jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Shun‐ichi Azuma | Dai Takakura | Ryo Ariizumi | Toru Asai
Source: arXiv (Cornell University) (preprint, 2023-12-23)
Field: Materials Science — Materials Chemistry

Networks of Classical Conditioning Gates and Their Learning Chemical AI is chemically synthesized artificial intelligence that has the ability of learning in addition to information processing. A research project on chemical AI, called the Molecular Cybernetics Project, was launched in Japan in 2021 with the goal of creating a molecular machine that can learn a type of conditioned reflex through the process called classical conditioning. If the project succeeds in developing such a molecular machine, the next step would be to configure a network of such machines to realize more complex functions. With this motivation, this paper develops a method for learning a desired function in the network of nodes each of which can implement classical conditioning. First, we present a model of classical conditioning, which is called here a classical conditioning gate. We then propose a learning algorithm for the network of classical conditioning gates. Conditioning ; Classical conditioning ; Cybernetics ; Conditioned reflex ; Artificial intelligence ; Computer science ; Process (computing) ; Function (biology) ; Artificial neural network ; Machine learning ; Cognitive science ; Reflex ; Neuroscience ; Mathematics ; Psychology Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Various Chemistry Research Topics
Authors: <p>Cao Tianzhi<sup>1</sup>, Hiroshi Okamoto<sup>2</sup></p>
Source: Academic Journal of Agriculture & Life Sciences (article, 2023-01-01)
Field: Chemistry — Analytical Chemistry

Defect Detection and Size Grading of Harvested Japanese Yam Using Computer Vision Technology Root crop yield estimate and harvest technology, especially Japanese Yam harvest production, has a high demand for intelligent automation systems. This paper develops a Japanese Yam quality grading system based on computer vision and deep learning, which can automatically detect the shape and quality of Japanese Yam and grade the size of harvested. Specifically, based on Shuffle-Net and transfer learning, a lightweight deep learning model (CDD Net) was constructed to detect surface and shape defects of Japanese Yam. It’s methods were also proposed based on minimum bounding rectangle (MBR) fitting and convex polygon approximation. Experimental results showed that the detection accuracy of the proposed CDD Net was 98.94% for binary classification (normal and defective) and 92.92% for multi-class classification (normal, curve, fork root, fracture), and demonstrated good performance both in time efficiency and detection accuracy. The size accuracy of MBR fitting and convex polygon approximation was 92.8% and 95.1% respectively. This study provides a practical method for defect detection and size grading, which has great potential for application in yield estimation of root crops. Grading (engineering) ; Artificial intelligence ; Computer vision ; Computer science ; Computer graphics (images) ; Engineering Spectroscopy and Chemometric Analyses
Authors: Kento Sasaki | Yuki Nakamura | Hao Gu | Moeta Tsukamoto | Shu Nakaharai | Takuya Iwasaki | Kenji Watanabe | Takashi Taniguchi | Shinichi Ogawa | Yukinori Morita | Kensuke Kobayashi
Source: arXiv (Cornell University) (preprint, 2023-01-30)
Field: Materials Science — Materials Chemistry

Magnetic field imaging by hBN quantum sensor nanoarray Placing a sensor close to the target at the nano-level is a central challenge in quantum sensing. We demonstrate high-spatial-resolution magnetic field imaging with a boron vacancy (V$_\text{B}^-$) defects array in hexagonal boron nitride with a few 10 nm thickness. V$_\text{B}^-$ sensor spots with a size of (100 nm)$^2$ are arranged periodically with nanoscale precision using a helium ion microscope and attached tightly to a gold wire. The sensor array allows us to visualize the magnetic field induced by the current in the wire with a spatial resolution beyond the diffraction limit. Each sensor exhibits a practical sensitivity of $73.6~μ\text{T/Hz}^{0.5}$, suitable for quantum materials research. Our technique of arranging V$_\text{B}^-$ quantum sensors periodically and tightly on measurement targets will maximize their potential. Magnetic field ; Materials science ; Image resolution ; Nanoscopic scale ; Resolution (logic) ; Quantum sensor ; Quantum ; Vacancy defect ; Liquid helium ; Microscope ; Image sensor ; Diffraction ; Optoelectronics ; Optics ; Nanotechnology ; Physics ; Helium ; Nuclear magnetic resonance ; Quantum information ; Atomic physics ; Quantum network ; Computer science Diamond and Carbon-based Materials Research ; Ion-surface interactions and analysis ; Metal and Thin Film Mechanics
Authors: M. Alhassan | M. Usman | S. I. Muazu
Source: Journal of applied science and environmental management (article, 2023-02-28)
Field: Materials Science — Materials Chemistry

Developing a Mathematical Formula that can Calculate the Density of MoO3-B2O3-Bi2O3 Glass System from Weight Percentages of its Components Research on glass systems for radiation shielding involves the fabrication of different samples in a sequential manner. In order to determine their shielding properties their densities have to be found experimentally. This procedure causes time and capital consumption and is associated with health risk due to the biological harms of some chemicals involved in it. Therefore, the objective of this work is to reduce the cost, time and health risks by developing a mathematical model to calculate the density of MoO3 - B2O3 - Bi2O3 glass system from weight percentages of its components using Phy-X/PSD software and Python Programming. The input needed are the densities and percentage weights of the constituent components. The coding made in Python programming language to test the formula shows its ability to reproduce or predict densities of the required samples of this glass system with accuracy within 99.59 – 99.88%. Therefore, making use of this formula will simplify the difficulty of refabricating glasses defined by the expression yMoO3 - xB2O3 - (100 – y – x) Bi2O3 for research purposes, which will reduce the financial cost and health risks. Python (programming language) ; Electromagnetic shielding ; Computer science ; Fabrication ; Software ; Fortran ; Mathematics ; Materials science ; Programming language ; Composite material Radiation Shielding Materials Analysis
Authors: Bin Wang | Hua Yang | Lily LI
Source: INMATEH Agricultural Engineering (article, 2023-08-17)
Field: Chemistry — Analytical Chemistry

DISCRIMINATION OF CERASUS HUMILIS FRUIT MATURITY BASED ON HYPERSPECTRAL IMAGING TECHNOLOGY In order to realize the rapid and accurate identification of different maturity of Cerasus humilis fruit, this study explored the nondestructive testing method of Cerasus Humilis fruit maturity based on hyperspectral imaging technology. The hyperspectral data of 320 samples of Cerasus humilis fruit were collected by using a hyperspectral imaging system in the range of 895~1700 nm. By comparing the prediction accuracy of the partial least squares (PLS) model established by four preprocessing methods, the competitive adaptive reweighted algorithm (CARS), successive projection algorithm (SPA), and random frog (RF) were used to extract characteristic wavelengths, and partial least squares-discriminant analysis (PLS-DA) and least squares-support vector machine (LS-SVM) discriminant models were established. The results showed that the SPA-LS-SVM model had the highest discrimination accuracy for the four types of maturity samples, and the discrimination accuracy of the correction set and prediction set were 85.00% and 87.50%, respectively. This study provides a theoretical reference for the rapid and nondestructive testing of the maturity of Cerasus Humilis fruit by hyperspectral imaging technology. Hyperspectral imaging ; Artificial intelligence ; Partial least squares regression ; Pattern recognition (psychology) ; Mathematics ; Support vector machine ; Linear discriminant analysis ; Computer science ; Statistics Spectroscopy and Chemometric Analyses ; Phytochemicals and Antioxidant Activities ; Water Quality Monitoring and Analysis
Authors: Arup Chakraborty | Bidisa Das | Indra Dasgupta
Source: International Journal of Quantum Chemistry (article, 2023-02-14)
Field: Materials Science — Materials Chemistry

Unlocking the electronic, optical and transport properties of semiconductor coupled quantum dots using first principles methods Abstract Semiconductor coupled quantum dots provide a unique opportunity for tuning band gaps by tailoring band offsets, making them ideal for photovoltaic and other applications. Here, we have studied stability, trends in the band gap, band offsets, and optical properties for a series of coupled quantum dots comprised of II–VI semiconductors using a hybrid functional method. We have shown how the quantum confinement and interfacial strain considerably affect the band gap and band offsets for these heterostructures at the nanoscale. We show that the trend in band offsets obtained from our first‐principles electronic structure calculations agrees with that obtained from the method of average electrostatic potential. It is found that a common anion rule for band offset is followed for these heterostructures at the nanoscale. Further, the calculated optical absorption spectra for these coupled quantum dots reveal that absorption peaks lie in the ultra‐violet (UV) region, whereas absorption edges are in the visible region. In addition to electronic and optical properties, we have also explored transport properties for two representative coupled quantum dots, either having common cations or common anions, which revealed asymmetric nature in current–voltage characteristics. Therefore, these semiconductor coupled quantum dots may be useful for photovoltaic, light‐emitting diode, and optoelectronic devices. Quantum dot ; Semiconductor ; Heterojunction ; Band offset ; Optoelectronics ; Band gap ; Absorption spectroscopy ; Absorption (acoustics) ; Materials science ; Diode ; Multiple exciton generation ; Chemistry ; Physics ; Optics Quantum Dots Synthesis And Properties ; Semiconductor Quantum Structures and Devices ; ZnO doping and properties
Authors: Arun S. Moorthy | Anthony J. Kearsley | William Mallard | W.E. Wallace | Stephen E. Stein
Source: ChemRxiv (preprint, 2023-04-26)
Field: Chemistry — Spectroscopy

Inferring the nominal molecular mass of an analyte from its electron ionization mass spectrum The performance of three algorithms for predicting nominal molecular mass from an analyte’s electron ionization mass spectrum are presented. The Peak Interpretation Method (PIM) attempts to quantify the likelihood that a molecular ion peak is contained in the mass spectrum, whereas the Simple Search Hitlist Method (SS-HM) and iterative Hybrid Search Hitlist Method (iHS-HM) leverage results from mass spectral library searching. These predictions can be employed in combination (recommended) or independently. The methods were tested on two sets of query mass spectra searched against libraries that did not contain reference mass spectra of the same compounds: 19,074 spectra of various organic molecules searched against NIST17 mass spectral library, and 162 spectra of small molecule drugs searched against SWGDRUG version 3.3. Individually, each molecular mass prediction method had computed precisions (the fraction of positive predictions that were correct) of 91 %, 89 % and 74 %, respectively. The methods become more valuable when predictions are taken together as an ensemble. When all three predictions were identical, which occurred in 33% of the test cases, the predicted molecular mass was almost always correct (> 99 %). Mass spectrum ; Ionization ; Analyte ; Electron ionization ; Polyatomic ion ; Spectral line ; Leverage (statistics) ; Chemistry ; Mass spectrometry ; Molecular mass ; Analytical Chemistry (journal) ; Ion ; Physics ; Mathematics ; Chromatography ; Statistics Analytical Chemistry and Chromatography ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Irina Piyanzina | Alexandr Evseev | Kirill V. Evseev | Р. Ф. Мамин | Oleg V. Nedopekin | D. A. Tayurskiı̆ | V. V. Kabanov
Source: Preprints.org (preprint, 2023-09-21)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Advantages of Ferroelectrics as a Component of Heterostructures for Electronic Purposes: A DFT Insight The main advantage of using the ferroelectric material as a component of complex heterostructure is the ability to tune various properties of the whole system by means of external electric field. In particular, the electric field may change the polarization direction within the ferroelectric material and consequently affect the structural properties, which in turn affects the electronic and magnetic properties of the neighboring material. Besides, the ferroelectrics proceed the electrostriction phenomenon, which is promising to be used to affect the magnetic states of interface state in the heterostructure with a magnetic component. The interfacial phenomena are of a great interest since they provide an extended functionality useful for electronic devices of a new generation. Following an idea of utilizing a ferroelectric in heterostructures component in the present work we consider 2DEG, Rashba effect, the effect of magnetoelectric coupling and magnetostriction in order to emphasize the advantages of such heterostructures as components of devices. For this purpose model systems of LaMnO3/BaTiO3, La2CuO4/BaTiO3, Bi/BaTiO3 and Bi/PbTiO3, Fe/BaTiO3 heterostructures are investigated by density functional theory calculations. Heterojunction ; Ferroelectricity ; Electrostriction ; Materials science ; Condensed matter physics ; Component (thermodynamics) ; Electric field ; Dielectric ; Optoelectronics ; Piezoelectricity ; Physics Multiferroics and related materials ; Chemical and Physical Properties of Materials ; Theoretical and Computational Physics
Authors: Felix Frohnert | Evert van Nieuwenburg
Source: arXiv (Cornell University) (preprint, 2023-06-09)
Field: Materials Science — Materials Chemistry

Explainable Representation Learning of Small Quantum States Unsupervised machine learning models build an internal representation of their training data without the need for explicit human guidance or feature engineering. This learned representation provides insights into which features of the data are relevant for the task at hand. In the context of quantum physics, training models to describe quantum states without human intervention offers a promising approach to gaining insight into how machines represent complex quantum states. The ability to interpret the learned representation may offer a new perspective on non-trivial features of quantum systems and their efficient representation. We train a generative model on two-qubit density matrices generated by a parameterized quantum circuit. In a series of computational experiments, we investigate the learned representation of the model and its internal understanding of the data. We observe that the model learns an interpretable representation which relates the quantum states to their underlying entanglement characteristics. In particular, our results demonstrate that the latent representation of the model is directly correlated with the entanglement measure concurrence. The insights from this study represent proof of concept towards interpretable machine learning of quantum states. Our approach offers insight into how machines learn to represent small-scale quantum systems autonomously. Computer science ; Representation (politics) ; Qubit ; Quantum entanglement ; Generative model ; Context (archaeology) ; Quantum machine learning ; Artificial intelligence ; Quantum ; Theoretical computer science ; Quantum state ; Quantum computer ; Machine learning ; Generative grammar ; Quantum mechanics ; Physics Machine Learning in Materials Science ; Quantum many-body systems ; Neural Networks and Reservoir Computing
Authors: O.A. Miryuk | A.I. Oleinik | K.M. Akhmedov
Source: Eurasian Physical Technical Journal (article, 2023-04-09)
Field: Materials Science — Materials Chemistry

Computer modeling of properties of a composite materials with porous fillers The article is devoted to forecasting of heat-shielding and mechanical properties of composite materials based on porous fillers. Analytical dependencies for determining the thermal conductivity coefficient of materials of homogeneous and heterogeneous structure are given. Based on the finite element method, there has been developed a method for numerical determination of the thermal conductivity coefficient of composite materials with a variotropic structure. The results of computer studies are in line with the dependences obtained on analytical models. The expediency of using multilayer composite materials based on porous fillers in load-bearing and enclosing structures of shell and plate types has been shown. Thermal conductivity ; Materials science ; Composite number ; Composite material ; Porosity ; Porous medium ; Finite element method ; Homogeneous ; Shell (structure) ; Thermal ; Material properties ; Structural engineering ; Mathematics ; Thermodynamics ; Engineering Structural mechanics and materials ; Industrial Engineering and Technologies ; Material Properties and Applications
Authors: Gizem Tırıs | Elif Naz Öven | Nevin Erk
Source: Ankara Universitesi Eczacilik Fakultesi Dergisi (article, 2023-06-14)
Field: Chemistry — Analytical Chemistry

SIMULTANEOUS SPECTROPHOTMETRIC DETERMINATION OF FLUOXETINE AND OLANZAPINE GREENNES ASSESSMENT Objective: In our study, the simultaneous determination of fluoxetine (FLX) and olanzapine (OLZ) was performed by absorbance subtraction and absorbance correction spectrophotometric methods. Material and Method: The active substances were determined by choosing the isosbestic point of 232 nm in the absorbance subtraction method and 255 nm and 245 nm wavelengths in the absorbance correction method. The accuracy of the methods was determined by applying the percentage recovery studies to the laboratory mixtures. The percent recovery values were found in the range of 98.1-100.2 for OLZ and 96.8-105.3 for FLX. The concentration range studied was 3.12-15.62 and 3.45-17.28 µg/ml for OLZ and FLX, respectively. Result and Discussion: In the study, two active substances used in antidepressant treatment were determined simultaneously. Today, these active substances used in the treatment have started to be used in combination in order to achieve a better effect of the treatment. Therefore, simultaneous analysis of two active substances becomes important. Two different spectrophotometric methods were used for analysis. The methods have been successfully applied and validated for the simultaneous determination of antidepressant active substances. Since the applied methods do not require pre-separation and can be applied directly, the amount of waste generated is reduced. Environmentally sensitive methods have been applied. Absorbance ; Subtraction ; Chromatography ; Chemistry ; Analytical Chemistry (journal) ; Materials science ; Mathematics Analytical Methods in Pharmaceuticals ; Electrochemical sensors and biosensors ; Analytical Chemistry and Chromatography
Authors: Andreas Herklotz | Florina Ștefania Rus | Martin M. Koch | Kyle M. Grove | Michael Bowen | David P. Cann | Kristin Tippey | Kathrin Dörr
Source: Coatings (article, 2023-12-07)
Field: Materials Science — Materials Chemistry

Epitaxial Stabilization of Perovskite ATeO3 Thin Films Tellurium oxides of the ATeO3 form typically do not crystallize in perovskite structures. Here, we show that perovskite-like ATeO3 (A = Ca, Sr, Ba) thin films can be grown on perovskite single-crystal substrates via epitaxial stabilization. These films are stable with high optical bandgaps, low dielectric losses, and a high electric breakdown strength. Hysteretic dielectric behavior found in SrTeO3 and BaTeO3 strongly suggests the presence of antiferroelectricity and ferroelectricity, respectively. These properties make perovskite tellurium oxides possibly appealing candidates for thin film coating or insulator materials in advanced microelectronics. Tellurium oxides constitute a largely unexplored class of materials that might show new and interesting functionalities in epitaxial thin-films. Our work encourages new work within this field. Perovskite (structure) ; Materials science ; Epitaxy ; Thin film ; Ferroelectricity ; Tellurium ; Microelectronics ; Dielectric ; Optoelectronics ; Antiferroelectricity ; Nanotechnology ; Crystallography ; Chemistry ; Metallurgy Electronic and Structural Properties of Oxides ; Perovskite Materials and Applications ; Ferroelectric and Piezoelectric Materials
Authors: Marcel Mlynarik | Gary A. Atkinson | Melvyn Smith | Khemraj Emrith
Source:  (article, 2023-05-25)
Field: Chemistry — Analytical Chemistry

Multispectral analysis for the determination of lycopene concentration in tomatoes This paper describes a novel computer vision method for the estimation of lycopene concentration in tomatoes using a multispectral imaging approach with up to 15 bands. It is shown that combining intensity measurements at wavelengths from near-infrared to ultraviolet using a neural network model achieved correlation of R2=0.977 and RMS error=4.63 mg/kg against ground truth lycopene concentration. Our results are comparable or superior to other methods from the literature, which are analysed in detail in the paper. The method can be reproduced with minimal cost and demonstrates the feasibility of the method for industrial application. The main contribution is that a broader range of wavelengths are considered compared to most previous work, with rigorous analysis using a combination of simple regression and artificial neural networks. Multispectral image ; Lycopene ; Ground truth ; Artificial neural network ; Computer science ; Wavelength ; Ultraviolet ; Artificial intelligence ; Near-infrared spectroscopy ; Infrared ; Biological system ; Pattern recognition (psychology) ; Remote sensing ; Materials science ; Optics ; Chemistry ; Carotenoid ; Optoelectronics ; Physics ; Geology ; Food science Spectroscopy and Chemometric Analyses ; Analytical Chemistry and Sensors ; Water Quality Monitoring and Analysis