jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Inesh Z. Zhumatayeva | Аrtem L. Kozlovskiy | Maxim V. Zdorovets | R. I. Shakirzyanov | А.В. Труханов
Source: NNC RK Bulletin (article, 2023-10-07)
Field: Materials Science — Materials Chemistry

STUDY OF THE INFLUENCE OF VARIATIONS IN THE PHASE COMPOSITION ON THE DIELECTRIC PROPERTIES OF FERROELECTRIC CaTiO&lt;sub&gt;3&lt;/sub&gt; CERAMICS DOPED WITH Y&lt;sub&gt;2&lt;/sub&gt;O&lt;sub&gt;3&lt;/sub&gt; The study of the relationship between the effect of phase composition variation on the dielectric characteristics of ferroelectric ceramics is one of the most important fundamental questions, the answer to which will allow us to determine the potential of using ferroelectrics in microelectronic applications and the creation of alternative energy sources (solid oxide fuel cells). The purpose of this study is to explore the effect of the Y 2 O 3 dopant on the phase formation processes and the properties of the synthesized ferroelectric ceramics of calcium titanate, as well as to establish the connection between the influence of the formation of impurity phases on the change in the dielectric properties of ceramics. According to the data of X-ray phase analysis, it was found that the addition of Y 2 O 3 with a concentration above 0.15 M leads to the formation of an orthorhombic CaY 2 O 4 phase in the ceramic structure, the weight contribution of which increases with the dopant concentration growth. An analysis of the dependence of the specific electrical conductivity (σ DC ) with varying dopant concentration showed that the maximum value of σ DC is achieved at dopant concentrations of 0.05 M, which leads to structural ordering due to the effect of adding yttrium oxide acting as a stabilizer, as well as the formation of impurity donor conductivity in the structure. An analysis of the dependence of the specific electrical conductivity (σ DC ) from dopant concentration was carried out. It has been established that the maximum value of σ DC is achieved at a dopant concentration of 0.05 M. This is explained by structural ordering due to the addition of a stabilizer – yttrium oxide, as well as the formation of impurity donor conductivity in the synthesized sample. At the same time, the established dependences of the change in dielectric characteristics are in good agreement with the change in the phase composition, and an increase in the concentration of charge carriers due to the introduction of a donor impurity in the form of Y 3+ leads to the appearance of volume-charge polarization in ceramics. Dopant ; Materials science ; Ferroelectricity ; Dielectric ; Orthorhombic crystal system ; Yttrium ; Ceramic ; Impurity ; Doping ; Conductivity ; Phase (matter) ; Analytical Chemistry (journal) ; Calcium titanate ; Mineralogy ; Oxide ; Chemistry ; Crystallography ; Crystal structure ; Physical chemistry ; Optoelectronics ; Composite material ; Metallurgy ; Organic chemistry Ferroelectric and Piezoelectric Materials ; Material Science and Thermodynamics ; Microwave Dielectric Ceramics Synthesis
Authors: Jackson J. Alcázar | Alessandra C. Misad Saide | Paola R. Campodónico
Source: Research Square (preprint, 2023-07-03)
Field: Chemistry — Organic Chemistry

Reliable and accurate prediction of basic pKa values in nitrogen compounds: The pKa shift in supramolecular systems as a case study Abstract This article presents a Quantitative Structure-Activity Relationship (QSAR) approach for predicting the acid dissociation constant (pK \(_a\) ) of nitrogenous compounds, including those within supramolecular complexes based on cucurbiturils. The model combines low-cost quantum mechanical calculations with QSAR methodology and linear regressions to achieve accurate predictions for a broad range of nitrogen-containing compounds. The model was developed using a diverse dataset of 130 nitrogenous compounds and exhibits excellent predictive performance, with a high coefficient of determination (R \(^2\) ) of 0.9905, low standard error ( s ) of 0.3066, and high Fisher statistic ( F ) of 2142. The model outperforms existing methods, such as Chemaxon software and previous studies, in terms of accuracy and its ability to handle heterogeneous datasets. External validation on pharmaceutical ingredients, dyes, and supramolecular complexes based on cucurbiturils confirms the reliability of the model. To enhance usability, a script-like tool has been developed, providing a streamlined process for users to access the model. This study represents a significant advancement in pK$_a$ prediction, offering valuable insights for drug design and supramolecular system optimization. Quantitative structure–activity relationship ; Supramolecular chemistry ; Computer science ; Usability ; Dissociation (chemistry) ; Chemistry ; Biological system ; Machine learning ; Molecule ; Physical chemistry ; Organic chemistry Free Radicals and Antioxidants ; Organic Chemistry Cycloaddition Reactions ; Computational Drug Discovery Methods
Authors: Xiaoguang Li
Source: arXiv (Cornell University) (preprint, 2023-05-21)
Field: Materials Science — Materials Chemistry

CNN-based Dendrite Core Detection from Microscopic Images of Directionally Solidified Ni-base Alloys Dendrite core is the center point of the dendrite. The information of dendrite core is very helpful for material scientists to analyze the properties of materials. Therefore, detecting the dendrite core is a very important task in the material science field. Meanwhile, because of some special properties of the dendrites, this task is also very challenging. Different from the typical detection problems in the computer vision field, detecting the dendrite core aims to detect a single point location instead of the bounding-box. As a result, the existing regressing bounding-box based detection methods can not work well on this task because the calculated center point location based on the upper-left and lower-right corners of the bounding-box is usually not precise. In this work, we formulate the dendrite core detection problem as a segmentation task and proposed a novel detection method to detect the dendrite core directly. Our whole pipeline contains three steps: Easy Sample Detection (ESD), Hard Sample Detection(HSD), and Hard Sample Refinement (HSR). Specifically, ESD and HSD focus on the easy samples and hard samples of dendrite cores respectively. Both of them employ the same Central Point Detection Network (CPDN) but do not share parameters. To make HSD only focus on the feature of hard samples of dendrite cores, we destroy the structure of the easy samples of dendrites which are detected by ESD and force HSD to learn the feature of hard samples. HSR is a binary classifier which is used to filter out the false positive prediction of HSD. We evaluate our method on the dendrite dataset. Our method outperforms the state-of-the-art baselines on three metrics, i.e., Recall, Precision, and F-score. Dendrite (mathematics) ; Computer science ; Minimum bounding box ; Artificial intelligence ; Segmentation ; Focus (optics) ; Point (geometry) ; Pattern recognition (psychology) ; Feature (linguistics) ; Computer vision ; Materials science ; Mathematics ; Physics ; Geometry ; Optics ; Image (mathematics) Machine Learning in Materials Science ; Nanoporous metals and alloys ; Advanced Memory and Neural Computing
Authors: Arnaud Demortiere
Source: Research Square (preprint, 2023-06-06)
Field: Materials Science — Surfaces, Coatings and Films

Adaptative Diffraction Image Registrationfor 4D-STEM to optimize ACOM Pattern Matching Abstract The technique known as 4D-STEM has recently emerged as a powerful tool for the local characterization of crystalline structures in materials, such as cathode materials for Li-ion batteries or perovskite materials for photovoltaics. However, the use of new detectors optimized for electron diffraction patterns and other advanced techniques requires constant adaptation of methodologies to address the challenges associated with crystalline materials. In this study, we present a novel image processing method to improve pattern matching in the determination of crystalline orientations and phases. Our approach uses sub-pixelar adaptative image processing to register and reconstruct electron diffraction signals in large 4D-STEM datasets. By using adaptive prominence and linear filters such as mean and gaussian blur, we are able to improve the quality of the diffraction pattern registration. The resulting data compression rate of 103 is well-suited for the era of big data and provides a significant enhancement in the performance of the entire ACOM data processing method. Our approach is evaluated using dedicated metrics, which demonstrate a high improvement in phase recognition. Our results demonstrate that this data preparation method not only enhances the quality of the resulting image but also boosts the confidence level in the analysis of the outcomes related to determining crystal orientation and phase. Additionally, it mitigates the impact of user bias that may occur during the application of the method through the manipulation of parameters. Computer science ; Gaussian ; Orientation (vector space) ; Diffraction ; Image registration ; Artificial intelligence ; Materials science ; Pattern recognition (psychology) ; Optics ; Image (mathematics) ; Mathematics ; Physics Electron and X-Ray Spectroscopy Techniques ; Advanced Electron Microscopy Techniques and Applications ; Geophysical and Geoelectrical Methods
Authors: Jianbing Huang | Yong Yu | Muhammad Raza Shah | Hao Wang | Xiaomeng Cheng | Liejin Guo | Peter D. Lund | Bin Zhu
Source: Research Square (preprint, 2023-07-21)
Field: Materials Science — Materials Chemistry

Proton Transport Along Fluorite Oxide-Ion Conductor: Unveiling Abnormally High Conduction Characteristics and Synergistic Mechanisms Fluorite ; Conductor ; Proton ; Ion ; Thermal conduction ; Oxide ; Materials science ; Ion transporter ; Chemistry ; Chemical physics ; Physics ; Nuclear physics ; Composite material ; Metallurgy Advancements in Solid Oxide Fuel Cells ; Electronic and Structural Properties of Oxides ; Nuclear Materials and Properties
Authors: Shibarata Basak | Junbeom Park | Janghyun Jo | Osmane Camara | Amir H. Tavabi | Hermann Tempel | Hans Kungl | Chandramohan George | Rafal E. Dunin–Borkowski | Joachim Mayer | Rüdiger‐A. Eichel
Source: Journal of Visualized Experiments (article, 2023-01-20)
Field: Materials Science — Surfaces, Coatings and Films

Screening of Coatings for an All-Solid-State Battery using &lt;em&gt;In Situ&lt;/em&gt; Transmission Electron Microscopy With the ever-increasing use of Li-ion batteries, especially due to their adoption in electric vehicles, their safety is in prime focus. Thus, the all-solid-state batteries (ASSBs) that use solid electrolytes instead of liquid electrolytes, which reduce the risk of flammability, have been the center stage of battery research for the last few years. However, in the ASSB, the ion transportation through the solid-solid electrolyte-electrode interface poses a challenge due to contact and chemical/electrochemical stability issues. Applying a suitable coating around the electrode and/or electrolyte particles offers a convenient solution, leading to better performance. For this, researchers are screening potential electronic/ionic conductive and nonconductive coatings to find the best coatings with suitable thickness for long-term chemical, electrochemical, and mechanical stability. Operando transmission electron microscopy (TEM) couples high spatial resolution with high temporal resolution to allow visualization of dynamic processes, and thus is an ideal tool to evaluate electrode/electrolyte coatings via studying (de)lithiation at a single particle level in real-time. However, the accumulated electron dose during a typical high-resolution in situ work may affect the electrochemical pathways, evaluation of which can be time-consuming. The current protocol presents an alternative procedure in which the potential coatings are applied on Si nanoparticles and are subjected to (de)lithiation during operando TEM experiments. The high volume changes of Si nanoparticles during (de)lithiation allow monitoring of the coating behavior at a relatively low magnification. Thus, the whole process is very electron-dose efficient and offers quick screening of potential coatings. Transmission electron microscopy ; In situ ; Materials science ; Battery (electricity) ; Solid-state ; Electron microscope ; Transmission (telecommunications) ; Microscopy ; Nanotechnology ; Chemistry ; Physics ; Optics ; Computer science ; Telecommunications ; Power (physics) ; Physical chemistry Electron and X-Ray Spectroscopy Techniques ; Transition Metal Oxide Nanomaterials
Authors: A Jones | See Dutta | J Han | X See Fan | X Hao | H See Ding | M Hayati | S Zonouri | G Hellings | A Beckers | G Hiblot | M Honda | J See Rafi | M Hossain | M Islam | C Hou | W Zhang | Y Hou | C Liu-Sun | B Liu | H Zhang | H Cai | J Hsuen | M Sk | J Hu | H See Ye | W Hu | H Wang | M Huang | P Kuo | P Huang | J Wu | J Hung | W Ma | J Hutchins | S See Alam | G Li | H Li | S Li | Z See Ding | T Li | Y Yang | W Li | X Liu | X Li | Y Li | Z Liao | Z Yuan | Y Yu | R Zhang | H Zhu | H Gao | F Meng | Y Lin | Y See Nien | J Chai | H Liu | T Ohsawa | K Liu | B Wu | L Liu | T Zhang | S Tang | M Liu | S Liu | W Liu | X Lan | Z Bekele | S Zhu | P Dou | Y Wang | J Zhang | S Wang | K Wang | F Lombardi | H Lou | C Ma
Source: IEEE Transactions on Nanotechnology (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

2023 Index IEEE Transactions on Nanotechnology Vol. 22 Nanotechnology ; Index (typography) ; Materials science ; Computer science ; World Wide Web MXene and MAX Phase Materials ; Conducting polymers and applications ; Gas Sensing Nanomaterials and Sensors
Authors: M Karplus | W Miller | E Neher | H Schwarz | J Simons | G Somorjai | R Zare | B Albinsson | H Kondoh | J Zhang | C Adamo | M Devries | C Diaz | S George | D Ghosh | K Holmberg | G Meijer | G Patwari | M Rodgers | S Sampath | M Suhm | A Troisi | J Nun ez | G Belletti | E Colombo | R Nazmutdinov | P Hou | Changhong Zhang | Sen Ming | Jiongjiong Xu | Kun Meng | Guohui Li | Pengyu Li | Zhi Ge | Dawei Yan | Wei Sun | Girolamo Casella | * Silvia Carlotto | Ana Ribeiro | Lu | M Martins ; Pa raic | M Keane | Clara Zehe | Fergus Poynton | Sandra Bright | Sandra Estayalo-Adria n | Stephen Devereux | Paul Donaldson | Igor Sazanovich | Michael Towrie | Stanley Botchway | Christine Cardin | D Williams | Thorfinnur Gunnlaugsson | Conor Long | * John | M Kelly | Susan Quinn
Source: Physical Chemistry Chemical Physics (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

Contents list Permissions Request permissions Contents list Phys. Chem. Chem. Phys., 2023, 25, 22543 DOI: 10.1039/D3CP90183A This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given. Read more about how to correctly acknowledge RSC content. Acknowledgement ; Chromatin structure remodeling (RSC) complex ; Attribution ; Computer science ; Library science ; Chemistry ; Psychology ; Computer security Luminescence Properties of Advanced Materials ; Quantum Dots Synthesis And Properties ; Advanced Photocatalysis Techniques
Authors: Flynn Walsh | Mingwei Zhang | Robert O. Ritchie | Mark Asta | Andrew M. Minor
Source: arXiv (Cornell University) (preprint, 2023-11-17)
Field: Materials Science — Materials Chemistry

Multiple origins of extra electron diffractions in fcc metals Diffuse intensities in the electron diffraction patterns of concentrated face-centered cubic solid solutions have been widely attributed to chemical short-range order, although this connection has been recently questioned. This article explores the many non-ordering origins of commonly reported features using a combination of experimental electron microscopy and multislice diffraction simulations, which suggest that diffuse intensities largely represent thermal and static displacement scattering. A limited number of observations may reflect additional contributions from planar defects, surface terminations incommensurate with bulk periodicity, or weaker dynamical effects Diffraction ; Electron diffraction ; Planar ; Scattering ; Electron ; Condensed matter physics ; Materials science ; Thermal ; Displacement (psychology) ; Electron microscope ; Short range order ; Crystallography ; Physics ; Molecular physics ; Optics ; Chemistry ; Quantum mechanics ; Thermodynamics ; Psychology Microstructure and mechanical properties ; X-ray Diffraction in Crystallography ; Surface and Thin Film Phenomena
Authors: Bicai Pan | Pengfei Yu
Source: Research Square (preprint, 2023-08-21)
Field: Materials Science — Materials Chemistry

Effect of vacancy defects on thermal transport properties of tungsten nitride compounds on divertor surface in ITER Divertor ; Tungsten ; Vacancy defect ; Materials science ; Thermal ; Nitride ; Nuclear engineering ; Plasma ; Metallurgy ; Condensed matter physics ; Nuclear physics ; Nanotechnology ; Thermodynamics ; Physics ; Tokamak ; Engineering Fusion materials and technologies ; Nuclear Materials and Properties ; Advanced materials and composites
Authors: Ricardo Báez-Cruz | Erick Beristain-Montiel
Source: World journal of nanomaterials/American journal of nanomaterials (article, 2023-01-20)
Field: Chemistry — Organic Chemistry

Gold Nanoparticles Microwave-assisted Synthesis Employing Exclusively Ascorbic Acid as a Reducing and Stabilizing Agent: An Experimental and Computational Study Using soft acids as reducing agents in synthesizing metallic nanoparticles have constituted a clear framework for achieving selected morphological properties with minimal toxicity. The system's complexity and the many variables involved represent a challenge for experimental studies desiring to design reproducible synthesis protocols. In this work, we explore the exclusion of any stabilizing agent to synthesize, in an aqueous solution, non-spherical gold nanoparticles (AuNPs) via Microwave-assisted synthesis, and instead, we employed pH control over reducing agent L-Ascorbic acid (AH2). The use of AH2 presents a direct approach that allows an understanding of the role of soft acids in synthesizing metallic nanoparticles. The results indicate that AuNPs synthesized at pH ≥ 10 exhibit relatively different morphologies than those obtained at higher pH values. The AuNPs were characterized via Transmission electron Microscopy and UV-Vis Spectroscopy. Our simulations reveal the plasmon distribution according to particle shape. The experimental analysis suggests that the pH variation mechanism over the reduction agent correlates with AuNPs geometry. These results indicate that pH is an applicable parameter for controlling the nanoparticle's geometry and extend the possibility of exploring computational studies on the impact of acids adsorbed on gold colloidal surfaces. Ascorbic acid ; Nanoparticle ; Reducing agent ; Microwave ; Nanotechnology ; Colloidal gold ; Materials science ; Combinatorial chemistry ; Chemistry ; Computer science ; Organic chemistry ; Telecommunications ; Food science Nanomaterials for catalytic reactions
Authors: Gerardo G. Naumis
Source: Axioms (article, 2023-12-22)
Field: Materials Science — Materials Chemistry

Richard Kerner’s Path Integral Approach Aims to Understand the Self-Organized Matter Agglomeration and Its Translation into the Energy Landscape Kinetics Paradigm Matter grows and self-assembles to produce complex structures such as virus capsids, carbon fullerenes, proteins, glasses, etc. Due to its complexity, performing pen-and-paper calculations to explain and describe such assemblies is cumbersome. Many years ago, Richard Kerner presented a pen-and-paper path integral approach to understanding self-organized matter. Although this approach successfully addressed many important problems, including the yield of fullerene formation, the glass transition temperature of doped chalcogenide glasses, the fraction of boroxol rings in B2O3 glasses, the first theoretical explanation for the empirical recipe of window and Pyrex glass and the understanding of virus capsid self-assembly, it still is not the primary choice when tackling similar problems. The reason lies in the fact that it diverges from mainstream approaches based on the energy landscape paradigm and non-equilibrium thermodynamics. In this context, a critical review is presented, demonstrating that the Richard Kerner method is, in fact, a clever way to identify relevant configurations. Its equations are simplified common physical sense versions of those found in the energy landscape kinetic equations. Subsequently, the utilization of equilibrium Boltzmann factors in the transition Markov chain probabilities is analyzed within the context of local two-level energy landscape models kinetics. This analysis demonstrates that their use remains valid when the local energy barrier between reaction coordinate states is small compared to the thermal energy. This finding places the Richard Kerner model on par with other more sophisticated methods and, hopefully, will promote its adoption as an initial and useful choice for describing the self-agglomeration of matter. Energy landscape ; Context (archaeology) ; Statistical physics ; Path integral formulation ; Computer science ; Physics ; Thermodynamics ; Quantum ; Quantum mechanics Material Dynamics and Properties ; Phase-change materials and chalcogenides ; Theoretical and Computational Physics
Authors: Tom V. Savage | Nausheen Basha | Jonathan McDonough | Omar K. Matar | Ehecatl Antonio del Rio‐Chanona
Source: arXiv (Cornell University) (preprint, 2023-05-01)
Field: Materials Science — Materials Chemistry

Multi-Fidelity Data-Driven Design and Analysis of Reactor and Tube Simulations The development of new manufacturing techniques such as 3D printing have enabled the creation of previously infeasible chemical reactor designs. Systematically optimizing the highly parameterized geometries involved in these new classes of reactor is vital to ensure enhanced mixing characteristics and feasible manufacturability. Here we present a framework to rapidly solve this nonlinear, computationally expensive, and derivative-free problem, enabling the fast prototype of novel reactor parameterizations. We take advantage of Gaussian processes to adaptively learn a multi-fidelity model of reactor simulations across a number of different continuous mesh fidelities. The search space of reactor geometries is explored through an amalgam of different, potentially lower, fidelity simulations which are chosen for evaluation based on weighted acquisition function, trading off information gain with cost of simulation. Within our framework we derive a novel criteria for monitoring the progress and dictating the termination of multi-fidelity Bayesian optimization, ensuring a high fidelity solution is returned before experimental budget is exhausted. The class of reactor we investigate are helical-tube reactors under pulsed-flow conditions, which have demonstrated outstanding mixing characteristics, have the potential to be highly parameterized, and are easily manufactured using 3D printing. To validate our results, we 3D print and experimentally validate the optimal reactor geometry, confirming its mixing performance. In doing so we demonstrate our design framework to be extensible to a broad variety of expensive simulation-based optimization problems, supporting the design of the next generation of highly parameterized chemical reactors. Computer science ; Parameterized complexity ; Mixing (physics) ; Chemical reactor ; Fidelity ; Design for manufacturability ; Bayesian optimization ; Nonlinear system ; High fidelity ; Process engineering ; Algorithm ; Mechanical engineering ; Engineering ; Artificial intelligence Machine Learning in Materials Science ; Advanced Control Systems Optimization ; Spectroscopy and Chemometric Analyses