Unraveling local dynamic charge processes is vital for progress in diverse fields, from microelectronics to energy storage. This relies on the ability to map charge carrier motion across multiple length- and timescales and understanding how these processes interact with the inherent material heterogeneities. Towards addressing this challenge, we introduce high-speed sparse scanning Kelvin probe force microscopy, which combines sparse scanning and image reconstruction. This approach is shown to enable sub-second imaging (>3 frames per second) of nanoscale charge dynamics, representing several orders of magnitude improvement over traditional Kelvin probe force microscopy imaging rates. Bridging this improved spatiotemporal resolution with macroscale device measurements, we successfully visualize electrochemically mediated diffusion of mobile surface ions on a LaAlO₃/SrTiO₃planar device. Such processes are known to impact band-alignment and charge-transfer dynamics at these heterointerfaces. Furthermore, we monitor the diffusion of oxygen vacancies at the single grain level in polycrystalline TiO₂. Through temperature-dependent measurements, we identify a charge diffusion activation energy of 0.18 eV, in good agreement with previously reported values and confirmed by DFT calculations. Together, these findings highlight the effectiveness and versatility of our method in understanding ionic charge carrier motion in microelectronics or nanoscale material systems.

With the advent of large language models (LLMs), in both the open source and proprietary domains, attention is turning to how to exploit such artificial intelligence (AI) systems in assisting complex scientific tasks, such as material synthesis, characterization, analysis and discovery. Here, we explore the utility of LLMs, particularly ChatGPT4, in combination with application program interfaces (APIs) in tasks of experimental design, programming workflows, and data analysis in scanning probe microscopy, using both in-house developed APIs and APIs given by a commercial vendor for instrument control. We find that the LLM can be especially useful in converting ideations of experimental workflows to executable code on microscope APIs. Beyond code generation, we find that the GPT4 is capable of analyzing microscopy images in a generic sense. At the same time, we find that GPT4 suffers from an inability to extend beyond basic analyses for more in-depth technical experimental design. We argue that an LLM specifically fine-tuned for individual scientific domains can potentially be a better language interface for converting scientific ideations from human experts to executable workflows. Such a synergy between human expertise and LLM efficiency in experimentation can open new doors for accelerating scientific research, enabling effective experimental protocols sharing in the scientific community.

Mapping the dielectric constant at the nanoscale of samples showing a complex topography, such as non-planar nanocomposite materials or single cells, poses formidable challenges to existing nanoscale dielectric microscopy techniques. Here we overcome these limitations by introducing Scanning Dielectric Force Volume Microscopy. This scanning probe microscopy technique is based on the acquisition of electrostatic force approach curves at every point of a sample and its post-processing and quantification by using a computational model that incorporates the actual measured sample topography. The technique provides quantitative nanoscale images of the local dielectric constant of the sample with unparalleled accuracy, spatial resolution and statistical significance, irrespectively of the complexity of its topography. We illustrate the potential of the technique by presenting a nanoscale dielectric constant map of a single bacterial cell, including its small-scale appendages. The bacterial cell shows three characteristic equivalent dielectric constant values, namely, ε_r,bac1 = 2.6 ± 0.2, ε_r,bac2 = 3.6 ± 0.4 and ε_r,bac3 = 4.9 ± 0.5, which enable identifying different dielectric properties of the cell wall and of the cytoplasmatic region, as well as, the existence of variations in the dielectric constant along the bacterial cell wall itself. Scanning Dielectric Force Volume Microscopy is expected to have an important impact in Materials and Life Sciences where the mapping of the dielectric properties of samples showing complex nanoscale topographies is often needed.