The development of cost-effective catalysts for the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) is crucial for enhancing the energy efficiency of many electrochemical energy ...conversion and storage devices. Owing to their low cost and high activity, transition metal oxides have attracted much attention as alternative electrocatalysts to replace the currently used noble metal-based catalysts. Anion defects (
e.g.
, oxygen vacancies, interstitials, and anion dopants) can significantly change the electronic structure of oxides or the stability of adsorbed intermediates, thus greatly enhancing the electrocatalytic activities of the oxide surface. Anionic defect engineering represents a potential new direction for rational design of high-performance electrocatalysts. In this review, recent progress in manipulating the anion defects in transition metal oxides for enhancing their activity and stability is summarized and the proposed mechanisms for enhanced performance are discussed in detail. Challenges and prospects are also discussed in the development of a new generation of highly efficient ORR and OER electrocatalysts.
Techniques for anionic defect engineering in transition metal oxides and mechanisms of how anion defects affect their oxygen reaction activities.
Abstract
Developing highly efficient and cost-effective oxygen evolution reaction (OER) electrocatalysts is critical for many energy devices. While regulating the proton-coupled electron transfer ...(PCET) process via introducing additive into the system has been reported effective in promoting OER activity, controlling the PCET process by tuning the intrinsic material properties remains a challenging task. In this work, we take double perovskite oxide PrBa
0.5
Sr
0.5
Co
1.5
Fe
0.5
O
5+δ
(PBSCF) as a model system to demonstrate enhancing OER activity through the promotion of PCET by tuning the crystal orientation and correlated proton diffusion. OER kinetics on PBSCF thin films with (100), (110), and (111) orientation, deposited on single crystal LaAlO
3
substrates, were investigated using electrochemical measurements, density functional theory (DFT) calculations, and synchrotron-based near ambient X-ray photoelectron spectroscopy. The results clearly show that the OER activity and the ease of deprotonation depend on orientation and follow the order of (100) > (110) > (111). Correlated with OER activity, proton diffusion is found to be the fastest in the (100) film, followed by (110) and (111) films. Our results point out a way of boosting PCET and OER activity, which can also be successfully applied to a wide range of crucial applications in green energy and environment.
Developing low‐cost, high‐performance electro‐catalysts is essential for large‐scale application of electrochemical energy devices. In this article, reported are the findings in understanding and ...controlling oxygen defects in PrBa0.5Sr0.5Co1.5Fe0.5O5+δ (PBSCF) for significantly enhancing the rate of oxygen evolution reaction (OER) are reported. Utilizing surface‐sensitive characterization techniques and first‐principle calculations, it is found that excessive oxygen vacancies promote OH− affiliation and lower the theoretical energy for the formation of O* on the surface, thus greatly facilitating the OER kinetics. On the other hand, however, oxygen vacancies also increase the energy band gap and lower the O 2p band center of PBSCF, which may hinder OER kinetics. Still, careful tuning of these competing effects has resulted in enhanced OER activity for PBSCF with oxygen defects. This work also demonstrates that oxygen defects generated by different techniques have very different characteristics, resulting in different impacts on the activity of electrodes. In particular, PBSCF nanotubes after electrochemical reduction exhibit outstanding OER activity compared with the recently reported perovskite‐based catalysts.
Oxygen vacancies in PrBa0.5Sr0.5Co1.5Fe0.5O5+δ (PBSCF) are found to promote OH‐ affiliation and lower the theoretical energy for the formation of O* on the surface. However, oxygen vacancies also increase the energy band gap and lower the O 2p band center of PBSCF. Careful tuning of these competing effects has resulted in enhanced oxygen evolution reaction activity for PBSCF with oxygen defects.
Transition metal dichalcogenides (TMDs) have attracted much attention due to their promising optical, electronic, magnetic, and catalytic properties. Engineering the defects in TMDs represents an ...effective way to achieve novel functionalities and superior performance of TMDs devices. However, it remains a significant challenge to create defects in TMDs in a controllable manner or to correlate the nature of defects with their functionalities. In this work, taking single-layer MoS2 as a model system, defects with controlled densities are generated by 500 keV Au irradiation with different ion fluences, and the generated defects are mostly S vacancies. We further show that the defects introduced by ion irradiation can significantly affect the properties of the single-layer MoS2, leading to considerable changes in its photoluminescence characteristics and electrocatalytic behavior. As the defect density increases, the characteristic photoluminescence peak of MoS2 first blueshifts and then redshifts, which is likely due to the electron transfer from MoS2 to the adsorbed O2 at the defect sites. The generation of the defects can also strongly improve the hydrogen evolution reaction activity of MoS2, attributed to the modified adsorption of atomic hydrogen at the defects.
In this paper, we present the globally optimal distributed Kalman filtering fusion with singular covariances of filtering errors and measurement noises. The following facts motivate us to consider ...the problem. First, the invertibility of estimation error covariance matrices is a necessary condition for most of the existing distributed fusion algorithms. However, it can not be guaranteed to exist in practice. For example, when state estimation for a given dynamic system is subject to state equality constraints, the estimation error covariance matrices must be singular. Second, the proposed fused state estimate is still exactly the same as the centralized Kalman filtering using all sensor raw measurements. Moreover, the existing performance analysis results on the distributed Kalman filtering fusion for the multisensor system with feedback are also extended to the singular covariance matrices of filtering error. The final numerical examples support the theoretical results and show an advantage of less computational burden.
When there is no feedback from the fusion center to local sensors, we present a distributed Kalman filtering fusion formula for linear dynamic systems with sensor noises cross-correlated, and prove ...that under a mild condition the fused state estimate is equivalent to the centralized Kalman filtering using all sensor measurements, therefore, it achieves the best performance. Then, for the same dynamic system, when there is feedback, a modified Kalman filtering fusion with feedback for distributed recursive state estimators is proposed, and prove that the fusion formula with feedback is, as the fusion without feedback, still exactly equivalent to the corresponding centralized Kalman filtering fusion formula; the various
P matrices in the feedback Kalman filtering at both local filters and the fusion center are still the covariance matrices of tracking errors; the feedback does reduce the covariance of each local tracking error.
Layered cathodes for lithium-ion battery, including LiCo1–x–y Ni x Mn y O2 and xLi2MnO3·(1–x)LiMO2 (M = Mn, Ni, and Co), are attractive for large-scale applications such as electric vehicles, ...because they can deliver additional specific capacity when the end of charge voltage is improved to over 4.2 V. However, operation under a high voltage might cause capacity decaying of layered cathodes during cycling. The failure mechanisms that have been given, up to date, include the electrolyte oxidation decomposition, the Ni, Co, or Mn ion dissolution, and the phase transformation. In this work, we report a new mechanism involving the exfoliation of layered cathodes when the cathodes are performed with deep cycling under 4.5 V in the electrolyte consisting of carbonate solvents and LiPF6 salt. Additionally, an electrolyte additive that can form a cathode interface film is applied to suppress this exfoliation. A representative layered cathode, LiCoO2, and an interface film-forming additive, dimethyl phenylphosphonite (DMPP), are selected to demonstrate the exfoliation and the protection of layered structure. When evaluated in half-cells, LiCoO2 exhibits a capacity retention of 24% after 500 cycles in base electrolyte, but this value is improved to 73% in the DMPP-containing electrolyte. LiCoO2/graphite full cell using DMPP behaves better than the Li/LiCoO2 half-cell, delivering an initial energy density of 700 Wh kg –1 with an energy density retention of 82% after 100 cycles at 0.2 C between 3 and 4.5 V, as compared to 45% for the cell without using DMPP.
In a multisensor target tracking system, observations produced by sensors typically arrive at a central processor out of sequence. There have been some update algorithms for single out-of-sequence ...measurement (OOSM). In this paper, we consider optimal centralized update algorithms with multiple asynchronous (different lag time) OOSMs. First, we generalize the optimal update algorithm with single one-step-lag OOSM in Y. Bar-Shalom, ldquoUpdate With Out-of-Sequence Measurements in Tracking: Exact Solution,rdquo IEEE Transactions on Aerospace and Electronic Systems , vol. 38, pp. 769-778, July 2002 to optimal centralized update algorithm with multiple one-step-lag OOSMs. Then, based on best linear unbiased estimation, we present an optimal centralized update algorithm with multiple arbitrary-step-lag OOSMs. Finally, two suboptimal centralized update algorithms are proposed to reduce the computational complexity. A numerical example shows that performances of two suboptimal centralized algorithms are close to that of the optimal centralized update algorithm.
This paper is concerned with optimal filtering in a distributed multiple sensor system with the so-called out-of-sequence measurements (OOSM). Based on best linear unbiased estimation (BLUE) fusion, ...we present two algorithms for updating with OOSM that are optimal for the information available at the time of update. Different minimum storages of information concerning the occurrence time of OOSMs are given for both algorithms. It is shown by analysis and simulation results that the two proposed algorithms are flexible and simple.
In this paper, the state estimation for dynamic system with unknown inputs modeled as an autoregressive AR (1) process is considered. We propose an optimal algorithm in mean square error sense by ...using difference method to eliminate the unknown inputs. Moreover, we consider the state estimation for multisensor dynamic systems with unknown inputs. It is proved that the distributed fused state estimate is equivalent to the centralized Kalman filtering using all sensor measurement; therefore, it achieves the best performance. The computation complexity of the traditional augmented state algorithm increases with the augmented state dimension. While, the new algorithm shows good performance with much less computations compared to that of the traditional augmented state algorithms. Moreover, numerical examples show that the performances of the traditional algorithms greatly depend on the initial value of the unknown inputs, if the estimation of initial value of the unknown input is largely biased, the performances of the traditional algorithms become quite worse. However, the new algorithm still works well because it is independent of the initial value of the unknown input.
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