jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Farzad Zangeneh‐Nejad
Source: Infoscience (Ecole Polytechnique Fédérale de Lausanne) (article, 2020-12-21)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Analog signal processing with topological metamaterials Originally discovered in condensed matter systems, topological insulators (TIs) have been ubiquitously extended to various fields of classical wave physics including photonics, phononics, acoustics, mechanics, and microwaves. In the bulk, like any other insulator, TIs prohibit energy propagation. On their surface, however, they support one-way propagative states with inherent protection against certain types of disorders and defects. In this work, I explore the possibility of performing advanced signal processing and analog computing tasks based on the boundary states of wave topological insulators. By providing numerical and experimental verifications, I demonstrate that such kind of computing scheme, referred to as topological analog signal processing, provides one with strong robustness against imperfection and disorder. It is in sharp contrast to conventional signal processors, which are often very sensitive to geometrical tolerances. Going a step further, I even demonstrate that, in some topological systems with specific parameter ranges, the harmful effects of the disorder can be turned into an asset so as trigger functionalities of interest. These findings open up large perspectives for a new generation of all-optical signal processors that are not only fast and power-efficient but also offer strong levels of reliability and robustness to disorder. Metamaterial ; Topology (electrical circuits) ; Signal processing ; Computer science ; Physics ; Telecommunications ; Electrical engineering ; Engineering ; Optoelectronics ; Radar Metamaterials and Metasurfaces Applications ; Advanced Optical Imaging Technologies ; Quantum optics and atomic interactions
Authors: Gianluigi Zangari del Balzo
Source: Zenodo (CERN European Organization for Nuclear Research) (article, 2020-06-18)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Quasi-liquid crystals of electrons and positrons This work concerns the discovery of a time-domain "anomaly" in the Infra-Red synchrotron radiation spectra emitted by electrons and positrons from both the DAPHNE -Factory (Frascati National Laboratories, Italy) and HFL (Hefei Light Source at NSRL(National Synchrotron Radiation Laboratory, People’s Republic of China). The study was conducted with the SHT unconventional statistical category calculus system, developed and patented by the present author for the analysis of complex systems. The anomaly found in the IR synchrotron radiation emission profile of each single bunch of electrons and positrons, has been resolved by SHT analysis in two distinct waveform components, one of which is "delayed" by a few hundred of ps with respect to the other.<br> A detailed and in-depth analysis excludes that the anomaly is the result of systematic errors.<br> The measured time differences between the two signals leads to an apparent discrepancy in the value of the speed of light in a vacuum.<br> A deep time series analysis of the anomaly, based on considerations on the coherent emission of synchrotron radiation (CSR), demonstrates the existence of a distribution of structures and degrees of freedom inside a bunch of particles. This evidence is in contrast with the "rigid bunch" model (J. Schwinger 1945). We therefore propose a model called "CFNM" (Coherent Fractal Nematic Mesophase), which describes the transition from a phase of maximum symmetry to a condensed phase, homologous to the nematic mesophase of liquid crystals. This model could have significant consequences in the study, modeling and measurement of the operating parameters of future machines and collectors of accelerators, in particular with regard to emission and brightness. Electron ; Positron ; Physics ; Nuclear physics ; Materials science ; Engineering physics Liquid Crystal Research Advancements ; Inorganic Fluorides and Related Compounds ; Advanced Chemical Physics Studies
Authors: Gianluigi Zangari del Balzo
Source: Zenodo (CERN European Organization for Nuclear Research) (article, 2020-06-18)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Quasi-liquid crystals of electrons and positrons This work concerns the discovery of a time-domain "anomaly" in the Infra-Red synchrotron radiation spectra emitted by electrons and positrons from both the DAPHNE -Factory (Frascati National Laboratories, Italy) and HFL (Hefei Light Source at NSRL(National Synchrotron Radiation Laboratory, People’s Republic of China). The study was conducted with the SHT unconventional statistical category calculus system, developed and patented by the present author for the analysis of complex systems. The anomaly found in the IR synchrotron radiation emission profile of each single bunch of electrons and positrons, has been resolved by SHT analysis in two distinct waveform components, one of which is "delayed" by a few hundred of ps with respect to the other.<br> A detailed and in-depth analysis excludes that the anomaly is the result of systematic errors.<br> The measured time differences between the two signals leads to an apparent discrepancy in the value of the speed of light in a vacuum.<br> A deep time series analysis of the anomaly, based on considerations on the coherent emission of synchrotron radiation (CSR), demonstrates the existence of a distribution of structures and degrees of freedom inside a bunch of particles. This evidence is in contrast with the "rigid bunch" model (J. Schwinger 1945). We therefore propose a model called "CFNM" (Coherent Fractal Nematic Mesophase), which describes the transition from a phase of maximum symmetry to a condensed phase, homologous to the nematic mesophase of liquid crystals. This model could have significant consequences in the study, modeling and measurement of the operating parameters of future machines and collectors of accelerators, in particular with regard to emission and brightness. Electron ; Positron ; Physics ; Nuclear physics ; Materials science ; Atomic physics Liquid Crystal Research Advancements ; Inorganic Fluorides and Related Compounds ; Advanced Chemical Physics Studies
Authors: Shogo Nagano | Yusuke Tanigaki | Hirokazu Fukuda
Source: Environment Control in Biology (article, 2020-10-01)
Field: Chemistry — Analytical Chemistry

Nondestructive Estimation of Circadian Time in Harvested Green Perilla Leaves Using Hyperspectral Data The circadian clock, an internal oscillator with a period of approximately 24 hours, plays an important role in the regulation of biological processes, and an understanding of circadian rhythms can be employed to improve the quality of plant production. Many studies have measured the circadian rhythms of plants and estimate their circadian times. However, the circadian time estimation methods used in previous studies are difficult to apply to commercial crops because they require extraction of plant contents such as RNA, which involves destroying plant tissues. In this study, we sought to develop a nondestructive method for estimating circadian time in harvested leaves of green perilla (Perilla frutescens var. crispa f. viridis). The results of RNA sequencing (RNA-Seq) show that the gene expression of perillyl alcohol depend on the circadian time. A hyperspectral camera captured the light reflectance of 141 wavebands from 350 to 1,050 nm on leaves, and machine learning using the reflectance data successfully estimated the circadian time corresponding to the harvest time. The study results demonstrate the potential for the nondestructive use of hyperspectral reflectance data in circadian time estimation and its applicability to improving the quality of plant production. Circadian rhythm ; Hyperspectral imaging ; Circadian clock ; Biology ; Perilla ; Botany ; Artificial intelligence ; Computer science ; Ecology ; Neuroscience Spectroscopy and Chemometric Analyses ; Natural Products and Biological Research ; Light effects on plants
Authors: An Su | Krishna Rajan
Source: ChemRxiv (preprint, 2020-07-01)
Field: Chemistry — Inorganic Chemistry

A Database Framework for Rapid Screening of Structure-Function Relationships in PFAS Chemistry This paper describes a database framework that enables one to rapidly explore systematics in structure-function relationships associated with new and emerging PFAS chemistries. The data infrastructure maps high dimensional information associated with SMILES encoding of molecular structure with activity/property data. This ‘PFAS-Map’ serves as a 3-dimensional unsupervised visualization learning tool to automatically classify new PFAS chemistries into current well-established criteria for PFAS classification. We provide examples on how the PFAS-Map can be utilized, including the ability to predict and estimate yet unmeasured fundamental physical properties of PFAS chemistries, uncovering hierarchical characteristics in existing classification schemes and the fusion of data from diverse sources. Computer science ; Function (biology) ; Visualization ; Data mining ; Property (philosophy) ; Database ; Biology Inorganic Fluorides and Related Compounds ; Fluorine in Organic Chemistry ; History and advancements in chemistry
Authors: Yin Shing Gary Chan
Source: eScholarship (California Digital Library) (article, 2020-01-01)
Field: Materials Science — Polymers and Plastics

Development of potentiostat platform for complex voltammetric measurements and self-adjustable electrolysis With rapid technological progress, electrochemical methods are being developed and improved throughout the years. Outdated models of electrochemical equipment like potentiostats are replaced with newer models with more functions and capability. Since those outdated models are programmed using programming language like C++, users can utilize the source code to program new features to the outdated potentiostats, extending its period of use. We developed methods enabling users to create new functionality of an electrochemical analytical system using its software development platform on MATLAB� to perform complex voltammetric measurements and self-adjustable electrolysis. Complex voltammetric measurement is defined by running chronoamperometry under arbitrary potential waveform rather than the traditional constant voltage chronoamperometry or triangular potential waveform used in cyclic voltammetry. Self-adjustable electrolysis is demonstrated as a proof-of-concept via a nanowire array electrode, monitoring, and self-adjusting potentiostat parameters throughout the experiment with the execution of a control loop. The development of arbitrary waveform allows the potential improvement of sensitivity in electroanalytical methods for detecting compounds and their redox potential, whereas the development of self-adjustable electrolysis facilitates in the self-optimization of method parameters in electrochemical measurement through a control loop mechanism. Potentiostat ; Chronoamperometry ; Waveform ; Electrolysis ; Cyclic voltammetry ; Computer science ; MATLAB ; Voltage ; Electroanalytical method ; Voltammetry ; Electronic engineering ; Electrochemistry ; Electrical engineering ; Electrode ; Engineering ; Chemistry ; Electrolyte ; Potentiometric titration Conducting polymers and applications ; Advanced Chemical Sensor Technologies ; Analytical Chemistry and Sensors
Authors: Ethan Stanifer
Source: Syracuse University Libraries (Syracuse University) (article, 2020-01-01)
Field: Materials Science — Materials Chemistry

Investigating the Relationships Between Disorder, Structure, and Dynamics in Amorphous Systems In this thesis, we investigate the relationships between the disorder, structure, and deformation in amorphous materials. First, to understand the surprising low-frequency vibrational modes in structural glasses, and how it arises from the microscopic disorder in the system, we study the spectra of a large ensemble of sparse random matrices where disorder is controlled by the distribution of bond weights and network coordination. When there is a finite probability density of infinitesimal bond weights, we find a region in the vibrational density of states that is consistent with the low-frequency behavior in structural glasses. Next, in order to investigate structural properties of active systems, we develop a novel method to generate static, finite packings in an artificial potential that reproduce the packing structures observed in a class of point-of-interest active self-propelled particle simulations. This allows us to compute structural measures, such as the vibrational modes, in an unstable active system. Finally, we evaluate the evolution of structure during strain-induced avalanches in athermal, amorphous systems using numerical simulation of soft spheres. We find that these avalanches can be decomposed into a series of bursts of localized deformations, and we develop an extension of persistent homology to isolate these bursts of localized deformations. Further, we extend existing tools for the structural evaluation of mechanically stable systems to generically unstable systems to identify how soft regions evolve and change throughout an avalanche. Dynamics (music) ; Amorphous solid ; Computer science ; Psychology ; Chemistry ; Crystallography Material Dynamics and Properties ; Liquid Crystal Research Advancements
Authors: Mariana Carvalho | Livia Martins da Costa Furtado Pimentel | Mariany Arduína Nogueira | Larissa Pimenta da Silva
Source: Anais do Simpósio Brasileiro de Pesquisa Operacional (article, 2020-01-01)
Field: Chemistry — Analytical Chemistry

AN ASSESSMENT ON THE INFLUENCE OF PROCESS INPUT AND CONDITIONS ON THE CRAFT BEER YIELD USING LINEAR REGRESSION AND MACHINE LEARNING TECHNIQUES The goal of this paper is to use data analysis techniques to identify the role of input and process conditions on the yield of a craft beer production.Data from batch forms were collected and organized in a database with 103 predictor variables.Three techniques are used to fit process yield: multiple linear regression, logistic regression and support vector machines.Validation results show that the linear regression approaches fit the data well.Although the sensitivity × specificity analysis of support vector machines approach indicates lower model adequacy than the one from logistic regression, the more complex relation between predictors and yield is evaluated.Results indicate that, besides process inputs (malt and water), specific process time intervals have also an important role on the yield. Craft ; Yield (engineering) ; Linear regression ; Process (computing) ; Computer science ; Regression ; Regression analysis ; Statistics ; Machine learning ; Artificial intelligence ; Mathematics ; Process engineering ; Engineering ; Materials science ; Composite material ; Visual arts ; Art Spectroscopy and Chemometric Analyses ; Horticultural and Viticultural Research ; Fermentation and Sensory Analysis
Authors: Sergio Pérez-Conesa | Eric G. Keeler | Dongyu Zhang | Lucie Delemotte | Ann E. McDermott
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2020-12-15)
Field: Chemistry — Spectroscopy

Informing NMR experiments with molecular dynamics simulations to characterize the dominant activated state of the KcsA ion channel As the first potassium channel with a X-ray structure determined, and given its homology to eukaryotic channels, the pH-gated prokaryotic channel KcsA has been extensively studied. Nevertheless, questions related in particular to the allosteric coupling between its gates remain open. The many currently available X-ray crystallography structures appear to correspond to various stages of activation and inactivation, offering insights into the molecular basis of these mechanisms. Since these studies have required mutations, complexation with antibodies, and substitution of detergents in place of lipids, examining the channel under more native conditions is desirable. Solid-state NMR (SSNMR) can be used to study the wild-type protein under activating conditions (low pH), at room temperature, and in bacteriomimetic liposomes. In this work, we sought to structurally assign the activated state present in SSNMR experiments. We used a combination of molecular dynamics (MD) simulations, chemical shift prediction algorithms, and Bayesian inference techniques to determine which of the most plausible X-ray structures resolved to date best represents the activated state captured in SSNMR. We first identified specific nuclei with simulated NMR chemical shifts that differed significantly when comparing partially open vs. fully open ensembles from MD simulations. The simulated NMR chemical shifts for those specific nuclei were then compared to experimental ones, revealing that the simulation of the partially open state was in good agreement with the SSNMR data. Nuclei that discriminate effectively between partially and fully open states belong to residues spread over the sequence and provide a molecular level description of the conformational change. KcsA potassium channel ; Molecular dynamics ; Solid-state nuclear magnetic resonance ; Chemical shift ; Chemistry ; Crystallography ; Chemical physics ; Biophysics ; Ion channel ; Computational chemistry ; Nuclear magnetic resonance ; Physics ; Physical chemistry ; Biochemistry ; Biology Advanced NMR Techniques and Applications ; Solid-state spectroscopy and crystallography ; Electron Spin Resonance Studies
Authors: Muhammad Haziq | Haikal Hisham | Nurlaila Ismail | Azah Mohd | Saıful Nizam Tajuddin | Mohd Nasir Taib | M Aziz | N Ismail | I Yassin | A Zabidi | M Ali | Y Liu | J Wei | Z Gao | Z Zhang | J Lyu | N Ali | M Jamil | M Rahiman | S Tajuddin | M Taib | W Noble | M Trotter | B Buxton | S Holden | R Lippman | Donald Specht | S Watkins | P Chau | R Tawel | C Micchelli | Z.-J Fu | W Chen | L Ling | J Park | I Sandberg | G Pavithra | P Abirami | S Bhuvaneshwari | S Dharani | B Haridharani | N Chandra Sekhar Reddy | Purna | Chandra Vemuri | A Govardhan
Source: International Journal of Emerging Trends in Engineering Research (article, 2020-09-15)
Field: Chemistry — Organic Chemistry

SVM Modelling of Agarwood Oil Quality Grading using Radial Basis Function (RBF) and Sequential Minimal Optimization (SMO) Learning Algorithms Agarwood Oil also known as Gaharu Oil is an expensive oil with extreme demand in the world trading especially in Japan, China and the Middle East countries. Currently, the grading of the agarwood oil quality only can be done by trained human graders by physically checked the color, odour and the resin content. However, this technique is limited due to human body limitation and not too accurate as it is supposed to be. To improve the problem faced by the existing method, the grading technique using Sequential Minimal Optimization (SMO) and Radial Basis Function (RBF) in Support Vector Machine (SVM) was conducted. The works involved of data collection, data pre-processing, SVM model development and testing of the developed SVM model. The finding showed that both RBF and SMO successfully can grade the agarwood oil quality due to their accuracies is above than 80 % and error rate or MSE is close to 0. Thus, the technique presented in this paper proved its capability in overcoming the constraint of human trained grader and benefit as well as contribute to the agarwood oil industry especially its oil quality grading. Radial basis function ; Computer science ; Support vector machine ; Artificial intelligence ; Machine learning ; Algorithm ; Artificial neural network Wood and Agarwood Research ; Image Processing and 3D Reconstruction ; Industrial Vision Systems and Defect Detection
Authors: W John Lough | Fletcher Gladden | R Wimal H Perera | Pankaj M. Kharabe | Audrey Lau | Murray Thomas
Source: ChromCom (article, 2020-09-01)
Field: Chemistry — Spectroscopy

Hypercarb™: Unique Retentivity Porous graphitic carbon HPLC packing material developed by John Knox’s research group and commercialised as Hypercarb™ has been available on the market for over thirty years. However, the unique properties of this phase still prove to be fundamentally novel and provide solutions to difficult separation applications. Of these properties, its lack of an elutropic series and hence ability to provide good retention not just in reversed-phase HPLC but even with non-aqueous solvents was put to good effect in this work. Herein it was demonstrated, the resolution of permethrin isomers, the isolation of coal tar extract constituents, the separation of a homologous series of garlic oil constituents, the clean-up of plant extract fractions and the provision of orthogonal selectivity for the separation of flurbiprofen and its related substances. Chromatography ; Chemistry ; High-performance liquid chromatography ; Coal tar ; Homologous series ; Porosity ; Selectivity ; Aqueous solution ; Resolution (logic) ; Organic chemistry ; Chemical engineering ; Coal ; Computer science Analytical Chemistry and Chromatography ; Analytical Chemistry and Sensors ; Analytical chemistry methods development
Authors: Yen‐Ju Wu | Yann‐Wen Lan | Shih‐Chieh Hsu | Chen‐Hao Yeh | Yu‐Seng Ku | Jyh‐Chiang Jiang | Yibin Xu
Source: Institutional Repositories DataBase (IRDB) (article, 2020-05-27)
Field: Materials Science — Materials Chemistry

Tuning Interfacial Thermal and Electrical Conductance across a Metal/MoS2 Monolayer through N‐Methyl‐2‐pyrrolidone Wet Cleaning Extensive effort has been dedicated to developing two-dimensional (2D) materials as an alternative to Si-based semiconductor technology. As the size decreases, heat dissipation at various interfaces becomes increasingly important in controlling device performance. On the other hand, the high interfacial thermal resistances can be applied for thermoelectric devices or thermal insulators by achieving ultra-low thermal conductivity via nanostructuring. Here, we found that (a) the thermal and electrical conductance of the Au/MoS2 monolayer interface can be tuned by changing the interfacial chemical properties through N-methyl-2-pyrrolidone (NMP) wet cleaning while preserving the MoS2 structure; (b) The effectiveness of the NMP cleaning process, which removes surface adsorbates, exhibits a temperature dependence; (c) Experimental results demonstrate that adequate oxygen adsorbates at the Au/MoS2 interface significantly improve the thermal and electrical conductance, in agreement with the simulation results. The interfacial thermal conductance increases by 339.87% when oxygen adsorbates partially removed and decreases by 74.37% as a sharp interface exists (oxygen adsorbates removed) compared to as-deposit interfaces. The electrical conductance shows up to two-order increase after NMP cleaning. This finding can both enhance the heat dissipation in functional devices and provide new options for the interface design of thermal insulating thin films. Monolayer ; Thermal ; Thermal conductivity ; Thermal contact conductance ; Electrical resistivity and conductivity ; Conductance 2D Materials and Applications ; Thermal properties of materials ; Graphene research and applications
Authors: Tony Edge
Source: ChromCom (article, 2020-09-01)
Field: Chemistry — Spectroscopy

Impact of Temperature on Efficiency and Selectivity in HPLC Temperature is often used in many forms of chromatography as a key variable to impact analyte behaviour [1], in particular, retention of volatile analytes in GC. However, it is seldom considered in LC as a means to modulate selectivity. Why is this, and what would the advantages be of using temperature as a variable within liquid chromatography? I will begin with the perceived disadvantages to try to understand why the use of temperature as a modulating parameter is often considered peripheral by many practitioners of chromatography. There are three major considerations; Column stability, Compound stability, System hardware compatibility. Analyte ; Selectivity ; High-performance liquid chromatography ; Chromatography ; Chemistry ; Compatibility (geochemistry) ; Materials science ; Organic chemistry Analytical Chemistry and Chromatography ; Microfluidic and Capillary Electrophoresis Applications ; Mass Spectrometry Techniques and Applications