Ordered SnO₂ nanostructures were prepared as humidity sensors by nanosphere lithography with the magnetron sputtering technique. The X-ray diffraction patterns of SnO₂ nanostructures show that all intense diffraction peaks correspond to the crystallographic planes of SnO₂. The Atomic Force Microscope (AFM) mage shows that these SnO₂ nanostructures exhibited a classic honeycomb structure. The resistance of this sensor was measured to show that the resistance of the sensor decreases with an increase from lower relative humidity (RH) to higher RH. Additionally, the longest response/recovery time was 32 s/42 s for 11–96% RH. The hysteresis for the SnO₂ nanostructure sensor was <5%.

This article presents a new numerical approach for parameter extraction in five-parameter single-diode or double-diode photovoltaic models, through a separable nonlinear least squares treatment of the problem. The parameter separation technique realizes a reduction of the number of independent parameters as well as the computational complexity. Then, a penalty-assisted direct search algorithm is proposed to solve the optimization problem. The proposed method is applicable to current – voltage ( I–V ) curves with at least 4 points or manufacturer datasheets with 3 key points, which breaks the 5-point limitation in previous numerical optimization methods. In two commonly-used case studies that are considered as the benchmark test for single-diode model, the proposed method shows a high accuracy close to the most accurate methods. After an additional curve-fitting refinement of the obtained parameters, the best accuracy documented until now is achieved in the case studies. Furthermore, the robustness of the proposed method is validated through a large-scale data repository containing more than one million I–V curves. Finally, to facilitate the application of the proposed method, a graphical easy-to-use program has been developed and available to public users.

Si nanocrystals are formed by using KrF pulsed laser crystallization of an amorphous SiC/ultrathin amorphous Si/amorphous SiC sandwiched structure. Electrons and holes are injected into Si nanocrystals via a biased conductive AFM tip and the carrier decay and transportation behaviours at the nanoscale are studied by joint characterization techniques of Kelvin probe force microscopy (KPFM) and conductive atomic force microscopy (CAFM). Quantification of the surface charge density is realized by solving the Poisson equation based on KPFM measurements. Besides, the asymmetric barrier height for electrons and holes is considered to play a dominant role in controlling the charge retention and transportation characteristics. The methodology developed in this work is promising for studying the charge injection and transportation process in other materials and structures at the nanoscale.

Kelvin probe force microscopy (KPFM) measurement has been extensively applied in metallic, semiconductor and organic electronic or photovoltaic devices, to characterize the local contact potential difference or surface potential of the samples at the nanoscale. Here, a comprehensive modeling of surface potential in KPFM is established, from the well-known single capacitance model to a precise electrodynamic model, considering the long range property of the electrostatic force in KPFM. The limitations and relations of different models are also discussed. Besides, the feedback condition of the KPFM system is reconsidered and modified, showing that the influence of the cantilever has been overestimated by about 20% in previous reports. Afterwards, the surface potential of charged Si-nanocrystals is reconstructed based on the electrodynamic model, and the calculated surface charge density is very consistent with the macroscopic capacitance–voltage (C–V) measurement. A deep understanding and correct reconstruction of surface potential is crucial to the quantitative analysis of KPFM results.

A comprehensive comparison study of electrostatic force microscopy (EFM) and Kelvin probe force microscopy (KPFM) is conducted in this manuscript. First, it is theoretically demonstrated that for metallic or semiconductor samples, both the EFM and KPFM signals are a convolution of the sample surface potential with their respective transfer functions. Then, an equivalent point-mass model describing cantilever deflection under distributed loads is developed to reevaluate the cantilever influence on detection signals, and it is shown that the cantilever has no influence on the EFM signal, while it will affect the KPFM signal intensity but not change the resolution. Finally, EFM and KPFM experiments are carried out, and the surface potential is extracted from the EFM and KPFM images by deconvolution processing, respectively. The extracted potential intensity is well consistent with each other and the detection resolution also complies with the theoretical analysis. Our work is helpful to perform a quantitative analysis of EFM and KPFM signals, and the developed point-mass model can also be used for other cantilever beam deflection problems.

Microscopic charge injection into the SiC/Si nanocrystals/SiC sandwiched structures through a biased conductive AFM tip is subsequently characterized by both electrostatic force microscopy and Kelvin probe force microscopy (KPFM). The charge injection and retention characteristics are found to be affected by not only the band offset at the Si nanocrystals/SiC interface but also the doping type of the Si substrate. On the other hand, capacitance-voltage (C-V) measurements investigate the macroscopic charging effect of the sandwiched structures with a thicker SiC capping layer, where the charges are injected from the Si substrates. The calculated macroscopic charging density is 3-4 times that of the microscopic one, and the possible reason is the underestimation of the microscopic charging density caused by the averaging effect and detection delay in the KPFM measurements.