Maximum Lifetime Research Articles

(Invited) Crosscutting Materials Innovation for Transformational Chemical and Electrochemical Energy Conversion Technologies—Solid Oxide Cells

The Solid Oxide Cell (SOC) primarily operated as Solid Oxide Fuel Cell (SOFC) converts the chemical energy of a fuel such as hydrogen directly into electricity with very high efficiencies. Reverse operation of the exact same SOCs—as Solid Oxide Electrolysis Cells (SOEC) converts electrical energy into chemical energy by using the electricity to split chemical molecules such as steam, carbon dioxide or mixtures of both into hydrogen, carbon monoxide or mixtures of both respectively.The SOC is basically a gas-tight and oxide-ion conducting solid electrolyte, sandwiched between porous oxide ion – and electron-conducting electrode materials—the oxygen electrode and the fuel electrode where the electrochemical conversions occur.Irrespective of operation mode, the choice of SOC materials and processing routes generally aim for maximum performance and lifetime at chosen conversion rate and efficiency at nominal operation. This is as much as the technology can intrinsically offer and by far not enough to guarantee either profitable production of electricity or chemicals hydrogen, carbon monoxide or both. Ultimately the materials and manufacturing costs of the cell, stack, module, and system play a key role in the involved invest. Generally, operation costs such as cost of natural gas or electricity as well as maintenance costs are much more significant in determining the profitability of the technology than the investment costs. These technology-independent factors can in turn orientate the technologist to optimize the cell for either for maximum efficiency or conversion rate capability.In this talk we will discuss specific SOC materials such as doped zirconia, doped ceria, manganates, cobaltites, and titanates. Intrinsic limitations and advantages with respect to performance, durability and costs; how they are withstanding the test of time and the ever decreasing operation temperature from micro/nano structuration, infiltration and exsolution of electrocatalysts through switching of cell supports. We will give a perspective on the dependency of cell material choices based on technology use cases and boundary conditions Figure 1

Spectroscopic properties of Pr:PbF2 crystal with different doping concentration

Three Pr:PbF2 single crystals with different doping concentrations (0.1, 0.5 and 1.0 at.%) have been detailed investigated to figure out the effect of doping concentration on spectroscopic properties for the first time. The XRD study shows the crystals belong to the cubic system and the lattice parameter of 1.0 at.% Pr:PbF2 crystal is 5.9336 Å. The maximum phonon energy of three crystals was speculated as low as 259 cm−1 through Raman spectra. The absorption and fluorescence spectra of the Pr:PbF2 crystals with different doping levels were recorded and analyzed with the J-O theory. The maximum absorption cross-section at 443 nm and maximum emission cross-section at 482 nm can be obtained as 1.00 × 10−20 cm2 and 1.08 × 10−20 cm2 in 1.0 at.% Pr:PbF2 crystal, respectively. The gain cross-sections of the Pr:PbF2 crystals become positive in a range of 482–497 nm once the population inversion level reaches 30 %. The maximum fluorescence lifetime of 3P0 energy level was found as 33 μs in 0.1 at.% Pr:PbF2 crystal. On the whole, the spectroscopic performance of Pr: PbF2 crystal would be improved by increasing the Pr3+ doping level appropriately.

PM2.5 bound polycyclic aromatic hydrocarbons in an Indian residential indoor air environment and their health risk

Polycyclic Aromatic Hydrocarbons (PAHs), a group of semi-volatile organic pollutants with 2–7 aromatic rings are emitted in association with particulates/gases from incomplete combustion. They are persistent and affect human health adversely. This is the first study wherein PM2.5 bound PAHs from 8 different indoor air pollution sources, namely dhoop (DH1, DH2), incense sticks (IS1, IS2), cigarette, mosquito coil and solid fuels ‘coal and wood’, that are widely used in South-Asian countries were studied. Their emission rates and concentration profiles were compared. Dhoop was studied for the first time and found to be emitting the highest quantity of total PAHs. FLA/(FLA + PYR) ratio rightly indicated ingredients like wood and grass as sources. However, other ratios indicated petrogenic/coal origin, while BaP/(BaP + CHR) and BaA/(BaA + CHR) ratios were not reported earlier. The highest Toxicity Equivalent Concentration and Mutagenic Equivalent Concentration were estimated for DH2 and the lowest for cigarette smoke. The maximum Inhalation Lifetime Cancer Risk equal to 1.85 × 10−05 (adults) was observed for DH2, exceeding the WHO guidelines. These inferences will help in optimizing the indoor sources’ combustion duration and formulating manmade indoor sources. They will assist in identifying high-risk indoor environments, causative sources and control mechanisms.

Structural characterization, electronic and photophysical properties of phosphane-based copper(I) complexes and their application to cyan LEDs

Two dinuclear Cu(I) complexes, [Cu2(dppe)(dppbz)2I2](1) and [Cu2(dppb)(dppbz)2I2] (2) (dppe = 1, 2-bis(diphenylphosphino)ethane, dppb = 1,4-bis(diphenylphosphino)butane, dppbz = 1,2-bis (diphe nylphosphino)benzene), have been prepared and characterized by IR, TG, XRD, elemental analysis and X-ray crystal structure analysis. Structural analysis indicates that diphosphane ligands connect two Cu atoms to form the S-shape configurations in complexes 1 and 2. DFT calculations demonstrate that the HOMO → LUMO energy gap and Mülliken atomic charges for 1 and 2 are affected by increasing the alkyl chain length of diphosphane ligands, but the composition of HOMOs and LUMOs are hardly changed at the different alkyl chain length of diphosphane ligands. The solid-state luminescent properties of complexes 1 and 2 are observed at 77 K and 298 K, showing that the maximum emission lifetime and quantum yields respectively approach to 6 μs and 26 % at 298 K. Moreover, dinuclear Cu(I) complexes are used to fabricate the cyan light-emitting diodes with the maximum EQE of ca. 20 %.

The psychological legacy of past obesity and early mortality: evidence from two longitudinal studies

BackgroundWe test a novel ‘weight scarring’ hypothesis which suggests that past obesity is associated with impairments in current psychological well-being and this increases risk of negative physical health outcomes associated with obesity. Across two nationally representative studies, we tested whether past obesity is associated with current psychological outcomes and whether these psychological outcomes explain the association between past obesity and subsequent early mortality.MethodsData were from the National Health and Nutrition Examination Survey (NHANES) (n = 29,047) and the Health and Retirement Study (HRS) (n = 11,998). Past obesity was defined based on maximum lifetime weight in NHANES and the highest weight from past study waves in the HRS. Across both studies, current depressive symptoms were analysed. A set of 10 additional well-being measures were combined to produce an ‘index of impaired well-being’ in HRS. Subsequent all-cause mortality was examined using National Deaths Index records in NHANES and household interviews in HRS. Linear or logistic regression, Cox proportional hazard regression, and causal mediation models were used.ResultsWe found that past obesity was associated with greater current depressive symptoms after controlling for current weight status and in analyses limited to those who were no longer classified as having obesity in NHANES (β = 0.17; 95% CI: 0.13, 0.22) and HRS (β = 0.20; 95% CI: 0.08, 0.31). In HRS, past obesity was also associated with a range of current negative psychological outcomes, including an index of impaired psychological well-being (β = 0.16; 95% CI: 0.05, 0.27). Past obesity was associated with a higher risk of early mortality in both NHANES and HRS (HR = 1.31; 95% CI: 1.16, 1.48 and HR = 1.34; 95% CI: 1.20, 1.50, respectively). Depressive symptoms explained 6% (95% CI: 0.01, 0.10) and 5% (95% CI: 0.01, 0.09) of the association between past obesity and premature mortality in NHANES and HRS, respectively. Impaired psychological well-being partly mediated the association between past obesity and premature mortality by 10% (95% CI: 0.04, 0.16) in HRS.ConclusionsOur findings suggest that there may be a psychological legacy of past obesity that is associated with raised mortality risk. Ensuring people with obesity receive psychological support even after experiencing weight loss may be important.

An Energy Flow Control Algorithm of Regenerative Braking for Trams Based on Pontryagin’s Minimum Principle

Energy savings in electric rail transport are important in order to increase energy efficiency and reduce its carbon footprint. This can be achieved by storing and using the energy generated during regenerative braking. The system described in this paper consists of a supercapacitor energy storage system (SC ESS), a bidirectional DC/DC converter, and an algorithm to control the energy flow. The proper design of the algorithm is critical for maximizing energy savings and stabilizing the power grid, and it affects the lifetime of the SC ESS. This paper presents an energy flow control algorithm based on Pontryagin’s minimum principle that balances maximum energy savings with maximum SC ESS lifetime. The algorithm also performs SC ESS recharging while the rail vehicle stops on inclines to reduce the impact of its next acceleration on the power grid. To validate the algorithm, offline simulations are performed using real tram speed measurements. The results are then verified with a real-time laboratory emulation setup with HIL simulation. The tram and power grid are emulated with LiFePO4 batteries, while the SC ESS is emulated with a supercapacitor. The proposed algorithm controls a three-phase converter that enables energy exchange between the batteries and the supercapacitor. The results show that the proposed algorithm is feasible in real time and that it can be used under real operating conditions.

Optimum Design Configuration of Thin-Film Transistors and Quantum-Dot Light-Emitting Diodes for Active-Matrix Displays.

Active matrix (AM) quantum-dot light-emitting diodes (QLEDs) driven by thin-film transistors (TFTs) have attracted significant attention for use in next-generation displays. Several challenges remain for the realisation of AM-QLEDs, such as device design, fabrication process, and integration between QLEDs and TFTs, depending on their device structures and configurations. Herein, efficient and stable AM-QLEDs are demonstrated using conventional and inverted structured QLEDs (C- and I-QLEDs, respectively) combined with facile type-convertible (p- and n-type) single-walled carbon nanotube (SWNT)-based TFTs. Based on the four possible configurations of the QLED-TFT subpixel, the performance of the SWNT TFT-driven QLEDs and the fabrication process to determine the ideal configuration are compared, taking advantage of each structure for AM-QLEDs. The QLEDs and TFTs are also optimized to maximise the performance of the AM-QLEDs-the inner shell composition of quantum dots and carrier type of TFTs-resulting in a maximum external quantum efficiency and operational lifetime (at an initial luminance of 100cdm2 ) of 21.2% and 38 100 000h for the C-QLED, and 19.1% and 133100000h for the I-QLED, respectively. Finally, a 5×5 AM-QLED display array controlled using SWNT TFTs is successfully demonstrated. This study is expected to contribute to the development of advanced AM-QLED displays.

Nature-Inspired Energy Enhancement Technique for Wireless Sensor Networks

Wireless Sensor Networks (WSN) play a major role in various applications, yet maintaining energy efficiency remains a critical challenge due to their limited energy availability. Network lifetime is one of the primary parameters for analyzing the performance of a WSN. This proposed work aims to improve the network lifetime of a WSN by enhancing its energy utilization through the Enhanced Monkey Search Algorithm (E-MSA). The E-MSA provides an optimum solution for this issue by finding a better routing decision by analyzing the available energy on the nodes and the distance between the source and destination. Additionally, a Class Topper Optimization (CTO) algorithm is also included in the work for determining an efficient node to be the cluster head and lead cluster head. In this technique, the data packets are collected by the lead cluster head from the other cluster heads for sending the information in a sequential manner to the base station for reducing data loss. A simulation model is implemented in the NS2 platform with 700 nodes in a 300 × 300 square meter area with 0.5 J of energy to each node for finding the efficiency of the proposed E-MSA with CTO algorithm over the traditional On-Demand Distance Vector (ODV) and Destination-Sequenced Distance Vector (DSDV) approaches. The experimental outcome indicates that the proposed work can reach a maximum lifetime of 1579 s which is comparatively better than the ODV and DSDV approaches by 212 and 358 s, respectively. Similarly, a packet delivery ratio of 79% is achieved with a throughput of 0.85 Mbps along with a delay of 0.48 s for the operation of all 700 nodes.

Controlled inertial nano-cavitation above 100 MHz

The maximum size and lifetime of an acoustically nucleated cavitation bubble is inversely proportional to the driving frequency and has achieved a limit of approximately 10 MHz. Smaller cavitation bubbles that are critical to microscopic applications require shorter lifetimes that correspond to higher oscillation frequencies. Here, we demonstrate that acoustic cavitation in the 100 MHz range and beyond can be achieved through wave propagation in a solid rather than in a liquid. The cavitation bubble is nucleated at a nano-sized fracture on a glass substrate, and its expansion is driven by a leaky Rayleigh wave, while the inertial collapse is induced by a trailing shock wave. As both waves travel at different velocities, the time interval between these two events is a function of the distance to the source. In this way, we demonstrate experimentally control of the lifetime of the bubbles in a range between 6 and 80 ns, corresponding to oscillation frequencies between 13 and 166 MHz. Our results agree with finite-volume fluid–structure interaction simulations.

Multi-objective numerical optimization of 3D-printed polylactic acid bio-metamaterial based on topology, filling pattern, and infill density via fatigue lifetime and mass.

Infill parameters are significant with regard to the overall cost and saving material while printing a 3D model. When it comes to printing time, we can decrease the printing time by altering the infill, which also reduces the total process extent. Choosing the right filling parameters affects the strength of the printed model. In this research, the effect of filling density and infill pattern on the fatigue lifetime of cylindrical polylactic acid (PLA) samples was investigated with finite element modeling and analysis. This causes the lattice structure to be considered macro-scale porosity in the additive manufacturing process. Due to the need for multi-objective optimization of several functions at the same time and the inevitable sacrifice of other objectives, the decision was to obtain a set of compromise solutions according to the Pareto-optimal solution technique or the Pareto non-inferior solution approach. As a result, a horizontally printed rectangular pattern with 60% filling was preferred over the four patterns including honeycomb, triangular, regular octagon, and irregular octagon by considering the sum of mass changes and fatigue lifetime changes, and distance from the optimal point, which is the lightest structure with the maximum fatigue lifetime as an objective function with an emphasis on mass as an important parameter in designing scaffolds and biomedical structures. A new structure was also proposed by performing a structural optimization process using computer-aided design tools and also, computer-aided engineering software by Dassault systems. Finally, the selected samples were printed and their 3D printing quality was investigated using field emission scanning electron microscopy inspection.

Room‐Temperature Phosphorescent Tough Hydrogels Based on Ionically Crosslinked Nonaromatic Polymers

AbstractOrganic photoluminescent materials exhibiting room‐temperature phosphorescence (RTP) have attracted widespread attention. However, most of them can emit phosphorescence only in the solid state, which strongly limits their applications. Herein, a type of phosphorescent hydrogel with excellent mechanical properties is prepared by immersing an as‐prepared poly(vinyl alcohol) (PVA) hydrogel in a poly(sodium maleate) solution and then in a CaCl2 solution, followed by drying under stretching at 90 °C and finally soaking it in deionized water until equilibrium swelling to produce poly(vinyl alcohol)/poly(calcium maleate)‐DS ( PVA/PMACa‐DS) hydrogels. Such hydrogels exhibit excellent mechanical properties, showing tensile strengths up to 15 MPa, due to the presence of strong hydrogen bonding and especially ionic bonding. The PVA/PMACa‐DS hydrogels emit varied phosphorescence emission colors from blue to yellow‐green upon excitation with 312–400 nm light, with a maximum lifetime of 13.4 ms. Experiments and theoretical calculations demonstrate that ionic crosslinking between Ca2+ and nonconventional chromophores prevents the contact of the nonconventional chromophores with water molecules and hence restricts nonradiative decay, leading to RTP emission. This work provides a reliable strategy for designing RTP hydrogels with excellent mechanical properties based on nonaromatic polymers for emerging applications.

First‐Principles Study of the Influences of Point Vacancies (VGa, Hi) on the Photocatalytic and Magnetic Performance of Ga2O3:Li/Na/K Systems

Under vacuum environment, an H interstitial must exist when Ga2O3 is prepared by organometallic chemical vapor deposition. However, few first‐principles systematic studies have been conducted on the influences of point vacancies (VGa, Hi) on the photocatalytic performance and magnetism of Ga2O3:(Li or Na or K) systems, and VGa is a challenge in experiments. Therefore, the first‐principles generalized gradient approximation GGA + U theory is adopted in this study. A first‐principles study is conducted on the formation energy (E f), photocatalytic performance, and magnetism of Ga30MO48 (M = Li or Na or K) and Ga30MHiO48 systems. In the results, it is shown that under Ga‐poor conditions, the Ga30MO48 and Ga30MHiO48 systems are structurally stable and prone to doping. The Ga30MHiO48 system has lower E f, more structural stability, and easier doping than the Ga30MO48 system. The Ga30KO48 system exhibits magnetism, mainly generated by the O1−‐2p spin‐polarized wandering electrons near VGa. The spin‐polarized O2−‐2p and Ga‐4s states near VGa contribute to the hybrid coupling double‐exchange interaction. Moreover, the visible spectrum of the Ga30LiHiO48 system exhibits a significant redshift, a relatively high carrier activity, carrier separation, and relative maximum lifetime. It is relatively best as a photocatalyst.

New insights into the poleward migration of tropical cyclones and its association with Hadley circulation

Recent investigations have shown a robust signature of poleward migration of the tropical cyclone latitudes using observations and climate model simulations. Most of these studies invoked the role of the Hadley circulation (HC) expansion in the poleward shifting of tropical cyclones. However, none of these studies focused on the dissection of the zonally asymmetric HC into ascending and descending regions at regional scales, which holds the key in establishing the association between these two phenomena. Here, we are reporting the poleward migration of tropical cyclones and their association with ascending region boundaries of the HC at regional scales for the first time. The results emphatically show that the tropical cyclone latitudes as well as latitudes of maximum lifetime intensity vary in tandem with boundaries of the ascending region of the HC as compared to its descending region thus providing a vital clue on processes governing poleward migration of tropical cyclones.

Optimizing wireless sensor network lifetime through K-coverage maximization and memetic search

Many wireless sensor networks (WSNs) not only need to cover targets within their sensing fields, but also operate for extended periods without requiring expensive recharging. This is a challenging task when planning deployments, as sensing and data processing consumes sensor energy. Redundant sensors can help extend the lifetime, but also require good placement and scheduling to be effective. This paper seeks to design a placement scheme and schedule that can achieve near-optimal network lifetime, while satisfying the target coverage constraint. The problem is approached in two phases. The first phase places sensors to maximize K-coverage, a metric closely related to lifetime, using a novel heuristic called Greedy Intersecting Arc Selection. The second phase schedules the nodes’ operations for maximum lifetime, using Memetic Set Scheduler, a novel memetic algorithm. Experimental results show notable improvements in both solution quality and running time for the proposed approach compared to two existing approaches to the problem.

Deep Belief Network Based Wireless Sensor Network Connectivity Analysis

Wireless sensor networks (WSNs) are widely used in various fields, and their deployment is critical to ensure area coverage and full network connectivity to achieve the maximum network lifetime. In this study, we present a mixed-integer programming (MIP) model that deeply investigates deployment parameters to optimize lifetime and analyze network connectivity. We further analyze the obtained results using Deep Belief Network (DBN) and Deep Neural Network (DNN) algorithms to achieve higher accuracy rates. Our evaluation shows that the DBN outperforms the DNN with an accuracy rate of 81.2%, precision of 81.2%, recall of 99.1%, and an F1-Score of 0.78. We also utilize two different datasets to justify the efficiency of the DBN in this research. The findings of this study emphasize the validity of our DBN algorithm and encourage further research into lifetime optimization and connectivity analysis in WSNs.

Study of optical and passivation properties of hydrogenated silicon carbide thin films deposited by reactive magnetron sputtering for c-Si solar cell application

In this paper, optical and passivating properties of hydrogenated silicon carbide synthesized by reactive magnetron sputtering for c-Si solar cell application were studied. SiC:H films were synthesized by sputtering a SiC target in an argon-hydrogen ambient at a Radio Frequency (RF) power of 100–250 W. The thickness, density, and roughness of the films were measured by X-ray reflectometry. The optical properties of the films were studied by UV–visible spectroscopy. It is shown that with an increase in RF power, the refractive index increases from 1.53 to 2.32 (at λ = 633 nm), and the extinction coefficient does not exceed 0.009 in most of the visible and near-IR spectrum. Based on the measured optical constants using computer simulation the optimal thicknesses were calculated to maximize antireflection effect. IR spectroscopy showed correlation between the structure and physical properties of the films. It has been established that, at a lower RF power (100–150 W), particles are deposited instead of atoms. This leads to the formation of voids at the particle boundaries, which are subsequently filled with oxygen. Using the non-contact microwave photoconductance decay method, it was shown that the maximum effective lifetime (τeff) is achieved at RF power of 250 W. In addition, influence of preliminary surface cleaning procedure and post-annealing in vacuum on the τeff was considered.

Biochemical characterization of patients with dihydrolipoamide dehydrogenase deficiency.

Dihydrolipoamide dehydrogenase (DLD; E3) oxidizes lipoic acid. Restoring the oxidized state allows lipoic acid to act as a necessary electron sink for the four mitochondrial keto-acid dehydrogenases: pyruvate dehydrogenase, alpha-ketoglutarate dehydrogenase, branched-chain α-keto-acid dehydrogenase, and 2-oxoadipate dehydrogenase. DLD deficiency (DLDD) is caused by biallelic pathogenic variants in DLD. Three major forms have been described: encephalopathic, hepatic, and myopathic, although DLDD patients exhibit overlapping phenotypes. Hyperlactatemia, hyperexcretion of tricarboxylic acid cycle (TCA) metabolites and branched-chain keto acids, increased plasma branched-chain amino acids and allo-isoleucine are intermittent metabolic abnormalities reported in patients with DLDD. However, the diagnostic performance of these metabolites has never been studied. Therefore, we sought to systematically evaluate the diagnostic utility of these biomarkers for DLDD. We retrospectively analyzed the results of biochemical testing of six unrelated DLDD patients, including values obtained during both well visits and acute decompensation episodes. Elevation of branched-chain amino acid concentrations was not consistently observed. We found that five of six patients in our cohort had a maximum lifetime value of allo-isoleucine of 6 μmol/L, showing that alloisoleucine elevations even during illness may be subtle. Urine organic acid analysis (UOA) during acute decompensation episodes was abnormal in all cases; however, the pattern of abnormalities had high intersubject variability. No single biomarker was universally present, even in patients experiencing metabolic decompensation. We also observed novel biochemical associations: three patients had hyperexcretion of TCA cycle metabolites during crisis; in two patients, 2-ketoadipic and 2-hydroxyadipic acids, by products of lysine degradation, were detected. We propose that these result from 2-oxoadipate dehydrogenase deficiency, an underappreciated biochemical abnormality in DLD. Given the diversity of biochemical profiles among the patients with DLDD, we conclude that accurate biochemical diagnosis relies on a high index of suspicion and multipronged biochemical analysis, including both plasma amino acid and urine organic acid quantitation during decompensation. Biochemical diagnosis during the well state is challenging. We emphasize the critical importance of multiple simultaneous biochemical tests for diagnosis and monitoring of DLDD. We also highlight the under-recognized role of DLD in the lysine degradation pathway. Larger cohorts of patients are needed to establish a correlation between the biochemical pattern and clinical outcomes, as well as a genotype-phenotype correlation.

Optimal lattice depth on lifetime of D-band ultracold atoms in a triangular optical lattice.

Ultracold atoms in optical lattices are a flexible and effective platform for quantum precision measurement, and the lifetime of high-band atoms is an essential parameter for the performance of quantum sensors. In this work, we investigate the relationship between the lattice depth and the lifetime of D-band atoms in a triangular optical lattice and show that there is an optimal lattice depth for the maximum lifetime. After loading the Bose-Einstein condensate into D band of optical lattice by shortcut method, we observe the atomic distribution in quasi-momentum space for the different evolution time, and measure the atomic lifetime at D band with different lattice depths. The lifetime is maximized at an optimal lattice depth, where the overlaps between the wave function of D band and other bands (mainly S band) are minimized. Additionally, we discuss the influence of atomic temperature on lifetime. These experimental results are in agreement with our numerical simulations. This work paves the way to improve coherence properties of optical lattices, and contributes to the implications for the development of quantum precision measurement, quantum communication, and quantum computing.

Effect of the thickness and surface interface of In2O3 films on the transport and recombination of charges in a polymer solar cell

Indium oxide films were obtained by spin coating from a solution of indium nitrate in ethylene glycol followed by annealing at 300 °C. The influence of the thickness and surface interface of In2O3 films on the optical and photo-electrophysical properties of a polymer solar cell has been studied. It is shown that the surface roughness of the film gradually decreases with a decrease in the thickness of the film to 60 nm, and a further decrease in the thickness of the films leads to its increase. The absorption spectra of the films were measured. The values of the optical band gap width are determined. It was found that with a decrease in the thickness of the films, the width of the forbidden zone (Eg) also decreases. It was found that the parameters of the current-voltage characteristics (VAC) and electrophysical measurements also depend on the thickness and interface of the surface of the In2O3 films. It was found that with an In2O3 film thickness equal to 60 nm, a maximum efficiency value of 3.42 % is observed, at the same time, electrons in the photoactive layer have a maximum charge carrier lifetime and a low recombination rate

Battery health prognostic using efficient and robust aging trajectory matching with ensemble deep transfer learning

Accurate aging trajectory and lifetime prediction are key objectives for battery prognostic and health management. However, effective health prognostic is difficult to realize due to the different aging characteristics at different aging stages and incomplete aging data for practical applications. To embrace these challenges, we propose an intelligent battery health prognostic method using efficient and robust aging trajectory matching with ensemble deep transfer learning (EDTL). Firstly, dispensing with expertise in battery degradation, spectral clustering is offline performed for unsupervised degradation pattern recognition. Secondly, to ensure the accuracy of aging trajectory matching, lifetime indicator-based candidate cell selection fusing with similarity assessment using dynamic time warping provides multi-dimensional information in finding the optimally matched battery aging trajectory from the historical data. Finally, to robustly and accurately capture the long-term dependencies of battery aging, the bi-directional long short-term memory network with EDTL is employed. Experimental results demonstrate that the proposed method could achieve accurate and reliable health prognostic at different battery aging stages or in the presence of incomplete data with a maximum lifetime prediction error of 6.35%. Compared with traditional methods, our method could provide a more accurate battery health prognostic, which is of great significance for battery predictive maintenance.