jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Rixi Peng | Simiao Ren | Jordan M. Malof | Willie J. Padilla
Source: Nanophotonics (article, 2024-03-22)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Transfer learning for metamaterial design and simulation We demonstrate transfer learning as a tool to improve the efficacy of training deep learning models based on residual neural networks (ResNets). Specifically, we examine its use for study of multi-scale electrically large metasurface arrays under open boundary conditions in electromagnetic metamaterials. Our aim is to assess the efficiency of transfer learning across a range of problem domains that vary in their resemblance to the original base problem for which the ResNet model was initially trained. We use a quasi-analytical discrete dipole approximation (DDA) method to simulate electrically large metasurface arrays to obtain ground truth data for training and testing of our deep neural network. Our approach can save significant time for examining novel metasurface designs by harnessing the power of transfer learning, as it effectively mitigates the pervasive data bottleneck issue commonly encountered in deep learning. We demonstrate that for the best case when the transfer task is sufficiently similar to the target task, a new task can be effectively trained using only a few data points yet still achieve a test mean absolute relative error of 3 % with a pre-trained neural network, realizing data reduction by a factor of 1000. Computer science ; Bottleneck ; Transfer of learning ; Metamaterial ; Artificial neural network ; Deep learning ; Artificial intelligence ; Task (project management) ; Inductive transfer ; Reduction (mathematics) ; Machine learning ; Residual ; Algorithm ; Physics ; Optics Metamaterials and Metasurfaces Applications ; Electromagnetic Scattering and Analysis ; Animal Vocal Communication and Behavior
Authors: Víctor Tuninetti | Diego Forcael | Marian Valenzuela | Alex Martínez | Andrés I. Ávila | Carlos Medina | Gonzalo Pincheira | Alexis Salas | Ángelo Oñate | Laurent Duchêne
Source: Materials (article, 2024-01-08)
Field: Materials Science — Materials Chemistry

Assessing Feed-Forward Backpropagation Artificial Neural Networks for Strain-Rate-Sensitive Mechanical Modeling The manufacturing processes and design of metal and alloy products can be performed over a wide range of strain rates and temperatures. To design and optimize these processes using computational mechanics tools, the selection and calibration of the constitutive models is critical. In the case of hazardous and explosive impact loads, it is not always possible to test material properties. For this purpose, this paper assesses the efficiency and the accuracy of different architectures of ANNs for the identification of the Johnson-Cook material model parameters. The implemented computational tool of an ANN-based parameter identification strategy provides adequate results in a range of strain rates required for general manufacturing and product design applications. Four ANN architectures are studied to find the most suitable configuration for a reduced amount of experimental data, particularly for cases where high-impact testing is constrained. The different ANN structures are evaluated based on the model's predictive capability, revealing that the perceptron-based network of 66 inputs and one hidden layer of 30 neurons provides the highest prediction accuracy of the effective flow stress-strain behavior of Ti64 alloy and three virtual materials. Artificial neural network ; Backpropagation ; Multilayer perceptron ; Perceptron ; Computer science ; Strain rate ; Range (aeronautics) ; Explosive material ; Calibration ; Identification (biology) ; Artificial intelligence ; Materials science ; Mathematics High-Velocity Impact and Material Behavior ; Metallurgy and Material Forming ; Metal and Thin Film Mechanics
Authors: Riichiro Saito | Nguyen Tuan Hung | Teng Yang | Jianqi Huang | Hsiang‐Lin Liu | Desman Perdamaian Gulo | Shiyi Han | Lianming Tong
Source: Small (review, 2024-02-27)
Field: Materials Science — Materials Chemistry

Deep‐Ultraviolet and Helicity‐Dependent Raman Spectroscopy for Carbon Nanotubes and 2D Materials Recent progress of Raman spectroscopy on carbon nanotubes and 2D materials is reviewed as a topical review. The Raman tensor with complex values is related to the chiral 1D/2D materials without mirror symmetry for the mirror in the propagating direction of light, such as chiral carbon nanotube and black phosphorus. The phenomenon of complex Raman tensor is observed by the asymmetric polar plot of helicity-dependent Raman spectroscopy using incident circularly-polarized lights. First-principles calculations of resonant Raman spectra directly give the complex Raman tensor that explains helicity-dependent Raman spectra and laser-energy-dependent relative intensities of Raman spectra. In deep-ultraviolet (DUV) Raman spectroscopy with 266 nm laser, since the energy of the photon is large compared with the energy gap, the first-order and double resonant Raman processes occur in general k points in the Brillouin zone. First-principles calculation is necessary to understand the DUV Raman spectra and the origin of double-resonance Raman spectra. Asymmetric line shapes appear for the G band of graphene for 266 nm laser and in-plane Raman mode of WS<sub>2</sub> for 532 nm laser, while these spectra show symmetric line shapes for other laser excitation. The interference effect on the asymmetric line shape is discussed by fitting the spectra to the Breit-Wigner-Fano line shapes. Carbon nanotube ; Raman spectroscopy ; Materials science ; Ultraviolet ; Helicity ; Carbon nanobud ; Carbon fibers ; Spectroscopy ; Nanotechnology ; Optical properties of carbon nanotubes ; Optoelectronics ; Nanotube ; Composite material ; Optics ; Physics ; Composite number Graphene research and applications ; 2D Materials and Applications ; Carbon Nanotubes in Composites
Authors: Jianwei Liang | Menghao Zhang | Yan Peng | Jiapo Wang
Source: Metals (article, 2024-04-29)
Field: Materials Science — Materials Chemistry

Advances in Understanding the Evolution Mechanism of Micropore Defects in Metal Materials under External Loads Micropores are one of the critical factors affecting materials’ performance and service life. As the need for a deeper understanding of micropore evolution and damage mechanisms grows, assessing the mechanical properties of materials containing micropores and predicting the lifespan of related metal structural components becomes increasingly complex. This paper focuses on the evolution process, regularities, and research methods of micropores in metal materials. Based on recent research and practical applications, the key stages of micropore evolution are discussed, encompassing nucleation, growth, coalescence, collapse, interaction, and the influence of other microstructures. Firstly, the advantages and limitations of commonly used characterization methods such as scanning electron microscopy, transmission electron microscopy, and X-ray computed tomography are introduced in the study of micropore evolution. Subsequently, critical theoretical models for micropore evolution, such as the Gurson model and its extensions, are summarized. By using a multiscale approach combining the crystal plasticity finite element method, dislocation dynamics, and molecular dynamics, the factors influencing the micropore evolution, such as external stress conditions, internal microstructures, and micropore characteristics, are specifically elaborated, and the basic physical mechanisms of micropore evolution are analyzed. Finally, a comprehensive review and summary of current research trends and key findings are provided, and a forward-looking perspective on future research directions is presented. Microporous material ; Coalescence (physics) ; Materials science ; Microstructure ; Nucleation ; Characterization (materials science) ; Nanotechnology ; Biochemical engineering ; Computer science ; Engineering ; Metallurgy ; Composite material ; Physics ; Thermodynamics Microstructure and mechanical properties ; Metallurgy and Material Forming ; Hydrogen embrittlement and corrosion behaviors in metals
Authors: Nigel Kurgan | Jeppe Kjærgaard Larsen | Atul S. Deshmukh
Source: Diabetologia (article, 2024-02-12)
Field: Chemistry — Spectroscopy

Harnessing the power of proteomics in precision diabetes medicine Human physiology ; Proteomics ; Precision medicine ; Diabetes mellitus ; Medicine ; Computational biology ; Computer science ; Internal medicine ; Biology ; Endocrinology ; Pathology ; Genetics Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Genetic Associations and Epidemiology
Authors: Mehmet Karahan | İrem Özyurt | S. Atalay | Serkan Turan | Aminoddin Hajı | Nevin Karahan
Source: Polymer Composites (article, 2024-10-29)
Field: Materials Science — Polymers and Plastics

Comparative study of virgin and recycled polyethylene terephthalate and polypropylene intermingled thermoplastic composites Abstract In this study, a comparative analysis of the use of recycled PET (R‐PET) in synthetic and natural fiber blended composites was made. PET, R‐PET, and PP yarns were folded with reinforcing fibers by commingling technique and then fabrics were prepared using weaving technology. Hot compression molding technology was used for composite fabrication. Tensile and impact characterization revealed the significant influence of reinforcing and TP fibers on mechanical properties. R‐PET matrix glass fiber reinforced composites exhibited 41.77% higher tensile strength than virgin PET and 20.41% higher than PP. In terms of tensile strength for linen reinforced samples, R‐PET shows an impressive 181% improvement over virgin PET and 154% over PP. According to the drop weight test results, glass fiber reinforced R‐PET matrix sample exhibited a peak load value 53% higher than that of the virgin PET matrix, although it was 9.47% lower than the PP matrix. In linen fiber reinforced samples, R‐PET demonstrated a 57.73% improvement over virgin PET but lower by 9.47% compared to the PP matrix. During this time, DSC, TGA, FTIR, and flammability tests were also performed on the composite samples. The results showed that R‐PET has easy processability as a matrix material and provides better wetting of the reinforcing fibers. For this reason, it has been shown that R‐PET matrix samples provide better mechanical properties than both PET and PP matrix samples. It has also been determined that R‐PET is a more suitable matrix material compared with natural fiber reinforced composites. Highlights Commingled yarns were used for preparing composites. R‐PET yarns were used as matrix in preparing glass and linen reinforced composites. R‐PET was compared with virgin PET and PP yarns. R‐PET showed great potential in easy preparation of TP composites. Composites made with R‐PET showed improved thermal and mechanical properties. Materials science ; Composite material ; Polypropylene ; Polyethylene terephthalate ; Thermoplastic ; Thermoplastic composites ; Polyethylene Natural Fiber Reinforced Composites ; biodegradable polymer synthesis and properties ; Polymer crystallization and properties
Authors: Israel Agranat
Source: Structural Chemistry (article, 2024-04-23)
Field: Chemistry — Organic Chemistry

Aromaticity – a theoretical notion Abstract In 2023, a themed collection on “Emerging frontiers in aromaticity” was published in Chemical Science . The collection included a Perspective Essay entitled “Aromaticity – Quo Vadis”, which presents a wealth of viewpoints on the multiple definitions of aromaticity. The present Prefatory Review revives the viewpoint that aromaticity is a theoretical notion and as such, its meaning is theory dependent. Therefore, when aromaticity is made to correspond to two or more ‘experimental’ ideas, e.g., energetic, structural, electronic, magnetic, it would be absurd to maintain that aromaticity is explicitly defined by each of these ideas in turn. The Review emphasizes that the descriptor ‘theoretical’ in general, including in the context of aromaticity does not mean ‘computational’. The theoretical notion of aromaticity is illustrated by Craig’s rules of aromaticity and by Craig’s second type of aromaticity based on symmetry and delocalization in pπ-dπ bonds, recently highlighted as ‘Craig-Type Möbius aromaticity’. Aromaticity ; Electron delocalization ; Chemistry ; Delocalized electron ; Annulene ; Status quo ; Context (archaeology) ; Computational chemistry ; Law ; Molecule ; Organic chemistry Synthesis and Properties of Aromatic Compounds ; Graph theory and applications ; Fullerene Chemistry and Applications
Authors: Mahdi Ghaderi | Seyed Ahmad Mireei | Aminollah Masoumi | Mohammad Sedghi | Majid Nazeri
Source: Scientific Reports (article, 2024-01-14)
Field: Chemistry — Analytical Chemistry

Fertility detection of unincubated chicken eggs by hyperspectral transmission imaging in the Vis-SWNIR region Detection of infertile eggs prior to incubation can lead to an increase in the hatchability rate and prevent the wastage of billions of non-fertile eggs ended up by failed incubation. In this study, the feasibility of a line-scan hyperspectral imaging system in the visible and short-wavelength near-infrared region was assessed for early detection of non-fertile eggs on day 0 before incubation. A total of 227 white-shell eggs including 131 fertile and 96 infertile eggs were collected from a flock with similar conditions in terms of hen age, feeding, and management. Hyperspectral images of eggs were captured on day 0 before incubation in a transmittance mode of illumination and then the eggs were incubated in a commercial incubator. The edge detection method was used to segment the egg, including both the white and yolk, from the background, and the image spectral information was extracted from the egg region. After applying various pretreatment methods, different classifiers including soft independent modeling of class analogy (SIMCA), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and artificial neural networks (ANN) classifiers were utilized to extract the predictive models. Following the acceptable results of SIMCA analysis accomplished by 1st derivative pretreatment (accuracy of 86.67%), the discrimination power plot was used to select the most informative wavebands. The results showed that by using fewer variables in effective wavebands better performance (precision and accuracy of 92.59% and 93.33%, respectively) could be obtained in comparison with the ANN classifier based on the whole spectral data (precision and accuracy of 89.29% and 91.11%, respectively). This study revealed the potential application of hyperspectral transmittance imaging in the Vis-SWNIR region to discern the fertile and infertile eggs before starting the incubation process. Hyperspectral imaging ; Linear discriminant analysis ; Artificial intelligence ; Quadratic classifier ; Biology ; Mathematics ; Pattern recognition (psychology) ; Computer science ; Classifier (UML) Spectroscopy and Chemometric Analyses ; Animal Nutrition and Physiology ; Meat and Animal Product Quality
Authors: Weikang Luo | Cong Chen | Xin Guo | Xiaohang Guo | Jun Zheng | Jingjing Liu | Xudong Fan | Min Luo | Zhe Yu | Haigang Li | Juewen Liu | Yang Wang
Source: Advanced Functional Materials (article, 2024-12-17)
Field: Materials Science — Biomaterials

Critical Challenges of Intravenous Nanomaterials Crossing the Blood‐Brain Barrier: from Blood to Brain Abstract Despite recent advancements in the development of blood‐brain barrier (BBB)‐crossing nanomaterials for intravenous administration, there have been very few successful cases in clinical trials. Ongoing challenges within the body impede the precise therapeutic effects of these nanomaterials from reaching their intended target area. Therefore, a comprehensive analysis of the entire pathway that BBB‐crossing nanomaterials must traverse‐from the bloodstream to the brain‐along with an understanding of the obstacles encountered along the way, is essential for advancing these materials to clinical trials. This review begins with a brief overview of the structure and function of the BBB, as well as the pathways and strategies for crossing it. Next, it is discussed and analyzed the common challenges that BBB‐crossing nanomaterials in reaching their target sites in the brain from the bloodstream. To address these challenges, an “eight‐step” guideline strategy is proposed. By leveraging the principles of precision medicine, the design and customization of cascade‐targeted BBB‐crossing nanomaterials that can overcome multiple obstacles show promise for future clinical trials and practical applications. Finally, a perspective on the future direction of this field is offered. Blood–brain barrier ; Materials science ; Brain trauma ; Nanomaterials ; Nanotechnology ; Neuroscience ; Medicine ; Traumatic brain injury ; Central nervous system ; Biology ; Psychiatry Nanoparticle-Based Drug Delivery ; Nanoplatforms for cancer theranostics ; Graphene and Nanomaterials Applications
Authors: Laura de Lorenzo | Tyler Stack | Kristin M. Fox | Katherine M. Walstrom
Source: Essays in Biochemistry (review, 2024-05-09)
Field: Materials Science — Materials Chemistry

Catalytic mechanism and kinetics of malate dehydrogenase Malate dehydrogenase (MDH) is a ubiquitous and central enzyme in cellular metabolism, found in all kingdoms of life, where it plays vital roles in the cytoplasm and various organelles. It catalyzes the reversible NAD+-dependent reduction of L-malate to oxaloacetate. This review describes the reaction mechanism for MDH and the effects of mutations in and around the active site on catalytic activity and substrate specificity, with a particular focus on the loop that encloses the active site after the substrates have bound. While MDH exhibits selectivity for its preferred substrates, mutations can alter the specificity of MDH for each cosubstrate. The kinetic characteristics and similarities of a variety of MDH isozymes are summarized, and they illustrate that the KM values are consistent with the relative concentrations of the substrates in cells. As a result of its existence in different cellular environments, MDH properties vary, making it an attractive model enzyme for studying enzyme activity and structure under different conditions. Malate dehydrogenase ; Enzyme ; Biochemistry ; Isozyme ; Cytoplasm ; Cofactor ; NAD+ kinase ; Enzyme kinetics ; Organelle ; Active site ; Biology ; Citrate synthase ; Substrate (aquarium) ; Chemistry Enzyme Structure and Function ; Amino Acid Enzymes and Metabolism ; Biochemical and Molecular Research
Authors: Christian A. Sanchez | Germán Vargas-Cuebas | Marina E. Michaud | Ryan A. Allen | Kelly R. Morrison-Lewis | Shehreen Siddiqui | Kevin P. C. Minbiole | William M. Wuest
Source: ACS Infectious Diseases (article, 2024-10-23)
Field: Chemistry — Organic Chemistry

Highly Effective Biocides against <i>Pseudomonas aeruginosa</i> Reveal New Mechanistic Insights Across Gram-Negative Bacteria <i>Pseudomonas aeruginosa</i> is a major nosocomial pathogen that persists in healthcare settings despite rigorous disinfection protocols due to intrinsic mechanisms conferring resistance. We sought to systematically assess cationic biocide efficacy against this pathogen using a panel of multidrug-resistant <i>P. aeruginosa</i> clinical isolates. Our studies revealed widespread resistance to commercial cationic disinfectants that are the current standard of care, raising concerns about their efficacy. To address this shortcoming, we highlight a new class of quaternary phosphonium compounds that are highly effective against all members of the panel. To understand the difference in efficacy, mechanism of action studies were carried out, which identified a discrete inner-membrane selective target. Resistance selection studies implicated the SmvRA efflux system (a transcriptionally regulated, inner membrane-associated efflux system) as a major determinant of resistance. This system is also implicated in resistance to two commercial bolaamphiphile antiseptics, octenidine and chlorhexidine, which was further validated herein. In sum, this work highlights, for the first time, a discrete inner-membrane specific mechanism for the bolaamphiphile class of disinfectants that contrasts with the prevailing model of indiscriminate membrane interactions of commercial amphiphiles paving the way for future innovations in disinfectant research. Pseudomonas aeruginosa ; Biocide ; Gram-negative bacteria ; Bacteria ; Microbiology ; Gram-negative bacterial infections ; Biology ; Gram ; Antibiotics ; Chemistry ; Escherichia coli ; Genetics Antimicrobial agents and applications ; Bacterial biofilms and quorum sensing ; Pharmaceutical and Antibiotic Environmental Impacts
Authors: Miguel Vega-Castellote | María‐Teresa Sánchez | Irina Torres | José Antonio Entrenas | Dolores Pérez‐Marín
Source: Foods (review, 2024-05-22)
Field: Chemistry — Analytical Chemistry

NIR Sensing Technologies for the Detection of Fraud in Nuts and Nut Products: A Review Food fraud is a major threat to the integrity of the nut supply chain. Strategies using a wide range of analytical techniques have been developed over the past few years to detect fraud and to assure the quality, safety, and authenticity of nut products. However, most of these techniques present the limitations of being slow and destructive and entailing a high cost per analysis. Nevertheless, near-infrared (NIR) spectroscopy and NIR imaging techniques represent a suitable non-destructive alternative to prevent fraud in the nut industry with the advantages of a high throughput and low cost per analysis. This review collects and includes all major findings of all of the published studies focused on the application of NIR spectroscopy and NIR imaging technologies to detect fraud in the nut supply chain from 2018 onwards. The results suggest that NIR spectroscopy and NIR imaging are suitable technologies to detect the main types of fraud in nuts. Nut ; Near-infrared spectroscopy ; Supply chain ; Computer science ; Quality (philosophy) ; Business ; Engineering ; Marketing ; Biology Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food ; Spectroscopy Techniques in Biomedical and Chemical Research