the potential for increased automation and integration with emerging technologies in the post-harvest fruit handling sector. The insights provided contribute to the ongoing dialog surrounding optimizing quality assessment processes in the agro-food industry. Computer science ; Artificial intelligence ; Convolutional neural network ; Thermography ; Hyperspectral imaging ; Automation ; Systems engineering ; Engineering Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Date Palm Research Studies
Authors: Katerina Djambazova | Jacqueline M. Van Ardenne | Jeffrey M. Spraggins
Source: TrAC Trends in Analytical Chemistry (article, 2023-10-14)
Field: Chemistry — Spectroscopy

Advances in imaging mass spectrometry for biomedical and clinical research Mass spectrometry imaging ; Context (archaeology) ; Mass spectrometry ; MALDI imaging ; Nanotechnology ; Desorption electrospray ionization ; Computer science ; Computational biology ; Data science ; Chemistry ; Matrix-assisted laser desorption/ionization ; Materials science ; Desorption ; Chromatography ; Ionization ; Biology Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Bacterial Identification and Susceptibility Testing
Authors: Eli J. Larson | Melissa R. Pergande | Michelle E. Moss | Kalina J. Rossler | Rephael Wenger | Boris Krichel | Harini Josyer | Jake A. Melby | David S. Roberts | Kyndalanne Pike | Zhuoxin Shi | Hsin‐Ju Chan | Bridget Knight | Holden T. Rogers | Kyle A. Brown | Irene M. Ong | Kyowon Jeong | Michael T. Marty | Sean J. McIlwain | Ying Ge
Source: Bioinformatics (article, 2023-06-01)
Field: Chemistry — Spectroscopy

MASH Native: a unified solution for native top-down proteomics data processing The MASH Native app, video tutorials, written tutorials, and additional documentation are freely available for download at https://labs.wisc.edu/gelab/MASH_Explorer/MASHSoftware.php. All data files shown in user tutorials are included with the MASH Native software in the download .zip file. Computer science ; Software ; Documentation ; Interface (matter) ; Download ; Source code ; User Friendly ; Database ; World Wide Web ; Information retrieval ; Programming language ; Operating system Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Yuncheng Liu | Ke Xu | Xuhao Fan | Xinger Wang | Xuan Yu | Wei Xiong | Hui Gao
Source: Opto-Electronic Advances (article, 2023-12-18)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Dynamic interactive bitwise meta-holography with ultra-high computational and display frame rates Interactive holography offers unmatched levels of immersion and user engagement in the field of future display. Despite of the substantial progress has been made in dynamic meta-holography, the realization of real-time, highly smooth interactive holography remains a significant challenge due to the computational and display frame rate limitations. In this study, we introduced a dynamic interactive bitwise meta-holography with ultra-high computational and display frame rates. To our knowledge, this is the first reported practical dynamic interactive metasurface holographic system. We spatially divided the metasurface device into multiple distinct channels, each projecting a reconstructed sub-pattern. The switching states of these channels were mapped to bitwise operations on a set of bit values, which avoids complex hologram computations, enabling an ultra-high computational frame rate. Our approach achieves a computational frame rate of 800 kHz and a display frame rate of 23 kHz on a low-power Raspberry Pi computational platform. According to this methodology, we demonstrated an interactive dynamic holographic Tetris game system that allows interactive gameplay, color display, and on-the-fly hologram creation. Our technology presents an inspiration for advanced dynamic meta-holography, which is promising for a broad range of applications including advanced human-computer interaction, real-time 3D visualization, and next-generation virtual and augmented reality systems. Holography ; Frame rate ; Computer science ; Holographic display ; Visualization ; Bitwise operation ; Frame (networking) ; Computer graphics (images) ; Virtual reality ; Computer vision ; Computation ; Artificial intelligence ; Optics ; Algorithm Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Advanced Optical Imaging Technologies