Chemical analysis at the nanoscale is critical to advance our understanding of materials and systems from medicine and biology to material science and computing. Macroscale-observed phenomena in these systems are in the large part driven by processes that take place at the nanoscale and are highly heterogeneous. Therefore, there is a clear need to develop a new technology that enables correlative imaging of material functionalities with nanoscale spatial and chemical resolutions that will enable us to untangle the structure−function relationship of functional materials. Therefore, here, we report on the analytical figures of merit of the newly developed correlative chemical imaging technique of helium ion microscopy coupled with secondary ion mass spectrometry (HIM-SIMS) that enables multimodal topographical/chemical imaging of organic and inorganic materials at the nanoscale. In HIM-SIMS, a focused ion beam acts as a sputtering and ionization source for chemical analysis along with simultaneous high-resolution surface imaging, providing an unprecedented level of spatial resolution for gathering chemical information on organic and inorganic materials. In this work, we demonstrate HIM-SIMS as a platform for a next-generation tool for an in situ material design and analysis capable of down to 8 nm spatial resolution chemical imaging, layered metal structure imaging in depth profiling, single graphene layer detection, and spectral analysis of metals, metal oxides, and polymers.

The current effort demonstrates that lutetium oxyorthosilicate doped with 1–10% cerium (Lu2SiO5:Ce, LSO:Ce) radioluminescent particles can be coated with a single dye or multiple dyes and generate an effective energy transfer between the core and dye(s) when excited via X-rays. LSO:Ce particles were surface modified with an alkyne modified naphthalimide (6-piperidin-1-yl-2-prop-2-yn-1-yl-1H-benzo­[de]­isoquinoline-1,3-(2H)-dione, AlNap) and alkyne modified rhodamine B (N-(6-diethylamino)-9-{2-[(prop-2-yn-1-yloxy)­carbonyl]­phenyl}-3H-xanthen-3-ylidene)-N-ethylethanaminium, AlRhod) derivatives to tune the X-ray excited optical luminescence from blue to green to red using Förster Resonance Energy Transfer (FRET). As X-rays penetrate tissue much more effectively than UV/visible light, the fluorophore modified phosphors may have applications as bioimaging agents. To that end, the phosphors were incubated with rat cortical neurons and imaged after 24 h. The LSO:Ce surface modified with AlNap was able to be successfully imaged in vitro with a low-output X-ray tube. To use the LSO:Ce fluorophore modified particles as imaging agents, they must not induce cytotoxicity. Neither LSO:Ce nor LSO:Ce modified with AlNap showed any cytotoxicity toward normal human dermal fibroblast cells or mouse cortical neurons, respectively.

Genome engineering for materials synthesis is a promising avenue for manufacturing materials with unique properties under ambient conditions. Biomineralization in diatoms, unicellular algae that use silica to construct micron-scale cell walls with nanoscale features, is an attractive candidate for functional synthesis of materials for applications including photonics, sensing, filtration, and drug delivery. Therefore, controllably modifying diatom structure through targeted genetic modifications for these applications is a very promising field. In this work, we used gene knockdown in Thalassiosira pseudonana diatoms to create modified strains with changes to structural morphology and linked genotype to phenotype using supervised machine learning. An artificial neural network (NN) was developed to distinguish wild and modified diatoms based on the SEM images of frustules exhibiting phenotypic changes caused by a specific protein (Thaps3_21880), resulting in 94% detection accuracy. Class activation maps visualized physical changes that allowed the NNs to separate diatom strains, subsequently establishing a specific gene that controls pores. A further NN was created to batch process image data, automatically recognize pores, and extract pore-related parameters. Class interrelationship of the extracted paraments was visualized using a multivariate data visualization tool, called CrossVis, and allowed to directly link changes in morphological diatom phenotype of pore size and distribution with changes in the genotype.