ABSTRACT
Organometallic halide perovskites have garnered significant attention in various fields of material science, particularly solar energy conversion, due to their desirable optoelectronic properties and compatibility with scalable fabrication techniques. It is often unclear, however, how carrier generation and transport within complex polycrystalline films are influenced by variations in local structure. Elucidating how distinct structural motifs within these heterogeneous systems affect behavior could help guide the continued improvement of perovskite-based solar cells. Here, we present studies applying scanning electron microscopy (SECCM) to map solar energy harvesting within well-defined model systems of organometallic halide perovskites. Methylammonium lead bromide (MAPbBr3) single crystals were prepared via a low-temperature solution-based route, and their photoelectrochemical properties were mapped via SECCM using p-benzoquinone (BQ) in dichloromethane as a redox mediator. Correlated SECCM mapping and electron microscopy studies enabled facet-to-facet variations in photoelectrochemical performance to be revealed and carrier transport lengths to be evaluated. The photoelectrochemical behavior observed within individual single crystals was quite heterogeneous, attributable to local variations in crystal structure/orientations, intrafacet junctions, and the presence of other structural defects. These observations underscore the significance of controlling the microstructure of single perovskite crystals, presenting a promising avenue for further enhancement of perovskite-based solar cells.
ABSTRACT
Well-ordered nanoparticle arrays are attractive platforms for a variety of analytical applications, but the fabrication of such arrays is generally challenging. Here, it is demonstrated that scanning electrochemical cell microscopy (SECCM) can be used as a powerful, instantly reconfigurable tool for the fabrication of ordered nanoparticle arrays. Using SECCM, Ag nanoparticle arrays were straightforwardly fabricated via electrodeposition at the interface between a substrate electrode and an electrolyte-filled pipet. By dynamically monitoring the currents flowing in an SECCM cell, individual nucleation and growth events could be detected and controlled to yield individual nanoparticles of controlled size. Characterization of the resulting arrays demonstrate that this SECCM-based approach enables spatial control of nanoparticle location comparable with the terminal diameter of the pipet employed and straightforward control over the volume of material deposited at each site within an array. These results provide further evidence for the utility of probe-based electrochemical techniques such as SECCM as tools for surface modification in addition to analysis.
Subject(s)
Metal Nanoparticles , Microscopy , Metal Nanoparticles/chemistry , Silver/chemistry , Electrolytes/chemistry , ElectrodesABSTRACT
Low frequency oscillation (LFO) is one of the major concerns for reliable operation of the power system. This LFO occurs due to the failure of the rotor to supply sufficient damping torque to compensate the imbalance between mechanical input and electrical output. Hence, in this paper, we adopt a third generation flexible AC transmission system (FACTS) device named generalized unified power flow controller (GUPFC) based damping controller in order to investigate its effect for mitigating LFO for an single machine infinite bus (SMIB) system. To find an effective damping controller-optimizer pair, we integrate proportional-integral (PI) or lead-lag as a controller and grey wolf optimizer (GWO), differential evolution (DE), particle swarm optimization (PSO), whale optimization algorithm (WOA), and chaotic whale optimization algorithm (CWOA) as an optimizer. Later, we investigate the performances for the above mentioned controller-optimizer pairs through time domain simulation, eigenvalue analysis, nyquist stability test, and quantitative analysis. Moreover, we carry out two non-parametric statistical tests named as one sample Kolmogorov-Smirnov (KS) test and paired sample t-test to identify statistical distribution as well as uniqueness of our optimization algorithms. Our analyses reveal that the GWO tuned lead-lag controller surpasses all other controller-optimizer combinations.
ABSTRACT
The kinetic compensation effect in the logistic distributed activation energy model (DAEM) for lignocellulosic biomass pyrolysis was investigated. The sum of square error (SSE) surface tool was used to analyze two theoretically simulated logistic DAEM processes for cellulose and xylan pyrolysis. The logistic DAEM coupled with the pattern search method for parameter estimation was used to analyze the experimental data of cellulose pyrolysis. The results showed that many parameter sets of the logistic DAEM could fit the data at different heating rates very well for both simulated and experimental processes, and a perfect linear relationship between the logarithm of the frequency factor and the mean value of the activation energy distribution was found. The parameters of the logistic DAEM can be estimated by coupling the optimization method and isoconversional kinetic methods. The results would be helpful for chemical kinetic analysis using DAEM.
