scholarly journals Virtual Experimentations by Deep learning on Tangible Materials

2021 ◽  
Author(s):  
Kenji Hata ◽  
Takashi Honda ◽  
Shun Muroga ◽  
Hideaki Nakajima ◽  
Taiyo Shimizu ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Deep Learning ◽  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Material Science ◽  
Specific Property ◽  
Generative Adversarial Networks ◽  
Structure Property ◽  
Virtual Experiments

Abstract Artificial intelligence is an emerging frontier in material science to discover new materials with targeted properties by an artificial neural network (ANN) constructed from existing structure-property databases. This approach has not been applicable to tangible materials, such as plastic composites, fabrics, and rubbers, because the complexities of their structures cannot be defined. Here we propose a deep learning computational framework that can implement “virtual” experiments on tangible materials (carbon nanotube (CNT) films) where structural representations (scanning electron microscope images at 4 levels of magnifications (x2k, x20k, x50k, x100k)) of the processed material (dispersing and filtering) were created by multiple generative adversarial networks from which an ANN predicted multiple properties (electrical conductivity and specific surface area). 1865 virtual experiments were finished within an hour, a task that would take years for real experiments. The accumulated data can be used as a versatile database for material science, in analogous to databases of molecules and solids used in cheminformatics, as exemplified by investigations of the correlation between the electrical conductivity and specific surface area, wall number phase diagrams, the most economical mixture of CNTs at specific property, and inversely designed CNT supercapacitors.

scholarly journals Virtual experimentations by deep learning on tangible materials

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Takashi Honda ◽  
Shun Muroga ◽  
Hideaki Nakajima ◽  
Taiyo Shimizu ◽  
Kazufumi Kobashi ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Deep Learning ◽  
Surface Area ◽  
Structural Complexity ◽  
Generative Adversarial Networks ◽  
Structure Property ◽  
Computational Framework ◽  
Virtual Experiments ◽  
Adversarial Networks ◽  
Four Levels

AbstractArtificial intelligence relying on structure-property databases is an emerging powerful tool to discover new materials with targeted properties. However, this approach cannot be easily applied to tangible structures, such as plastic composites and fabrics, because of their high structural complexity. Here, we propose a deep learning computational framework that can implement virtual experiments on tangible structures. Structural representations of complex carbon nanotube films were conducted by multiple generative adversarial networks of scanning electron microscope images at four levels of magnifications, enabling a deep learning prediction of multiple properties such as electrical conductivity and surface area. 1716 virtual experiments were completed within an hour, a task that would take years for real experiments. The data can be used as a versatile database for material science, in analogy to databases of molecules and solids used in cheminformatics. Useful examples are the investigation of correlations between electrical conductivity, specific surface area, wall number phase diagrams, economic performance, and inversely designed supercapacitors.

scholarly journals Carbon fibers derived from pure alkali lignin fibers through electrospinning with carbonization

BioResources ◽  
2020 ◽  
Vol 15 (2) ◽  
pp. 2412-2427
Author(s):  
Tunnapat Worarutariyachai ◽  
Surawut Chuangchote
Keyword(s):  
Electrical Conductivity ◽  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Carbon Fibers ◽  
Smooth Surface ◽  
Synthetic Polymer ◽  
Inorganic Salts ◽  
Alkali Lignin ◽  
Surface Tension Reduction

Alkali lignin (AL) fibers with a smooth surface and fine morphological appearance were successfully produced via electrospinning using a simple heated single spinneret system, instead of typical electrospinning of lignin with added synthetic polymer blends or conventional co-axial electrospinning. To reduce the size of the fibers, glycerol was added to the spinning solution as a co-solvent for surface tension reduction and electrospinnability improvement. After electrospinning, stabilization and carbonization were subsequently performed to convert AL fibers to carbon fibers (CFs). The obtained CFs displayed rough and uneven surfaces. However, the CFs derived from glycerol-added solution showed greater electrical conductivity, specific surface area, and porosity compared with those from pure AL solution. Furthermore, the results indicated that the inorganic salts on the rough surface of CFs were successfully removed by sulfuric acid (H2SO4) washing. After H2SO4 washing, the CFs revealed a smoother surface and higher electrical conductivity, specific surface area, and porosity.

Simulated electrical conductivity response of clogging mechanisms for managed aquifer recharge

Geophysics ◽  
2014 ◽  
Vol 79 (2) ◽  
pp. D81-D89 ◽  
Author(s):  
A. Rowan Cockett ◽  
Adam Pidlisecky
Keyword(s):  
Electrical Conductivity ◽  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Film Growth ◽  
Volume Fraction ◽  
Pore Space ◽  
Managed Aquifer Recharge ◽  
Aquifer Recharge ◽  
Conductive Film

Motivated by the need for improved understanding and monitoring of clogging during managed aquifer recharge, we use numerical experiments to evaluate the effect of three different clogging mechanisms on electrical conductivity (EC), porosity, specific surface area, and electrical tortuosity of a simulated sediment pack. The clogging experiments are designed to simulate effect of clogging due to: (a) addition of finer grains, (b) addition of nonconductive films, and (c) addition of conductive films. The simulations involved starting with a random grain pack of 43% porosity, and subsequently reducing the porosity as would occur during clogging. For each of the experiments, we compute the EC response, specific surface area, and electrical tortuosity across the range of porosities. The differences in EC response between (a) and (b) is minor, however, the sediment parameters measuring pore-space configuration show very different responses (i.e., specific surface area and tortuosity), indicating EC is limited in its sensitivity to specific pore configurations. The results from simulations (a) and (b) are well described by Archie’s equation. For the conductive film experiments (c), we explore the effect of film growth for four different surface conductivities ranging from [Formula: see text] to [Formula: see text]. These conductivities correspond to a range of 5–35 times more conductive than the pore fluid conductivity. The bulk EC signal for each of the films results in a distinct manifestation in terms of measured bulk EC. We fit the EC response of the conductive film experiments with a model based on volume fraction occupied by the film; although the model fit the observed results, we required a unique set of fitting parameters for each Film conductivity.

scholarly journals Enhanced capacitive performance by improving the graphitized structure in carbon aerogel microspheres

RSC Advances ◽  
2020 ◽  
Vol 10 (37) ◽  
pp. 22242-22249
Author(s):  
Xichuan Liu ◽  
Lei Yuan ◽  
Minglong Zhong ◽  
Shuang Ni ◽  
Fan Yang ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
High Temperature ◽  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Carbon Aerogel ◽  
High Specific Surface Area ◽  
Activation Method ◽  
Carbon Aerogels ◽  
Capacitive Performance

Carbon aerogels (CAs) microspheres with good electrical conductivity and high specific surface area were synthesized by high temperature carbonization and CO2 activation method, which exhibit an enhanced capacitive performance in supercapacitors.

scholarly journals Modification of carbon felt anodes using double-oxidant HNO3/H2O2 for application in microbial fuel cells

RSC Advances ◽  
2018 ◽  
Vol 8 (4) ◽  
pp. 2059-2064 ◽  
Author(s):  
Yu Zhao ◽  
Yan Ma ◽  
Ting Li ◽  
Zhishuai Dong ◽  
Yuxue Wang
Keyword(s):  
Electrical Conductivity ◽  
Fuel Cells ◽  
Specific Surface ◽  
Surface Area ◽  
Anode Material ◽  
Specific Surface Area ◽  
Microbial Fuel Cells ◽  
Low Cost ◽  
High Specific Surface Area ◽  
Carbon Felt

Carbon felt is widely used as an anode material in microbial fuel cells (MFCs) because of its high specific surface area, low cost, good electrical conductivity, and biocompatibility.

scholarly journals Effect of Sb-Doped SnO2 Nanostructures on Electrocatalytic Performance of a Pt Catalyst for Methanol Oxidation Reaction

Catalysts ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 866
Author(s):  
Seul-Gi Lee ◽  
Sang-Beom Han ◽  
Woo-Jun Lee ◽  
Kyung-Won Park
Keyword(s):  
Electrical Conductivity ◽  
Specific Surface ◽  
Surface Area ◽  
Methanol Oxidation ◽  
Specific Surface Area ◽  
Oxidation Reaction ◽  
Direct Methanol Fuel Cells ◽  
Pt Catalyst ◽  
Methanol Oxidation Reaction ◽  
Sno2 Nanostructures

In this study, antimony-doped tin oxide (ATO) support materials for a Pt anode catalyst in direct methanol fuel cells were prepared and electrochemically evaluated. When the heating temperature was increased from 300 to 400 °C, the ATO samples exhibited a slightly decreased specific surface area and increased electrical conductivity. In particular, the ATO sample heated at 350 °C in an air atmosphere showed improved electrical conductivity (1.3 S cm−1) with an optimum specific surface area of ~34 m2 g−1. The supported Pt catalysts were synthesized using a polyol process with as-prepared and heated ATO samples and Vulcan XC-72R as supports (denoted as Pt/ATO, Pt/ATO-350, and Pt/C, respectively). In the methanol oxidation reaction (MOR), compared to Pt/C and Pt/ATO, Pt/ATO-350 exhibited the best electrocatalytic activity and stability for MOR, which could be attributed to Pt nanoparticles on the relatively stable oxide support with high electrical conductivity and interaction between the Pt catalyst and the heated ATO support.

scholarly journals Synthesis of Monolithic TiO2 Aerogels With Relatively Low Shrinkage and Improved Formability Assisted by CTAB

2021 ◽  
Vol 8 ◽  
Author(s):  
Tingting Niu ◽  
Bin Zhou ◽  
Zehui Zhang ◽  
Jianming Yang ◽  
Xiujie Ji ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Sol Gel ◽  
Supercritical Drying ◽  
High Specific Surface Area ◽  
Structure Property ◽  
Surface Areas ◽  
Polycondensation Process

Monolithic TiO2 aerogels without severe shrink were obtained by the sol-gel method with the addition of the surfactant cetyltrimethylammonium bromide (CTAB) to control the hydrolysis and polycondensation process and acetonitrile solvent as the solvent to improve the crystallinity. After CO2 supercritical drying, the shrinkage ratio of monolithic TiO2 aerogels modified by CTAB decreased by up to ∼26.9%, compared with the pure TiO2 aerogel. Their apparent densities were all lower than 300 g/cm3. X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), Fourier Transform infrared spectroscopy (FTIR) and BET Specific Surface Area Analysis were used to analyze the as-synthesized samples. The results revealed that all the samples were anatase-TiO2 phase with nanoporous network structures. The specific surface areas reached 250.2 m2/g confirmed by the BET (Brunaur–Emmett–Teller method) analysis. However, TiO2 aerogels without the addition of CTAB showed evident agglomeration and collapse of the network in comparison with CTAB-added samples. To further study the structure-property relationship, the photocatalysis performance of as-synthesized and 300°C-calcined aerogels was carried out contrastively. Interestingly, the influences of the CTAB adding amount of as-synthesized and calcined TiO2 aerogels are negative and positive, respectively, which is probably due to the synergistic effect of CTAB hindrance and grain refinement. Potentially, This kind of TiO2 aerogels assisted by CATB with low density, small shrinkage, improved formability, high specific surface area and fine crystalline grain may be applied in various applications, such as electrochemistry, photocatalysis, etc.

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