Multi-Field Characterization of Single Wall Nano-Tube Composites for Hydrogen Storage

Author(s):  
John G. Michopoulos ◽  
Sam G. Lambrakos ◽  
Nick E. Tran

The goal of the present work is three fold. Firstly to create the forward continuum model of a multi-species diffusing system under simultaneous presence of chemical reactivity and temperature as the general case of all hydrogen storage systems. Secondly, cast the problem of hydrogen storage in a pragmatic product-design context where the appropriate design parameters of the system are determined via appropriate optimization methods that utilize extensive experimental data encoding the behavior of the system. Thirdly, demonstrate this methodology on characterizing certain systemic parameters. Thus, the context of the work presented is defined by a data-driven characterization of coupled heat and mass diffusion models of hydrogen storage systems from a multiphysics perspective at the macro length scale. In particular, a single wall nanotube (SWNT) based composite is modeled by coupled partial differential equations representing spatio-temporal evolution of distributions of temperature and hydrogen concentration. Analytical solutions of these equations are adopted for an inverse analysis that defines a non-linear optimization problem for determining the parameters of the model by objective function minimization. Experimentally acquired and model produced data are used to construct the system’s objective function. Simulations to demonstrate the applicability of the methodology and a discussion of its potential extension to multi-scale and manufacturing process optimization are also presented.

2014 ◽  
Vol 721 ◽  
pp. 464-467
Author(s):  
Tao Fu ◽  
Qin Zhong Gong ◽  
Da Zhen Wang

In view of robustness of objective function and constraints in robust design, the method of maximum variation analysis is adopted to improve the robust design. In this method, firstly, we analyses the effect of uncertain factors in design variables and design parameters on the objective function and constraints, then calculate maximum variations of objective function and constraints. A two-level optimum mathematical model is constructed by adding the maximum variations to the original constraints. Different solving methods are used to solve the model to study the influence to robustness. As a demonstration, we apply our robust optimization method to an engineering example, the design of a machine tool spindle. The results show that, compared with other methods, this method of HPSO(hybrid particle swarm optimization) algorithm is superior on solving efficiency and solving results, and the constraint robustness and the objective robustness completely satisfy the requirement, revealing that excellent solving method can improve robustness.


2016 ◽  
Vol 328 ◽  
pp. 567-577 ◽  
Author(s):  
S. Börries ◽  
O. Metz ◽  
P.K. Pranzas ◽  
J.M. Bellosta von Colbe ◽  
T. Bücherl ◽  
...  

2008 ◽  
Vol 604-605 ◽  
pp. 87-96 ◽  
Author(s):  
Ignacio Rieiro ◽  
Jesus Castellanos ◽  
Manuel Carsí ◽  
Julio Muñoz ◽  
Oscar A. Ruano

A model for describing the plastic flow has been developed. The model is based on a strain dependent Garofalo equation and predicts the variation with strain of grain size refinement by dynamic recrystallization using non-linear optimization methods. The predictions have been applied to two wrought magnesium alloys, AZ31 and AZ61 and are in good agreement with experimental data.


2018 ◽  
Author(s):  
◽  
Joseph Schaeperkoetter

The automotive industry is already showing signs of moving beyond a century long dependence on petroleum. The tens of billions of dollars in the electric vehicle (EV) consumer market are a powerful demonstration of this transition. Hydrogen fuel cell electric vehicles also offer a clean alternative to petroleum and have advantages to EVs in some transportation sectors. To grow the hydrogen economy, significant progress must be made in hydrogen storage systems. Adsorbent based storage systems have the potential to lower the pressure requirements while simultaneously improving the storage capacity of these systems. The research presented in this dissertation focuses on the development and characterization of new adsorption storage systems based upon modified graphene. Early work involved substitutional doping of activated carbon with boron to alter the surface chemistry of the adsorbing surface with the goal of improving adsorption strength. Boron-doped samples were characterized with X-ray Photoelectron Spectroscopy to correlate specific boron chemistries to adsorption performance metrics. A maximum of 2% substitutional doping was observed. Later work focused on framework materials built up from graphene oxide and benzene diboronic acid (GOFs). GOFs are an ideal material to study the structural response of an adsorbent during adsorption due to their layered structure and relatively well-defined pore geometry. To study GOF's adsorption-induced structural response, we built a computer-controlled gas handing system for in situ neutron diffraction measurements at the University of Missouri Research Reactor. For the first time, supercritical adsorption-induced structural change was observed. Through correlation of adsorption and structural data, we are able to predict the rate of expansion in GOF based on the critical temperature and vdW diameter of the adsorbate molecule.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Giulia Tedeschi ◽  
Lorenzo Scipioni ◽  
Maria Papanikolaou ◽  
Geoffrey W. Abbott ◽  
Michelle A. Digman

AbstractVoltage-gated potassium (Kv) channels are a family of membrane proteins that facilitate K+ ion diffusion across the plasma membrane, regulating both resting and action potentials. Kv channels comprise four pore-forming α subunits, each with a voltage sensing domain, and they are regulated by interaction with β subunits such as those belonging to the KCNE family. Here we conducted a comprehensive biophysical characterization of stoichiometry and protein diffusion across the plasma membrane of the epithelial KCNQ1-KCNE2 complex, combining total internal reflection fluorescence (TIRF) microscopy and a series of complementary Fluorescence Fluctuation Spectroscopy (FFS) techniques. Using this approach, we found that KCNQ1-KCNE2 has a predominant 4:4 stoichiometry, while non-bound KCNE2 subunits are mostly present as dimers in the plasma membrane. At the same time, we identified unique spatio-temporal diffusion modalities and nano-environment organization for each channel subunit. These findings improve our understanding of KCNQ1-KCNE2 channel function and suggest strategies for elucidating the subunit stoichiometry and forces directing localization and diffusion of ion channel complexes in general.


2021 ◽  
pp. 116927
Author(s):  
Bruna de Ramos ◽  
Melanie Vianna Alencar ◽  
Fábio Lameiro Rodrigues ◽  
Ana Luzia de Figueiredo Lacerda ◽  
Maíra Carneiro Proietti

2021 ◽  
Vol 46 (24) ◽  
pp. 13082-13087
Author(s):  
Ki Beom Park ◽  
Tae-Wook Na ◽  
Young Do Kim ◽  
Jae-Young Park ◽  
Jang-Won Kang ◽  
...  

2021 ◽  
pp. 109953
Author(s):  
Hiroyuki Saitoh ◽  
Toyoto Sato ◽  
Mai Tanikami ◽  
Kazutaka Ikeda ◽  
Akihiko Machida ◽  
...  

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