Spatial heterogeneity in composition and organisation of the primary cell wall affects the mechanics of cellular morphogenesis. However, directly correlating cell wall composition, organisation and mechanics has been challenging. To overcome this barrier, we applied atomic force microscopy coupled with infrared (AFM-IR) spectroscopy to generate spatially correlated maps of chemical and mechanical properties for paraformaldehyde-fixed, intact Arabidopsis thaliana epidermal cell walls. AFM-IR spectra were deconvoluted by non-negative matrix factorisation (NMF) into a linear combination of IR spectral factors representing sets of chemical groups comprising different cell wall components. This approach enables quantification of chemical composition from IR spectral signatures and visualisation of chemical heterogeneity at nanometer resolution. Cross-correlation analysis of the spatial distribution of NMFs and mechanical properties suggests that the carbohydrate composition of cell wall junctions correlates with increased local stiffness. Together, our work establishes new methodology to use AFM-IR for the mechanochemical analysis of intact plant primary cell walls.

The advent of modern, high-speed electron detectors has made the collection of multidimensional hyperspectral transmission electron microscopy datasets, such as 4D-STEM, a routine. However, many microscopists find such experiments daunting since analysis, collection, long-term storage, and networking of such datasets remain challenging. Some common issues are their large and unwieldy size that often are several gigabytes, non-standardized data analysis routines, and a lack of clarity about the computing and network resources needed to utilize the electron microscope. The existing computing and networking bottlenecks introduce significant penalties in each step of these experiments, and thus, real-time analysis-driven automated experimentation for multidimensional TEM is challenging. One solution is to integrate microscopy with edge computing, where moderately powerful computational hardware performs the preliminary analysis before handing off the heavier computation to high-performance computing (HPC) systems. Here we trace the roots of computation in modern electron microscopy, demonstrate deep learning experiments running on an edge system, and discuss the networking requirements for tying together microscopes, edge computers, and HPC systems.

An emerging family of materials—metal halide perovskites (MHPs)—have made incredible achievements in optoelectronics in the past decade. Owing to its potential role in optoelectronic properties, the ferroic state of MHPs has been investigated by lots of researchers. Here, we review the literature regarding investigations into possible ferroic behaviors in MHPs. We summarize the recent discoveries of ferroic twin domains in MHPs. We examine the ferroelasticity and the ferroelectricity of these twin domains. Several properties relevant to the twin domains are critically analyzed, including crystallographic structure, mechanical variation, chemical variation, etc. Finally, we discussed the effects of these domains on materials’ optoelectronic properties and their potential roles in photovoltaic action.

Helium ion microscopy (HIM), enabled by a gas field ion source (GFIS), is an emerging imaging and nanofabrication technique compatible with many applications in materials science. The scanning electron microscope (SEM) has become ubiquitous in materials science for high-resolution imaging of materials. However, due to the fundamental limitation in focusing of electron beams, ion-beam microscopy is now being developed (e.g., at 20 kV the SEM beam diameter ranges from 0.5 to 1 nm, whereas the HIM offers 0.35 nm). The key technological advantage of the HIM is in its multipurpose design that excels in a variety of disciplines. The HIM offers higher resolution than the best available SEMs as well as the traditional gallium liquid-metal ion source (LMISs) focused ion beams (FIBs), and is capable of imaging untreated biological or other insulating samples with unprecedented resolution, depth of field, materials contrast, and image quality. GFIS FIBs also offer a direct path to defect engineering via ion implantation, three-dimensional direct write using gaseous and liquid precursors, and chemical-imaging options with secondary ion mass spectrometry. HIM covers a wide range of tasks that otherwise would require multiple tools or specialized sample preparation. In this article, we describe the underlying technology, present materials, relevant applications, and offer an outlook for the potential of FIB technology in processing materials.