RESUMO
We use scanning probe microscopy to study ion migration in formamidinium (FA)-containing halide perovskite semiconductor Cs0.22FA0.78Pb(I0.85Br0.15)3 in the presence and absence of chemical surface passivation. We measure the evolving contact potential difference (CPD) using scanning Kelvin probe microscopy (SKPM) following voltage poling. We find that ion migration leads to a â¼100 mV shift in the CPD of control films after poling with 3 V for only a few seconds. Moreover, we find that ion migration is heterogeneous, with domain interfaces leading to a larger CPD shift than domain interiors. Application of (3-aminopropyl)trimethoxysilane (APTMS) as a surface passivator further leads to 5-fold reduction in the CPD shift from â¼100 to â¼20 mV. We use hyperspectral microscopy to confirm that APTMS-treated perovskite films undergo less photoinduced halide migration than control films. We interpret these results as due to a reduction in the halide vacancy concentration after APTMS passivation.
RESUMO
Advances in scanning probe microscopy (SPM) methods such as time-resolved electrostatic force microscopy (trEFM) now permit the mapping of fast local dynamic processes with high resolution in both space and time, but such methods can be time-consuming to analyze and calibrate. Here, we design and train a regression neural network (NN) that accelerates and simplifies the extraction of local dynamics from SPM data directly in a cantilever-independent manner, allowing the network to process data taken with different cantilevers. We validate the NN's ability to recover local dynamics with a fidelity equal to or surpassing conventional, more time-consuming, calibrations using both simulated and real microscopy data. We apply this method to extract accurate photoinduced carrier dynamics on n = 1 butylammonium lead iodide, a halide perovskite semiconductor film that is of interest for applications in both solar photovoltaics and quantum light sources. Finally, we use SHapley Additive exPlanations to evaluate the robustness of the trained model, confirm its cantilever-independence, and explore which parts of the trEFM signal are important to the network.
Assuntos
Iodetos , Redes Neurais de Computação , Calibragem , Microscopia de Força Atômica/métodos , Eletricidade EstáticaRESUMO
Two-dimensional (2D) materials show great potential for use in battery electrodes and are believed to be particularly promising for high-rate applications. However, there does not seem to be much hard evidence for the superior rate performance of 2D materials compared to non-2D materials. To examine this point, we have analyzed published rate-performance data for a wide range of 2D materials as well as non-2D materials for comparison. For each capacity-rate curve, we extract parameters that quantify performance which can then be analyzed using a simple mechanistic model. Contrary to expectations, by comparing a previously proposed figure of merit, we find 2D-based electrodes to be on average â¼40 times poorer in terms of rate performance than non-2D materials. This is not due to differences in solid-state diffusion times which were similarly distributed for 2D and non-2D materials. In fact, we found the main difference between 2D and non-2D materials is that ion mobility within the electrolyte-filled pores of the electrodes is significantly lower for 2D materials, a situation which we attribute to their high aspect ratios.
RESUMO
IT127 is a dinuclear transition metal complex that contains a Pt(ii) and a Ru(iii) metal center. We have shown that IT127 is significantly more effective in binding the 29-base sarcin ricin loop (SRL) RNA in comparison to Cisplatin, a hallmark anticancer agent. Binding site analysis shows that IT127 prefers purine bases and the GAGA tetraloop region of SRL RNA. Our results with a dihydrofolate reductase (DHFR) model system reveal that IT127 binding to mRNA reduces translation of DHFR enzyme and that the Ru(iii) and Pt(ii) centers in IT127 appear to work in a synergistic manner.