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At least 631 records · Page 35

Method of information entropy for convergence assessment of molecular dynamics simulations

The lack of a reliable method to evaluate the convergence of molecular dynamics simulations has contributed to discrepancies in different areas of molecular dynamics. Here, the method of information entropy is introduced to molecular dynamics for stationarity assessment. The Shannon information entropy formalism is used to monitor the convergence of the atom motion to a steady state in a continuous spatial domain and is also used to assess the stationarity of calculated multidimensional fields such as the temperature field in a discrete spatial domain. It is demonstrated in this work that monitoring the information entropy of the atom position matrix provides a clear indicator of reaching steady state in radiation damage simulations, non-equilibrium molecular dynamics thermal conductivity computations, and simulations of Poiseuille and Couette flow in nanochannels. A main advantage of the present technique is that it is non-local and relies on fundamental quantities available in all molecular dynamics simulations. Unlike monitoring average temperature, the technique is applicable to simulations that conserve total energy such as reverse non-equilibrium molecular dynamics thermal conductivity computations and to simulations where energy dissipates through a boundary as in radiation damage simulations. The method is applied to simulations of iron using the Tersoff/ZBL splined potential, silicon using the Stillinger–Weber potential, and to Lennard–Jones fluid. Its applicability to both solids and fluids shows that the technique has potential for generalization to other areas in molecular dynamics.

74 ATOMIC AND MOLECULAR PHYSICS↗

Experimental determination of the magnetic anisotropy in five-coordinated Co( II ) field-induced single molecule magnets

Magnetic anisotropy of the central metal atom is a crucial property of single molecule magnets (SMMs). Small structural changes can alter the magnetic properties, and accurate experimental methods to investigate magnetic anisotropy are therefore critical. Here, we investigate two five-coordinated Co( II ) SMMs, [CoCl 2 Cltpy] (1) and [CoBr 2 Cltpy] (2) (Cltpy = 4′-chloro-2,2′:6′,2′′-terpyridine), through multiple techniques. Ab initio theoretical calculations performed on the two compounds show that both possess axial magnetic anisotropy with the magnetic easy axis pointing towards one of the terminal halogen atoms. Theoretical calculations on SMMs are typically done on isolated molecular species, and to validate this approximation the magnetic anisotropy was further studied through experimental techniques. EPR measurements confirm an axial anisotropy of 1, and magnetic measurements provide experimental Zero-Field Splitting (ZFS) parameters, showing that the values from theoretical calculations are slightly overestimated. The X-ray electron density determined from 20 K single-crystal synchrotron X-ray diffraction data provides estimated d-orbital populations also suggesting axial magnetic anisotropy in both systems, and furthermore suggesting a more pronounced axiality in 1 compared to 2. This is in good agreement with the results obtained from both magnetic measurements and theoretical calculations. The magnetic anisotropy of 1 is quantified experimentally through polarized powder neutron diffraction via the site susceptibility method, confirming an axial magnetic anisotropy of the compound. A slight deviation in the easy axis direction is observed between experimental and theoretical results. This, together with the overestimation of the ZFS parameters from theoretical calculations, shows that experimental investigation of the magnetic anisotropy of SMMs is of high relevance. Magnetic anisotropy of the central metal atom is a crucial property of single molecule magnets (SMMs).

Slavensky, Hannah H. [Aarhus Univ. (Denmark)] (ORC↗

Redefining precision interferometry and spectroscopy with high-performance optical interference coatings

High-performance optical interference coatings have transformed precision interferometry and spectroscopy by enabling unparalleled control over light–matter interactions. This review explores recent innovations in ion-beam sputtered amorphous dielectric, as well as substrate-transferred crystalline coatings, and their impact on systems at the forefront of precision metrology. These state-of-the-art coating techniques generate multilayers with ultralow optical losses, yielding mirrors with exceptional reflectivity. Refinements in their noise performance push the ultimate limits of sensitivity, resolution, and stability in demanding laser-based metrology applications. These technologies underpin the most advanced timekeeping and spatial measurement tools, enabling high-finesse reference cavities for the world’s most precise optical atomic clocks and low-noise reflective test masses for km-baseline gravitational-wave detectors. Emerging hybrid designs combining these techniques expand access to the mid-infrared spectral region, enabling the first ultralow-optical-loss coatings in the 3000–5000 nm wavelength range for enhanced spectroscopy and trace-gas detection. We highlight how these technologies redefine coating performance metrics and set new benchmarks in quantum science, fundamental physics, and precision optical sensing.

Cole, Garrett D. [University of Arizona, Tucson, A↗

Identifying Dense NiSe 2 /CoSe 2 Heterointerfaces Coupled with Surface High-Valence Bimetallic Sites for Synergistically Enhanced Oxygen Electrocatalysis

Constructing heterostructures with abundant interfaces is essential for integrating the multiple functionalities in single entities. Herein, the synthesis of NiSe 2 /CoSe 2 heterostructures with different interfacial densities via an innovative strategy of successive ion injection is reported. The resulting hybrid electrocatalyst with dense heterointerfaces exhibits superior electrocatalytic properties in an alkaline electrolyte, superior to other benchmarks and precious metal catalysts. Advanced synchrotron techniques, post structural characterizations, and density functional theory (DFT) simulations reveal that the introduction of atomic-level interfaces can lower the oxidation overpotential of bimetallic Ni and Co active sites (whereas Ni$^{2+}$ can be more easily activated than Co$^{2+}$) and induce the electronic interaction between the core selenides and surface in situ generated oxides/hydroxides, which play a critical role in synergistically reducing energetic barriers and accelerating reaction kinetics for catalyzing the oxygen evolution. Hence, the heterointerface structure facilitates the catalytic performance enhancement via increasing the intrinsic reactivity of metallic atoms and enhancing the synergistic effect between the inner selenides and surface oxidation species. This work not only complements the understanding on the origins of the activity of electrocatalysts based on metal selenides, but also sheds light on further surface and interfacial engineering of advanced hybrid materials.

36 MATERIALS SCIENCE↗

Manipulating Pore Topology and Functionality to Promote Fluorocarbon-Based Adsorption Cooling

With the worldwide demand for refrigeration and cooling expected to triple, it is increasingly important to search for alternative energy resources to drive the refrigeration cycles with reduced electricity consumption. Recently, adsorption cooling has gained increased attention since energy reallocation in such systems is based on gas adsorption/desorption, which can be driven by waste/natural heat sources. Eco-friendly sorption-based cooling relies on the cyclic transfer of refrigerant gas from a high to low energy state by the pseudo-compression effect resulting from adsorption and desorption. The driving force for energy transfer relies on heat rather than electricity. The performance of a sorption chiller is primarily influenced by this cyclic sorption behavior, which is characterized as the working capacity of the porous sorbent. Thus increases in this working capacity directly translate to a more compact and efficient cooling system. How-ever, a lack of highly effective sorbent/refrigerant pairs lowers cooling performance, and therefore has limited applicability. To this end, synthetic metal-organic frameworks (MOFs) and covalent organic polymers (COPs) possess higher porosity and greater tunability leading to more substantial potential benefits for adsorption, compared to traditional sorbent materials. Similarly, hydrofluorocarbon refrigerants have more favorable applicability given ease of operation above atmospheric pressures due to suitable saturated vapor pressures and boiling points. For these reasons, our work focuses on an ongoing strategy to promote sorption cooling via improvements in the sorbent/refrigerant pair. Specifically, we target the interaction of hydrofluorocarbon refrigerants with MOF/COP materials at a molecular level by interpreting the host-guest chemistry and the role of framework pore topology. These molecular level differences translate to cooling performance, which is described herein. These strategies include engineering framework porosity (i.e., pore size, pore volume) by using elongated organic linkers and stereochemistry control during synthesis; manipulating the sorb-ate/sorbent interaction by introducing functional moieties or unsaturated metal centers to enhance working capacities in narrow pressure ranges; varying pore topology/morphology to impact adsorption isotherm behavior; and leveraging defective sites within the frameworks to further enhance adsorption capability. Here this atomic level understanding of sorb-ate-sorbent interactions is conducted using various in situ experimental techniques such as synchrotron-based X-ray diffraction, X-ray absorption spectroscopy, in situ Fourier transform infrared spectroscopy, and direct sorption energies determinization with calorimetry. Moreover, the experimentally studied interactions and the corresponding adsorption mechanism are corroborated by computational studies using density functional theory (DFT) and grand canonical Monte Carlo (GCMC) simulations. Using this approach, we envision the capability to engineer designed frameworks with precise molecular control to target refrigerant molecules and thereby enhance the performance of desired working pairs for sorption-based cooling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Investigation of the Structure of Atomically Dispersed NiN x Sites in Ni and N-Doped Carbon Electrocatalysts by 61 Ni Mössbauer Spectroscopy and Simulations

Ni and nitrogen-doped carbons are selective catalysts for CO 2 reduction to CO (CO 2 R), but the hypothesized NiNx active sites are challenging to probe with traditional characterization methods. Here, we synthesize 61 Ni-enriched model catalysts, termed 61 NiPACN, in order to apply 61 Ni Mössbauer spectroscopy using synchrotron radiation ( 61 Ni-SR-MS) to characterize the structure of these atomically dispersed NiNx sites. First, we demonstrate that the CO 2 R results and standard characterization techniques (SEM, PXRD, XPS, XANES, EXAFS) point to the existence of dispersed Ni active sites. Then, 61 Ni-SR-MS reveal significant internal magnetic fields of ~5.4 T, which is characteristic of paramagnetic, high-spin Ni 2+ , in the 61NiPACN samples. Finally, theoretical calculations for a variety of Ni-N x moieties confirm that high-spin Ni 2+ is stable in non-planar, tetrahedrally distorted geometries, which results in calculated isotropic hyperfine coupling that is consistent with 61 Ni-SR-MS measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Valence-to-core X-ray emission spectroscopy of vanadium oxide and lithiated vanadyl phosphate materials

In this work, we report valence-to-core (VTC) X-ray emission spectroscopy (XES) measurements and theoretical calculations of the electrochemical sequence ε-VOPO 4 , ε-LiVOPO 4 , ε-Li 2 VOPO 4 and the reference oxides V 2 O 3 , VO 2 , and V 2 O 5 . In our analysis of these results, we establish a framework for interrogating chemical bonding that is generally applicable to a wide range of systems, including complex, extended inorganic compounds. While this latter regime has garnered less focused application than, e.g. , metalloenzymes in many excellent catalysis studies, we show that the technique provides high utility in materials-focused energy storage research. Here, sensitivities to the local atomic structure and hybridization schemes are discussed in detail. Similarly, the effect of lithiation on oxidation, delocalization, and shifts in ligand valence energy levels are all readily apparent in the analyzed results. Finally, the TDDFT projections clearly reveal the directional dependencies of the valence band at each of the vanadium sites. Our results demonstrate laboratory-based X-ray spectroscopy instrumentation is a viable route for attaining well-resolved VTC-XES features for inorganic compounds of 3d transition metals, even for samples of limited quantity or suffering from sensitivity to the atmosphere. The experimental results are in good agreement with results produced by real-space Green's function and time-dependent density functional theory (TDDFT) methods, respectively. Hence, we propose that VTC-XES, when equipped with appropriate theoretical support, can be a valuable complement to X-ray absorption pre-edge features for more detailed characterization of a compound's electronic structure. We expect similar analyses will find application in a broad range of materials chemistry research and provide both fundamental and applied insights.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

27 AlNMR chemical shift of Al(OH)$^{-}_{4}$ calculated from first principles: Assessment of error cancellation in chemically distinct reference and target systems

Predicting accurate nuclear magnetic resonance chemical shieldings relies upon cancellation of different types of errors between the theoretically calculated shielding constant of the analyte of interest and the reference. Often, the intrinsic error in computed shieldings due to basis sets, approximations in the Hamiltonian, description of the wave function, and dynamic effects is nearly identical between the analyte and reference, yet if the electronic structure or sensitivity to local environment differs dramatically, this cannot be taken for granted. Detailed prior work has examined the octahedral trivalent cation Al(H 2 O)$^{3+}_{6}$, accounting for ab initio intrinsic errors. However, the use of this species as a reference for the chemically distinct tetrahedral anion Al(OH)$^{-}_{4}$ requires an understanding of how these errors cancel, in order to define the limits of accurately predicting 27 Al chemical shielding in Al(OH)$^{-}_{4}$. In this work, we estimate the absolute shielding of the 27 Al nucleus in Al(OH)$^{-}_{4}$ at the coupled cluster level (515.1± 5.3 ppm). Shielding sensitivity to the choice of method approximation and atomic basis sets used has been evaluated. Solvent and thermal effects are assessed through ensemble averaging techniques using ab-initio molecular dynamics. The contribution of each type of intrinsic error is assessed for the Al(H 2 O)$^{3+}_{6}$ and Al(OH)$^{-}_{4}$ ions, revealing significant differences that fundamentally hamper the ability to accurately calculate the 27 Al chemical shift of Al(OH)$^{-}_{4}$ from first principles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spectroscopy-guided discovery of three-dimensional structures of disordered materials with diffusion models

Spectroscopy techniques such as x-ray absorption near edge structure (XANES) provide valuable insights into the atomic structures of materials, yet the inverse prediction of precise structures from spectroscopic data remains a formidable challenge. In this study, we introduce a framework that combines generative artificial intelligence models with XANES spectroscopy to predict three-dimensional atomic structures of disordered systems, using amorphous carbon (a-C) as a model system. In this work, we introduce a new framework based on the diffusion model, a recent generative machine learning method, to predict 3D structures of disordered materials from a target property. For demonstration, we apply the model to identify the atomic structures of a-C as a representative material system from the target XANES spectra. We show that conditional generation guided by XANES spectra reproduces key features of the target structures. Furthermore, we show that our model can steer the generative process to tailor atomic arrangements for a specific XANES spectrum. Finally, our generative model exhibits a remarkable scale-agnostic property, thereby enabling generation of realistic, large-scale structures through learning from a small-scale dataset (i.e. with small unit cells). Our work represents a significant stride in bridging the gap between materials characterization and atomic structure determination; in addition, it can be leveraged for materials discovery in exploring various material properties as targeted.

36 MATERIALS SCIENCE↗

Spectroscopic diagnostics of high-temperature plasma in stellar coronae using Fe XXIV-XXIV K-shell lines with XRISM

The RS CVn type binary star GT Muscae was observed during its quiescence using the Resolve X-ray microcalorimeter spectrometer onboard XRISM. The main and satellite lines of the Fe XXIV-XXIV K-shell transitions were resolved for the first time from stellar sources. We conducted line ratio analysis to investigate any deviations from collisional ionization equilibrium and Maxwell electron energy distribution with a single temperature. By using five combinations of direct excitation lines and dielectronic recombination satellite lines in three line complexes (Fe He$\alpha$, Ly$\alpha$, and He$\beta$), we found that the plasma is well characterized by two-temperature thermal plasmas with temperatures of 1.7 and 4.3 keV, which is consistent with thermal broadening of Fe xxv, and the broad-band fitting results in the 1.7–10 keV band. Other forms of deviation from a single-temperature plasma, such as different ionization and electron temperatures or the $\kappa$ distribution for the electron energy distributions, are not favored, which is reasonable for stellar coronae at quiescence. This study demonstrates the utility of the Fe K-shell line ratio diagnostics to probe plasma conditions using X-ray microcalorimeters.

X-rays: stars↗

Seeing is Believing: Autonomous Microscopy and the Data Revolution in Materials Science

This presentation explores the transformative potential of autonomous electron microscopy and artificial intelligence (AI) in accelerating materials science discovery, particularly for energy applications and materials operating in extreme environments. We discuss pioneering self-driving laboratories at NREL designed to intelligently probe material synthesis and degradation across multiple scales, aiming to rapidly bridge the gap between atomic-level understanding and the development of high-performance, reliable materials. Utilizing advanced machine learning techniques, such as few-shot learning and multimodal analysis integrating imaging and spectroscopy, we demonstrate methods to extract actionable descriptors for material behavior, quantify complex microstructural evolution, and statistically link synthesis parameters to defect populations. This AI-driven approach promises to accelerate the creation of predictive materials tailored for specific missions, enabling faster development cycles and enhanced material assurance.

36 MATERIALS SCIENCE↗

Seeing is Believing: Autonomous Microscopy and the Data Revolution in Materials Science

This presentation explores the transformative potential of autonomous electron microscopy and artificial intelligence (AI) in accelerating materials science discovery, particularly for energy applications and materials operating in extreme environments. We discuss pioneering self-driving laboratories at NREL designed to intelligently probe material synthesis and degradation across multiple scales, aiming to rapidly bridge the gap between atomic-level understanding and the development of high-performance, reliable materials. Utilizing advanced machine learning techniques, such as few-shot learning and multimodal analysis integrating imaging and spectroscopy, we demonstrate methods to extract actionable descriptors for material behavior, quantify complex microstructural evolution, and statistically link synthesis parameters to defect populations. This AI-driven approach promises to accelerate the creation of predictive materials tailored for specific missions, enabling faster development cycles and enhanced material assurance.

97 MATHEMATICS AND COMPUTING↗

Position-specific kinetic isotope effects for nitrous oxide: a new expansion of the Rayleigh model

Nitrous oxide (N 2 O) is a potent greenhouse gas and the most significant anthropogenic ozone-depleting substance currently being emitted. A major source of anthropogenic N 2 O emissions is the microbial conversion of fixed nitrogen species from fertilizers in agricultural soils. Thus, understanding the enzymatic mechanisms by which microbes produce N 2 O has environmental significance. Measurement of the 15 N/ 14 N isotope ratios of N 2 O produced by purified enzymes or axenic microbial cultures is a promising technique for studying N 2 O biosynthesis. Typically, N 2 O-producing enzymes combine nitrogen atoms from two identical substrate molecules (NO or NH 2 OH). Position-specific isotope analysis of the central (N α ) and outer (N β ) nitrogen atoms in N 2 O enables the determination of the individual kinetic isotope effects (KIEs) for N α and N β , providing mechanistic insight into the incorporation of each nitrogen atom. Previously, position-specific KIEs (and fractionation factors) were quantified using the Rayleigh distillation equation, i.e., via linear regression of δ 15 N α or δ 15 N β against [–f In f / (1 – f)], where f is the fraction of substrate remaining in a closed system. This approach, however, is inaccurate for N α and N β because it does not account for fractionation at N α affecting the isotopic composition of substrate available for incorporation into the β position (and vice versa). Therefore, we developed a new expansion of the Rayleigh model that includes specific terms for fractionation at the individual N 2 O nitrogen atoms. By applying this Expanded Rayleigh model to a variety of simulated N 2 O synthesis reactions with different combinations of normal, inverse, and/or no KIEs at N α and N β , we demonstrate that our new model is both accurate and robust. We also applied this new model to two previously published datasets describing N 2 O production from NH 2 OH oxidation in a methanotroph culture (Methylosinus trichosporium) and N 2 O production from NO by a purified Histoplasma capsulatum (fungal) P450 NOR, demonstrating that the Expanded Rayleigh model is a useful tool in calculating position-specific fractionation for N 2 O synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A bi-channel aided stitching of atomic force microscopy images

Microscopy is an essential tool in scientific research, enabling the visualization of structures at micro- and nanoscale resolutions. However, the field of microscopy often encounters limitations in field-of-view (FOV), restricting the amount of sample that can be imaged in a single capture. To overcome this limitation, image stitching techniques have been developed to seamlessly merge multiple overlapping images into a single, high-resolution composite. The images collected from microscope need to be optimally stitched before accurate physical information can be extracted from post analysis. However, the existing stitching tools either struggle to stitch images together when the microscopy images are feature sparse or cannot address all the transformations of images when performing image stitching. To address these issues, we propose a bi-channel aided feature-based image stitching method and demonstrate its use on Atomic Force Microscopy (AFM) generated Pantoea sp. YR343 biofilm and PTO thin film sample images as experimental data. The topographical channel image of AFM data captures the morphological details of the sample, and a stitched topographical image is desired for researchers. We utilize the amplitude and phase channels of AFM data to maximize the matching features and to estimate the position of the original topographical images and show that the proposed bi-channel aided stitching method outperforms the traditional direct stitching approach in AFM topographical image stitching task. Here, we demonstrated the application on AFM, but similar approaches could be employed of optical microscopy with brightfield and fluorescence channels. We believe this proposed workflow can serve as a valuable augmentation strategy for microscopy image stitching tasks and will benefit the experimentalist to avoid erroneous analysis and discovery due to incorrect stitching.

Atomic force microscopy↗

Discovering invariant spatial features in electron energy loss spectroscopy images on the mesoscopic and atomic levels

Over the last two decades, Electron Energy Loss Spectroscopy (EELS) imaging with a scanning transmission electron microscope has emerged as a technique of choice for visualizing complex chemical, electronic, plasmonic, and phononic phenomena in complex materials and structures. The availability of the EELS data necessitates the development of methods to analyze multidimensional data sets with complex spatial and energy structures. Traditionally, the analysis of these data sets has been based on analysis of individual spectra, one at a time, whereas the spatial structure and correlations between individual spatial pixels containing the relevant information of the physics of underpinning processes have generally been ignored and analyzed only via the visualization as 2D maps. Here, we develop a machine learning-based approach and workflows for the analysis of spatial structures in 3D EELS data sets using a combination of dimensionality reduction and multichannel rotationally invariant variational autoencoders. This approach is illustrated for the analysis of both the plasmonic phenomena in a system of nanowires and in the core excitations in functional oxides using low loss and core-loss EELS, respectively. The code developed in this manuscript is open sourced and freely available and provided as a Jupyter notebook for the interested reader.

36 MATERIALS SCIENCE↗

Powder‐to‐Film Conversion of Nickel Single‐Atom Catalysts into Binder‐Free and Resistant Electrodes

Although a few binder-free and self-supported single-atom electrodes have been reported, achieving mechanically robust, defect-engineered, and reproducible films that preserve atomic dispersion under electrochemical operation remains challenging. This work addresses this limitation by presenting a versatile and generalizable strategy to transform powders into standalone, defect-engineered thin films hosting atomically dispersed Ni centers within conductive 2D frameworks. The physicochemical and electronic properties of these materials are thoroughly characterized using a comprehensive set of spectroscopic and microscopic techniques and confirmed the homogeneous dispersion and monoatomic nature of the Ni centers (0.94 wt.%) on the electrode films. Electrochemical testing via cyclic voltammetry and electrochemical impedance spectroscopy under a range of experimental conditions revealed that integration of Ni single atoms markedly enhanced performance and stability compared to carbon nanotube-only electrodes, maintaining integrity after 15 h of continuous operation. This improvement is accompanied by a notable reduction in charge transfer resistance (30.50 Ω) and an increase in double-layer capacitance (295.45 µF). Post-electrochemical analyses corroborated the structural integrity and robustness of the electrodes. Overall, this work bridges atomically precise catalysis and device-level electrochemistry, opening a route toward reproducible and scalable single-atom electrodes for sensing and energy conversion.

36 MATERIALS SCIENCE↗

Molecular Layer Etching of Metalcone Films Using Lithium Organic Salts and Trimethylaluminum

Advances in semiconductor device manufacturing are limited by our ability to precisely add and remove thin layers of material in multistep fabrication processes. Recent reports on atomic layer etching (ALE) have provided the means for the precise removal of inorganic thin films deposited by atomic layer deposition (ALD), opening new avenues for nanoscale device design. Here, we report on a new technique for the precise removal of metal organic thin films deposited by molecular layer deposition (MLD), which we term molecular layer etching. This etching process employs sequential exposures of lithium organic salt (LOS) and trimethylaluminum (TMA) precursors to produce self-limiting etching behavior. We employ quartz crystal microbalance experiments to demonstrate (i) etching of alucone films preloaded with LOS upon TMA exposures and (ii) layer-by-layer etching of alucone films using alternating exposures of LOS and TMA. We also identify the selectivity of these etching mechanisms. We probe the mechanism for the layer-by-layer etching of alucone using a quartz crystal microbalance and Fourier transform infrared spectroscopy and identify that the etching proceeds via heterolytic cleaving of Al-O bonds in alucone upon LOS exposure followed by methylation to produce volatile species upon TMA exposure. The etching process results in the removal of 0.4 nm/cycle of alucone at 160 °C and up to 3.6 nm/cycle of alucone at 266 °C in ex situ etching experiments on silicon wafers. This halogen-free etching process enables etching of MLD films and provides new fabrication pathways for the control of material geometries at the nanoscale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Interferometric 4D-STEM for Lattice Distortion and Interlayer Spacing Measurements of Bilayer and Trilayer 2D Materials

Van der Waals materials composed of stacks of individual atomic layers have attracted considerable attention due to their exotic electronic properties that can be altered by, e.g., manipulating the twist angle of bilayer materials or the stacking sequence of trilayer materials. To fully understand and control the unique properties of these few-layer materials, a technique that can provide information about their local in-plane structural deformations, twist direction, and out-of-plane structure is needed. In principle, interference in overlap regions of Bragg disks originating from separate layers of a material encodes 3D information about the relative positions of atoms in the corresponding layers. Here, an interferometric 4D scanning transmission electron microscopy technique is described that utilizes this phenomenon to extract precise structural information from few-layer materials with nm-scale resolution. It is demonstrated how this technique enables measurement of local pm-scale in-plane lattice distortions as well as twist direction and average interlayer spacings in bilayer and trilayer graphene, and therefore provides a means to better understand the interplay between electronic properties and precise structural arrangements of few-layer 2D materials.

36 MATERIALS SCIENCE↗