jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Yan Chen | Boyuan Gou | Bincheng Yuan | Xiangdong Ding | Jun Sun | Ekhard K. H. Salje
Source: physica status solidi (b) (article, 2021-11-19)
Field: Materials Science — Materials Chemistry

Multiple Avalanche Processes in Acoustic Emission Spectroscopy: Multibranching of the Energy−Amplitude Scaling Several physical processes can conspire to generate avalanches in materials. Such processes include avalanche mechanisms like dislocation movements, friction processes by pinning magnetic domain walls, moving dislocation tangles, hole collapse in porous materials, collisions of ferroelectric and ferroelastic domain boundaries, kinks in interfaces, and many more. Known methods to distinguish between these species which allow the physical identification of multiavalanche processes are reviewed. A new approach where the scaling relationship between the avalanche energies E and amplitudes A is considered is then described. Avalanches with single mechanisms scale experimentally as E = S i A i 2 . The energy E reflects the duration D of the avalanche and A ( t ), the temporal amplitude. The scaling prefactor S depends explicitly on the duration of the avalanche and on details of the avalanche profiles. It is reported that S is not a universal constant but assumes different values depending on the avalanche mechanism. If avalanches coincide, they can still show multivalued scaling between E and A with different S ‐values for each branch. Examples for this multibranching effect in low‐Ni 316L stainless steel, 316L stainless steel, polycrystalline Ni, TC21 titanium alloy, and a Fe 40 Mn 40 Co 10 Cr 10 high‐entropy alloy are shown. Scaling ; Amplitude ; Condensed matter physics ; Dislocation ; Materials science ; Avalanche breakdown ; Alloy ; Physics ; Frequency scaling ; Barkhausen effect ; Magnetic field ; Magnetization ; Composite material ; Optics ; Breakdown voltage ; Geometry ; Quantum mechanics ; Voltage Microstructure and mechanical properties ; High Temperature Alloys and Creep ; Hydrogen embrittlement and corrosion behaviors in metals
Authors: Ge Zhang | Sean A. Ridout | Andrea J. Liu
Source: Physical Review X (article, 2021-10-27)
Field: Materials Science — Materials Chemistry

Interplay of Rearrangements, Strain, and Local Structure during Avalanche Propagation Jammed soft disks exhibit avalanches of particle rearrangements under quasistatic shear. We introduce a framework for understanding the statistics of the progression of avalanches. We follow the avalanches (simulated using steepest descent energy minimization) to decompose them into individual localized rearrangements. We characterize the local structural environment of each particle by a machine-learned quantity, softness, designed to be highly correlated with rearrangements, and analyze the interplay between softness, rearrangements, and strain. Local yield strain has long been incorporated into elastoplastic models; here we show that softness provides a useful proxy for local yield strain. Our findings demonstrate that elastoplastic models must take into account the fully tensorial strain field in order to include the effects of changes in local yield strain due to rearrangements and introduce the equations underpinning a structuroelastoplastic model that includes local softness. Strain (injury) ; Materials science ; Physics ; Statistical physics ; Medicine Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Microstructure and mechanical properties
Authors: Amirhossein Alaghmandfard | Hamid Reza Madaah Hosseini
Source: Applied Nanoscience (article, 2021-01-03)
Field: Materials Science — Materials Chemistry

A facile, two-step synthesis and characterization of Fe3O4–LCysteine–graphene quantum dots as a multifunctional nanocomposite Nanocomposite ; Materials science ; Superparamagnetism ; Graphene ; Fourier transform infrared spectroscopy ; Quantum dot ; Nanoparticle ; Nanotechnology ; Nanochemistry ; Transmission electron microscopy ; Magnetic nanoparticles ; Scanning electron microscope ; Photoluminescence ; Chemical engineering ; Magnetization ; Optoelectronics ; Composite material ; Magnetic field Carbon and Quantum Dots Applications ; Graphene and Nanomaterials Applications ; Nanocluster Synthesis and Applications
Authors: Soo Chung | Seung-Chul Yoon
Source: Applied Sciences (article, 2021-12-16)
Field: Chemistry — Analytical Chemistry

Detection of Foreign Materials on Broiler Breast Meat Using a Fusion of Visible Near-Infrared and Short-Wave Infrared Hyperspectral Imaging Foreign material (FM) found on a poultry product lowers the quality and safety of the product. We developed a fusion method combining two hyperspectral imaging (HSI) modalities in the visible-near infrared (VNIR) range of 400–1000 nm and the short-wave infrared (SWIR) range of 1000–2500 nm for the detection of FMs on the surface of fresh raw broiler breast fillets. Thirty different types of FMs that could be commonly found in poultry processing plants were used as samples and prepared in two different sizes (5 × 5 mm2 and 2 × 2 mm2). The accuracies of the developed Fusion model for detecting 2 × 2 mm2 pieces of polymer, wood, and metal were 95%, 95%, and 81%, respectively, while the detection accuracies of the Fusion model for detecting 5 × 5 mm2 pieces of polymer, wood, and metal were all 100%. The performance of the Fusion model was higher than the VNIR- and SWIR-based detection models by 18% and 5%, respectively, when F1 scores were compared, and by 38% and 5%, when average detection rates were compared. The study results suggested that the fusion of two HSI modalities could detect FMs more effectively than a single HSI modality. VNIR ; Hyperspectral imaging ; Broiler ; Infrared ; Chicken breast ; Materials science ; Fusion ; Remote sensing ; Optics ; Food science ; Chemistry ; Geology ; Physics Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Remote-Sensing Image Classification
Authors: Erika Carlos Medeiros | Leandro M. Almeida | José Gilson de Almeida Teixeira Filho
Source: Informatics (article, 2021-10-19)
Field: Chemistry — Analytical Chemistry

Computer Vision and Machine Learning for Tuna and Salmon Meat Classification Aquatic products are popular among consumers, and their visual quality used to be detected manually for freshness assessment. This paper presents a solution to inspect tuna and salmon meat from digital images. The solution proposes hardware and a protocol for preprocessing images and extracting parameters from the RGB, HSV, HSI, and L*a*b* spaces of the collected images to generate the datasets. Experiments are performed using machine learning classification methods. We evaluated the AutoML models to classify the freshness levels of tuna and salmon samples through the metrics of: accuracy, receiver operating characteristic curve, precision, recall, f1-score, and confusion matrix (CM). The ensembles generated by AutoML, for both tuna and salmon, reached 100% in all metrics, noting that the method of inspection of fish freshness from image collection, through preprocessing and extraction/fitting of features showed exceptional results when datasets were subjected to the machine learning models. We emphasize how easy it is to use the proposed solution in different contexts. Computer vision and machine learning, as a nondestructive method, were viable for external quality detection of tuna and salmon meat products through its efficiency, objectiveness, consistency, and reliability due to the experiments’ high accuracy. Tuna ; Artificial intelligence ; RGB color model ; Preprocessor ; Computer science ; Consistency (knowledge bases) ; Machine learning ; Pattern recognition (psychology) ; Confusion matrix ; Fish <Actinopterygii> ; Computer vision ; Fishery ; Biology Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food ; Advanced Chemical Sensor Technologies
Authors: Niccolò Peruzzi | Silvia Galli | Heike Helmholz | Nikolay Kardjilov | Diana Krüger | Henning Markötter | Julian Moosmann | Dmytro Orlov | Zdenka Prgomet | Regine Willumeit‐Römer | Ann Wennerberg | Martin Bech
Source: Acta Biomaterialia (article, 2021-09-30)
Field: Materials Science — Biomaterials

Multimodal ex vivo methods reveal that Gd-rich corrosion byproducts remain at the implant site of biodegradable Mg-Gd screws Extensive research is being conducted on magnesium (Mg) alloys for bone implant manufacturing, due to their biocompatibility, biodegradability and mechanical properties. Gadolinium (Gd) is among the most promising alloying elements for property control in Mg alloy implants; however, its toxicity is controversial. Investigating Gd behavior during implant corrosion is thus of utmost importance. In this study, we analyzed the degradation byproducts at the implant site of biodegradable Mg-5Gd and Mg-10Gd implants after 12 weeks healing time, using a combination of different imaging techniques: histology, energy-dispersive x-ray spectroscopy (EDX), x-ray microcomputed tomography (µCT) and neutron µCT. The main finding has been that, at the healing time in exam, the corrosion appears to have involved only the Mg component, which has been substituted by calcium and phosphorus, while the Gd remains localized at the implant site. This was observed in 2D by means of EDX maps and extended to 3D with a novel application of neutron tomography. X-ray fluorescence analysis of the main excretory organs also did not reveal any measurable accumulation of Gd, further reinforcing the conclusion that very limited or no removal at all of Gd-alloy happened during degradation. STATEMENT OF SIGNIFICANCE: Gadolinium is among the most promising alloying elements for property control in biodegradable magnesium alloy implants, but its toxicity is controversial and its behavior during corrosion needs to be investigated. We combine 2D energy dispersive x-ray spectroscopy and 3D neutron and x-ray tomography to image the degradation of magnesium-gadolinium implants after 12 weeks of healing time. We find that, at the time in exam, the corrosion has involved only the magnesium component, while the gadolinium remains localized at the implant site. X-ray fluorescence analysis of the main excretory organs also does not reveal any measurable accumulation of Gd, further reinforcing the conclusion that very limited or no removal at all of Gd-alloy has happened during degradation. Materials science ; Biocompatibility ; Gadolinium ; Corrosion ; Implant ; Alloy ; Magnesium ; Energy-dispersive X-ray spectroscopy ; Biomedical engineering ; Nuclear chemistry ; Metallurgy ; Composite material ; Scanning electron microscope ; Medicine ; Chemistry ; Surgery Magnesium Alloys: Properties and Applications ; Hydrogen Storage and Materials ; Metal and Thin Film Mechanics
Authors: Étienne Polack | Geneviève Dusson | Benjamin Stamm | Filippo Lipparini
Source: arXiv (Cornell University) (article, 2021-07-28)
Field: Materials Science — Materials Chemistry

Grassmann extrapolation of density matrices for Born-Oppenheimer\n molecular dynamics Born-Oppenheimer Molecular Dynamics (BOMD) is a powerful but expensive\ntechnique. The main bottleneck in a density functional theory bomd calculation\nis the solution to the Kohn-Sham (KS) equations, that requires an iterative\nprocedure that starts from a guess for the density matrix. Converged densities\nfrom previous points in the trajectory can be used to extrapolate a new guess,\nhowever, the non-linear constraint that an idempotent density needs to satisfy\nmake the direct use of standard linear extrapolation techniques not possible.\nIn this contribution, we introduce a locally bijective map between the manifold\nwhere the density is defined and its tangent space, so that linear\nextrapolation can be performed in a vector space while, at the same time,\nretaining the correct physical properties of the extrapolated density using\nmolecular descriptors. We apply the method to real-life, multiscale polarizable\nQM/MM.\n Extrapolation ; Molecular dynamics ; Tangent space ; Density matrix ; Statistical physics ; Krylov subspace ; Bottleneck ; Nonlinear system ; Convergence (economics) ; Density functional theory ; Born–Oppenheimer approximation ; Physics ; Applied mathematics ; Computer science ; Mathematics ; Iterative method ; Algorithm ; Mathematical analysis ; Quantum mechanics Machine Learning in Materials Science ; Advanced NMR Techniques and Applications ; Protein Structure and Dynamics
Authors: Sadegh Imani Yengejeh | Seyedeh Alieh Kazemi | William Wen | Yun Wang
Source: RSC Advances (review, 2021-01-01)
Field: Materials Science — Materials Chemistry

Multiscale numerical simulation of in-plane mechanical properties of two-dimensional monolayers Many applications of two dimensional (2D) materials are often achieved through strain engineering, which is directly dependent on their in-plane mechanical characteristics. Therefore, understanding the in-plane mechanical characteristics of the 2D monolayers becomes imperative. Nevertheless, direct experimental measurements of in-plane mechanical properties of 2D monolayers face great difficulties due to the issues related to the availability of high-quality 2D materials and sophisticated facilities. As an alternative, numerical simulation has the potential to theoretically predict such properties. This review presents some recent progress in numerically exploring the in-plane mechanical properties of 2D materials, including first-principles density functional theory, force-field based classical molecular dynamics, and the finite-element method. The relevant case studies are provided to describe the applications of these methods along with their pros and cons. We hope that the multiscale simulation methods discussed in this review will inspire new ideas and boost further advances of the computational study on the in-plane mechanical properties of 2D materials. Monolayer ; Plane (geometry) ; Materials science ; Statistical physics ; Composite material ; Nanotechnology ; Physics ; Geometry ; Mathematics Thermal properties of materials ; Graphene research and applications ; MXene and MAX Phase Materials
Authors: Bin Ren | Zhong-Chao Cai | Xue‐Jie Zhao | Linsong Li | Mei‐Xia Zhao
Source: International Journal of Nanomedicine (article, 2021-10-01)
Field: Materials Science — Materials Chemistry

Evaluation of the Biological Activity of Folic Acid-Modified Paclitaxel-Loaded Gold Nanoparticles The AuNPs drug delivery system showed good target selectivity for folate-receptor overexpressing cancer cells to induce target cell-specific apoptosis. These AuNPs may have great potential as theranostic agents such as in cancer. HeLa ; Folate receptor ; Drug delivery ; MTT assay ; Polyethylene glycol ; Chemistry ; Cancer cell ; PEG ratio ; Colloidal gold ; Biophysics ; Apoptosis ; Materials science ; Biochemistry ; Nanoparticle ; Cell ; Nanotechnology ; Biology ; Cancer ; Organic chemistry Nanocluster Synthesis and Applications ; Nanoparticle-Based Drug Delivery ; Gold and Silver Nanoparticles Synthesis and Applications
Authors: Maryam Zarghami Dehaghani | Fatemeh Molaei | Farrokh Yousefi | S. Mohammad Sajadi | Amin Esmaeili | Ahmad Mohaddespour | Omid Farzadian | Sajjad Habibzadeh | Amin Hamed Mashhadzadeh | Christos Spitas | Mohammad Reza Saeb
Source: Scientific Reports (article, 2021-11-29)
Field: Materials Science — Materials Chemistry

An insight into thermal properties of BC3-graphene hetero-nanosheets: a molecular dynamics study Simulation of thermal properties of graphene hetero-nanosheets is a key step in understanding their performance in nano-electronics where thermal loads and shocks are highly likely. Herein we combine graphene and boron-carbide nanosheets (BC3N) heterogeneous structures to obtain BC3N-graphene hetero-nanosheet (BC3GrHs) as a model semiconductor with tunable properties. Poor thermal properties of such heterostructures would curb their long-term practice. BC<sub>3</sub>GrHs may be imperfect with grain boundaries comprising non-hexagonal rings, heptagons, and pentagons as topological defects. Therefore, a realistic picture of the thermal properties of BC<sub>3</sub>GrHs necessitates consideration of grain boundaries of heptagon-pentagon defect pairs. Herein thermal properties of BC<sub>3</sub>GrHs with various defects were evaluated applying molecular dynamic (MD) simulation. First, temperature profiles along BC<sub>3</sub>GrHs interface with symmetric and asymmetric pentagon-heptagon pairs at 300 K, ΔT = 40 K, and zero strain were compared. Next, the effect of temperature, strain, and temperature gradient (ΔT) on Kaptiza resistance (interfacial thermal resistance at the grain boundary) was visualized. It was found that Kapitza resistance increases upon an increase of defect density in the grain boundary. Besides, among symmetric grain boundaries, 5-7-6-6 and 5-7-5-7 defect pairs showed the lowest (2 × 10<sup>-10</sup> m<sup>2</sup> K W<sup>-1</sup>) and highest (4.9 × 10<sup>-10</sup> m<sup>2</sup> K W<sup>-1</sup>) values of Kapitza resistance, respectively. Regarding parameters affecting Kapitza resistance, increased temperature and strain caused the rise and drop in Kaptiza thermal resistance, respectively. However, lengthier nanosheets had lower Kapitza thermal resistance. Moreover, changes in temperature gradient had a negligible effect on the Kapitza resistance. Interfacial thermal resistance ; Graphene ; Grain boundary ; Materials science ; Molecular dynamics ; Thermal conductivity ; Thermal resistance ; Thermal ; Condensed matter physics ; Semiconductor ; Nanosheet ; Phonon ; Nanotechnology ; Composite material ; Thermodynamics ; Microstructure ; Optoelectronics ; Chemistry ; Computational chemistry ; Physics Graphene research and applications ; Thermal properties of materials ; Boron and Carbon Nanomaterials Research
Authors: Sophie Bravo-Veyrat | Gérard Hopfgartner
Source: Analytical and Bioanalytical Chemistry (review, 2021-08-23)
Field: Chemistry — Spectroscopy

Mass spectrometry based high-throughput bioanalysis of low molecular weight compounds: are we ready to support personalized medicine? Liquid chromatography coupled to mass spectrometry (LC-MS) is the gold standard in bioanalysis for the development of quantitative assays to support drug development or therapeutic drug monitoring. High-throughput and low-cost gene sequencing have enabled a paradigm shift from one treatment fits all to personalized medicine (PM). However, gene monitoring provides only partial information about the health state. The full picture requires the combination of gene monitoring with the screening of exogenous compounds, metabolites, lipids, and proteins. This critical review discusses how mass spectrometry-based technologies and approaches including separation sciences, ambient ionization, and ion mobility are/could be used to support high-throughput bioanalysis of endogenous end exogenous low molecular weight compounds. It includes also various biological sample types (from blood to expired air), and various sample preparation techniques. Bioanalysis ; Mass spectrometry ; Chemistry ; Personalized medicine ; Throughput ; Chromatography ; Sample preparation ; Nanotechnology ; Bioinformatics ; Computer science ; Materials science ; Biology Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Analytical Chemistry and Chromatography
Authors: Д. А. Иванов | М. Ф. Садыков | D. A. Yaroslavsky | А. В. Голенищев-Кутузов | Tatyana Galieva
Source: Energies (article, 2021-09-09)
Field: Materials Science — Materials Chemistry

Non-Contact Methods for High-Voltage Insulation Equipment Diagnosis during Operation The article describes a complex of non-contact methods for remote diagnosis of high-voltage insulators as well as the two-channel method for remote diagnostics of the operating state of high-voltage insulators, based on the registration of partial discharges by electromagnetic and acoustic sensors. The presented device allows visual inspection and searches for faulty high-voltage equipment and a remote non-contact method of recording high-intensity electric fields of industrial frequency and their spatial distribution based on the electro-optical effect. The scheme of using the system for monitoring and diagnosing the technical condition of high-voltage support insulators of open switchgear is described. The results of experimental studies confirm the possibility of industrial applicability of the proposed method for non-contact remote diagnostics of the state of high-voltage insulators under operating voltage. Switchgear ; Voltage ; High voltage ; Partial discharge ; Electrical engineering ; Electrical equipment ; Engineering ; Electronic engineering ; Computer science High voltage insulation and dielectric phenomena ; Electrical Fault Detection and Protection ; Power Transformer Diagnostics and Insulation
Authors: Pijush Dutta | Shobhandeb Paul | Madhurima Majumder
Source: Research Square (preprint, 2021-11-08)
Field: Chemistry — Analytical Chemistry

An Efficient SMOTE Based Machine Learning classification for Prediction &amp;amp; Detection of PCOS Artificial intelligence ; Oversampling ; Machine learning ; Random forest ; Support vector machine ; Computer science ; Polycystic ovary ; Logistic regression ; Internal medicine ; Medicine ; Insulin Spectroscopy and Chemometric Analyses ; Imbalanced Data Classification Techniques ; Traditional Chinese Medicine Studies
Authors: Donghoon Kwak | Guk-Jin Son | Mi‐Kyung Park | Young‐Duk Kim
Source: Sensors (article, 2021-08-04)
Field: Chemistry — Analytical Chemistry

Rapid Foreign Object Detection System on Seaweed Using VNIR Hyperspectral Imaging The consumption of seaweed is increasing year by year worldwide. Therefore, the foreign object inspection of seaweed is becoming increasingly important. Seaweed is mixed with various materials such as laver and sargassum fusiforme. So it has various colors even in the same seaweed. In addition, the surface is uneven and greasy, causing diffuse reflections frequently. For these reasons, it is difficult to detect foreign objects in seaweed, so the accuracy of conventional foreign object detectors used in real manufacturing sites is less than 80%. Supporting real-time inspection should also be considered when inspecting foreign objects. Since seaweed requires mass production, rapid inspection is essential. However, hyperspectral imaging techniques are generally not suitable for high-speed inspection. In this study, we overcome this limitation by using dimensionality reduction and using simplified operations. For accuracy improvement, the proposed algorithm is carried out in 2 stages. Firstly, the subtraction method is used to clearly distinguish seaweed and conveyor belts, and also detect some relatively easy to detect foreign objects. Secondly, a standardization inspection is performed based on the result of the subtraction method. During this process, the proposed scheme adopts simplified and burdenless calculations such as subtraction, division, and one-by-one matching, which achieves both accuracy and low latency performance. In the experiment to evaluate the performance, 60 normal seaweeds and 60 seaweeds containing foreign objects were used, and the accuracy of the proposed algorithm is 95%. Finally, by implementing the proposed algorithm as a foreign object detection platform, it was confirmed that real-time operation in rapid inspection was possible, and the possibility of deployment in real manufacturing sites was confirmed. Hyperspectral imaging ; Computer science ; Artificial intelligence ; Camouflage ; Background subtraction ; Object detection ; Computer vision ; Subtraction ; VNIR ; Image subtraction ; Standardization ; Pattern recognition (psychology) ; Image processing ; Mathematics ; Image (mathematics) ; Pixel Spectroscopy and Chemometric Analyses ; Remote-Sensing Image Classification ; Identification and Quantification in Food