Multicolor Inks of Black Phosphorus for Midwave-Infrared Optoelectronics.

Black phosphorus (bP) based ink with a bulk bandgap of 0.33 eV (λ = 3.7 µm) has recently been shown to be promising for large-area, high performance mid-wave infrared (MWIR) optoelectronics. However, the development of multicolor bP inks expanding across the MWIR wavelength range has been challenging. Here a multicolor ink process based on bP with spectral emission tuned from 0.28 eV (λ = 4.4 µm) to 0.8 eV (λ = 1.5 µm) is demonstrated. Specifically, through the reduction of bP particle size distribution (i.e., lateral dimension and thickness), the optical bandgap systematically blueshifts, reaching up to 0.8 eV. Conversely, alloying bP with arsenic (bP1- xAsx) induces a redshift in the bandgap to 0.28 eV. The ink processed films are passivated with an infrared-transparent epoxy for stable infrared emission in ambient air. Utilizing these multicolor bP-based inks as an infrared light source, a gas sensing system is demonstrated that selectively detects gases, such as CO2 and CH4 whose absorption band varies around 4.3 and 3.3 µm, respectively. The presented ink formulation sets the stage for the advancement of multiplex MWIR optoelectronics, including spectrometers and spectral imaging using a low-cost material processing platform.

Oxygen Transport through Amorphous Cathode Coatings in Solid-State Batteries.

All solid-state batteries (SSBs) are considered the most promising path to enabling higher energy-density portable energy, while concurrently improving safety as compared to current liquid electrolyte solutions. However, the desire for high energy necessitates the choice of high-voltage cathodes, such as nickel-rich layered oxides, where degradation phenomena related to oxygen loss and structural densification at the cathode surface are known to significantly compromise the cycle and thermal stability. In this work, we show, for the first time, that even in an SSB, and when protected by an intact amorphous coating, the LiNi0.5Mn0.3Co0.2O2 (NMC532) surface transforms from a layered structure into a rocksalt-like structure after electrochemical cycling. The transformation of the surface structure of the Li3B11O18 (LBO)-coated NMC532 cathode in a thiophosphate-based solid-state cell is characterized by high-resolution complementary electron microscopy techniques and electron energy loss spectroscopy. Ab initio molecular dynamics corroborate facile transport of O2- in the LBO coating and in other typical coating materials. This work identifies that oxygen loss remains a formidable challenge and barrier to long-cycle life high-energy storage, even in SSBs with durable, amorphous cathode coatings, and directs attention to considering oxygen permeability as an important new design criteria for coating materials.

Mid-Infrared, Optically Active Black Phosphorus Thin Films on Centimeter Scale.

Black phosphorus (BP) is a narrow bandgap (∼0.3 eV) semiconductor with a great potential for optoelectronic devices in the mid-infrared wavelength. However, it has been challenging to achieve a high-quality scalable BP thin film. Here we present the successful synthesis of optically active BP films on a centimeter scale. We utilize the pulsed laser deposition of amorphous red phosphorus, another allotrope of phosphorus, followed by a high-pressure treatment at ∼8 GPa to induce a phase conversion into BP crystals. The crystalline quality was improved through thermal annealing, resulting in the observation of photoluminescence emission at mid-infrared wavelengths. We demonstrate high-pressure conversion on a centimeter scale with a continuous film with a thickness of ∼18 nm using a flat-belt-type high-pressure apparatus. This synthesis procedure presents a promising route to obtain optical-quality BP films, enabling the exploration of integrated optoelectronic device applications such as light-emitting devices and mid-infrared cameras on a chip scale.

Quantitative Mid-infrared Photoluminescence Characterization of Black Phosphorus-Arsenic Alloys.

Black phosphorus (bP) is a promising material for mid-infrared (mid-IR) optoelectronic applications, exhibiting high performance light emission and detection. Alloying bP with arsenic extends its operation toward longer wavelengths from 3.7 µm (bP) to 5 µm (bP3As7), which is of great practical interest. Quantitative optical characterizations are performed to establish black phosphorus-arsenic (bPAs) alloys optoelectronic quality. Anisotropic optical constants (refractive index, extinction coefficient, and absorption coefficient) of bPAs alloys from near-infrared to mid-IR (0.2-0.9 eV) are extracted with reflection measurements, which helps optical device design. Quantitative photoluminescence (PL) of bPAs alloys with different As concentrations are measured from room temperature to 77 K. PL quantum yield measurements reveal a 2 orders of magnitude decrease in radiative efficiency with increasing As concentration. An optical cavity is designed for bP3As7, which allows for up to an order of magnitude enhancement in the quantum yield due to the Purcell effect. Our comprehensive optical characterization provides the foundation for high performance mid-IR optical device design using bPAs alloys.

Much more to explore with an oxidation state of nearly four: Pr valence instability in intermetallic m-Pr2Co3Ge5.

For some intermetallic compounds containing lanthanides, structural transitions can result in intermediate electronic states between trivalency and tetravalency; however, this is rarely observed for praseodymium compounds. The dominant trivalency of praseodymium limits potential discoveries of emergent quantum states in itinerant 4f1 systems accessible using Pr4+-based compounds. Here, we use in situ powder x-ray diffraction and in situ electron energy-loss spectroscopy (EELS) to identify an intermetallic example of a dominantly Pr4+ state in the polymorphic system Pr2Co3Ge5. The structure-valence transition from a nearly full Pr4+ electronic state to a typical Pr3+ state shows the potential of Pr-based intermetallic compounds to host valence-unstable states and provides an opportunity to discover previously unknown quantum phenomena. In addition, this work emphasizes the need for complementary techniques like EELS when evaluating the magnetic and electronic properties of Pr intermetallic systems to reveal details easily overlooked when relying on bulk magnetic measurements alone.

Generalization Across Experimental Parameters in Neural Network Analysis of High-Resolution Transmission Electron Microscopy Datasets.

Neural networks are promising tools for high-throughput and accurate transmission electron microscopy (TEM) analysis of nanomaterials, but are known to generalize poorly on data that is "out-of-distribution" from their training data. Given the limited set of image features typically seen in high-resolution TEM imaging, it is unclear which images are considered out-of-distribution from others. Here, we investigate how the choice of metadata features in the training dataset influences neural network performance, focusing on the example task of nanoparticle segmentation. We train and validate neural networks across curated, experimentally collected high-resolution TEM image datasets of nanoparticles under various imaging and material parameters, including magnification, dosage, nanoparticle diameter, and nanoparticle material. Overall, we find that our neural networks are not robust across microscope parameters, but do generalize across certain sample parameters. Additionally, data preprocessing can have unintended consequences on neural network generalization. Our results highlight the need to understand how dataset features affect deployment of data-driven algorithms.

Effect of solid-electrolyte pellet density on failure of solid-state batteries.

Despite the potentially higher energy density and improved safety of solid-state batteries (SSBs) relative to Li-ion batteries, failure due to Li-filament penetration of the solid electrolyte and subsequent short circuit remains a critical issue. Herein, we show that Li-filament growth is suppressed in solid-electrolyte pellets with a relative density beyond ~95%. Below this threshold value, however, the battery shorts more easily as the density increases due to faster Li-filament growth within the percolating pores in the pellet. The microstructural properties (e.g., pore size, connectivity, porosity, and tortuosity) of [Formula: see text] with various relative densities are quantified using focused ion beam-scanning electron microscopy tomography and permeability tests. Furthermore, modeling results provide details on the Li-filament growth inside pores ranging from 0.2 to 2 µm in size. Our findings improve the understanding of the failure modes of SSBs and provide guidelines for the design of dendrite-free SSBs.

Analysis of Strain and Defects in Tellurium-WSe2 Moiré Heterostructures Using Scanning Nanodiffraction.

In recent years, there has been an increasing focus on 2D nongraphene materials that range from insulators to semiconductors to metals. As a single-elemental van der Waals semiconductor, tellurium (Te) has captivating anisotropic physical properties. Recent work demonstrated growth of ultrathin Te on WSe2 with the atomic chains of Te aligned with the armchair directions of the substrate using physical vapor deposition (PVD). In this system, a moiré superlattice is formed where micrometer-scale Te flakes sit on top of the continuous WSe2 film. Here, we determined the precise orientation of the Te flakes with respect to the substrate and detailed structure of the resulting moiré lattice by combining electron microscopy with image simulations. We directly visualized the moiré lattice using center of mass-differential phase contrast (CoM-DPC). We also investigated the local strain within the Te/WSe2 layered materials using scanning nanodiffraction techniques. There is a significant tensile strain at the edges of flakes along the direction perpendicular to the Te chain direction, which is an indication of the preferred orientation for the growth of Te on WSe2. In addition, we observed local strain relaxation regions within the Te film, specifically attributed to misfit dislocations, which we characterize as having a screw-like nature. The detailed structural analysis gives insight into the growth mechanisms and strain relaxation in this moiré heterostructure.

Solving complex nanostructures with ptychographic atomic electron tomography.

Transmission electron microscopy (TEM) is essential for determining atomic scale structures in structural biology and materials science. In structural biology, three-dimensional structures of proteins are routinely determined from thousands of identical particles using phase-contrast TEM. In materials science, three-dimensional atomic structures of complex nanomaterials have been determined using atomic electron tomography (AET). However, neither of these methods can determine the three-dimensional atomic structure of heterogeneous nanomaterials containing light elements. Here, we perform ptychographic electron tomography from 34.5 million diffraction patterns to reconstruct an atomic resolution tilt series of a double wall-carbon nanotube (DW-CNT) encapsulating a complex ZrTe sandwich structure. Class averaging the resulting tilt series images and subpixel localization of the atomic peaks reveals a Zr11Te50 structure containing a previously unobserved ZrTe2 phase in the core. The experimental realization of atomic resolution ptychographic electron tomography will allow for the structural determination of a wide range of beam-sensitive nanomaterials containing light elements.

Ordering of room-temperature magnetic skyrmions in a polar van der Waals magnet.

Control and understanding of ensembles of skyrmions is important for realization of future technologies. In particular, the order-disorder transition associated with the 2D lattice of magnetic skyrmions can have significant implications for transport and other dynamic functionalities. To date, skyrmion ensembles have been primarily studied in bulk crystals, or as isolated skyrmions in thin film devices. Here, we investigate the condensation of the skyrmion phase at room temperature and zero field in a polar, van der Waals magnet. We demonstrate that we can engineer an ordered skyrmion crystal through structural confinement on the µm scale, showing control over this order-disorder transition on scales relevant for device applications.

Unraveling Li growth kinetics in solid electrolytes due to electron beam charging.

Revealing the local structure of solid electrolytes (SEs) with electron microscopy is critical for the fundamental understanding of the performance of solid-state batteries (SSBs). However, the intrinsic structural information in the SSB can be misleading if the sample's interactions with the electron beams are not fully understood. In this work, we systematically investigate the effect of electron beams on Al-doped lithium lanthanum zirconium oxide (LLZO) under different imaging conditions. Li metal is observed to grow directly on the clean surface of LLZO. The Li metal growth kinetics and the morphology obtained are found to be heavily influenced by the temperature, accelerating voltage, and electron beam intensity. We prove that the lithium growth is due to the LLZO delithiation activated by a positive charging effect under electron beam emission. Our results deepen the understanding of the electron beam impact on SEs and provide guidance for battery material characterization using electron microscopy.

Direct Observation of Transient Structural Dynamics of Atomically Thin Halide Perovskite Nanowires.

Halide perovskite is a unique dynamical system, whose structural and chemical processes happening across different timescales have significant impact on its physical properties and device-level performance. However, due to its intrinsic instability, real-time investigation of the structure dynamics of halide perovskite is challenging, which hinders the systematic understanding of the chemical processes in the synthesis, phase transition, and degradation of halide perovskite. Here, we show that atomically thin carbon materials can stabilize ultrathin halide perovskite nanostructures against otherwise detrimental conditions. Moreover, the protective carbon shells enable atomic-level visualization of the vibrational, rotational, and translational movement of halide perovskite unit cells. Albeit atomically thin, protected halide perovskite nanostructures can maintain their structural integrity up to an electron dose rate of 10,000 e-/Å2·s while exhibiting unusual dynamical behaviors pertaining to the lattice anharmonicity and nanoscale confinement. Our work demonstrates an effective method to protect beam-sensitive materials during in situ observation, unlocking new solutions to study new modes of structure dynamics of nanomaterials.

Understanding the Influence of Receptive Field and Network Complexity in Neural Network-Guided TEM Image Analysis.

Trained neural networks are promising tools to analyze the ever-increasing amount of scientific image data, but it is unclear how to best customize these networks for the unique features in transmission electron micrographs. Here, we systematically examine how neural network architecture choices affect how neural networks segment, or pixel-wise separate, crystalline nanoparticles from amorphous background in transmission electron microscopy (TEM) images. We focus on decoupling the influence of receptive field, or the area of the input image that contributes to the output decision, from network complexity, which dictates the number of trainable parameters. For low-resolution TEM images which rely on amplitude contrast to distinguish nanoparticles from background, we find that the receptive field does not significantly influence segmentation performance. On the other hand, for high-resolution TEM images which rely on both amplitude and phase-contrast changes to identify nanoparticles, receptive field is an important parameter for increased performance, especially in images with minimal amplitude contrast. Rather than depending on atom or nanoparticle size, the ideal receptive field seems to be inversely correlated to the degree of nanoparticle contrast in the image. Our results provide insight and guidance as to how to adapt neural networks for applications with TEM datasets.

Analysis of Interpretable Data Representations for 4D-STEM Using Unsupervised Learning.

Understanding the structure of materials is crucial for engineering devices and materials with enhanced performance. Four-dimensional scanning transmission electron microscopy (4D-STEM) is capable of mapping nanometer-scale local crystallographic structure over micron-scale field of views. However, 4D-STEM datasets can contain tens of thousands of images from a wide variety of material structures, making it difficult to automate detection and classification of structures. Traditional automated analysis pipelines for 4D-STEM focus on supervised approaches, which require prior knowledge of the material structure and cannot describe anomalous or deviant structures. In this article, a pipeline for engineering 4D-STEM feature representations for unsupervised clustering using non-negative matrix factorization (NMF) is introduced. Each feature is evaluated using NMF and results are presented for both simulated and experimental data. It is shown that some data representations more reliably identify overlapping grains. Additionally, real space refinement is applied to identify spatially distinct sample regions, allowing for size and shape analysis to be performed. This work lays the foundation for improved analysis of nanoscale structural features in materials that deviate from expected crystallographic arrangement using 4D-STEM.