Tomography Experiments Research Articles

Time-lapse shear-wave tomography at a test dyke with changing water levels

Although seismic methods using S waves can offer high-resolution images of the shallow soil layers, the use of body S-wave tomography for near-surface water monitoring remains underexplored, and the quantitative interpretation of any observed changes in S-wave velocity ( V S) in the field conditions is challenging. We conduct a time-lapse S-wave tomography experiment on a field-scale test dike with controlled water levels, allowing for detailed examination of how VS responds to water infiltration. Our results demonstrate that VS decreases progressively, starting from the high-water-side slope and extending across the dike, as the water level rises, with the most significant changes occurring in the sand body and not in the clay cover. The maximum reduction in VS is approximately 40–60 m/s, corresponding to approximately 25%–30% reduction from the initial condition. We use the squared velocity ratio to evaluate the relative contributions of bulk density and shear modulus to VS changes. In the initially unsaturated zone, both these factors contribute significantly to the observed VS changes as the zone becomes fully saturated. In fully saturated zones, we assess the changes in the effective stress using the squared VS ratio. Although the low-water side of the dike shows stress changes that are consistent with numerical modeling, the high-water side shows large stress changes than expected, possibly due to excess pore pressure during the dynamic flow conditions. These findings highlight the potential of body S-wave tomography for high-resolution, near-surface hydrologic monitoring, and provide insights into the complex interactions between physical properties that influence VS changes under varying water levels in field environments.

Development of 99mTc-Labeled Complexes with a Niraparib HYNIC Derivative for PARP-Positive Tumor Imaging.

As an enzyme that plays an important role in DNA repair, poly(ADP-ribose) polymerase-1 (PARP-1) has become a popular target for cancer therapy. Nuclear medicine molecular imaging technology, supplemented by radiolabeled PARP-1 inhibitors, can accurately determine the expression level of PARP-1 at lesion sites to help patients choose an appropriate treatment plan. In this work, niraparib was modified with a hydrazinonicotinamide (HYNIC) group to generate the ligand NPBHYNIC, which has an in vitro affinity (IC50) of 450.90 nM for PARP-1. The ligand NPBHYNIC was labeled with technetium-99m and six different coligands to yield [99mTc]Tc-(X/tricine)-NPBHYNIC (X = TPPTS, TPPMS, PSA, PDA, NIC and ISONIC). These complexes were hydrophilic and exhibited good stability in vitro, and low levels of these complexes were taken up by nontarget organs and tissues in Kunming mice. Among these complexes, [99mTc]Tc-(TPPTS/tricine)-NPBHYNIC and [99mTc]Tc-(NIC/tricine)-NPBHYNIC were selected for biodistribution in HeLa tumor-bearing BALB/c nude mice at 2 h post injection. The results revealed that the tumor uptake of [99mTc]Tc-(TPPTS/tricine)-NPBHYNIC (1.02 ± 0.07% ID/g) was greater than that of [99mTc]Tc-(NIC/tricine)-NPBHYNIC (0.36 ± 0.05% ID/g). Additionally, in biodistribution, single-photon emission computed tomography/computed tomography (SPECT/CT) and radioautography experiments, the tumor uptake of [99mTc]Tc-(TPPTS/tricine)-NPBHYNIC was significantly reduced in the blocked group, indicating PARP-1 specificity. Therefore, it has potential for use as a niraparib-based tumor imaging agent that targets PARP-1.

Magnetotactic bacteria affiliated with diverse Pseudomonadota families biomineralize intracellular Ca-carbonate.

Intracellular calcium carbonate formation has long been associated with a single genus of giant Gammaproteobacteria, Achromatium. However, this biomineralization has recently received increasing attention after being observed in photosynthetic Cyanobacteriota and in two families of magnetotactic bacteria affiliated with the Alphaproteobacteria. In the latter group, bacteria form not only intracellular amorphous calcium carbonates into large inclusions that are refringent under the light microscope, but also intracellular ferrimagnetic crystals into organelles called magnetosomes. Here new observations suggest that magnetotactic bacteria previously identified in the sediments and water column of Lake Pavin (France) were only a small fraction of the diversity of bacteria producing intracellular amorphous calcium carbonates. To explore this diversity further, we conducted a comprehensive investigation of magnetotactic populations with refractive granules using a combination of environmental microbiology, genomic and mineralogy approaches on cells sorted by micromanipulation. Several species belonging to divergent genera of two Pseudomonadota classes were identified and characterized. Scanning transmission electron microscopy coupled with energy-dispersive X-ray spectrometry support that all these species indeed form intracellular amorphous calcium carbonates. Cryo soft X-ray tomography experiments conducted on ice-vitrified cells, enabled 3D investigation of inclusions volume, which was found to occupy 44-68% of the cell volume. Metabolic network modeling highlighted different metabolic abilities of Alpha- and Gammaproteobacteria, including methylotrophy and CO2 fixation via the reverse Krebs cycle or the Calvin-Benson-Bassham cycle. Overall, this study strengthens a convergent evolution scenario for intracellular carbonatogenesis in Bacteria, and further supports that it is promoted by the fixation of CO2 in anoxic environments.

Reduction of artifacts associated with missing data in coherent diffractive imaging.

Coherent diffractive imaging experiments often collect incomplete datasets containing regions that lack any measurements. These regions can arise because of beamstops, gaps between detectors, or, in tomography experiments, a missing wedge of data due to a limited sample rotation range. We describe practical and effective approaches to mitigate reconstruction artifacts by bringing uniqueness back to the phase retrieval problem. This is accomplished by looking for a solution that both matches the data and has minimum total variation, which essentially sets the unconstrained modes to reduce oscillations within the reconstruction. Two algorithms are described. The first algorithm assumes that there is an accurate estimate of the phase and can be used for pre- and post-processing. The second algorithm attempts to simultaneously minimize the total variation and recover the phase. We demonstrate the utility of these algorithms with numerical simulations and, experimentally, on a large, three-dimensional dataset.

Field deployment and analysis of hydraulic tomography experiments with periodic slug tests in an anisotropic littoral aquifer

Field deployment and analysis of hydraulic tomography experiments with periodic slug tests in an anisotropic littoral aquifer

Validation of Light–Ion Quantum Molecular Dynamics (LIQMD) model for hadron therapy

Purpose:This study aims to validate the Light-Ion Quantum Molecular Dynamics (LIQMD) model, an advanced version of the QMD model for more accurate simulations in hadron therapy, incorporated into Geant4 (release 11.2). Methods:Two sets of experiments are employed. The first includes positron-emitter distributions along the beam path for 350 MeV/u 12C ions incident on a PMMA target, obtained from in–vivo Positron Emission Tomography (PET) experiments at QST (Chiba, Japan). The second comprises cross-sections for 95 MeV/u 12C ions incident on thin targets (H, C, O, Al, and Ti), obtained from experiments at GANIL (Caen, France). The LIQMD model’s performance is compared with the experimental data and the default QMD model results. Results:The LIQMD model can predict the profile shape of positron-emitting radionuclide yields with better accuracy than the default QMD model, although some discrepancies remains. The consistency observed in the production of positron-emitting radionuclides aligns with the thin target cross-section analysis. The LIQMD model significantly improves the differential and double-differential cross-sections of fragments produced in thin targets, especially in the forward direction. The overestimation of 10C production in the in–vivo PET benchmark is consistent with the 95 MeV/u 12C cross-section test. Overall, the LIQMD model demonstrates better agreement with experimental measurements for nearly all fragment species compared to the QMD model. Conclusions:The LIQMD model offers an improved description of the fragmentation process in hadron therapy. Future work should involve further validation against additional experimental measurements to confirm these findings.

Exploiting activation radiation from neutron tomography reveals the hidden elemental composition of 3D art objects for free

Neutron tomography is gaining popularity particularly in cultural heritage research, for non-destructively analysing the inner structure of bulk metal artefacts, such as bronzes, but the induced temporary decay radiation is often considered as a drawback. However, this delayed gamma-emission can be put to good use: by performing gamma spectroscopy after neutron tomography, the interior elemental composition of artefacts can be obtained “for free”. Inspired by this, we propose a ray-tracing approach to non-invasively quantify both interior geometry and elemental composition using only a single neutron tomography experiment. This strategy aligns well with both the aim for efficient use of neutron beam time and the expectation from curators and conservators for minimal neutron irradiation. Here, we outline the core principle of this method, demonstrate the extent of its quantification capability on bulk objects of known composition by fusing neutron tomography and delayed-gamma spectroscopy data sets. We also showcase its practical application on an ancient solid-cast Indonesian bronze statuette, by which we gain insights into how the pristine inner bronze segregated into a different composition than the surrounding shell. Similarly, the method allows us to quantify the composition of a hidden offering in the statuette that consecrates the bronze for worship purposes.

Chitosan-based multimodal polymeric nanoparticles targeting pancreatic β-cells

Multimodal in vivo imaging of pancreatic islets might improve monitoring of endocrine grafts upon implantation, helping clinical validation of new regenerative therapies based on the replacement of β-cells in type 1 diabetes affected patients. Herein, the generation of chitosan-based multimodal diagnostic nanoparticles (NPs) able to target β-cells is described. The NPs, composed of chitosan (CH) and γ-poly-glutamic-acid (γ-PGA) with different “clickable” functional groups were chemoselectively decorated at the surface with Exendin-4 (Ex4), a ligand of glucagon-like peptide 1 (GLP-1) β-cell receptors, and with a DOTA containing linker, to chelate diagnostic radioisotopes. Furthermore, the NPs were conjugated with IRDye®800CW for multispectral optoacoustic tomography (MSOT). The affinity of Ex4 decorated NPs towards GLP-1R was confirmed by competitive flow cytometry tests. The detectability of the NPs labeled with IRDye®800CW and Ex4 in MSOT experiments was demonstrated. In vivo biodistribution of Ex4 decorated NPs labelled with Ga-68 was studied with positron emission tomography (PET) experiments in mice. Specific binding to GLP-1 receptor expressing tissue was demonstrated in autoradiography experiments, showing potential of the multimodal NPs for specifically targeting β-cells.

Solving Inverse PDE Problems using Grid-Free Monte Carlo Estimators

Partial differential equations can model diverse physical phenomena including heat diffusion, incompressible flows, and electrostatic potentials. Given a description of an object's boundary and interior, traditional methods solve such PDEs by densely meshing the interior and then solving a large and sparse linear system derived from this mesh. Recent grid-free solvers take an alternative approach and avoid this complexity in exchange for randomness: they compute stochastic solution estimates and generally bear a striking resemblance to physically-based rendering algorithms. In this article, we develop algorithms targeting the inverse form of this problem: given an already existing solution of a PDE, we infer parameters characterizing the boundary and interior. In the grid-free setting, there are again significant connections to rendering, and we show how insights from both fields can be combined to compute unbiased derivative estimates that enable gradient-based optimization. In this process, we encounter new challenges that must be addressed to obtain practical solutions. We introduce acceleration and variance reduction strategies and show how to differentiate branching random walks in reverse mode. We finally demonstrate our approach on both simulated data and a real-world electrical impedance tomography experiment, where we reconstruct the position of a conducting object from voltage measurements taken in a saline-filled tank.

Characterization of coal pore structures and flow simulation based on CT and experiments of MIP and SEM

Characterization of pore structures and flow simulation are essential to spatial migration of coalbed methane. In this paper, coal samples from Xinjing and Xinzhuang coal mines are collected and a comprehensive characterization method by using computed tomography (CT) technique and experiments of mercury intrusion porosimetry (MIP) and scanning electron microscopy (SEM) is proposed. Pore structure parameters are finely characterized and analyzed. Moreover, the flow process for coal samples is visualized and flow characteristics are analyzed. The result shows that pore structures of coal samples are strongly heterogeneous and are dominated by micropores, and filled with kaolinite, calcium monofluorophosphate, pyrite, etc. The flow velocity increases obviously in micropores and narrow throats. The flow is greatly affected by the pore structure. This study is of practical significance for the coalbed methane recoverability evaluation and exploration.

Effects of aging on otolith morphology and functions in mice.

Increased fall risk caused by vestibular system impairment is a significant problem associated with aging. A vestibule is composed of linear acceleration-sensing otoliths and rotation-sensing semicircular canals. Otoliths, composed of utricle and saccule, detect linear accelerations. Otolithic organs partially play a role in falls due to aging. Aging possibly changes the morphology and functions of otoliths. However, the specific associations between aging and otolith changes remain unknown. Therefore, this study aimed to clarify these associations in mice. Young C56BL/6 N (8 week old) and old (108-117 weeks old) mice were used in a micro-computed tomography (μCT) experiment for morphological analysis and a linear acceleration experiment for functional analysis. Young C56BL/6 N (8 week old) and middle-aged (50 week old) mice were used in electron microscopy experiments for morphological analysis. μCT revealed no significant differences in the otolith volume (p = 0.11) but significant differences in the otolith density (p = 0.001) between young and old mice. μCT and electron microscopy revealed significant differences in the structure of striola at the center of the otolith (μCT; p = 0.029, electron microscopy; p = 0.017). Significant differences were also observed in the amplitude of the eye movement during the vestibulo-ocular reflex induced by linear acceleration (maximum amplitude of stimulation = 1.3G [p = 0.014]; maximum amplitude of stimulation = 0.7G [p = 0.015]), indicating that the otolith function was worse in old mice than in young mice. This study demonstrated the decline in otolith function with age caused by age-related morphological changes. Specifically, when otolith density decreased, inertial force acting on the hair cells decreased, and when the structure of striola collapsed, the function of cross-striolar inhibition decreased, thereby causing a decline in the overall otolith function.

Cepharanthine-mediated endoplasmic reticulum stress inhibits Notch1 via binding GRP78 for suppressing hepatocellular carcinoma metastasis

BackgroundThe metastasis of hepatocellular carcinoma (HCC) leads to a poor prognosis, wherein the activation of Notch1 is an essential contributor. Cepharanthine (Cep) has been identified for its effective antiviral function and versatile intracellular targets. Our previous study has only reported the anti-cancer efficacy of Cep in lung cancer, without an in-depth exploration. Herein, the present study aims to investigate the anti-metastasis effect in HCC, the target involved, and the molecular mechanism of Cep. MethodsStable over-expression of Notch1-N1ICD yielded C5WN1 cells compared with C5WBF344 cells. The C5WN1 cells and C5WN1 cell-bearing mice were applied as the HCC model. The bioinformatics analysis, RNA sequencing, molecular docking, cellular thermal shift assay (CETSA), drug affinity responsive target stability (DARTS), microscale thermophoresis (MST), and transient knockdown techniques were carried out to identify the underlying target. The apoptosis assay, immunofluorescent staining, qRT-PCR, Western blots, Elisa, flow cytometry, migration and scratching experiments, Transmission electron microscopy (TEM), laser scanning confocal microscopy (LSCM), micro-computed tomography (micro-CT), and histopathological experiments were conducted to assay the anti-HCC efficacy, functions, and mechanism. ResultsNotch1 had an increased expression in HCC and contributed to metastasis thereupon. Surprisingly, Cep (2 μg/ml in vitro, 5 mg kg-1in vivo) presented potent Notch1 signaling pathway inhibitory effect and anti-metastasis efficacy in C5WN1 cells and in situ mice models as evidenced by reduced Notch1/MMP-2/MMP-9 expression, TGF-β release, decreased cell migration, diminished pulmonary metastases, and prolonged survival. RNA sequencing showed that the differential gene of Cep-treated HCC cells was positioned in the endoplasmic reticulum (ER). Molecular docking, CETSA, DARTS, and MST further identified that the possible target of Cep was GRP78, which was distributed in the ER. As expected, Cep (2 μg/ml) up-regulated the critical molecules of ER stress such as GRP78, induced β-amyloid accumulation, and promoted calcium burst in HCC. In contrast, suppression of GRP78 attenuated Cep-induced ER stress. Furthermore, inhibition of ER stress abated Cep-induced Notch1 inactivation and HCC cells’ migration. ConclusionsTaken together, the present study finds that Cep possesses excellent anti-metastasis of HCC, wherein the GRP78 could be directly bound and activated by Cep, leading to ER stress and Notch1 blockage. This study reveals for the first time the effect, critical target, and mechanism of the Cep-mediated anti-cancer effect, providing novel insights into the molecular target therapy by phytomedicine.

Damage quantification in concrete under uniaxial compression using microcomputed tomography and digital volume correlation with consideration of heterogeneity

Finite element-based digital volume correlation with mechanical regularization was utilized to measure the deformation fields in a concrete specimen under uniaxial compression based on in-situ (via microcomputed tomography) experiment. Heterogeneous and damage settings were introduced in the mechanical regularization. The mechanical response of the matrix and aggregates was investigated. The three-dimensional morphology of subvoxel microcrack openings was measured, the overall assessment and local depiction of concrete damage were quantified. Subvoxel microcrack openings greater than 0.26 vx were identified. The average maximum principal and average volumetric strains in the matrix were higher than those in the aggregates, and noticeable strain concentrations existed in the interfacial transition zone and pore edges. Microcracks initiated in the macroscopic elastic stage, whereas voxel-level crack openings were observed at 90% of the ultimate load. This study provides experimental support for further revealing the growth process of concrete damage.

An efficient ultrasound vibration strategy for suppressing intra-bundle pores and regulating pore morphology in carbon fiber-reinforced composites

The competitive resin flow between intra- and inter-bundles, always causes the generation of intra-bundle pores during resin transfer molding (RTM), thereby weakening composite mechanical performance. Accordingly, an ultrasound vibration strategy is originally developed to efficiently suppress and improve the spatial morphology and distribution of intra-bundle pores in RTM manufacturing. The effects of ultrasound vibration on the spatial evolution of intra-bundle pores are systematically investigated, furthermore, the suppression mechanisms of intra-bundle pores are revealed. Additionally, an empirical model that predicts porosity under ultrasound vibration, is established and well validated for the developed ultrasound vibration strategy, which provides a feasible path for effectively manufacturing composites. X-ray micro-computed tomography experiments verify that applying a short period of ultrasound vibration balances the dual-scale flow by regulating the modified capillary number, thereby significantly reducing porosity by up to 59.4 %. Numerical analyses indicate that the acoustic cavitation and acoustic flow induced by the ultrasound vibration, facilitate the collapse and transverse migration of larger bubbles, thereby remarkably suppressing the connected pores and larger pores. In particular, the ultrasound vibration strategy completely removes the pores larger than 300 μm. Besides, the collective effects of vibration, compression, and shear forces contribute to forming near-circular pores, which are beneficial for ensuring the expected mechanical performance of composites.

Uncertainty quantification in electrical resistivity tomography inversion: hybridizing block-wise bootstrapping with geostatistics

SUMMARY Electrical resistivity tomography inversion often encounters uncertainty stemming from two primary sources: epistemic uncertainty, arising from imperfect underlying physics and improper initial approximation of model parameters, and aleatory variability in observations due to measurement errors. Despite the widespread application of electrical resistivity tomography in imaging, the resistivity distribution of subsurface structures for various hydro-geophysical and engineering purposes, the assessment of uncertainty is seldom addressed within the inverted resistivity tomograms. To explore the combined impact of epistemic and aleatory uncertainty on resistivity models, we initially perturb the observed data using non-parametric block-wise bootstrap resampling with an optimal choice of the block size, generating different realizations of the field data. Subsequently, a geostatistical method is applied to stochastically generate a set of initial models for each bootstrapped data set from the previous step. Finally, we employ a globally convergent homotopic continuation method on each bootstrapped data set and initial model realization to explore the posterior resistivity models. Uncertainty information about the inversion results is provided through posterior statistical analysis. Our algorithm’s simplicity enables easy integration with existing gradient-based inversion methods, requiring only minor modifications. We demonstrate the versatility of our approach through its application to various synthetic and real electrical resistivity tomography experiments. The results reveal that this approach for quantifying uncertainty is straightforward to implement and computationally efficient.

Polymer‐Sorbent Direct Air Capture Contactors with Complex Geometries 3D‐Printed via Templated Phase Inversion

AbstractLow‐cost direct air capture (DAC) systems require efficient gas–solid contactors. These contactors provide rapid rates of heat and mass transport with minimal pressure drops. Triply periodic minimal surfaces (TPMS) are a class of geometries that are shown to have heat transfer properties that exceed those of other geometries, and these benefits are expected to manifest in mass transfer as well due to the analogies between heat and mass transfer. However, creating TPMS contactors is difficult using conventional manufacturing techniques such as injection molding. Non‐solvent‐induced phase separation (NIPS) of a polymeric ink containing the adsorbent is one way to construct adsorption contactors with excellent mass transport rates, but contactors have to date only been fabricated in simple geometries (e.g., films, fibers). This study demonstrates that NIPS of polymeric inks occurs within a simultaneously‐dissolving, water‐soluble, 3D‐printed template. This templated phase inversion (TPI) technique can create seemingly unlimited macroscopic architectures, including TPMS contactors, using a variety of potential DAC adsorbents, including zeolite, silica, activated carbon, and metal–organic frameworks. SEM, micro‐computed tomography, and nitrogen adsorption experiments reveal the microscopic pore structures and macroscopic geometries of the resulting sorbent contactors. TPMS DAC contactors with poly(ethyleneimine)/silica adsorbents are shown to have CO2 capture performances that rival or exceed other contactor geometries.

Constitutive model of high-temperature rapid fracture of Si3N4 ceramics for engine turbine discs and their pore insensitivity parameters

ABSTRACT The metallic materials used to manufacture turbine components can potentially be replaced with ceramics such as Si3N4, but the stress on turbine discs is difficult to determine experimentally, which hinders the development and optimization of ceramics. The finite element method solves this problem, but it requires an accurate constitutive model and parameters. Existing methods for determining model parameters lack versatility and do not consider the internal pores of ceramics. This work proposes a method for determining the parameters of the high-temperature rapid fracture constitutive model of ceramics with internal pores based on the results of industrial computed tomography (CT) and high-temperature fracture toughness experiments. The constitutive model for a ceramic with internal pores was selected based on the typical service conditions of turbine discs. Industrial CT was used to measure pore information. A finite element preprocessor was developed to create simulated specimens with pores. The high-temperature fracture toughness of the ceramics was measured. Pore insensitivity was the parameter obtained from the high-temperature constitutive model of ceramics with pores using this method. The maximum relative error between the predicted and experimental flexural strengths was 6.8%. It provides a new idea for determining the parameters of constitutive models for materials with pores.

A protocol and graphical user interface to assist new users with the planning of X-ray computed tomography experiments

X-ray computed micro tomography (CT) is the main 3D technique for imaging the internal microstructures of samples. Experimental planning is crucial to ensure the adequacy of CT results to answer specific scientific questions, optimizing the use of resources and maximizing the quality of results. Proper planning requires a certain level of expertise in the technique and the details of the specific scientific question to be answered. Notably, potential new CT users who have formulated a scientific question may not have the in-depth knowledge about CT necessary to make a first assessment of whether CT is suitable for their work. Here, a step-by-step protocol to plan CT experiments and an interactive graphical user interface (XCT-Explorer) are proposed to guide users through the different steps of the protocol and to link the various CT parameters required to perform a scan. The protocol is based on the experience gained within EXCITE (Electron and X-ray microscopy Community for structural and chemical Imaging Techniques for Earth materials) through interactions between facility managers and users from various scientific fields. The planning protocol aims to 1) help potential CT users with limited knowledge of CT (e.g. first-time users) to decide whether CT can answer their scientific question; 2) guide users to decide which parameters are the most appropriate for their sample/problem; 3) facilitate the initial contact between CT provider and new users; and 4) standardize the planning stage of CT experiments as the foundation for FAIR (Findable Accessible Interoperable and Reusable) practices.

Deep‐Learning Analysis of Fracture Networks Leading to System‐Size Failure in Rocks

AbstractFracture networks in rocks and other geomaterials form by seismic and aseismic damage processes that could lead to system‐size failure. Here, we use a multi‐view convolutional neural network model to predict the stress proximity to macroscopic failure of experimentally deformed rock samples using two‐dimensional images. Models are trained on time series of fractures observed in rock samples through dynamic in situ synchrotron X‐ray tomography experiments. The results demonstrate that deep learning models outperform traditional estimates based on fracture density, increasing the accuracy of the predictions. Furthermore, the models provide insights into fundamental characteristics of fracture patterns that may provide precursory information on impending material failure. The trained deep learning models estimate the angle of the fracture plane relative to the principal loading direction, which is a key factor contributing to shear failure. The predicted angle of the fracture plane, in the range of 10°–30° with respect to the direction of maximum compressive stress, is consistent with the established failure criteria used in rock mechanics.

Phase space framework enables a variable-scale diffraction model for coherent imaging and display

The fast algorithms in Fourier optics have invigorated multifunctional device design and advanced imaging technologies. However, the necessity for fast computations limits the widely used conventional Fourier methods, where the image plane has a fixed size at certain diffraction distances. These limitations pose challenges in intricate scaling transformations, 3D reconstructions, and full-color displays. Currently, the lack of effective solutions makes people often resort to pre-processing that compromises fidelity. In this paper, leveraging a higher-dimensional phase space method, a universal framework is proposed for customized diffraction calculation methods. Within this framework, a variable-scale diffraction computation model is established for adjusting the size of the image plane and can be operated by fast algorithms. The model’s robust variable-scale capabilities and its aberration automatic correction capability are validated for full-color holography, and high fidelity is achieved. The tomography experiments demonstrate that this model provides a superior solution for holographic 3D reconstruction. In addition, this model is applied to achieve full-color metasurface holography with near-zero crosstalk, showcasing its versatile applicability at nanoscale. Our model presents significant prospects for applications in the optics community, such as beam shaping, computer-generated holograms (CGHs), augmented reality (AR), metasurface optical elements (MOEs), and advanced holographic head-up display (HUD) systems.