Characterization methods and modelling for Li-ion batteries: entropy, impedance, pressure, diffusivity & temperature swings induced aging

Lithium-ion batteries are commonly used for energy storage systems, and temperature is one key impact factor on the cell performance and lifetime. In literature, the focus has been on the ambient temperature of the test condition, and there is little discussion about how the temperature swing during cycling affects the battery lifetime. In this study, lithium-ion cells are cycled with the same current but different temperature swings for more than two years. The results show that the cells cycled with a high temperature swing aged faster. Moreover, pure thermal cycling does not introduce significant aging to the cell.During the study, a series of characterization methods were also developed, including a physics-based circuit model, a convenient method to measure the entropic coefficient, an on-line impedance measurement technique, an effective reference performance test procedure, and methods to measure the cellpressure and thickness change during cycling. A selection of results are that the physics-based circuit model could predict key quantities, such as overpotential, concentrations etc., with less than 0.05% deviation compared with a state-of-art model. Furthermore, the on-line impedance measurement technique managed to extract the battery pack impedance between 0.01 Hz and 5 Hz based on CAN signals. In addition, the cell pressure and thickness change during cycling of a commercial cell were found to be up to 60 kPa and 150 μm

Physical Models of Tissue in Shear Fields11This article is dedicated to our friend and colleague, Robert C. Waag.

AbstractThis review considers three general classes of physical as opposed to phenomenological models of the shear elasticity of tissues. The first is simple viscoelasticity. This model has a special role in elastography because it is the language in which experimental and clinical data are communicated. The second class of models involves acoustic relaxation, in which the medium contains inner time-dependent systems that are driven through the external bulk medium. Hysteresis, the phenomenon characterizing the third class of models, involves losses that are related to strain rather than time rate of change of strain. In contrast to the vast efforts given to tissue characterization through their bulk moduli over the last half-century, similar research using low-frequency shear data is in its infancy. Rather than a neat summary of existing facts, this essay is a framework for hypothesis generation—guessing what physical mechanisms give tissues their shear properties

Analysis of Nanopore Detector Measurements using Machine Learning Methods, with Application to Single-Molecule Kinetics

At its core, a nanopore detector has a nanometer-scale biological membrane across which a voltage is applied. The voltage draws a DNA molecule into an á-hemolysin channel in the membrane. Consequently, a distinctive channel current blockade signal is created as the molecule flexes and interacts with the channel. This flexing of the molecule is characterized by different blockade levels in the channel current signal. Previous experiments have shown that a nanopore detector is sufficiently sensitive such that nearly identical DNA molecules were classified successfully using machine learning techniques such as Hidden Markov Models and Support Vector Machines in a channel current based signal analysis platform [4-9]. In this paper, methods for improving feature extraction are presented to improve both classification and to provide biologists and chemists with a better understanding of the physical properties of a given molecule

Mechanics Of Fluctuating Elastic Plates And Fiber Networks

Lipid membranes and fiber networks in biological systems perform important mechanical functions at the cellular and tissue levels. In this thesis I delve into two detailed problems -- thermal fluctuation of membranes and non-linear compression response of fiber networks. Typically, membrane fluctuations are analysed by decomposing into normal modes or by molecular simulations. In the first part of my thesis, I propose a new semi-analytic method to calculate the partition function of a membrane. The membrane is viewed as a fluctuating von Karman plate and discretized into triangular elements. Its energy is expressed as a function of nodal displacements, and then the partition function and co-variance matrix are computed using Gaussian integrals. I recover well-known results for the dependence of the projected area of a lipid bilayer membrane on the applied tension, and recent simulation results on the ependence of membrane free energy on geometry, spontaneous curvature and tension. As new applications I use this technique to study a membrane with heterogeneity and different boundary conditions. I also use this technique to study solid membranes by taking account of the non-linear coupling of in-plane strains with out-of-plane deflections using a penalty energy, and apply it to graphene, an ultra-thin two-dimensional solid. The scaling of graphene fluctuations with membrane size is recovered. I am able to capture the dependence of the thermal expansion coefficient of graphene on temperature. Next, I study curvature mediated interactions between inclusions in membranes. I assume the inclusions to be rigid, and show that the elastic and entropic forces between them can compete to yield a local maximum in the free energy if the membrane bending modulus is small. If the spacing between the inclusions is less than this local maximum then the attractive entropic forces dominate and the separation between the inclusions will be determined by short range interactions; if the spacing is more than the local maximum then the elastic repulsive forces dominate and the inclusions will move further apart. This technique can be extended to account for entropic effects in other methods which rely on quadratic energies to study the interactions of inclusions in membranes. In the second part of this thesis I study the compression response of two fiber network materials -- blood clots and carbon nanotube forests. The stress-strain curve of both materials reveals four characteristic regions, for compression-decompression: 1) linear elastic region; 2) upper plateau or softening region; 3) non-linear elastic region or re-stretching of the network; 4) lower plateau in which dissociation of some newly made connections occurs. This response is described by a phase transition based continuum model. The model is inspired by the observation of one or more moving interfaces across which densified and rarefied phases of fibers co-exist. I use a quasi-static version of the Abeyaratne-Knowles theory of phase transitions for continua with a stick-slip type kinetic law and a nucleation criterion based on the critical stress for buckling to describe the formation and motion of these interfaces in uniaxial compression experiments. Our models could aid the design of biomaterials and carbon nanotube forests to have desired mechanical properties and guide further understanding of their behavior under large deformations

Technical and economic feasibility of centralized facilities for solar hydrogen production via photocatalysis and photoelectrochemistry

Photoelectrochemical water splitting is a promising route for the renewable production of hydrogen fuel. This work presents the results of a technical and economic feasibility analysis conducted for four hypothetical, centralized, large-scale hydrogen production plants based on this technology. The four reactor types considered were a single bed particle suspension system, a dual bed particle suspension system, a fixed panel array, and a tracking concentrator array. The current performance of semiconductor absorbers and electrocatalysts were considered to compute reasonable solar-to-hydrogen conversion efficiencies for each of the four systems. The U.S. Department of Energy H2A model was employed to calculate the levelized cost of hydrogen output at the plant gate at 300 psi for a 10 tonne per day production scale. All capital expenditures and operating costs for the reactors and auxiliaries (compressors, control systems, etc.) were considered. The final cost varied from $1.60–$10.40 per kg H2 with the particle bed systems having lower costs than the panel-based systems. However, safety concerns due to the cogeneration of O_2 and H_2 in a single bed system and long molecular transport lengths in the dual bed system lead to greater uncertainty in their operation. A sensitivity analysis revealed that improvement in the solar-to-hydrogen efficiency of the panel-based systems could substantially drive down their costs. A key finding is that the production costs are consistent with the Department of Energy's targeted threshold cost of $2.00–$4.00 per kg H_2 for dispensed hydrogen, demonstrating that photoelectrochemical water splitting could be a viable route for hydrogen production in the future if material performance targets can be met