Thermodynamically consistent derivation of chemical potential of a battery solid particle from the regular solution theory applied to LiFePO4.
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ABSTRACT:
SUBMITTER: Zelic K
PROVIDER: S-EPMC6375981 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Lithium-ion batteries are essential for electric vehicles and energy storage devices. With the increasing demand for their production and the concomitant surge in waste generation, the need for an efficient and environmentally friendly recycling process has become imperative. This work presents a new approach for recycling of metals from the LiFePO4 (LFP) cathode material. The cathode material was first leached by a HCl solution without an oxidizing agent. Subsequently, an ionic-liquid-based aqueous biphasic system (IL-based ABS) was used for the separation of lithium and iron from leachate solutions, followed by a precipitation process. The influence of the acid concentration, solid-to-liquid ratio and leaching time on the leaching yield was investigated. UV-vis absorption spectra revealed the presence of mixed-valent iron in the leachate, with 83 ± 1% Fe(ii) and 17 ± 1% Fe(iii). The ABS systems comprised tributyltetradecylphosphonium chloride [P44414]Cl and a salting-out agent (HCl or NaCl). The extraction percentage of iron reached 90% and less than 1% of lithium was extracted under the studied optimal conditions. Further enhancement of iron extraction, reaching 98%, was achieved via a two-stage cross-current extraction process. Iron was precipitated from the loaded IL phase with an efficiency of 97% as Fe(OH)2 and Fe(OH)3, using an aqueous ammonia solution. Lithium was precipitated as Li3PO4 with a lithium purity of 99.5% by adding K3PO4 solution. The ionic liquid used in the process was efficiently regenerated and used in four extraction cycles with no activity decline, with an extraction percentage of 90% of iron in each cycle.
| S-EPMC10949915 | biostudies-literature
Project description:BackgroundThe dynamics of biochemical reaction systems are constrained by the fundamental laws of thermodynamics, which impose well-defined relationships among the reaction rate constants characterizing these systems. Constructing biochemical reaction systems from experimental observations often leads to parameter values that do not satisfy the necessary thermodynamic constraints. This can result in models that are not physically realizable and may lead to inaccurate, or even erroneous, descriptions of cellular function.ResultsWe introduce a thermodynamically consistent model calibration (TCMC) method that can be effectively used to provide thermodynamically feasible values for the parameters of an open biochemical reaction system. The proposed method formulates the model calibration problem as a constrained optimization problem that takes thermodynamic constraints (and, if desired, additional non-thermodynamic constraints) into account. By calculating thermodynamically feasible values for the kinetic parameters of a well-known model of the EGF/ERK signaling cascade, we demonstrate the qualitative and quantitative significance of imposing thermodynamic constraints on these parameters and the effectiveness of our method for accomplishing this important task. MATLAB software, using the Systems Biology Toolbox 2.1, can be accessed from http://www.cis.jhu.edu/~goutsias/CSS lab/software.html. An SBML file containing the thermodynamically feasible EGF/ERK signaling cascade model can be found in the BioModels database.ConclusionsTCMC is a simple and flexible method for obtaining physically plausible values for the kinetic parameters of open biochemical reaction systems. It can be effectively used to recalculate a thermodynamically consistent set of parameter values for existing thermodynamically infeasible biochemical reaction models of cellular function as well as to estimate thermodynamically feasible values for the parameters of new models. Furthermore, TCMC can provide dimensionality reduction, better estimation performance, and lower computational complexity, and can help to alleviate the problem of data overfitting.
| S-EPMC3117730 | biostudies-literature
Project description:The requirement of energy-storage equipment needs to develop the lithium ion battery (LIB) with high electrochemical performance. The surface modification of commercial LiFePO4 (LFP) by utilizing zeolitic imidazolate frameworks-8 (ZIF-8) offers new possibilities for commercial LFP with high electrochemical performances. In this work, the carbonized ZIF-8 (CZIF-8) was coated on the surface of LFP particles by the in situ growth and carbonization of ZIF-8. Transmission electron microscopy indicates that there is an approximate 10 nm coating layer with metal zinc and graphite-like carbon on the surface of LFP/CZIF-8 sample. The N2 adsorption and desorption isotherm suggests that the coating layer has uniform and simple connecting mesopores. As cathode material, LFP/CZIF-8 cathode-active material delivers a discharge specific capacity of 159.3 mAh g-1 at 0.1C and a discharge specific energy of 141.7 mWh g-1 after 200 cycles at 5.0C (the retention rate is approximate 99%). These results are attributed to the synergy improvement of the conductivity, the lithium ion diffusion coefficient, and the degree of freedom for volume change of LFP/CZIF-8 cathode. This work will contribute to the improvement of the cathode materials of commercial LIB.
| S-EPMC6199046 | biostudies-literature
Project description:Open-circuit voltage (OCV) models as a function of state-of-charge (SOC) are fundamental to modeling the performance of batteries. The second law of thermodynamics enforces that the OCV should be monotonic with respect to the SOC. In this Perspective, we first review some of the currently popular empirical OCV fitting methods which compromise thermodynamics for the flexibility of empirical fitting. We propose a simple thermodynamically consistent OCV model enabled by differentiable thermodynamic modeling, which obeys the second law of thermodynamics. We cast the common-tangent condition derived from the second law of thermodynamics as a fixed-point solving problem and use implicit function theorem to enable efficient gradient-based parameters optimization. We demonstrate this on the OCV of 12 popular electrode materials, and this is integrated with open-source battery modeling software PyBaMM. We perform pseudo-2D discharge simulations to show the seamless integration of the above OCV models with battery modeling software. Given the simplicity of integration and implementation, we believe that thermodynamically consistent OCV models should be a requirement for future Li-ion battery models.
| S-EPMC10839898 | biostudies-literature
Project description:Rechargeable lithium-ion batteries (LIBs) have a wide range of applications but face challenges in harsh working or operating environments at high temperatures. In this work, a solid polymer electrolyte with MWCNT-COOH as an additive (MWCNT-SPE) was obtained. MWCNT-SPE has a high thermal stability and can be used in high-temperature operating environments. Solid-state lithium batteries based on MWCNT-SPE and LiFePO4 were assembled. The resulting lithium batteries exhibited excellent electrochemical properties at 70 and 120 °C, demonstrating a wide range of operations suitable for solid-state batteries with extreme demands. The symmetrical Li/MWCNT-SPE/Li cell operated for 1800 h with low polarization voltage and no short circuit, and the LiFePO4/MWCNT-SPE/Li cell delivered superior cycling performance under both 0.2 and 0.5 C-rates, indicating that the interface compatibility between the lithium metal and MWCNT-SPE membrane was good and could effectively suppress the formation of lithium dendrites. The superior performance of the resulting MWCNT-SPE was due to the weak interaction between PEO, PVDF-HFP, and MWCNT-COOH, which reduced the tendency of PEO's crystallinity and thereby significantly increased the Li+ migration ability and improved the cycling life of the batteries.
| S-EPMC8567355 | biostudies-literature
Project description:Lithium battery materials can be advantageously used for the selective sequestration of lithium ions from natural resources, which contain other cations in high excess. However, for practical applications, this new approach for lithium production requires the battery host materials to be stable over many cycles while retaining the high lithium selectivity. Here, a nearly symmetrical cell design was employed to show that LiFePO4 shows good capacity retention with cycling in artificial lithium brines representative of brines from Chile, Bolivia and Argentina. A quantitative correlation was identified between brine viscosity and capacity degradation, and for the first time it was demonstrated that the dilution of viscous brines with water significantly enhanced capacity retention and rate capability. The electrochemical and X-ray diffraction characterisation of the cycled electrodes also showed that the high lithium selectivity was preserved with cycling. Raman spectra of the cycled electrodes showed no signs of degradation of the carbon coating of LiFePO4 , while scanning electron microscopy images showed signs of particle cracking, thus pointing towards interfacial reactions as the cause of capacity degradation.
| S-EPMC9299151 | biostudies-literature
Project description:BackgroundEstimating the rate constants of a biochemical reaction system with known stoichiometry from noisy time series measurements of molecular concentrations is an important step for building predictive models of cellular function. Inference techniques currently available in the literature may produce rate constant values that defy necessary constraints imposed by the fundamental laws of thermodynamics. As a result, these techniques may lead to biochemical reaction systems whose concentration dynamics could not possibly occur in nature. Therefore, development of a thermodynamically consistent approach for estimating the rate constants of a biochemical reaction system is highly desirable.ResultsWe introduce a Bayesian analysis approach for computing thermodynamically consistent estimates of the rate constants of a closed biochemical reaction system with known stoichiometry given experimental data. Our method employs an appropriately designed prior probability density function that effectively integrates fundamental biophysical and thermodynamic knowledge into the inference problem. Moreover, it takes into account experimental strategies for collecting informative observations of molecular concentrations through perturbations. The proposed method employs a maximization-expectation-maximization algorithm that provides thermodynamically feasible estimates of the rate constant values and computes appropriate measures of estimation accuracy. We demonstrate various aspects of the proposed method on synthetic data obtained by simulating a subset of a well-known model of the EGF/ERK signaling pathway, and examine its robustness under conditions that violate key assumptions. Software, coded in MATLAB®, which implements all Bayesian analysis techniques discussed in this paper, is available free of charge at http://www.cis.jhu.edu/~goutsias/CSS%20lab/software.html.ConclusionsOur approach provides an attractive statistical methodology for estimating thermodynamically feasible values for the rate constants of a biochemical reaction system from noisy time series observations of molecular concentrations obtained through perturbations. The proposed technique is theoretically sound and computationally feasible, but restricted to quantitative data obtained from closed biochemical reaction systems. This necessitates development of similar techniques for estimating the rate constants of open biochemical reaction systems, which are more realistic models of cellular function.
| S-EPMC3248051 | biostudies-literature
Project description:For the successful use of lithium-ion batteries in automotive applications, reliable availability of high storage capacity and very short recharging times are essential. In order to develop the perfect battery for a certain application, structure-property relationships of each active material must be fully understood. LiFePO4 is of great interest due to its fast-charging capability and high stability regarding its thermal resistance and chemical reactivity. The anisotropic lithium-ion diffusion through the LiFePO4 crystal structure indicates a strong dependence of the electrochemical performance of a nanostructured active material on particle morphology. In this paper, the relationship of the particle morphology and fast-charging capability of LiFePO4/C core/shell nanoparticles in half-cells was studied. For this purpose, a new multistep synthesis strategy was developed. It involves the combination of a solvothermal synthesis followed by an in situ polymer coating and thermal calcination step. Monodisperse rodlike LiFePO4 nanoparticles with comparable elongation along the b-axis (30-50 nm) and a varying aspect ratio c/a (2.4-6.9) were obtained. A strong correlation of the fast-charging capability with the aspect ratio c/a was observed. When using LiFePO4 nanoparticles with the smallest aspect ratio c/a, the best electrochemical performance was received regarding the specific capacity at high C-rates and the cycling stability. A reduction of the aspect ratio c/a by 30% (3.6 to 2.4) was found to enhance the charge capacity at 10 C up to an order of magnitude (7.4-73 mA h·g-1).
| S-EPMC8459431 | biostudies-literature
Project description:The aim of this work is to incorporate cooperativity into Huxley-type cross-bridge model in thermodynamically consistent way. While the Huxley-type models assume that cross-bridges act independently from each other, we take into account that each cross-bridge is influenced by its neighbors and cooperativity is induced by tropomyosin movement. For that, we introduce ensembles of cross-bridge groups connected by elastic tropomyosin. By taking into account that the mechanical displacement of tropomyosin induces free energy change of the cross-bridge group ensemble, we develop the formalism for thermodynamically consistent description of the cooperativity in muscle contraction. An example model was composed to test the approach. The model parameters were found by optimization from the linear relation between oxygen consumption and stress-strain area as well as experimentally measured stress dynamics of rat trabecula. We have found a good agreement between the optimized model solution and experimental data. Simulations also showed that it is possible to study cooperativity with the approach developed in this work.
| S-EPMC4567334 | biostudies-literature
Project description:The principal pacemaker of the circadian clock of the cyanobacterium S. elongatus is a protein phosphorylation cycle consisting of three proteins, KaiA, KaiB and KaiC. KaiC forms a homohexamer, with each monomer consisting of two domains, CI and CII. Both domains can bind and hydrolyze ATP, but only the CII domain can be phosphorylated, at two residues, in a well-defined sequence. While this system has been studied extensively, how the clock is driven thermodynamically has remained elusive. Inspired by recent experimental observations and building on ideas from previous mathematical models, we present a new, thermodynamically consistent, statistical-mechanical model of the clock. At its heart are two main ideas: i) ATP hydrolysis in the CI domain provides the thermodynamic driving force for the clock, switching KaiC between an active conformational state in which its phosphorylation level tends to rise and an inactive one in which it tends to fall; ii) phosphorylation of the CII domain provides the timer for the hydrolysis in the CI domain. The model also naturally explains how KaiA, by acting as a nucleotide exchange factor, can stimulate phosphorylation of KaiC, and how the differential affinity of KaiA for the different KaiC phosphoforms generates the characteristic temporal order of KaiC phosphorylation. As the phosphorylation level in the CII domain rises, the release of ADP from CI slows down, making the inactive conformational state of KaiC more stable. In the inactive state, KaiC binds KaiB, which not only stabilizes this state further, but also leads to the sequestration of KaiA, and hence to KaiC dephosphorylation. Using a dedicated kinetic Monte Carlo algorithm, which makes it possible to efficiently simulate this system consisting of more than a billion reactions, we show that the model can describe a wealth of experimental data.
| S-EPMC5371392 | biostudies-literature