jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Juliane Klare | Marc Rurik | Eric Rottmann | Anke Bollen | Oliver Kohlbacher | Markus Fischer | Thomas Hackl
Source: Journal of Agricultural and Food Chemistry (article, 2020-10-26)
Field: Chemistry — Analytical Chemistry

Determination of the Geographical Origin of <i>Asparagus officinalis</i> L. by <sup>1</sup>H NMR Spectroscopy Food authenticity concerning the geographical origin becomes increasingly important for consumers, food industries, and food authorities. In this study, <i>nontargeted</i> <sup>1</sup>H NMR metabolomics combined with machine learning methodologies was applied to successfully distinguish the geographical origin of 237 samples of white asparagus from Germany, Poland, The Netherlands, Spain, Greece, and Peru. Support vector classification of the geographical origin achieved an accuracy of 91.5% for the entire sample set and 87.8% after undersampling the majority class. Important regions of the spectra could be identified and assigned to potential chemical markers. A subset of samples was compared to isotope-ratio mass spectrometry (IRMS), an established method for the determination of origin of white asparagus in Germany. Here, SVM classification led to accuracies of 79.4% for NMR and 70.9% for IRMS. Finally, the classification of asparagus from different German regions was evaluated, and the influence of year and variety was analyzed. Asparagus ; Officinalis ; Nuclear magnetic resonance spectroscopy ; Spectroscopy ; Chemistry ; Botany ; Physics ; Stereochemistry ; Biology Spectroscopy and Chemometric Analyses ; Metabolomics and Mass Spectrometry Studies ; Phytochemistry and Biological Activities
Authors: Wentian Jin | Sheriff Sadiqbatcha | Zeyu Sun | Han Zhou | Sheldon X.-D. Tan
Source:  (article, 2020-10-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

EM-GAN: Data-Driven Fast Stress Analysis for Multi-Segment Interconnects Electromigration (EM) analysis for complicated interconnects requires the solving of partial differential equations, which is expensive. In this paper, we propose a fast transient hydrostatic stress analysis for EM failure assessment for multisegment interconnects using generative adversarial networks (GANs). Our work is inspired by the image synthesis and feature of generative deep neural networks. The stress evaluation of multi-segment interconnects, modeled by partial differential equations, can be viewed as time-varying 2D-images-to-image problem where the input is the multi-segment interconnects topology with current densities and the output is the EM stress distribution in those wire segments at the given aging time. We show that the conditional GAN can be exploited to attend the temporal dynamics for modeling the time-varying dynamic systems like stress evolution over time. The resulting algorithm, called EM-GAN, can quickly give accurate stress distribution of a general multi-segment wire tree for a given aging time, which is important for full-chip fast EM failure assessment. Our experimental results show that the EM-GAN shows 6.6% averaged error compared to COMSOL simulation results with orders of magnitude speedup. It also delivers 8.3× speedup over state-of-the-art analytic based EM analysis solver. Speedup ; Computer science ; Solver ; Algorithm ; Stress (linguistics) ; Transient (computer programming) ; Partial differential equation ; Feature (linguistics) ; Topology (electrical circuits) ; Parallel computing ; Mathematics ; Mathematical analysis Copper Interconnects and Reliability ; Advancements in Photolithography Techniques ; Integrated Circuits and Semiconductor Failure Analysis
Authors: Xujing Zhang | Jianping Zhou | Yan Xu
Source: Journal of Biomedical Materials Research Part B Applied Biomaterials (article, 2020-08-04)
Field: Materials Science — Biomaterials

Optimized parameters for the preparation of silk fibroin <scp>drug‐loaded</scp> microspheres based on the response surface method and a genetic algorithm<scp>–</scp>backpropagation neural network model Using silk fibroin as the base material, the drug-loaded microspheres are prepared by an emulsification method. In order to determine the drug-loading and drug-release performance parameters of the microspheres, the central composite design method is used to design and investigate the effects of the parameters of the microsphere preparation process, such as the oil-water ratio, stirring temperature, and stirring rate, on the microsphere particle size, drug-loading rate, and drug release rate. The "overall desirability" is taken as a comprehensive evaluation index, and the response surface method (RSM) and genetic algorithm-backpropagation (GA-BP) neural network GA-BP model are used to predict and evaluate the parameters of the drug-loaded microsphere preparation process. The root-mean-square error values obtained from the RSM and BP-GA model experiments are 0.000325 and 0.00022, respectively. The results show that the BP-GA model has better prediction accuracy and optimization ability than the RSM. The optimal microsphere preparation process conditions were determined to be as follows: a water-oil ratio of 10:1, at a temperature of 45°C with stirring at a speed of 400 rpm, the particle size of the microspheres is 1.392 μm, the drug-loading rate is 3.218%, and the drug release rate is 51.991%. The results of this study indicate that this approach is an effective method for the optimization of the parameters of the drug-loaded microsphere preparation process. Response surface methodology ; Materials science ; Particle size ; Fibroin ; Central composite design ; Backpropagation ; Microsphere ; Composite material ; Chemical engineering ; Chromatography ; Artificial neural network ; Chemistry ; Computer science ; SILK ; Engineering ; Machine learning Silk-based biomaterials and applications ; Hydrogels: synthesis, properties, applications ; Wound Healing and Treatments
Authors: Zuzanna Małyjurek | Beata Zawisza | Dalene de Beer | Elizabeth Joubert | Beata Walczak
Source: Food Control (article, 2020-11-19)
Field: Chemistry — Analytical Chemistry

Authentication of honeybush and rooibos herbal teas based on their elemental composition Composition (language) ; Herbal tea ; Authentication (law) ; Chemistry ; Traditional medicine ; Food science ; Antioxidant ; Geography ; Medicine Spectroscopy and Chemometric Analyses ; Heavy Metals in Plants ; Metabolomics and Mass Spectrometry Studies
Authors: Fabiola Cappia | Brandon Miller | Jeffery A. Aguiar | Lingfeng He | Daniel J. Murray | B.J. Frickey | John David Stanek | Jason Harp
Source: Journal of Nuclear Materials (article, 2020-01-10)
Field: Materials Science — Materials Chemistry

Electron microscopy characterization of fast reactor MOX Joint Oxyde-Gaine (JOG) Tetragonal crystal system ; Materials science ; Crystallography ; Stoichiometry ; Characterization (materials science) ; Crystal structure ; Crystallite ; Fission ; Oxide ; Electron microscope ; Chemistry ; Nanotechnology ; Metallurgy ; Physical chemistry ; Optics ; Nuclear physics Nuclear Materials and Properties ; Nuclear reactor physics and engineering ; Nuclear Physics and Applications
Authors: Manju Manju | Megha Jain | Saibabu Madas | Pargam Vashishtha | Parasmani Rajput | Govind Gupta | Mousumi Upadhyay Kahaly | K. Özdoğan | Ankush Vij | Anup Thakur
Source: Scientific Reports (article, 2020-10-15)
Field: Materials Science — Materials Chemistry

Oxygen vacancies induced photoluminescence in $$\hbox {SrZnO}_2$$ nanophosphors probed by theoretical and experimental analysis We report, for the first time, the influence of oxygen vacancies on band structure and local electronic structure of [Formula: see text] (SZO) nanophosphors by combined first principle calculations based on density functional theory and full multiple scattering theory, correlated with experimental results obtained from X-ray absorption and photoluminescence spectroscopies. The band structure analysis from density functional theory revealed the formation of new energy states in the forbidden gap due to introduction of oxygen vacancies in the system, thereby causing disruption in intrinsic symmetry and altering bond lengths in SZO system. These defect states are anticipated as origin of observed photoluminescence in SZO nanophosphors. The experimental X-ray absorption near edge structure (XANES) at Zn and Sr K-edges were successfully imitated by simulated XANES obtained after removing oxygen atoms around Zn and Sr cores, which affirmed the presence and signature of oxygen vacancies on near edge structure. XANES ; Photoluminescence ; Density functional theory ; Materials science ; Oxygen ; Extended X-ray absorption fine structure ; Absorption (acoustics) ; Band gap ; Electronic structure ; Absorption edge ; Scattering ; Absorption spectroscopy ; Crystallography ; Chemical physics ; Spectroscopy ; Chemistry ; Computational chemistry ; Physics ; Optoelectronics ; Optics ZnO doping and properties ; Electronic and Structural Properties of Oxides ; Gas Sensing Nanomaterials and Sensors
Authors: Yifeng Han | Meixia Wu | Churen Gui | Chuanhui Zhu | Zhongxiong Sun | Mei-Huan Zhao | Aleksandra A. Savina | Artem M. Abakumov | Biao Wang | Feng Huang | Lunhua He | Jie Chen | Q. Huang | Mark Croft | Steven N. Ehrlich | Syed Khalid | Zheng Deng | Changqing Jin | Christoph P. Grams | J. Hemberger | Xueyun Wang | Jiawang Hong | Umut Adem | Meng Ye | Shuai Dong | Man‐Rong Li
Source: npj Quantum Materials (article, 2020-12-09)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Data-driven computational prediction and experimental realization of exotic perovskite-related polar magnets Rational design of technologically important exotic perovskites is hampered by the insufficient geometrical descriptors and costly and extremely high-pressure synthesis, while the big-data driven compositional identification and precise prediction entangles full understanding of the possible polymorphs and complicated multidimensional calculations of the chemical and thermodynamic parameter space. Here we present a rapid systematic data-mining-driven approach to design exotic perovskites in a high-throughput and discovery speed of the <i>A</i> <sub>2</sub> <i>BB</i>'O<sub>6</sub> family as exemplified in <i>A</i> <sub>3</sub>TeO<sub>6</sub>. The magnetoelectric polar magnet Co<sub>3</sub>TeO<sub>6</sub>, which is theoretically recognized and experimentally realized at 5 GPa from the six possible polymorphs, undergoes two magnetic transitions at 24 and 58 K and exhibits helical spin structure accompanied by magnetoelastic and magnetoelectric coupling. We expect the applied approach will accelerate the systematic and rapid discovery of new exotic perovskites in a high-throughput manner and can be extended to arbitrary applications in other families. Realization (probability) ; Magnet ; Perovskite (structure) ; Polar ; Throughput ; Space (punctuation) ; Coupling (piping) ; Spin (aerodynamics) ; Identification (biology) ; Materials science ; Parameter space ; Computer science ; Physics ; Chemistry ; Crystallography ; Thermodynamics ; Quantum mechanics ; Mathematics Multiferroics and related materials ; Magnetic and transport properties of perovskites and related materials ; Advanced Condensed Matter Physics
Authors: Buraq T. Sh. Al-Mosawi | Mohammed M. Sabri | Muhanad A. Ahmed
Source: International Journal of Low-Carbon Technologies (article, 2020-09-18)
Field: Materials Science — Materials Chemistry

Synergistic effect of ZnO nanoparticles with organic compound as corrosion inhibition Abstract In chemical manufactures, the corrosion inhibitors were added in order to reduce the corrosion of mild steel. Chemical molecules are often used on mild steel surfaces as portion of the latest finishing steps before painting and/or storage. Here, this work elucidated the utilization of an isatin derivative, namely, 3-((3-acetylphenyl)imino)indolin-2-one synergistic with zinc oxide nanoparticles for improving the impedance of mild steel (MS) against corrosion in 1.0 M hydrochloric acid using the weight loss method and scanning electron microscopy (SEM). Weight loss measurements demonstrated that the best 3-((3-acetylphenyl)imino)indolin-2-one concentration was 0.5 mM and the inhibition efficiency was 83% whereas the inhibition efficiency was 92% with addition of ZnO NPs. 3-((3-Acetylphenyl)imino)indolin-2-one retards the corrosion process at 300 K and demonstrates low inhibition efficiencies at 310, 320 and 330 K. Corrosion ; Hydrochloric acid ; Zinc ; Nanoparticle ; Scanning electron microscope ; Nuclear chemistry ; Materials science ; Isatin ; Corrosion inhibitor ; Chemistry ; Inorganic chemistry ; Metallurgy ; Organic chemistry ; Nanotechnology ; Composite material Corrosion Behavior and Inhibition ; Concrete Corrosion and Durability ; ZnO doping and properties
Authors: Kamal Choudhary | Jaafar N. Ansari | Igor I. Mazin | Karen L. Sauer
Source: Scientific Data (article, 2020-10-21)
Field: Chemistry — Spectroscopy

Density functional theory-based electric field gradient database The deviation of the electron density around the nuclei from spherical symmetry determines the electric field gradient (EFG), which can be measured by various types of spectroscopy. Nuclear Quadrupole Resonance (NQR) is particularly sensitive to the EFG. The EFGs, and by implication NQR frequencies, vary dramatically across materials. Consequently, searching for NQR spectral lines in previously uninvestigated materials represents a major challenge. Calculated EFGs can significantly aid at the search's inception. To facilitate this task, we have applied high-throughput density functional theory calculations to predict EFGs for 15187 materials in the JARVIS-DFT database. This database, which will include EFG as a standard entry, is continuously increasing. Given the large scope of the database, it is impractical to verify each calculation. However, we assess accuracy by singling out cases for which reliable experimental information is readily available and compare them to the calculations. We further present a statistical analysis of the results. The database and tools associated with our work are made publicly available by JARVIS-DFT ( https://www.ctcms.nist.gov/~knc6/JVASP.html ) and NIST-JARVIS API ( http://jarvis.nist.gov/ ). Electric field gradient ; Quadrupole ; Density functional theory ; Electric field ; Field (mathematics) ; Work (physics) ; Symmetry (geometry) ; Scope (computer science) Advanced NMR Techniques and Applications ; Solid-state spectroscopy and crystallography ; X-ray Diffraction in Crystallography
Authors: Yong Yang | Jianping Chen | Yong He | Feng Liu | Xuping Feng | Jinnuo Zhang
Source: RSC Advances (article, 2020-01-01)
Field: Chemistry — Analytical Chemistry

Assessment of the vigor of rice seeds by near-infrared hyperspectral imaging combined with transfer learning Rice seed vigor plays a significant role in determining the quality and quantity of rice production. Thus, the quick and non-destructive identification of seed vigor is not only beneficial to fully obtain the state of rice seeds but also the intelligent development of agriculture by instant monitoring. Thus, herein, near-infrared hyperspectral imaging technology, as an information acquisition tool, was introduced combined with a deep learning algorithm to identify the rice seed vigor. Both the spectral images and average spectra of the rice seeds were sent to discriminant models including deep learning models and traditional machine learning models, and the highest accuracy of vigor identification reached 99.5018% using the self-built model. The parameters of the established deep learning models were frozen to be feature extractor for transfer learning. The identification results whose highest number also reached almost 98% indicated the possibility of applying transfer learning to improve the universality of the models. Moreover, by visualizing the output of convolutional layers, the progress and mechanism of spectral image feature extraction in the established deep learning model was explored. Overall, the self-built deep learning models combined with near-infrared hyperspectral images in the determination of rice seed vigor have potential to efficiently perform this task. Hyperspectral imaging ; Transfer of learning ; Infrared ; Agricultural engineering ; Remote sensing ; Environmental science ; Chemistry ; Artificial intelligence ; Computer science ; Geography ; Engineering ; Physics ; Optics Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Smart Agriculture and AI
Authors: Gina Prado-Prone | Maasoomeh Bazzar | Maria Letizia Focarete | Jorge A. García-Macedo | Javier Pérez-Orive | Clemente Ibarra | Cristina Velasquillo | Phaedra Silva-Bermúdez
Source: Biomedical Materials (article, 2020-01-03)
Field: Materials Science — Biomaterials

Single-step, acid-based fabrication of homogeneous gelatin-polycaprolactone fibrillar scaffolds intended for skin tissue engineering Blends of natural and synthetic polymers have recently attracted great attention as scaffolds for tissue engineering applications due to their favorable biological and mechanical properties. Nevertheless, phase-separation of blend components is an important challenge facing the development of electrospun homogeneous fibrillar natural-synthetic polymers scaffolds; phase-separation can produce significant detrimental effects for scaffolds fabricated by electrospinning. In the present study, blends of gelatin (Gel; natural polymer) and polycaprolactone (PCL; synthetic polymer), containing 30 and 45 wt% Gel, were prepared using acetic acid as a 'green' sole solvent to straightforwardly produce appropriate single-step Gel-PCL solutions for electrospinning. Miscibility of Gel and PCL in the scaffolds was assessed and the morphology, chemical composition and structural and solid-state properties of the scaffolds were thoroughly investigated. Results showed that the two polymers proved miscible under the single-step solution process used and that the electrospun scaffolds presented suitable properties for potential skin tissue engineering applications. Viability, metabolic activity and protein expression of human fibroblasts cultured on the Gel-PCL scaffolds were evaluated using LIVE/DEAD (calcein/ethidium homodimer), MTT-Formazan and immunocytochemistry assays, respectively. In vitro results showed that the electrospun Gel-PCL scaffolds enhanced cell viability and proliferation in comparison to PCL scaffolds. Furthermore, scaffolds allowed fibroblasts expression of extracellular matrix proteins, tropoelastin and collagen Type I, in a similar way to positive controls. Results indicated the feasibility of the single-step solution process used herein to obtain homogeneous electrospun Gel-PCL scaffolds with Gel content ≥30 wt% and potential properties to be used as scaffolds for skin tissue engineering applications for wound healing. Polycaprolactone ; Gelatin ; Fabrication ; Materials science ; Tissue engineering ; Biomedical engineering ; Homogeneous ; Scaffold ; Composite material ; Chemistry ; Polymer ; Medicine ; Organic chemistry ; Pathology Electrospun Nanofibers in Biomedical Applications ; 3D Printing in Biomedical Research ; Silk-based biomaterials and applications
Authors: Mauno Vihinen
Source: ADMET & DMPK (article, 2020-06-28)
Field: Materials Science — Materials Chemistry

Solubility of proteins Solubility is a fundamental protein property that has important connotations for therapeutics and use in diagnosis. Solubility of many proteins is low and affect heterologous overexpression of proteins, formulation of products and their stability. Two processes are related to soluble and solid phase relations. Solubility refers to the process where proteins have correctly folded structure, whereas aggregation is related to the formation of fibrils, oligomers or amorphous particles. Both processes are related to some diseases. Amyloid fibril formation is one of the characteristic features in several neurodegenerative diseases, but it is related to many other diseases, including cancers. Severe complex V deficiency and cataract are examples of diseases due to reduced protein solubility. Methods and approaches are described for prediction of protein solubility and aggregation, as well as predictions of consequences of amino acid substitutions. Finally, protein engineering solutions are discussed. Protein solubility can be increased, although such alterations are relatively rare and can lead to trade-off with some other properties. The aggregation prediction methods mainly aim to detect aggregation-prone sequence patches and then making them more soluble. The solubility predictors utilize a wide spectrum of features. Solubility ; Protein aggregation ; Protein stability ; Chemistry ; Protein folding ; Biophysics ; Biochemistry ; Organic chemistry ; Biology Enzyme Structure and Function ; Protein Structure and Dynamics ; Protein purification and stability
Authors: Sandro Wieser | Tomas Kamencek | Johannes P. Dürholt | Rochus Schmid | Natalia Bedoya‐Martínez | Egbert Zojer
Source: Advanced Theory and Simulations (article, 2020-12-01)
Field: Chemistry — Inorganic Chemistry

Identifying the Bottleneck for Heat Transport in Metal–Organic Frameworks Abstract Controlling the transport of thermal energy is key to most applications of metal–organic frameworks (MOFs). Analyzing the evolution of the effective local temperature, the interfaces between the metal nodes and the organic linkers are identified as the primary bottlenecks for heat conduction. Consequently, changing the bonding strength at that node–linker interface and the mass of the metal atoms can be exploited to tune the thermal conductivity. This insight is generated employing molecular dynamics simulations in conjunction with advanced, ab initio parameterized force fields. The focus of the present study is on MOF‐5 as a prototypical example of an isoreticular MOF. However, the key findings prevail for different node structures and node–linker bonding chemistries. The presented results lay the foundation for developing detailed structure‐to‐property relationships for thermal transport in MOFs with the goal of devising strategies for the application‐specific optimization of heat conduction. Bottleneck ; Node (physics) ; Energy transport ; Key (lock) ; Thermal ; Energy consumption ; Interface (matter) ; Focus (optics) ; Mass transport Metal-Organic Frameworks: Synthesis and Applications ; Thermal properties of materials ; X-ray Diffraction in Crystallography
Authors: Kris Meier | Sven Bühlmann | Josep Arús‐Pous | Jean‐Louis Reymond
Source: CHIMIA International Journal for Chemistry (review, 2020-04-25)
Field: Chemistry — Spectroscopy

The Generated Databases (GDBs) as a Source of 3D-shaped Building Blocks for Use in Medicinal Chemistry and Drug Discovery Drug discovery is in constant need of new molecules to develop drugs addressing unmet medical needs. To assess the chemical space available for drug design, our group investigates the generated databases (GDBs) listing all possible organic molecules up to a defined size, the largest of which is GDB-17 featuring 166.4 billion molecules up to 17 non-hydrogen atoms. While known drugs and bioactive compounds are mostly aromatic and planar, the GDBs contain a plethora of non-aromatic 3D-shaped molecules, which are very useful for drug discovery since they generally have more desirable absorption, distribution, metabolism, excretion and toxicity (ADMET) properties. Here we review GDB enumeration methods and the selection and synthesis of GDB molecules as modulators of ion channels. We summarize the constitution of GDB subsets focusing on fragments (FDB17), medicinal chemistry (GDBMedChem) and ChEMBL-like molecules (GDBChEMBL), and the ring system database GDB4c as a rich source of novel 3D-shaped chiral molecules containing quaternary centers, such as the recently reported trinorbornane. Chemical space ; chEMBL ; Drug discovery ; Chemistry ; Molecule ; Combinatorial chemistry ; Small molecule ; Database ; Computer science ; Nanotechnology ; Materials science ; Organic chemistry Analytical Chemistry and Chromatography ; Computational Drug Discovery Methods ; Chemical Synthesis and Analysis