Dark-field Imaging Research Articles

Spontaneous Deposition of Single Platinum Atoms on Anatase TiO2 for Photocatalytic H2 Evolution.

Single-atom (SA) decoration has emerged as a frontier in catalysis due to its unique characteristics. Recently, decorated Pt single atoms on titania have shown promise in photocatalytic hydrogen evolution. In this work, we demonstrate that Pt SAs can spontaneously deposit on the surface, driven by electrostatic forces; the key is to determine the golden pH and surface potential. We conducted a comprehensive investigation into the influence of the pH of the deposition precursor on the spontaneous adsorption of Pt SAs onto TiO2 nanosheets (TiNSs). We introduced a straightforward pH-dependent and charge-dependent strategy for the solid electrostatic anchoring of Pt SAs on TiO2. Furthermore, we established that the level of Pt loading can be controlled by adjusting the precursor pH. X-ray photoelectron spectroscopy (XPS) and high-angle annular dark-field imaging scanning transmission electron microscopy (HAADF-STEM) were used to evaluate the Pt SA-decorated samples. Photocatalytic hydrogen production activity was assessed under ultraviolet (UV) (365 nm) irradiation. Notably, we found that at a pH of 8, slightly below the measured point of zero charge (PZC), a unique mixture of Pt clusters and single atoms was deposited on the surface of TiNSs. This unique composition significantly improved hydrogen production, resulting in ∼3.7 mL of hydrogen generated after 8 h of UV exposure by only 10 mg of the Pt-decorated TiNS (with Pt loadings of 0.12 at. %), which is ∼300 times higher than the undecorated TiNS.

Dynamically Reconstructed Triple-Copper-Vacancy Associates Confined in Cu Nanowires Enabling High-Rate and Selective CO2 Electroreduction to C2+ Products.

Electrochemically reconstructed Cu-based catalysts always exhibit enhanced CO2 electroreduction performance; however, it still remains ambiguous whether the reconstructed Cu vacancies have a substantial impact on CO2 -to-C2+ reactivity. Herein, Cu vacancies are first constructed through electrochemical reduction of Cu-based nanowires, in which high-angle annular dark-field scanning transmission electron microscopy image manifests the formation of triple-copper-vacancy associates with different concentrations, confirmed by positron annihilation lifetime spectroscopy. In situ attenuated total reflection-surface enhanced infrared absorption spectroscopy discloses the triple-copper-vacancy associates favor *CO adsorption and fast *CO dimerization. Moreover, density-functional-theory calculations unravel the triple-copper-vacancy associates endow the nearby Cu sites with enriched and disparate local charge density, which enhances the *CO adsorption and reduces the CO-CO coupling barrier, affirmed by the decreased *CO dimerization energy barrier by 0.4eV. As a result, the triple-copper-vacancy associates confined in Cu nanowires achieve a high Faradaic efficiency of over 80% for C2+ products in a wide current density range of 400-800mA cm-2 , outperforming most reported Cu-based electrocatalysts.

Synchrotron Radiation Refraction-Contrast Computed Tomography Based on X-ray Dark-Field Imaging Optics of Pulmonary Malignancy: Comparison with Pathologic Examination.

Refraction-contrast computed tomography based on X-ray dark-field imaging (XDFI) using synchrotron radiation (SR) has shown superior resolution compared to conventional absorption-based methods and is often comparable to pathologic examination under light microscopy. This study aimed to investigate the potential of the XDFI technique for clinical application in lung cancer diagnosis. Two types of lung specimens, primary and secondary malignancies, were investigated using an XDFI optic system at beamline BL14B of the High-Energy Accelerator Research Organization Photon Factory, Tsukuba, Japan. Three-dimensional reconstruction and segmentation were performed on each specimen. Refraction-contrast computed tomographic images were compared with those obtained from pathological examinations. Pulmonary microstructures including arterioles, venules, bronchioles, alveolar sacs, and interalveolar septa were identified in SR images. Malignant lesions could be distinguished from the borders of normal structures. The lepidic pattern was defined as the invasive component of the same primary lung adenocarcinoma. The SR images of secondary lung adenocarcinomas of colorectal origin were distinct from those of primary lung adenocarcinomas. Refraction-contrast images based on XDFI optics of lung tissues correlated well with those of pathological examinations under light microscopy. This imaging method may have the potential for use in lung cancer diagnosis without tissue damage. Considerable equipment modifications are crucial before implementing them from the lab to the hospital in the near future.

Phase and Composition Engineering of Self-Intercalated 2D Metallic Tantalum Sulfide for Second-Harmonic Generation.

Self-intercalation in two-dimensional (2D) materials is significant, as it offers a versatile approach to modify material properties, enabling the creation of interesting functional materials, which is essential in advancing applications across various fields. Here, we define ic-2D materials as covalently bonded compounds that result from the self-intercalation of a metal into layered 2D compounds. However, precisely growing ic-2D materials with controllable phases and self-intercalation concentrations to fully exploit the applications in the ic-2D family remains a great challenge. Herein, we demonstrated the controlled synthesis of self-intercalated H-phase and T-phase Ta1+xS2 via a temperature-driven chemical vapor deposition (CVD) approach with a viable intercalation concentration spanning from 10% to 58%. Atomic-resolution scanning transmission electron microscopy-annular dark field imaging demonstrated that the self-intercalated Ta atoms occupy the octahedral vacancies located at the van der Waals gap. The nonperiodic Ta atoms break the centrosymmetry structure and Fermi surface properties of intrinsic TaS2. Therefore, ic-2D T-phase Ta1+xS2 consistently exhibit a spontaneous nonlinear optical (NLO) effect regardless of the sample thickness and self-intercalation concentrations. Our results propose an approach to activate the NLO response of centrosymmetric 2D materials, achieving the modulation of a wide range of optoelectronic properties via nonperiodic self-intercalation in the ic-2D family.

Reliable extraction of x-ray refraction and dark-field signals with a large field of view, multi-modal scanning system at spectral energies up to 150 kVp

Abstract Multi-modal x-ray scanning allows the simultaneous acquisition of attenuation, refraction and ultra-small angle scattering or dark field images. While many examples of multi-modal x-ray scanning exist in the literature, extension to high x-ray energy, necessary to investigate dense and high-Z materials, still poses challenges. We present the investigation of attenuation, refraction and dark field images taken at 90, 120 and 150 kVp, using a scanning, large field of view multi-modal imaging system. Increases in tube voltage reduce both contrast and signal to noise but still produce satisfactory results suitable for quantitative analysis. On top of benchmarking against phantoms made of known materials, we illustrate this by scanning a 9 V PP3 battery; a highly absorbing sample which causes photon starvation at lower energies.

Combining Wave and Particle Effects in the Simulation of X-ray Phase Contrast—A Review

X-ray phase-contrast imaging (XPCI) is a family of imaging techniques that makes contrast visible due to phase shifts in the sample. Phase-sensitive techniques can potentially be several orders of magnitude more sensitive than attenuation-based techniques, finding applications in a wide range of fields, from biomedicine to materials science. The accurate simulation of XPCI allows for the planning of imaging experiments, potentially reducing the need for costly synchrotron beam access to find suitable imaging parameters. It can also provide training data for recently proposed machine learning-based phase retrieval algorithms. The simulation of XPCI has classically been carried out using wave optics or ray optics approaches. However, these approaches have not been capable of simulating all the artifacts present in experimental images. The increased interest in dark-field imaging has also prompted the inclusion of scattering in XPCI simulation codes. Scattering is classically simulated using Monte Carlo particle transport codes. The combination of the two perspectives has proven not to be straightforward, and several methods have been proposed. We review the available literature on the simulation of XPCI with attention given to particular methods, including the scattering component, and discuss the possible future directions for the simulation of both wave and particle effects in XPCI.

X-ray phase and dark-field computed tomography without optical elements.

X-ray diffusive dark-field imaging, which allows spatially unresolved microstructure to be mapped across a sample, is an increasingly popular tool in an array of settings. Here, we present a new algorithm for phase and dark-field computed tomography based on the x-ray Fokker-Planck equation. Needing only a coherent x-ray source, sample, and detector, our propagation-based algorithm can map the sample density and dark-field/diffusion properties of the sample in 3D. Importantly, incorporating dark-field information in the density reconstruction process enables a higher spatial resolution reconstruction than possible with previous propagation-based approaches. Two sample exposures at each projection angle are sufficient for the successful reconstruction of both the sample density and dark-field Fokker-Planck diffusion coefficients. We anticipate that the proposed algorithm may be of benefit in biomedical imaging and industrial settings.

Grating-based x-ray dark-field CT for lung cancer diagnosis in mice

BackgroundThe low absorption of x-rays in lung tissue and the poor resolution of conventional computed tomography (CT) limits its use to detect lung disease. However, x-ray dark-field imaging can sense the scattered x-rays deflected by the structures being imaged. This technique can facilitate the detection of small alveolar lesions that would be difficult to detect with conventional CT. Therefore, it may provide an alternative imaging modality to diagnose lung disease at an early stage.MethodsEight mice were inoculated with lung cancers simultaneously. Each time two mice were scanned using a grating-based dark-field CT on days 4, 8, 12, and 16 after the introduction of the cancer cells. The detectability index was calculated between nodules and healthy parenchyma for both attenuation and dark-field modalities. High-resolution micro-CT and pathological examinations were used to crosscheck and validate our results. Paired t-test was used for comparing the ability of dark-field and attenuation modalities in pulmonary nodule detection.ResultsThe nodules were shown as a signal decrease in the dark-field modality and a signal increase in the attenuation modality. The number of nodules increased from day 8 to day 16, indicating disease progression. The detectability indices of dark-field modality were higher than those of attenuation modality (p = 0.025).ConclusionsCompared with the standard attenuation CT, the dark-field CT improved the detection of lung nodules.Relevance statementDark-field CT has a higher detectability index than conventional attenuation CT in lung nodule detection. This technique could improve the early diagnosis of lung cancer.Key points• Lung cancer progression was observed using x-ray dark-field CT.• Dark-field modality complements with attenuation modality in lung nodule detection.• Dark-field modality showed a detectability index higher than that attenuation in nodule detection.Graphical

Underwater microbubbles detection and identification based on dark field imaging

Underwater microbubbles detection and identification based on dark field imaging

Enhancing Reproducibility in Precipitate Analysis: A FAIR Approach with Automated Dark-Field Transmission Electron Microscope Image Processing

High-strength aluminum alloys used in aerospace and automotive applications obtain their strength through precipitation hardening. Achieving the desired mechanical properties requires precise control over the nanometer-sized precipitates. However, the microstructure of these alloys changes over time due to aging, leading to a deterioration in strength. Typically, the size, number, and distribution of precipitates for a quantitative assessment of microstructural changes are determined by manual analysis, which is subjective and time-consuming. In our work, we introduce a progressive and automatable approach that enables a more efficient, objective, and reproducible analysis of precipitates. The method involves several sequential steps using an image repository containing dark-field transmission electron microscopy (DF-TEM) images depicting various aging states of an aluminum alloy. During the process, precipitation contours are generated and quantitatively evaluated, and the results are comprehensibly transferred into semantic data structures. The use and deployment of Jupyter Notebooks, along with the beneficial implementation of Semantic Web technologies, significantly enhances the reproducibility and comparability of the findings. This work serves as an exemplar of FAIR image and research data management.

Synergistic interaction of nanoparticles and probiotic delivery: A review.

Nanotechnology is an expanding and new technology that prompts production with nanoparticle-based (1-100 nm) organic and inorganic materials. Such a tool has an imperative function in different sectors like bioengineering, pharmaceuticals, electronics, energy, nuclear energy, and fuel, and its applications are helpful for human, animal, plant, and environmental health. In exacting, the nanoparticles are synthesized by top-down and bottom-up approaches through different techniques such as chemical, physical, and biological progress. The characterization is vital and the confirmation of nanoparticle traits is done by various instrumentation analyses like UV-Vis spectrophotometry (UV-Vis), Fourier transform infrared spectroscopy, scanning electron microscope, transmission electron microscopy, X-ray diffraction, atomic force microscopy, annular dark-field imaging, and intracranial pressure. In addition, probiotics are friendly microbes which while administered in sufficient quantity confer health advantages to the host. Characterization investigation is much more significant to the identification of good probiotics. Similarly, haemolytic activity, acid and bile salt tolerance, autoaggregation, antimicrobial compound production, inhibition of pathogens, enhance the immune system, and more health-beneficial effects on the host. The synergistic effects of nanoparticles and probiotics combined delivery applications are still limited to food, feed, and biomedical applications. However, the mechanisms by which they interact with the immune system and gut microbiota in humans and animals are largely unclear. This review discusses current research advancements to fulfil research gaps and promote the successful improvement of human and animal health.

Motion Contrast, Phase Gradient, and Simultaneous OCT Images Assist in the Interpretation of Dark-Field Images in Eyes with Retinal Pathology.

The cellular-level visualization of retinal microstructures such as blood vessel wall components, not available with other imaging modalities, is provided with unprecedented details by dark-field imaging configurations; however, the interpretation of such images alone is sometimes difficult since multiple structural disturbances may be present in the same time. Particularly in eyes with retinal pathology, microstructures may appear in high-resolution retinal images with a wide range of sizes, sharpnesses, and brightnesses. In this paper we show that motion contrast and phase gradient imaging modalities, as well as the simultaneous acquisition of depth-resolved optical coherence tomography (OCT) images, provide additional insight to help understand the retinal neural and vascular structures seen in dark-field images and may enable improved diagnostic and treatment plans.

Holistic Prediction of AuNP Aggregation in Diverse Aqueous Suspensions Based on Machine Vision and Dark-Field Scattering Imaging.

The localized surface-plasmon resonance of the AuNP in aqueous media is extremely sensitive to environmental changes. By measuring the signal of plasmon scattering light, the dark-field microscopic (DFM) imaging technique has been used to monitor the aggregation of AuNPs, which has attracted great attention because of its simplicity, low cost, high sensitivity, and universal applicability. However, it is still challenging to interpret DFM images of AuNP aggregation due to the heterogeneous characteristics of the isolated and discontinuous color distribution. Herein, we introduce machine vision algorithms for the training of DFM images of AuNPs in different saline aqueous media. A visual deep learning framework based on AlexNet is constructed for studying the aggregation patterns of AuNPs in aqueous suspensions, which allows for rapid and accurate identification of the aggregation extent of AuNPs, with a prediction accuracy higher than 0.96. With the aid of machine learning analysis, we further demonstrate the prediction ability of various aggregation phenomena induced by both cation species and the concentration of the external saline solution. Our results suggest the great potential of machine vision frameworks in the accurate recognition of subtle pattern changes in DFM images, which can help researchers build predictive analytics based on DFM imaging data.

Three-Dimensional Reconstruction of Interface Roughness and Alloy Disorder in Ge/GeSi Asymmetric Coupled Quantum Wells Using Electron Tomography.

Interfaces play an essential role in the performance of ever-shrinking semiconductor devices, making comprehensive determination of their three-dimensional (3D) structural properties increasingly important. This becomes even more relevant in compositional interfaces, as is the case for Ge/GeSi heterostructures, where chemical intermixing is pronounced in addition to their morphology. We use the electron tomography method to reconstruct buried interfaces and layers of asymmetric coupled Ge/Ge0.8Si0.2 multiquantum wells, which are considered a potential building block in THz quantum cascade lasers. The three-dimensional reconstruction is based on a series of high-angle annular dark-field scanning transmission electron microscopy images. It allows chemically sensitive investigation of a relatively large interfacial area of about (80 × 80) nm2 with subnanometer resolution as well as the analysis of several interfaces within the multiquantum well stack. Representing the interfaces as iso-concentration surfaces in the tomogram and converting them to topographic height maps allows the determination of their morphological roughness as well as layer thicknesses, reflecting low variations in either case. Simulation of the reconstructed tomogram intensities using a sigmoidal function provides in-plane-resolved maps of the chemical interface widths showing a relatively large spatial variation. The more detailed analysis of the intermixed region using thin slices from the reconstruction and additional iso-concentration surfaces provides an accurate picture of the chemical disorder of the alloy at the interface. Our comprehensive three-dimensional image of Ge/Ge0.8Si0.2 interfaces reveals that in the case of morphologically very smooth interfaces─depending on the scale considered─the interface alloy disorder itself determines the overall characteristics, a result that is fundamental for highly miscible material systems.

Implementation of a dual-phase grating interferometer for multi-scale characterization of building materials by tunable dark-field imaging

The multi-scale characterization of building materials is necessary to understand complex mechanical processes, with the goal of developing new more sustainable materials. To that end, imaging methods are often used in materials science to characterize the microscale. However, these methods compromise the volume of interest to achieve a higher resolution. Dark-field (DF) contrast imaging is being investigated to characterize building materials in length scales smaller than the resolution of the imaging system, allowing a direct comparison of features in the nano-scale range and overcoming the scale limitations of the established characterization methods. This work extends the implementation of a dual-phase X-ray grating interferometer (DP-XGI) for DF imaging in a lab-based setup. The interferometer was developed to operate at two different design energies of 22.0 keV and 40.8 keV and was designed to characterize nanoscale-size features in millimeter-sized material samples. The good performance of the interferometer in the low energy range (LER) is demonstrated by the DF retrieval of natural wood samples. In addition, a high energy range (HER) configuration is proposed, resulting in higher mean visibility and good sensitivity over a wider range of correlation lengths in the nanoscale range. Its potential for the characterization of mineral building materials is illustrated by the DF imaging of a Ketton limestone. Additionally, the capability of the DP-XGI to differentiate features in the nanoscale range is proven with the dark-field of Silica nanoparticles at different correlation lengths of calibrated sizes of 106 nm, 261 nm, and 507 nm.

CRISPR/Cas13a-assisted amplification-free miRNA biosensor via dark-field imaging and magnetic gold nanoparticles.

MicroRNAs (miRNAs) are short (about 18-24 nucleotides) non-coding RNAs and have emerged as potential biomarkers for various diseases, including cancers. Due to their short lengths, the specificity often becomes an issue in conventional amplification-based methods. Next-generation sequencing techniques could be an alternative, but the long analysis time and expensive costs make them less suitable for routine clinical diagnosis. Therefore, it is essential to develop a rapid, selective, and accurate miRNA detection assay using a simple, affordable system. In this work, we report a CRISPR/Cas13a-based miRNA biosensing using point-of-care dark-field (DF) imaging. We utilized magnetic-gold nanoparticle (MGNPs) complexes as signal probes, which consist of 200 nm-sized magnetic beads and 60 nm-sized gold nanoparticles (AuNPs) linked by DNA hybridization. Once the CRISPR/Cas13a system recognized the target miRNAs (miR-21-5p), the activated Cas13a cleaved the bridge linker containing RNA sequences, releasing 60 nm-AuNPs detected and quantified by a portable DF imaging system. The combination of CRISPR/Cas13a, MGNPs, and DF imaging demonstrated amplification-free detection of miR-21-5p within 30 min at a detection limit of 500 attomoles (25 pM) and with single-base specificity. The CRISPR/Cas13a-assisted MGNP-DF assay achieved rapid, selective, and accurate detection of miRNAs with simple equipment, thus providing a potential application for cancer diagnosis.

Super resolution label-free dark-field microscopy by deep learning.

Dark-field microscopy (DFM) is a powerful label-free and high-contrast imaging technique due to its ability to reveal features of transparent specimens with inhomogeneities. However, owing to the Abbe's diffraction limit, fine structures at sub-wavelength scale are difficult to resolve. In this work, we report a single image super resolution DFM scheme using a convolutional neural network (CNN). A U-net based CNN is trained with a dataset which is numerically simulated based on the forward physical model of the DFM. The forward physical model described by the parameters of the imaging setup connects the object ground truths and dark field images. With the trained network, we demonstrate super resolution dark field imaging of various test samples with twice resolution improvement. Our technique illustrates a promising deep learning approach to double the resolution of DFM without any hardware modification.

Atom column analysis of (Fe,Cr)2B phase in high B containing ferritic steel

This paper depicts nuances of atomistic level characterization of (Fe,Cr)2B crystal in a high B containing P91 steel using probe aberration-corrected Scanning Transmission Electron Microscope (STEM) based techniques. Substitution of Cr atoms in Fe atom positions resulted in intensity variation of atomic columns of a STEM-High Angle Annular Dark Field (HAADF) image. Image simulation has been used to understand this variation. Relative estimation of Cr atom substitution in Fe atom columns has also been quantified through the analysis of changes in peak profile intensity ratio of STEM-HAADF image in comparison with simulated images. Imaging light atoms, such as B, has recently been made possible with the advent of the Differential Phase Contrast (DPC) detectors. In this work, STEM based Integrated DPC (iDPC) has been used to obtain a very detailed image of the (Fe,Cr)2B crystal showing projection of the Fe/Cr and B atom columns along [100]. However, the observed delocalization of B atom columns was intriguing. Computational analysis using density functional theory (DFT) modelling was employed to understand the effect of Cr substitution on BB bond length with actually little or no effect. Further theoretical calculations confirmed that the energy imparted by the incident electron during imaging was responsible for the B atom delocalization.

In-flow tomographic imaging for single cells analysis

Gold standard imaging modalities in biological field are based on fluorescence signals providing high specificity and high resolution. Recently, Fluorescence Microscopy has been combined with microfluidics to develop instrumentations called Imaging Flow Cytometers, high-throughput tools that supply bright-field, darkfield and multiple-channels fluorescence images of each single cell passing in the Field Of View (FOV). Nevertheless, Fluorescence Microscopy has some drawbacks as phototoxicity, photobleaching, expensive costs for sample preparations and also the a-priori knowledge of the tags to be used. For these reasons label-free imaging methods greatly increase in the recent years as the Quantitative Phase Imaging (QPI) technologies for microscopy. One of the optical techniques to achieve QPI is Digital Holography. DH in microscopy has several advantages such as the possibility to numerically scan the focal distance, a properties that open to the integration of DH in microfluidics. Indeed DH combined with microfluidic circuits allows to image particles or cells flowing into the FOV at different depths. Here the capabilities of label-free single-cell imaging by DH are presented and their implications on next future biomedical applications discussed. Static or in-flow configurations will be showed describing recent results and perspectives also in combination with Artificial Intelligence architectures for future applications in biomedical and clinical fields.

Nb<sub>0.8</sub>CoSb ordering transformation caused by <i>in situ</i> heating-induced Nb diffusion

<sec>This study focuses on the investigation of Nb<sub>0.8</sub>CoSb half-Heusler alloy covered with Nb films. By employing <i>in-situ</i> heating transmission electron microscopy (TEM) technique, diffusion of Nb is observed at high temperature, showing the ordering transformation from Nb<sub>0.8</sub>CoSb to Nb<sub>0.8+δ</sub>CoSb. Through observations of high-angle annular dark-field (HAADF) images and selected-area electron diffraction (SAED) patterns, it is found that under elevated temperatures, the diffuse streaks representing short-range disorder in Nb<sub>0.8</sub>CoSb sample transform into superlattice diffraction spots representing long-range order. The modulation wave vector of this superstructure is determined to be <inline-formula><tex-math id="M3">\begin{document}$ q={1}/{3}({a}^{*}+{b}^{*}-{c}^{*}) $\end{document}</tex-math><alternatives><graphic specific-use="online" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="11-20240325_M3.jpg"/><graphic specific-use="print" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="11-20240325_M3.png"/></alternatives></inline-formula>. This structural evolution primarily arises from the diffusion of Nb atoms from the Nb film into the Nb<sub>0.8</sub>CoSb sample at high temperature, leading to compositional changes in Sb and Nb.</sec><sec>Further comparative analysis reveals significant differences between <i>in-situ</i> synthesized Nb<sub>0.8+δ</sub>CoSb samples and <i>ex-situ</i> synthesized Nb<sub>0.84</sub>CoSb samples despite both exhibiting superstructures. In the <i>ex-situ</i> synthesized Nb<sub>0.84</sub>CoSb, the modulation wave vector of the superstructure is <inline-formula><tex-math id="M4">\begin{document}$ q={1}/{3}({2a}^{*}-2{c}^{*}) $\end{document}</tex-math><alternatives><graphic specific-use="online" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="11-20240325_M4.jpg"/><graphic specific-use="print" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="11-20240325_M4.png"/></alternatives></inline-formula>, which is mainly attributed to Nb compositional variations. Moreover, the superstructure in Nb<sub>0.84</sub>CoSb sample can remain stable from room temperature to high temperature, whereas in Nb<sub>0.8+δ</sub>CoSb samples, it only exists at elevated temperatures and gradually weakens as the temperature decreases, suggesting that it may be a metastable structure between Nb<sub>0.8</sub>CoSb and Nb<sub>0.84</sub>CoSb.</sec><sec>This study reveals the diversity of superstructures induced by compositional variations and the complexity of structural phase transitions in half-Heusler alloys, enriching the understanding of these materials and providing important guidance for the design and functional control of phase-change materials.</sec>