jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Tomio Iwasaki
Source: Journal of the Society of Materials Science Japan (article, 2020-02-15)
Field: Materials Science — Materials Chemistry

Design of Ceramic Materials with Strong Adhesion to B-DNA with an Efficient Materials Informatics Technology Appropriate ceramic materials with strong adhesion to B-DNA, which is an eco-friendly ( biodegradable and biocompatible) organic material considered to be used for electronics devices, were selected by using a combination of an orthogonal array and a response-surface method. In this technique, at the first stage, the important factors that significantly influence the adhesion strength were selected from various factors that characterize ceramic materials by using an orthogonal array with molecular dynamics simulations. As a result, the short-side and long-side lattice constants (a and b ) were selected from four ceramic-material factors (a, b, the surface energy, S, and the cohesive energy, C ). At the second stage, the adhesion strength was described as a function of the selected important factors by using a response-surface method. From this function, the optimal solution (the best values for a and b) that made the adhesion strength maximum was obtained. The best values for a and b were obtained as 0.340 nm and 0.589 nm, respectively. At the third stage, the best ceramic material whose lattice constants were equal to the best values (a =0.340 nm and b =0.589 nm), which are B-DNA’s lattice constants, was selected by use of the simulation results of lattice constants. As a result, ZrO2/CaO/HfO2, HfO2/CaO/SrO and CaO/SrO/HfO2, whose lattice constants were a =0.340 nm and b =0.589 nm, were selected as the best ceramic materials with the strongest adhesion to B-DNA. The results show that lattice matching is important in the adhesion between B-DNA and ceramics. Ceramic ; Materials science ; Lattice constant ; Adhesion ; Lattice (music) ; Lattice energy ; Surface energy ; Composite material ; Nanotechnology ; Crystal structure ; Crystallography ; Chemistry ; Optics Machine Learning in Materials Science ; Additive Manufacturing and 3D Printing Technologies ; Advanced ceramic materials synthesis
Authors: Kosuke Ogata | Chih‐Hsiang Chang | Yasushi Ishihama
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2020-06-15)
Field: Chemistry — Spectroscopy

Effect of Phosphorylation on the Collision Cross Sections of Peptide Ions in Ion Mobility Spectrometry Abstract The insertion of ion mobility spectrometry (IMS) between LC and MS can improve peptide identification in both proteomics and phosphoproteomics by providing structural information that is complementary to LC and MS, because IMS separates ions on the basis of differences in their shapes and charge states. However, it is necessary to know how phosphate groups affect the peptide collision cross sections (CCS) in order to accurately predict phosphopeptide CCS values and to maximize the usefulness of IMS. In this work, we systematically characterized the CCS values of 4,433 pairs of mono-phosphopeptide and corresponding unphosphorylated peptide ions using trapped ion mobility spectrometry (TIMS). Nearly one-third of the mono-phosphopeptide ions evaluated here showed smaller CCS values than their unphosphorylated counterparts, even though phosphorylation results in a mass increase of 80 Da. Significant changes of CCS upon phosphorylation occurred mainly in structurally extended peptides with large numbers of basic groups, possibly reflecting intramolecular interactions between phosphate and basic groups. Phosphopeptide ; Ion-mobility spectrometry ; Phosphoproteomics ; Peptide ; Chemistry ; Mass spectrometry ; Ion ; Phosphorylation ; Phosphate ; Protein phosphorylation ; Chromatography ; Biochemistry ; Protein kinase A ; Organic chemistry Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Abhishek Sharma | Maks Ovsjanikov
Source: HAL (Le Centre pour la Communication Scientifique Directe) (preprint, 2020-06-18)
Field: Materials Science — Materials Chemistry

Weakly Supervised Deep Functional Map for Shape Matching A variety of deep functional maps have been proposed recently, from fully supervised to totally unsupervised, with a range of loss functions as well as different regularization terms.However, it is still not clear what are minimum ingredients of a deep functional map pipeline and whether such ingredients unify or generalize all recent work on deep functional maps.We show empirically minimum components for obtaining state of the art results with different loss functions, supervised as well as unsupervised.Furthermore, we propose a novel framework designed for both full-to-full as well as partial to full shape matching that achieves state of the art results on several benchmark datasets outperforming even the fully supervised methods by a significant margin.Our code is publicly available at https://github.com/Not-IITian/Weakly-supervised-Functional-map Artificial intelligence ; Computer science ; Matching (statistics) ; Pattern recognition (psychology) ; Deep learning ; Computer vision ; Mathematics ; Statistics Machine Learning in Materials Science ; Supramolecular Self-Assembly in Materials ; Advanced Computing and Algorithms
Authors: Vincenzo Barone | Cristina Puzzarini
Source: EPJ Web of Conferences (article, 2020-01-01)
Field: Chemistry — Spectroscopy

Looking for the bricks of the life in the interstellar medium: The fascinating world of astrochemistry The discovery in the interstellar medium of molecules showing a certain degree of complexity, and in particular those with a prebiotic character, has attracted great interest. A complex chemistry takes place in space, but the processes that lead to the production of molecular species are a matter of intense discussion, the knowledge still being at a rather primitive stage. Debate on the origins of interstellar molecules has been further stimulated by the identification of biomolecular building blocks, such as nucleobases and amino acids, in meteorites and comets. Since many of the molecules found in space play a role in the chemistry of life, the issue of their molecular genesis and evolution might be related to the profound question of the origin of life itself. Understanding the underlying chemical processes, including the production, reactions and destruction of compounds, requires the concomitant study of spectroscopy, gas-phase reactivity, and heterogeneous processes on dust-grains. The aim of this contribution is to provide a general view of a complex and multifaceted challenge, while focusing on the role played by molecular spectroscopy and quantum-chemical computations. In particular, the derivation of the molecular spectroscopic features and the investigation of gas-phase formation routes of prebiotic species in the interstellar medium are addressed from a computational point of view. Abiogenesis ; Astrobiology ; Interstellar medium ; Astrochemistry ; Meteorite ; Chemical physics ; Extraterrestrial life ; Chemistry ; Molecule ; Physics ; Nanotechnology ; Astrophysics ; Materials science ; Organic chemistry ; Galaxy Molecular Spectroscopy and Structure ; Advanced Chemical Physics Studies ; Astrophysics and Star Formation Studies
Authors: Daniela Souza Ferreira
Source: Journal of Spectral Imaging (article, 2020-07-21)
Field: Chemistry — Analytical Chemistry

Thermal imaging as a tool in food analysis This Letter reviews the application of thermal imaging for food quality control. Thermal imaging uses a single, portable device, which provides a visible image of the invisible infrared radiation, and can be used for real-time monitoring at low cost compared to spectral imaging technology. To monitor the quality parameters of the sample, classification or regression models are constructed using multivariate analysis or chemometrics tools. Few studies have used thermography for the analysis of food to-date, so this Letter will only address thermal mapping, internal defect detection, adulteration detection and the prediction of compound concentration. Chemometrics ; Thermography ; Partial least squares regression ; Computer science ; Sample (material) ; Quality (philosophy) ; Thermal ; Artificial intelligence ; Infrared ; Remote sensing ; Data mining ; Machine learning ; Optics ; Chemistry ; Physics ; Geography Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Meat and Animal Product Quality
Authors: Michael C. Gerten | James I. Lathrop | Myra B. Cohen | Titus H. Klinge
Source:  (article, 2020-12-21)
Field: Materials Science — Materials Chemistry

ChemTest In recent years the use of non-traditional computing mechanisms has grown rapidly. One paradigm uses chemical reaction networks (CRNs) to compute via chemical interactions. CRNs are used to prototype molecular devices at the nanoscale such as intelligent drug therapeutics. In practice, these programs are first written and simulated in environments such as MatLab and later compiled into physical molecules such as DNA strands. However, techniques for testing the correctness of CRNs are lacking. Current methods of validating CRNs include model checking and theorem proving, but these are limited in scalability. In this paper we present the first (to the best of our knowledge) testing framework for CRNs, ChemTest. ChemTest evaluates test oracles on individual simulation traces and supports functional, metamorphic, internal and hyper test cases. It also allows for flakiness and programs that are probabilistic. We performed a large case study demonstrating that ChemTest can find seeded faults and scales beyond model checking. Of our tests, 21% are inherently flaky, suggesting that systematic support for this paradigm is needed. On average, functional tests find 66.5% of the faults, while metamorphic tests find 80.4%, showing the benefit of using metamorphic relationships in our test framework. In addition, we show how the time at evaluation impacts fault detection. Correctness ; Computer science ; Scalability ; Distributed computing ; Model checking ; Probabilistic logic ; Theoretical computer science ; Artificial intelligence ; Algorithm ; Database Machine Learning in Materials Science ; Advanced biosensing and bioanalysis techniques ; Software Testing and Debugging Techniques
Authors: A. Anitha Lakshmi | Swathi | Tanya Buddi | Ch. Bandhavi | Ram Subbiah
Source: E3S Web of Conferences (article, 2020-01-01)
Field: Materials Science — Materials Chemistry

Investigation of Microstructure and Mechanical Properties of Austenite Stainless Steel 304 during Tempering and Cryogenic Heat Treatment In the present study, the influence of heat treatment (tempering &amp; cryogenic) on the grain orientation and few important mechanical properties of Austenite Stainless Steel 304 (ASS 304) are examined. The significant mechanical properties like ultimate strength, elongation percentage and surface hardness etc., of the experimented and untreated specimens are computed using pre standard methods and the micrographs of the specimens was conducted using metallurgical microscope. The effect of strain rate ranging from lower to higher strain rates 0.001s-1 to 0.1s-1, on true stress - true strain behaviour of tempered austenitic stainless steel 304 is investigated. Experimental results exhibited that the mechanical behaviour of ASS 304 can be reformed and improvised by several heat treatment procedures for a specific application. The results showed that the cryogenic treated specimens indicate lowest tensile strength, hardness and highest percent of elongation value compared with tempered specimen gave the maximum tensile strength, hardness and minimum percent of elongation in length value. Materials science ; Tempering ; Elongation ; Ultimate tensile strength ; Austenite ; Microstructure ; Metallurgy ; Cryogenic treatment ; Austenitic stainless steel ; Grain size ; Composite material ; Corrosion Metal Alloys Wear and Properties ; Microstructure and Mechanical Properties of Steels ; Metallurgy and Material Forming
Authors: Lidya E. Simanjuntak | Tri Edhi Budhi Soesilo | Herdis Herdiansyah
Source: Polish Journal of Environmental Studies (article, 2020-03-27)
Field: Chemistry — Analytical Chemistry

Analysis of Near Infra Red (NIR) Impactas the Control Process of a Palm Oil Milland Refinery Plant for EnvironmentalSustainability The development of the plantation sector in Indonesia is overgrowing. Industry, aside from being an indicator of potential economic activities and employment equity, impacts the environment. Processing of crude palm oil (CPO) into its derivatives through several stages of the process, sampling took in each stage of the process and analysis of samples by conventional methods that use chemicals that produce hazardous waste. The use of near infrared (NIR) in the samples does not require chemical substances, thereby reducing the amount of hazardous waste and thus causing less negative environmental impact compared to other analytical methods. Since the NIR analysis method does not require chemical substances, the timing of analysis becomes faster and more efficient, albeit at relatively high equipment prices. The purpose of this research is to analyze the effectiveness of NIR used as the process control. This study uses a statistical method to see the accuracy and precision. The result of this study show that the NIR analysis can shorten the analysis time compared to the primary standard method (extraction). With the NIR method, time taken from preparing the samples to data analysis obtained is 5 minutes, while with the standard method (extraction) it takes 9.5 hours. This research will be expected as a literature review or reference in the assessment of the effectiveness of the use of NIR in reducing waste at various CPO refinery factories in Indonesia. It is expected that the result of this study is utilized as a stakeholder reference for NIR usage as the control process for environmental sustainability. Refinery ; Sustainability ; Palm oil ; Environmental science ; Mill ; Oil refinery ; Waste management ; Pulp and paper industry ; Engineering ; Environmental engineering ; Agroforestry Spectroscopy and Chemometric Analyses
Authors: Xiaoyan Qiao
Source: IEEE Access (article, 2020-01-01)
Field: Chemistry — Analytical Chemistry

Research on Imbalanced Microscopic Image Classification of Harmful Algae Image analysis based on biological morphological differences is an important development direction for classification and determination of planktonic algae. However, it has some shortages, such as high degree of sample imbalance and difficult to have formalized description of local physiological features. To overcome these shortages, this study decomposed recognition of harmful algae microscopic images into sample supplementation, accurate segmentation, feature extraction and classification and identification. Firstly, sample imbalance is solved by Kernel-ADASYN method to generate enough samples. Target cells are separated through integration of multi-directional projections. Refined segmentation between the spine and cingulum detail regions is further realized. Later, effective feature extraction and description of global and local features were performed one by one by matching physiological features of algae with machine recognition features. Finally, the SVM model was applied for multi-class recognition. Results demonstrated that the proposed method can reduce imbalance rate of sample size and realize multi-class recognition of microscopic images of 15 categories of algae cells. Pattern recognition (psychology) ; Artificial intelligence ; Computer science ; Feature extraction ; Sample (material) ; Segmentation ; Economic shortage ; Support vector machine ; Pooling ; Kernel (algebra) ; Feature (linguistics) ; Algae ; Matching (statistics) ; Image segmentation ; Gabor filter ; Identification (biology) ; Computer vision ; Mathematics ; Biology ; Botany ; Statistics Spectroscopy and Chemometric Analyses ; Cell Image Analysis Techniques ; Digital Imaging for Blood Diseases
Authors: Takeo Hoshi | Takeshi Ogita | Katsuhisa Ozaki | Takeshi Terao
Source: Journal of Computational and Applied Mathematics (article, 2020-02-29)
Field: Materials Science — Materials Chemistry

An a posteriori verification method for generalized real-symmetric eigenvalue problems in large-scale electronic state calculations Eigenvalues and eigenvectors ; A priori and a posteriori ; Divide-and-conquer eigenvalue algorithm ; Interval (graph theory) ; Scale (ratio) ; Applied mathematics ; Computer science ; State (computer science) ; Algorithm ; Mathematics ; Mathematical optimization ; Combinatorics ; Quantum mechanics ; Physics Machine Learning in Materials Science ; Advanced Physical and Chemical Molecular Interactions ; Advanced Chemical Physics Studies
Authors: Răzvan Mihai Prisada
Source: FARMACIA (article, 2020-04-15)
Field: Chemistry — Organic Chemistry

PERSPECTIVES TO DESCRIBE SURFACE PROPERTIES OF RAW PHARMACEUTICAL MATERIALS. A FRACTAL APPROACH ON THE WETTING OF POWDERS Surface science is a currently expanding field which attracts attention through numerous possible correlations between different superficial phenomena. Modern approaches regarding superficial properties include extreme wetting interpretations through adapted regimes. Moreover, innovative applications arise from special surface properties like superhydrophilicity/ superhydrophobicity, through biomimicry, improving classic materials or generating new better artificial ones, of important interest in many domains. Liquid marbles, known as superhydrophobic-like structures also gained researcher's attention due to their special superficial properties. Experimental data in this direction are scarce, especially regarding active ingredients in the pharmaceutical domain and taking into account different morphologies and formulation versatility of liquid marbles. This paper focuses on anti-inflammatory powders and their superficial properties as raw pharmaceutical materials, but also as liquid marbles' components (external phases). Interpretations concern powders wettability degree expressed through contact angles and apparent contact angles of corresponding liquid marbles. These wetting parameters are correlated through a mathematical model, which also allows evaluation of fractal quantitative indexes: rugosity and fractal dimension. Applying a fractal wetting model to anti-inflammatory powders represents a step forward towards proposing contact angles and other wetting parameters as key indicators in pre-formulation processes. Dissolution and absorption of active ingredients are only two examples of processes in which a drug's pharmacokinetic profile is directly correlated to wetting parameters of its components. The importance of predicting a pharmaceutical products' behaviour is crucial in designing new products, making superficial properties investigations mandatory steps of the process. Wetting ; Fractal ; Materials science ; Surface (topology) ; Raw material ; Polymer science ; Chemical engineering ; Nanotechnology ; Composite material ; Chemistry ; Mathematics ; Organic chemistry ; Geometry ; Engineering ; Mathematical analysis Surfactants and Colloidal Systems ; Electrohydrodynamics and Fluid Dynamics ; Nanomaterials and Printing Technologies
Authors: Shuzhi Xiao | Jiemei Chen | Tao Pan
Source: American Journal of Analytical Chemistry (article, 2020-01-01)
Field: Chemistry — Analytical Chemistry

Visible and Near-Infrared Spectroscopic Discriminant Analysis Applied to Brand Identification of Wine High-end wine brand is made through the use of high-quality grape variety and yeast strain, and through a unique process. Not only is it rich in nutrients, but also it has a unique taste and a fragrant scent. Brand identification of wine is difficult and complex because of high similarity. In this paper, visible and near-infrared (NIR) spectroscopy combined with partial least squares discriminant analysis (PLS-DA) was used to explore the feasibility of wine brand identification. Chilean Aoyo wine (2016 vintage) was selected as the identification brand (negative, 100 samples), and various other brands of wine were used as interference brands (positive, 373 samples). Samples of each type were randomly divided into the calibration, prediction and validation sets. For comparison, the PLS-DA models were established in three independent and two complex wavebands of visible (400 - 780 nm), short-NIR (780 - 1100 nm), long-NIR (1100 - 2498 nm), whole NIR (780 - 2498 nm) and whole scanning (400 - 2498 nm). In independent validation, the five models all achieved good discriminant effects. Among them, the visible region model achieved the best effect. The recognition-accuracy rates in validation of negative, positive and total samples achieved 100%, 95.6% and 97.5%, respectively. The results indicated the feasibility of wine brand identification with Vis-NIR spectroscopy. Wine ; Linear discriminant analysis ; Partial least squares regression ; Vintage ; Mathematics ; Near-infrared spectroscopy ; Chemometrics ; Food science ; Chemistry ; Chromatography ; Statistics ; Psychology Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Identification and Quantification in Food
Authors: Seong Jun Kim | Changhyun Lee | Sangtae Jeon | Junghyun Park | Soo Jin Kim
Source: Nanophotonics (article, 2020-11-17)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Subwavelength sorting of full‐color based on anti‐Hermitian metasurfaces Abstract Splitting the spectrum of incident light at nanoscale has been of great scientific and practical interest due to its potential application in various optical sensors. For many years, researchers have been striving to realize the full‐color sorting of light at subwavelength scale, while keeping the loss of incident photons to a minimum. In this article, we present semiconductor‐based metasurfaces that facilitate the efficient sorting of full‐color by inducing anti‐Hermitian coupling between multiple nanoantenna arrays. To achieve this, we first explore how the coherent interactions between maximally crafted nanoantennas in the metasurfaces can be effectively controlled by judiciously positioning them in both lateral and vertical directions, which leads to the switched coupling of light at each target position. Based on the analysis, we demonstrate a metasurface‐based absorber that features efficient, spectropolarimetric detections over the entire visible spectrum, ranging from 470 to 630 nm. In addition, the metasurface detects relatively narrow spectral linewidth of 60 nm and shows the sensitivity up to 70%, which surpasses the previous works on subwavelength photon sorting or color filter‐based detection system. We envision that our approach provides guidelines for realizing the metasurfaces with enhanced functionalities, that is the increase of spectral channels for detection in a given subwavelength‐scaled unit cell. Sorting ; Color gel ; Laser linewidth ; Optics ; Photon ; Optoelectronics ; Coupling (piping) ; Physics ; Photonics ; Plasmon ; Ray ; Nanoscopic scale ; Materials science ; Computer science ; Nanotechnology ; Laser Metamaterials and Metasurfaces Applications ; Plasmonic and Surface Plasmon Research ; Orbital Angular Momentum in Optics