Predicting the state of charge and health of batteries using data-driven machine learning

Machine learning is a specific application of artificial intelligence that allows computers to learn and improve from data and experience via sets of algorithms, without the need for reprogramming. In the field of energy storage, machine learning has recently emerged as a promising modelling approach to determine the state of charge, state of health and remaining useful life of batteries. First, we review the two most studied types of battery models in the literature for battery state prediction: the equivalent circuit and physics-based models. Based on the current limitations of these models, we showcase the promise of various machine learning techniques for fast and accurate battery state prediction. Finally, we highlight the major challenges involved, especially in accurate modelling over length and time, performing in situ calculations and high-throughput data generation. Overall, this work provides insights into real-time, explainable machine learning for battery production, management and optimization in the future

Robust optimization of multilayer conductors of HTS AC cable using PSO and perturbation analysis

For a High Temperature Superconducting (HTS) cable, a non-uniform AC current distribution among the multilayer conductors gives rise to increased AC losses. To get a uniform current distribution among the multilayer conductors, a constrained optimization model is constructed with continuous and discrete variables, such as the winding angle, radius and the winding direction of each layer. Under the constraints of the mechanical properties and critical current of the tape, the Particle Swarm Optimization (PSO) algorithm is employed for structural parameter optimization in both warm and cold dielectric type HTS cables. A uniform current distribution among layers is realized by optimizing the structural parameters. The perturbation analysis is employed to evaluate the parameters after optimization. It is found that the robust stabilizations are different among the various optimal results. The PSO is proved to be a more powerful tool than the Genetic Algorithm (GA) for structural parameter optimization. © 2006 IEEE

Effect of the filament discharge current on the microstructure and performance of plasma-enhanced magnetron sputtered TiN coatings

© 2017 Elsevier B.V. Titanium nitride (TiN) coatings were synthesized by plasma-enhanced magnetron sputtering (PEMS) on 316L austenitic stainless steel and YG8 cemented carbide substrates. The plasma enhancement process involved the use of hot filaments as additional sources of electrons for the magnetron discharge. The structural, morphology, crystallinity, thickness, abrasion resistance and adhesion of the TiN coatings, as well as the nanohardness and Young's modulus were investigated at different filament discharge currents. The results showed that with increasing discharge current, the deposition rate of the coating decreased, the structural morphology of the TiN coatings became finer and denser and the columnar grain size decreased. The critical load for failure in scratch adhesion tests of the coatings on stainless steel and YG8 substrates were over 22 N and 141 N, respectively. The nanohardness and Young's modulus both improved significantly from 8 GPa and 200 GPa to 38 GPa and 500 GPa, respectively, after the discharge current increased from 6 A up to 12 A. The adhesion and the abrasion resistance of the coating on cemented carbide increased, and those on stainless steel decreased, with increasing filament discharge current. It was found that matching the Young's modulus of the coating to that of the substrate was important to improve the adhesion and abrasion resistance of the coating. The results demonstrate that TiN coatings can be prepared by PEMS at appropriate filament discharge currents, resulting in coatings with uniform thickness, dense structure and high hardness, abrasion resistance and adhesion

Photobacterium profundum under Pressure:A MS-Based Label-Free Quantitative Proteomics Study

Photobacterium profundum SS9 is a Gram-negative bacterium, originally collected from the Sulu Sea. Its genome consists of two chromosomes and a 80 kb plasmid. Although it can grow under a wide range of pressures, P. profundum grows optimally at 28 MPa and 15°C. Its ability to grow at atmospheric pressure allows for both easy genetic manipulation and culture, making it a model organism to study piezophily. Here, we report a shotgun proteomic analysis of P. profundum grown at atmospheric compared to high pressure using label-free quantitation and mass spectrometry analysis. We have identified differentially expressed proteins involved in high pressure adaptation, which have been previously reported using other methods. Proteins involved in key metabolic pathways were also identified as being differentially expressed. Proteins involved in the glycolysis/gluconeogenesis pathway were up-regulated at high pressure. Conversely, several proteins involved in the oxidative phosphorylation pathway were up-regulated at atmospheric pressure. Some of the proteins that were differentially identified are regulated directly in response to the physical impact of pressure. The expression of some proteins involved in nutrient transport or assimilation, are likely to be directly regulated by pressure. In a natural environment, different hydrostatic pressures represent distinct ecosystems with their own particular nutrient limitations and abundances. However, the only variable considered in this study was atmospheric pressure

Photodisintegration of 4^4He into p+t

The two-body photodisintegration of $^4$He into a proton and a triton has been studied using the CEBAF Large-Acceptance Spectrometer (CLAS) at Jefferson Laboratory. Real photons produced with the Hall-B bremsstrahlung-tagging system in the energy range from 0.35 to 1.55 GeV were incident on a liquid $^4$He target. This is the first measurement of the photodisintegration of $^4$He above 0.4 GeV. The differential cross sections for the $\gamma$$^4$He$\to pt$ reaction have been measured as a function of photon-beam energy and proton-scattering angle, and are compared with the latest model calculations by J.-M. Laget. At 0.6-1.2 GeV, our data are in good agreement only with the calculations that include three-body mechanisms, thus confirming their importance. These results reinforce the conclusion of our previous study of the three-body breakup of $^3$He that demonstrated the great importance of three-body mechanisms in the energy region 0.5-0.8 GeV .Comment: 13 pages submitted in one tgz file containing 2 tex file and 22 postscrip figure

Exclusive ρ0\rho^0 electroproduction on the proton at CLAS

The $e p\to e^\prime p \rho^0$ reaction has been measured, using the 5.754 GeV electron beam of Jefferson Lab and the CLAS detector. This represents the largest ever set of data for this reaction in the valence region. Integrated and differential cross sections are presented. The $W$, $Q^2$ and $t$ dependences of the cross section are compared to theoretical calculations based on $t$-channel meson-exchange Regge theory on the one hand and on quark handbag diagrams related to Generalized Parton Distributions (GPDs) on the other hand. The Regge approach can describe at the $\approx$ 30% level most of the features of the present data while the two GPD calculations that are presented in this article which succesfully reproduce the high energy data strongly underestimate the present data. The question is then raised whether this discrepancy originates from an incomplete or inexact way of modelling the GPDs or the associated hard scattering amplitude or whether the GPD formalism is simply inapplicable in this region due to higher-twists contributions, incalculable at present.Comment: 29 pages, 29 figure

First Measurement of Beam-Recoil Observables Cx and Cz in Hyperon Photoproduction

Spin transfer from circularly polarized real photons to recoiling hyperons has been measured for the reactions $\vec\gamma + p \to K^+ + \vec\Lambda$ and $\vec\gamma + p \to K^+ + \vec\Sigma^0$. The data were obtained using the CLAS detector at Jefferson Lab for center-of-mass energies $W$ between 1.6 and 2.53 GeV, and for $-0.85<\cos\theta_{K^+}^{c.m.}< +0.95$. For the $\Lambda$, the polarization transfer coefficient along the photon momentum axis, $C_z$, was found to be near unity for a wide range of energy and kaon production angles. The associated transverse polarization coefficient, $C_x$, is smaller than $C_z$ by a roughly constant difference of unity. Most significantly, the {\it total} $\Lambda$ polarization vector, including the induced polarization $P$, has magnitude consistent with unity at all measured energies and production angles when the beam is fully polarized. For the $\Sigma^0$ this simple phenomenology does not hold. All existing hadrodynamic models are in poor agreement with these results.Comment: 28 pages, 18 figures, Submitted to Physical Review

Synthesis, Biological Evaluation and Mechanism Studies of Deoxytylophorinine and Its Derivatives as Potential Anticancer Agents

Previous studies indicated that (+)-13a-(S)-Deoxytylophorinine (1) showed profound anti-cancer activities both in vitro and in vivo and could penetrate the blood brain barrier to distribute well in brain tissues. CNS toxicity, one of the main factors to hinder the development of phenanthroindolizidines, was not obviously found in 1. Based on its fascinating activities, thirty-four derivatives were designed, synthesized; their cytotoxic activities in vitro were tested to discover more excellent anticancer agents. Considering the distinctive mechanism of 1 and interesting SAR of deoxytylophorinine and its derivatives, the specific impacts of these compounds on cellular progress as cell signaling transduction pathways and cell cycle were proceeded with seven representative compounds. 1 as well as three most potent compounds, 9, 32, 33, and three less active compounds, 12, 16, 35, were selected to proform this study to have a relatively deep view of cancer cell growth-inhibitory characteristics. It was found that the expressions of phospho-Akt, Akt, phospho-ERK, and ERK in A549 cells were greater down-regulated by the potent compounds than by the less active compounds in the Western blot analysis. To the best of our knowledge, this is the first report describing phenanthroindolizidines alkaloids display influence on the crucial cell signaling proteins, ERK. Moreover, the expressions of cyclin A, cyclin D1 and CDK2 proteins depressed more dramatically when the cells were treated with 1, 9, 32, and 33. Then, these four excellent compounds were subjected to flow cytometric analysis, and an increase in S-phase was observed in A549 cells. Since the molecular level assay results of Western blot for phospho-Akt, Akt, phospho-ERK, ERK, and cyclins were relevant to the potency of compounds in cellular level, we speculated that this series of compounds exhibit anticancer activities through blocking PI3K and MAPK signaling transduction pathways and interfering with the cell cycle progression