Abstract:A multifrequency open loop Kelvin probe force microscopy (KPFM) approach utilizing photothermal as opposed to electrical excitation is developed. Photothermal band excitation (PthBE)-KPFM is implemented here in a grid mode on a model test sample comprising a metal-insulator junction with local charge-patterned regions. Unlike the previously described open loop BE-KPFM, which relies on capacitive actuation of the cantilever, photothermal actuation is shown to be highly sensitive to the electrostatic force gradi… Show more
“…The changes in the Fermi levels of the nanoforged MoSe 2 were explored using Band-Excitation Kelvin Probe Microscopy (BE-KPFM) 36 37 38 . The difference in Fermi levels stems from trapped charges and uncompensated dangling bonds present after irradiation, as highlighted by the DFT calculations in Fig.…”
Development of devices and structures based on the layered 2D materials critically hinges on the capability to induce, control, and tailor the electronic, transport, and optoelectronic properties via defect engineering, much like doping strategies have enabled semiconductor electronics and forging enabled introduction the of iron age. Here, we demonstrate the use of a scanning helium ion microscope (HIM) for tailoring the functionality of single layer MoSe2 locally, and decipher associated mechanisms at the atomic level. We demonstrate He+ beam bombardment that locally creates vacancies, shifts the Fermi energy landscape and increases the Young’s modulus of elasticity. Furthermore, we observe for the first time, an increase in the B-exciton photoluminescence signal from the nanoforged regions at the room temperature. The approach for precise defect engineering demonstrated here opens opportunities for creating functional 2D optoelectronic devices with a wide range of customizable properties that include operating in the visible region.
“…The changes in the Fermi levels of the nanoforged MoSe 2 were explored using Band-Excitation Kelvin Probe Microscopy (BE-KPFM) 36 37 38 . The difference in Fermi levels stems from trapped charges and uncompensated dangling bonds present after irradiation, as highlighted by the DFT calculations in Fig.…”
Development of devices and structures based on the layered 2D materials critically hinges on the capability to induce, control, and tailor the electronic, transport, and optoelectronic properties via defect engineering, much like doping strategies have enabled semiconductor electronics and forging enabled introduction the of iron age. Here, we demonstrate the use of a scanning helium ion microscope (HIM) for tailoring the functionality of single layer MoSe2 locally, and decipher associated mechanisms at the atomic level. We demonstrate He+ beam bombardment that locally creates vacancies, shifts the Fermi energy landscape and increases the Young’s modulus of elasticity. Furthermore, we observe for the first time, an increase in the B-exciton photoluminescence signal from the nanoforged regions at the room temperature. The approach for precise defect engineering demonstrated here opens opportunities for creating functional 2D optoelectronic devices with a wide range of customizable properties that include operating in the visible region.
“…This approach is expected to be immediately applicable for other resonance-based SPM techniques including atomic force acoustic microscopy (AFAM) 48,49 , magnetic force microscopy (MFM) 50 , and KPFM. 51 In the future, the implementation of these networks into hardware will greatly accelerate processing, and thereby enhance effective instrument capabilities with existing experimental Fig. 6 Piezoresponse force microscopy phase maps obtained by fitting the lateral PFM signal with decreasing drive amplitude: a comparison of least-squares with uniform guesses (a), least-squares with guesses generated using traditional methods (b), deep neural network fitting (c) and a hybrid fit (d)…”
The rapid development of spectral-imaging methods in scanning probe, electron, and optical microscopy in the last decade have given rise for large multidimensional datasets. In many cases, the reduction of hyperspectral data to the lower-dimension materialsspecific parameters is based on functional fitting, where an approximate form of the fitting function is known, but the parameters of the function need to be determined. However, functional fits of noisy data realized via iterative methods, such as least-square gradient descent, often yield spurious results and are very sensitive to initial guesses. Here, we demonstrate an approach for the reduction of the hyperspectral data using a deep neural network approach. A combined deep neural network/least-square approach is shown to improve the effective signal-to-noise ratio of band-excitation piezoresponse force microscopy by more than an order of magnitude, allowing characterization when very small driving signals are used or when a material's response is weak.
“…The parabolic dependence of the electrostatic force can be recovered directly by plotting the cantilever response versus the applied voltage as seen in Figure 3. This measurement can be compared with conventional Kelvin probe force spectroscopy (KPFS), in which a linear DC bias sweep is applied to either the tip or the sample, over a single sample location while monitoring the electrostatic force (or force gradient) response using heterodyne detection [66]. This approach avoids many of the complications associated with typical closed-loop KPFM [62] and has even been used to image a single molecular charge under UHV. Figure 3 G-Mode KPFM.…”
Scanning Probe Microscopy (SPM) has unlocked the nanoworld for exploration and control. While substantial effort has been dedicated toward the development of better instrumental platforms and probes, opportunities related to signal processing and data acquisition in SPM are often overlooked. Here, we discuss opportunities offered by capturing the full information of the data stream from the detector, referred to as General Mode (G-Mode) SPM. This approach allows exploration of the complex tip-surface interactions, spatial mapping of multidimensional variability of material properties and their mutual interactions, and imaging at the information channel capacity limit, providing a new paradigm for SPM detection.
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