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Understanding interactions at the interfaces of carbon with ionic liquids (ILs) is crucially beneficial for the diagnostics and performance improvement of electrochemical devices containing carbon as active materials or conductive additives in electrodes and ILs as solvents or additives in electrolytes. The interfacial interactions of three typical imidazolium-based ILs, 1-alkyl-3-methylimidazolium bis(trifluoromethanesulfonyl)imide (AMImTFSI) ILs having ethyl (C2), butyl (C4) and octyl (C8) chains in their cations, with highly oriented pyrolytic graphite (HOPG) were studied in-situ by electrochemical scanning tunneling microscopy (EC-STM). The etching of HOPG surface and the exfoliation of graphite/graphene flakes as well as cation intercalation were observed at the HOPG/C2MImTFSI interface. The etching also takes place in C4MImTFSI at −1.5 V vs Pt but only at step edges with a much slower rate, whereas C8MIm+ cations adsorbs strongly on the HOPG surface under similar conditions with no observable etching or intercalation. The EC-STM observations can be explained by the increase in van der Waals interaction between the cations and the graphite surface with increasing length of alkyl chains.

In the version of this Article originally published, the author Baran Eren was mistakenly affiliated with the Harbin Institute of Technology, China; it has now been corrected to Materials Science Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.

Bimetallic and multi-component catalysts typically exhibit composition-dependent activity and selectivity, and when optimized often outperform single-component catalysts. Here we used ambient-pressure X-ray photoelectron spectroscopy (AP-XPS) and in situ and ex situ transmission electron microscopy (TEM) to elucidate the origin of composition dependence observed in the catalytic activities of monodisperse CoPd bimetallic nanocatalysts for CO oxidation. We found that the catalysis process induced a reconstruction of the catalysts, leaving CoOx on the nanoparticle surface. The synergy between Pd and CoOx coexisting on the surface promotes the catalytic activity of the bimetallic catalysts. This synergistic effect can be optimized by tuning the Co/Pd ratios in the nanoparticle synthesis, and it reaches a maximum at compositions near Co0.24Pd0.76, which achieves complete CO conversion at the lowest temperature. Our combined AP-XPS and TEM studies provide direct observation of the surface evolution of the bimetallic nanoparticles under catalytic conditions and show how this evolution correlates with catalytic properties.

The utilization of nickel-rich single-crystalline LiNi1−x−yCoxMnyO2 cathodes at elevated voltages encounters hindrances stemming from crack formation within micron-sized particles. While reducing particle dimensions offers a potential strategy to mitigate stress-induced cracking, it simultaneously exacerbates surface side reactions. Ta doping is presented to address these challenges, a Ta-doped single-crystalline LiNi0.8Co0.1Mn0.1O2 (Ta-SC) is engineered, integrating advantages of grain refinement and surface stability. Ta doping inhibits the growth of single crystals during sintering and suppresses the irreversible surface phase transition during cycling. Unlike the undoped SC cathode, which is susceptible to intragranular cracking, the Ta-SC cathode demonstrates excellent structural integrity upon high voltage cycling. This preservation of structural integrity in the Ta-SC cathode is attributed to homogeneous H2–H3 phase transition favoured by reduced kinetic barriers and short distance for Li+ diffusion. Benefitting from the structural stability, the Ta-SC cathode provides superior cycling stability. It maintains a coin cell capacity of 180.7 mA h g−1 and retains an energy density of 679.8 W h kg−1 after 200 cycles in the 2.8–4.8 V range at 1 C. This work highlights the potential of Ta doping as a general approach to improve the durability and electrochemical performance of layered cathode materials. [ABSTRACT FROM AUTHOR]

Knowledge of the molecular composition and electronic structure of electrified solid-liquid interfaces is key to understanding elemental processes in heterogeneous reactions. Using X-ray absorption spectroscopy in the interface-sensitive electron yield mode (EY-XAS), first-principles electronic structure calculations, and multiscale simulations, we determined the chemical composition of the interfacial region of a polycrystalline platinum electrode in contact with aqueous sulfuric acid solution at potentials between the hydrogen and oxygen evolution reactions. We found that between 0.7 and 1.3 V vs Ag/AgCl the electrical double layer (EDL) region comprises adsorbed sulfate ions with hydrated hydronium ions in the next layer. No evidence was found for bisulfate or Pt-O/Pt-OH species, which have very distinctive spectral signatures. In addition to resolving the long-standing issue of the EDL structure, our work establishes interface- and element-sensitive EY-XAS as a powerful spectroscopic tool for studying condensed phase, buried solid-liquid interfaces relevant to various electrochemical processes and devices.

We investigated the X-ray absorption spectroscopy (XAS) fingerprint of EMImTFSI ionic liquid (IL) and its fragmentation products created by X-ray irradiation. To accomplish this, we used an open geometry where an IL droplet is directly exposed in the vacuum chamber and an enclosed geometry where the IL is confined in a cell covered by an X-ray transparent membrane. In the open geometry, the XAS signature was stable and consistent with experimental and theoretical spectra reported in the literature. In contrast, when the IL is enclosed, its XAS evolves continuously under X-ray illumination due to the accumulation of volatile fragmentation products inside the closed cell, while they evaporate in the open geometry. The changes in the XAS from the core levels of relevant elements (C, N, S, F) together with density functional theory calculations allowed us to identify the chemical nature of the fragment products and the chemical bonds most vulnerable to rupture under soft X-ray irradiation.

The electrochemical lithiation/delithiation of oxygen-containing functional groups (OCFGs) of nanocarbon materials, particularly graphene, have attracted intensive interest in recent years. Here, we propose a controllable potentiostatic oxidation approach to tune the OCFGs of as-prepared reduced graphene oxide (rGO) in a carbonate-based electrolyte to improve the specific capacity and rate capability. By X-Ray absorption spectroscopy in total fluorescence yield mode and X-Ray diffraction, we confirm that potentiostatic oxidations generate new OCFGs in the inner-layer of rGO. The content of OCFGs increases as oxidation potential being elevated. Such increasing of OCFGs in quantity significantly enhances the capacity. For instance, the specific capacity of 170.4 mAh g−1 for pristine rGO electrode is increased to 290.5 mAh g−1 after the oxidation at 5.0 V. We demonstrate that oxidations at moderate potentials can reduce the electrochemical and ohmic polarizations of rGO electrodes without deteriorating diffusion dynamic, thereby improving rate capability. After the optimal oxidation at 4.7 V, rGO electrode exhibits an excellent rate capability, delivering 58.4 mAh g−1 at 20 A g−1.

With increasingly sophisticated laser applications in industry and science, a reliable method to characterize the intensity distribution of the laser beam has become a more and more important task. However, traditional optic and electronic methods can offer only a laser beam intensity profile but, cannot separate the main mode components in the laser beam intensity distribution. Recently, independent component analysis has been a surging and developing method in which the goal is to find a linear representation of a non-Gaussian data set. Such a linear representation seems to be able to capture the essential structure of a laser beam profile. After assembling image data of a laser spot, we propose a new analytical approach to extract laser beam mode components based on the independent component analysis technique. For noise reduction and laser spot area location, wavelet thresholding, Canny edge detection, and the Hough transform are also used in this method before extracting mode components. Finally, the experimental results show that our approach can separate the principal mode components in a real laser beam efficiently. OCIS codes: 070.6020, 140.3300, 230.2090.

We propose a new, to our knowledge, denoising method for lidar signals based on a regression model and a wavelet neural network (WNN) that permits the regression model not only to have a good wavelet approximation property but also to make a neural network that has a self-learning and adaptive capability for increasing the quality of lidar signals. Specifically, we investigate the performance of the WNN for antinoise approximation of lidar signals by simultaneously addressing simulated and real lidar signals. To clarify the antinoise approximation capability of the WNN for lidar signals, we calculate the atmosphere temperature profile with the real signal processed by the WNN. To show the contrast, we also demonstrate the results of the Monte Carlo moving average method and the finite impulse response filter. Finally, the experimental results show that our proposed approach is significantly superior to the traditional methods. OCIS codes: 010.0010, 010.3640, 010.1290.

An iterative learning control (ILC) algorithm, which in essence is a stochastic approximation algorithm, is proposed for output tracking for nonlinear stochastic systems with unknown dynamics and unknown noise statistics. The nonlinear function of the system dynamics is allowed to grow up as fast as a polynomial of any degree, but the system is linear with respect to control. It is proved that the ILC generated by the algorithm a.s. converges to the optimal one at each time t [EPSILON] [0, 1, ..., N] and the output tracking error is asymptotically minimized in the mean square sense as the number of iterates tends to infinity, although the convergence rate is rather slow. The only information used in the algorithm is the noisy observation of the system output and the reference signal [y.sub.d](t). When the system state equation is free of noise and the system output is realizable, then the exact state tracking is asymptotically achieved and the tracking error is purely due to the observation noise. Index Terms--Almost sure (a.s.) convergence, iterative learning control, nonlinear stochastic system, output tracking, stochastic approximation.

Performance potentials play a crucial role in performance sensitivity analysis and policy iteration of Markov decision processes. The potentials can be estimated on a single sample path of a Markov process. In this paper, we propose two potential-based online policy iteration algorithms for performance optimization of Markov systems. The algorithms are based on online estimation of potentials and stochastic approximation. We prove that with these two algorithms the optimal policy can be attained after a finite number of iterations. A simulation example is given to illustrate the main ideas and the convergence rates of the algorithms. Index Terms--Markov decision process, potential, recursive optimization.

Stochastic adaptive stabilization usually leads to the boundedness of the average of squared output of the stabilized system, but gives no conclusion on stability of the resulting system. This note proves that adaptively stabilized stochastic system in its steady state is truly stable in the conventional sense. Index Terms--Adaptive stabilization, ARMA, stability.