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Mohsen Danaie

Publications and source records attributed to Mohsen Danaie.

7 recordsLinked to original sources

Real-space overlap is not enough: ambiguity in nanobeam iterative ptychography

High-resolution iterative ptychography typically relies on a well-aligned, high-convergence-angle electron probe. Here we explore whether it can instead be performed at small convergence angles, relaxing the need for probe correctors and enabling experiments at low accelerating voltages or with a de-excited objective lens, as in Lorentz mode. Through experiments and simulations, we show that once the convergence angle is small enough that no diffracted disks overlap, the resulting reconstruction is ambiguous, posing a significant challenge for robust interpretation of results. This challenge arises because of the lack of interference between Bragg disks in the recorded diffraction pattern intensity, leading to no phase information for each reflection. Reconstructions with these data lead to degenerate objects in which rigid translations of the lattice and reversals of contrast of the object produce the same error between experimental data and the ptychography forward model. Increasing the real-space overlap between probe positions does not lift this degeneracy. An amorphous substrate can supply the missing phase relationships by giving the Bragg beams support in the gaps between disks. This phasing is fragile, however, and survives only where the forward model matches the experiment. At fixed dose, either constraining the object to be a pure phase object or introducing thermal motion into the forward model is enough on its own to make the solution non-unique, highlighting why our experimental reconstructions below the overlap threshold are ambiguous despite ample dose and real-space redundancy. Most troublingly, the lattice spacing and orientation are always recovered correctly, so a non-unique reconstruction looks convincing and can be diagnosed only by repeating the reconstruction from different starting points.

cond-mat.mtrl-sci↗

An Interactive, Automated 4D-STEM data acquisition and analysis routine for Scanning Electron Nanobeam Diffraction and Ptychography experiments

Modern transmission electron microscopes are versatile instruments which have become indispensable tools for understanding structure and chemical composition at the nano- and atomic scale. In the physical sciences these instruments are still largely manually controlled, requiring significant operator expertise, limiting throughput, and precluding statistical analysis of large datasets. Recent technical advances in both hardware and in control software now allow for the interaction with almost every functionality of the microscope through a programming interface. This enables better experimental design and data collection automation while also reducing operator collection bias and required expertise. In this study, we present an automated data collection routine with machine-driven decision-making to enable the collection of hundreds of 4D-STEM nanobeam diffraction and ptychography data from a large distribution of size-selectively deposited Pt nanoparticles. We present a semi-automated data analysis workflow to extract pertinent information from the large volumes of collected data. For the nanobeam diffraction data, reducing each dataset to its azimuthal variance profile and combining automated crystal orientation mapping with per-particle morphology descriptors reveals the orientation, shape and phase distributions across the ensemble, including a weak {110} texture. For the ptychographic data, an automated screening pipeline identifies on-zone-axis particles and enables atomic-resolution phase imaging and lattice-strain mapping of individual grains. Together these demonstrate how automation turns instrument throughput into statistically meaningful, atomic-scale microstructural information.

physics.ins-det↗

In Situ Dynamics of the Microscopic Crystallographic Dehydration Pathway in a Model Channel Hydrate, Theophylline

Solid-state phase transformations in molecular crystal hydrates govern stability and functional performance across a range of applications, including pharmaceutical, agrochemical and coordination framework materials. During dehydration, these hydrates can undergo substantial structural reorganisation involving changes in molecular orientation, intermolecular interactions, and lattice symmetry. Despite extensive study, the microscopic crystallographic pathways by which such transformations proceed remain poorly understood. Here, we investigate the dynamics of solid-state dehydration of theophylline monohydrate as a model molecular hydrate using in situ low-dose scanning electron diffraction (SED). Simultaneous observations of changes in morphology and crystallographic phase and orientation mapped across single particles reveal how complete dehydration proceeds via a two-step, reconstructive topotactic solid-state transformation: anisotropic, surface-specific mass loss of material near water channel sides (suggesting the monohydrate adopts a non-centrosymmetric crystal structure) is followed by surface-localised nucleation and growth of anhydrous form II on the parent monohydrate while preserving similar molecular orientations at a common plane. By providing direct, local crystallographic insight into hydrate dehydration, this work demonstrates how surface-controlled mass loss, morphological changes, and lattice orientation jointly govern solid-state transformations in molecular hydrates. More broadly, it establishes low-dose SED as an effective approach for probing dynamic phase transformations in beam-sensitive molecular crystals.

cond-mat.mtrl-sci↗

Atomic-resolution imaging of gold species at organic liquid-solid interfaces

Understanding solid-liquid interfaces at the atomic-scale is key to improved performance of heterogeneous catalysts, electrodes and membranes. Here we combine unique specimen design, record atomic resolution in situ electron microscopy, and artificial intelligence-enabled analysis to achieve a step change in quantitative understanding of interfacial atomic behaviour. We create the first graphene liquid cells with organic solvents and employ them to track over 106 gold adatoms and clusters at a graphene surface immersed in acetone and cyclohexanone. We reveal dynamic correlated behaviour of gold adatom monomers, dimers, trimers and clusters, strongly influenced by each other, the solvent properties, and the atomic lattice of the substrate, in good agreement with theoretical calculations. We use the results to interpret differences in catalytic activity towards the industrially important acetylene hydrochlorination reaction. This new capability for exploration of atomic scale chemistry could enable rational design of future catalysts, membranes and electrodes with improved functionality.

cond-mat.mtrl-sci↗

Characterization of Nanostructural Imperfections in Superconducting Quantum Circuits

Decoherence in superconducting quantum circuits, caused by loss mechanisms like material imperfections and two-level system (TLS) defects, remains a major obstacle to improving the performance of quantum devices. In this work, we present atomic-level characterization of cross-sections of a Josephson junction and a spiral resonator to assess the quality of critical interfaces. Employing scanning transmission electron microscopy (STEM) combined with energy-dispersive X-ray spectroscopy (EDS) and electron-energy loss spectroscopy (EELS), we identify structural imperfections associated with oxide layer formation and carbon-based contamination, and correlate these imperfections to the patterning and etching steps in the fabrication process and environmental exposure. These results suggest that TLS imperfections at critical interfaces significantly contribute to limiting device performance, emphasizing the need for an improved fabrication process.

quant-ph↗

Direct TEM observation and quantification of the Gibbs-Thomson effect in a nickel superalloy

Gibbs-Thompson effect is the general term referring to the influence of interfaces on the course of phase transformations such as precipitation or solidification. Whilst attention is most often focused on the Gibbs-Thomson effect on nucleation, growth and coarsening, the present study considers the reverse process of precipitate dissolution in a nickel-base superalloy during in situ TEM observation. The presence of several distinct populations of gamma-prime precipitates (primary, secondary, tertiary and grain boundary) allows the differences due to particle size to be quantified and interpreted. Important implications arise for the selection of heat treatment schedules for nickel-base superalloys and other alloy systems.

cond-mat.mtrl-sci↗

Versatile Domain Mapping Of Scanning Electron Nanobeam Diffraction Datasets Utilising Variational AutoEncoders and Decoder-Assisted Latent-Space Clustering

Advancements in fast electron detectors have enabled the statistically significant sampling of crystal structures on the nanometre scale by means of Scanning Electron Nanobeam Diffraction (SEND). Characterisation of structural similarity across this length scale is key to bridging the gap between local atomic structure (using atomic resolution techniques such as High Resolution Scanning Transmission Electron Microscopy (HR-STEM)) and the macro-scale (using bulk techniques such as powder X-ray and neutron diffraction). The use of SEND technique allows for structural investigation of a broad range of samples, due to the techniques ability to operate with low electron dosage and its tolerance for sample thickness, relative to HR-STEM. This, coupled with the capacity for data collection over a wide areas and the automation of this collection, allows for statistically representative sampling of the microstructure. Also due to these factors, SEND generates large datasets and as a result automated/ semi-automated data processing workflows are required to aid in maximal extraction of useful information. As such, this paper outlines a versatile, data-driven approach for producing domain maps, as well as a statistical approach for assessing their applicability. The production of such domain maps for a dataset can help highlight nuance in the microstructure, as well as improve the manageability of that dataset for further investigation. The workflow outlined utilises a Variational AutoEncoder to identify and learn the sources of variance in the diffraction signal and this, in combination with clustering techniques, is used to produce domain maps for a set of varied example cases. This approach: is agnostic to domain crystallinity; requires no prior knowledge of crystal structure; and does not require the, potentially prohibitive, simulation of a library of appropriate diffraction patterns.

cond-mat.mtrl-sci↗