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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

WE-AB-204-02: Molecular-Imaging Based Assessment of Liver Complications for Yttrium-90 Microsphere Treatments: Can Existing NTCP Models Explain Clinical Outcomes?

Purpose: To evaluate weather the current radiobiological models can predict the normal liver complications of radioactive Yttrium-90 ({sup 90}Y) selective-internal-radiation-treatment (SIRT) for metastatic liver lesions based on the post-infusion {sup 90}Y PET images. Methods: A total of 20 patients with metastatic liver tumors treated with SIRT that received a post-infusion {sup 90}Y-PET/CT scan were analyzed in this work. The 3D activity distribution of the PET images was converted into a 3D dose distribution via a kernel convolution process. The physical dose distribution was converted into the equivalent dose (EQ2) delivered at 2 Gy based on the linear-quadratic (LQ) model considering the dose rate effect. The biological endpoint of this work was radiation-induce liver disease (RILD). The NTCPs were calculated with four different repair-times (T1/2-Liver-Repair= 0,0.5,1.0,2.0 hr) and three published NTCP models (Lyman-external-RT, Lyman 90Y-HCC-SIRT, parallel model) were compared to the incidence of RILD of the recruited patients to evaluate their ability of outcome prediction. Results: The mean normal liver physical dose (avg. 51.9 Gy, range 31.9–69.8 Gy) is higher than the suggested liver dose constraint for external beam treatment (∼30 Gy). However, none of the patients in our study developed RILD after the SIRT. The estimated probability of ‘no patient developing RILD’ obtained from the two Lyman models are 46.3% to 48.3% (T1/2-Liver-Repair= 0hr) and <1% for all other repair times. For the parallel model, the estimated probability is 97.3% (0hr), 51.7% (0.5hr), 2.0% (1.0hr) and <1% (2.0hr). Conclusion: Molecular-images providing the distribution of {sup 90}Y enable the dose-volume based dose/outcome analysis for SIRT. Current NTCP models fail to predict RILD complications in our patient population, unless a very short repair-time for the liver is assumed. The discrepancy between the Lyman {sup 90}Y-HCC-SIRT model predicted and the clinically observed outcomes further demonstrates the need of an NTCP model specific to the metastatic liver SIRT.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Real-time X-ray phase-contrast imaging using SPINNet—a speckle-based phase-contrast imaging neural network

X-ray phase-contrast imaging has become indispensable for visualizing samples with low absorption contrast. In this regard, speckle-based techniques have shown significant advantages in spatial resolution, phase sensitivity, and implementation flexibility compared with traditional methods. However, the computational cost associated with data inversion has hindered their wider adoption. By exploiting the power of deep learning, we developed a speckle-based phase-contrast imaging neural network (SPINNet) that significantly improves the imaging quality and boosts the phase retrieval speed by at least 2 orders of magnitude compared to existing methods. To achieve this performance, we combined SPINNet with a coded-mask-based technique, an enhanced version of the speckle-based method. Using this scheme, we demonstrate the simultaneous reconstruction of absorption and phase images on the order of 100 ms, where a traditional correlation-based analysis would take several minutes even with a cluster. In addition to significant improvement in speed, our experimental results show that the imaging and phase retrieval quality of SPINNet outperform existing single-shot speckle-based methods. Furthermore, we successfully demonstrate SPINNet application in x-ray optics metrology and 3D x-ray phase-contrast tomography. Our result shows that SPINNet could enable many applications requiring high-resolution and fast data acquisition and processing, such as in situ and in operando 2D and 3D phase-contrast imaging and real-time at-wavelength metrology and wavefront sensing.

36 MATERIALS SCIENCE↗
DOE OSTI2014

The simulation of 3D mass models in 2D digital mammography and breast tomosynthesis

Purpose: This work proposes a new method of building 3D breast mass models with different morphological shapes and describes the validation of the realism of their appearance after simulation into 2D digital mammograms and breast tomosynthesis images. Methods: Twenty-five contrast enhanced MRI breast lesions were collected and each mass was manually segmented in the three orthogonal views: sagittal, coronal, and transversal. The segmented models were combined, resampled to have isotropic voxel sizes, triangularly meshed, and scaled to different sizes. These masses were referred to as nonspiculated masses and were then used as nuclei onto which spicules were grown with an iterative branching algorithm forming a total of 30 spiculated masses. These 55 mass models were projected into 2D projection images to obtain mammograms after image processing and into tomographic sequences of projection images, which were then reconstructed to form 3D tomosynthesis datasets. The realism of the appearance of these mass models was assessed by five radiologists via receiver operating characteristic (ROC) analysis when compared to 54 real masses. All lesions were also given a breast imaging reporting and data system (BIRADS) score. The data sets of 2D mammography and tomosynthesis were read separately. The Kendall's coefficient of concordance was used for the interrater observer agreement assessment for the BIRADS scores per modality. Further paired analysis, using the Wilcoxon signed rank test, of the BIRADS assessment between 2D and tomosynthesis was separately performed for the real masses and for the simulated masses. Results: The area under the ROC curves, averaged over all observers, was 0.54 (95% confidence interval [0.50, 0.66]) for the 2D study, and 0.67 (95% confidence interval [0.55, 0.79]) for the tomosynthesis study. According to the BIRADS scores, the nonspiculated and the spiculated masses varied in their degrees of malignancy from normal (BIRADS 1) to highly suggestive for malignancy (BIRADS 5) indicating the required variety of shapes and margins of these models. The assessment of the BIRADS scores for all observers indicated good agreement based on Kendall's coefficient for both the 2D and the tomosynthesis evaluations. The paired analysis of the BIRADS scores between 2D and tomosynthesis for each observer revealed consistent behavior for the real and simulated masses. Conclusions: A database of 3D mass models, with variety of shapes and margins, was validated for the realism of their appearance for 2D digital mammography and for breast tomosynthesis. This database is suitable for use in future observer performance studies whether in virtual clinical trials or in patient images with simulated lesions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Sci-Thur PM - Colourful Interactions: Highlights 04: A Fast Quantitative MRI Acquisition and Processing Pipeline for Radiation Treatment Planning and Simulation

MRI-only Radiation Treatment Planning (RTP) is becoming increasingly popular because of a simplified work-flow, and less inconvenience to the patient who avoids multiple scans. The advantages of MRI-based RTP over traditional CT-based RTP lie in its superior soft-tissue contrast, and absence of ionizing radiation dose. The lack of electron-density information in MRI can be addressed by automatic tissue classification. To distinguish bone from air, which both appear dark in MRI, an ultra-short echo time (UTE) pulse sequence may be used. Quantitative MRI parametric maps can provide improved tissue segmentation/classification and better sensitivity in monitoring disease progression and treatment outcome than standard weighted images. Superior tumor contrast can be achieved on pure T{sub 1} images compared to conventional T{sub 1}-weighted images acquired in the same scan duration and voxel resolution. In this study, we have developed a robust and fast quantitative MRI acquisition and post-processing work-flow that integrates these latest advances into the MRI-based RTP of brain lesions. Using 3D multi-echo FLASH images at two different optimized flip angles (both acquired in under 9 min, and 1mm isotropic resolution), parametric maps of T{sub 1}, proton-density (M{sub 0}), and T{sub 2}{sup *} are obtained with high contrast-to-noise ratio, and negligible geometrical distortions, water-fat shifts and susceptibility effects. An additional 3D UTE MRI dataset is acquired (in under 4 min) and post-processed to classify tissues for dose simulation. The pipeline was tested on four healthy volunteers and a clinical trial on brain cancer patients is underway.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Poster – 39: Using Optical Scanner and 3D Printer Technology to Create Lead Shielding for Radiotherapy of Facial Skin Cancer with Low Energy Photons

Purpose: Treatment of skin cancers of the face using orthovoltage radiotherapy often requires lead shielding. However, creating a lead shield can be difficult because the face has complex and intricate contours. The traditional process involved creating a plaster mould of the patient’s face can be difficult for patients. Our goal was to develop an improved process by using an optical scanner and 3D printer technology. Methods: The oncologist defined the treatment field by drawing on each patient’s skin. Three-dimensional images were acquired using a consumer-grade optical scanner. A 3D model of each patient’s face was processed with mesh editing software before being printed on a 3D printer. Using a hammer, a 3 mm thick layer of lead was formed to closely fit the contours of the model. A hole was then cut out to define the field. Results: The lead shields created were remarkably accurate and fit the contours of the patients. The hole defining the field exposed only a minimally sized site to be exposed to radiation, while the rest of the face was protected. It was easy to obtain perfect symmetry for the definition of parallel opposed beams. Conclusion: We are routinely using this technique to build lead shielding that wraps around the patient as an alternative to cut-outs. We also use it for treatment of the tip of the nose using a parallel opposed pair beams with a wax nose block. We found this technique allows more accurate delineation of the cut-out and a more reproducible set-up.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

An Evaluation of Three Dimensional Scene Reconstruction Tools for Safeguards Applications

Over the past 5 years, advances in digital imaging and image processing have enabled everyday computing hardware, such as that found on laptops and even phones, to easily create 3D models of scenes from a series of still images. This field is broadly known as photogrammetry. For safeguards applications, a safeguards inspector could evaluate a 3D model of a facility (such as an enrichment plant or the top of a reactor) constructed from multiple photos instead of reviewing each photo individually. This report compares the detailed capabilities of a particular commercial offering (Quidient) that Oak Ridge National Laboratory (ORNL) has investigated in depth with the general capabilities provided in the industry and recommends areas where the general technology could be pursued for potential safeguards applications.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2014

A new architecture for fast ultrasound imaging

Some ultrasound imaging applications require high frame rate, for example 3D imaging and automated inspections of large components. Being the signal-processing throughput of the system the main bottleneck, parallel beamforming is required to achieve hundreds to thousands of images per second. Simultaneous A-scan line beamforming in all active channels is required to reach the intended high frame rate. To this purpose, a new parallel beamforming architecture that exploits the currently available processing resources available in state-of-the-art FPGAs is proposed. The work aims to get the optimal resource usage, high scalability and flexibility for different applications. To achieve these goals, the basic beamforming function is reformulated to be adapted to the DSP-cell architecture of state-of-the-art FPGAs. This allows performing simultaneous dynamic focusing on multiple A-scan lines. Some realistic examples are analyzed, evaluating resource requirements and maximum operating frequency. For example, a 128-channel system, with 128 scan lines and acquiring at 20 MSPS, can be built with 4 mid-range FPGAs, achieving up to 18000 frames per second, just limited by the maximum PRF. The gold standard Synthetic Transmit Aperture method (also called Total Focusing Method) can be carried out in real time at a processing rate of 140 high-resolution images per second (16 cm depth on steel)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Design of smart 3D-digital X-ray microtomographic scanners for non-destructive testing of materials and components of electronic devices with a multilayered structure

The article studies the operating procedures of an X-ray microtomographic scanner and the module of reconstruction and analysis 3D-image of a test sample in particular. An algorithm for 3D-image reconstruction based on image shadow projections and mathematical methods of the processing are described. Chapter 1 describes the basic principles of X-ray tomography and general procedures of the device developed. Chapters 2 and 3 are devoted to the problem of resources saving by the system during the X-ray tomography procedure, which is achieved by preprocessing of the initial shadow projections. Preprocessing includes background noise removing from the images, which reduces the amount of shadow projections in general and increases the efficiency of the group shadow projections compression. Chapter 4 covers general procedures of defect search, which is based on vector analysis principles. In conclusion, the main applications of X-ray tomography are presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

X-ray microtomographic scanners

The article studies the operating procedures of an X-ray microtomographic scanner and the module of reconstruction and analysis 3D-image of a test sample in particular. An algorithm for 3D-image reconstruction based on image shadow projections and mathematical methods of the processing are described. Chapter 1 describes the basic principles of X-ray tomography and general procedures of the device developed. Chapters 2 and 3 are devoted to the problem of resources saving by the system during the X-ray tomography procedure, which is achieved by preprocessing of the initial shadow projections. Preprocessing includes background noise removing from the images, which reduces the amount of shadow projections in general and increases the efficiency of the group shadow projections compression. In conclusion, the main applications of X-ray tomography are presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

SU-F-J-72: A Clinical Usable Integrated Contouring Quality Evaluation Software for Radiotherapy

Purpose: To introduce the Auto Contour Evaluation (ACE) software, which is the clinical usable, user friendly, efficient and all-in-one toolbox for automatically identify common contouring errors in radiotherapy treatment planning using supervised machine learning techniques. Methods: ACE is developed with C# using Microsoft .Net framework and Windows Presentation Foundation (WPF) for elegant GUI design and smooth GUI transition animations through the integration of graphics engines and high dots per inch (DPI) settings on modern high resolution monitors. The industrial standard software design pattern, Model-View-ViewModel (MVVM) pattern, is chosen to be the major architecture of ACE for neat coding structure, deep modularization, easy maintainability and seamless communication with other clinical software. ACE consists of 1) a patient data importing module integrated with clinical patient database server, 2) a 2D DICOM image and RT structure simultaneously displaying module, 3) a 3D RT structure visualization module using Visualization Toolkit or VTK library and 4) a contour evaluation module using supervised pattern recognition algorithms to detect contouring errors and display detection results. ACE relies on supervised learning algorithms to handle all image processing and data processing jobs. Implementations of related algorithms are powered by Accord.Net scientific computing library for better efficiency and effectiveness. Results: ACE can take patient’s CT images and RT structures from commercial treatment planning software via direct user input or from patients’ database. All functionalities including 2D and 3D image visualization and RT contours error detection have been demonstrated with real clinical patient cases. Conclusion: ACE implements supervised learning algorithms and combines image processing and graphical visualization modules for RT contours verification. ACE has great potential for automated radiotherapy contouring quality verification. Structured with MVVM pattern, it is highly maintainable and extensible, and support smooth connections with other clinical software tools.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials (Second Annual Progress Report)

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of nuclear reactor parts. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which can introduce internal material flaws, such as pores and anisotropy. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures due to exposure to high temperature, radiation and corrosive environment in a nuclear reactor. Thermal tomography (TT) provides a capability for non-destructive evaluation of sub-surface defects in arbitrary size structures. Thermal tomography is a computational method for heat diffusion-based imaging of solids, which provides 3D visualization of data from flash thermography measurements. We investigate thermal tomography imaging and nondestructive evaluation of stainless steel and nickel super alloy metallic structures produced with laser powder bed fusion (LPBF) additive manufacturing (AM) process. Metallic structures produced with LPBF contain defects, and there are limited capabilities to evaluate these structures non-destructively. Thermal tomography reconstruction of 3D apparent spatial effusivity provides information about AM structure geometry and internal material flaws. We study performance of thermal tomography in imaging of metallic structures through COMSOL computer simulations of transient heat transfer, and through reconstruction of data obtained from experimental measurements. Reconstruction of internal defects is investigated using a stainless steel 316L specimen with flat bottom hole (FBH) indentations, and Inconel 718 plate produced with laser powder bed fusion (LPBF) method, which contains imprinted hemispherical shape low density regions containing non-sintered metallic powder. The FBH’s have the same sizes as the imprinted defects in the LPBF specimens, but offer better imaging contrast. Thermal tomography reconstructions provide visualizations of internal defects, and allow for estimation of their sizes and locations. Detection sensitivity of TT is limited by noises. We investigate separation of signal from noise in thermography images using several machine learning (ML) methods, including new spatio-temporal blind source separation (STBSS) and spatio-temporal sparse dictionary learning (STSDL) methods. Performance of the ML methods is benchmarked using thermography data obtained from imaging stainless steel 316L and Inconel 718 specimens produced LPBF method with imprinted calibrated porosity defects. The ML methods are ranked by F-score and execution runtime. Finally, we investigate TT of AM stainless steel 316L specimen with imprinted internal porosity defects using relatively low-cost, small form factor infrared (IR) camera based on uncooled micro bolometer detector. Sparse coding related K-means singular value decomposition (SVD) machine learning, image processing algorithms are developed to improve quality of TT images through removal of Additive white Gaussian noise without blurring the images. Following initial qualification of an AM component for deployment in a nuclear reactor, a compact TT can also be used for in-service nondestructive evaluation (NDE). With capability to perform in-service NDE of the AM component lifecycle, TT data can be used for development of a component digital twin.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

MO-A-9A-01: Innovation in Medical Physics Practice: 3D Printing Applications

3D printing, also called additive manufacturing, has great potential to advance the field of medicine. Many medical uses have been exhibited from facial reconstruction to the repair of pulmonary obstructions. The strength of 3D printing is to quickly convert a 3D computer model into a physical object. Medical use of 3D models is already ubiquitous with technologies such as computed tomography and magnetic resonance imaging. Thus tailoring 3D printing technology to medical functions has the potential to impact patient care. This session will discuss applications to the field of Medical Physics. Topics discussed will include introduction to 3D printing methods as well as examples of real-world uses of 3D printing spanning clinical and research practice in diagnostic imaging and radiation therapy. The session will also compare 3D printing to other manufacturing processes and discuss a variety of uses of 3D printing technology outside the field of Medical Physics. Learning Objectives: Understand the technologies available for 3D Printing Understand methods to generate 3D models Identify the benefits and drawbacks to rapid prototyping / 3D Printing Understand the potential issues related to clinical use of 3D Printing.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

CSAPR2 Optimized Convective Cell Tracking Data during TRACER

One of the challenges in analyzing convective cell properties is to observe the quick evolution of individual convective cells. While the operational radar data provide a volumetric data set to analyze radar observables of convective precipitation clouds, previous studies also suggested the quick evolution of cell life cycle that might not be captured by conventional radar volume scan strategies that take ~5-7 minutes. Aiming at enhancing our understanding of the links between convective cloud kinematic and microphysical processes as well as life cycles, the Tracking Aerosol Convection Interactions ExpeRiment (TRACER; Jensen et al. 2019) was conducted at Houston, Texas, in 2022. The TRACER campaign deployed the 2nd generation C-band Scanning ARM Precipitation Radar (CSAPR2), which performed frequent updates of range height indicator (RHI) and sector plan position indicator (PPI) scans to track individual convective cells every < 2 minutes, guided by a new cell tracking framework, Multisensor Agile Adaptive Sampling (MAAS; Kollias et al. 2020). This allows for capturing fast-evolving radar observables. We provide the processed CSAPR2 cell tracking data in CfRadial format collected during the TRACER field campaign from June to September 2022. The data files include processed radar variables: noise-masked reflectivity and differential reflectivity corrected for rain attenuation and systematic biases, noise-masked dealiased radial velocity, specific differential phase, locations of target cells (latitude, longitude, radar range), and radar-echo classification. Figure 1 provides an example of a 3D image of CSAPR2 reflectivity from the lowest PPI scan and an RHI scan after data processing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Anatomy of an agricultural antagonist: Feeding complex structure and function of three xylem sap‐feeding insects illuminated with synchrotron‐based 3D imaging

Abstract Many insects feed on xylem or phloem sap of vascular plants. Although physical damage to the plant is minimal, the process of insect feeding can transmit lethal viruses and bacterial pathogens. Disparities between insect‐mediated pathogen transmission efficiency have been identified among xylem sap‐feeding insects; however, the mechanistic drivers of these trends are unclear. Identifying and understanding the structural factors and associated integrated functional components that may ultimately determine these disparities are critical for managing plant diseases. Here, we applied synchrotron‐based X‐ray microcomputed tomography to digitally reconstruct the morphology of three xylem sap‐feeding insect vectors of plant pathogens: Graphocephala atropunctata (blue‐green sharpshooter; Hemiptera, Cicadellidae) and Homalodisca vitripennis (glassy‐winged sharpshooter; Hemiptera, Cicadellidae), and the spittlebug Philaenus spumarius (meadow spittlebug; Hemiptera, Aphrophoridae). The application of this technique revealed previously undescribed anatomical features of these organisms, such as key components of the salivary complex. The visualization of the 3D structure of the precibarial valve led to new insights into the mechanism of how this structure functions. Morphological disparities with functional implications between taxa were highlighted as well, including the morphology and volume of the cibarial dilator musculature responsible for extracting xylem sap, which has implications for force application capabilities. These morphological insights will be used to target analyses illuminating functional differences in feeding behavior.

3D imaging↗
DOE OSTI2014

MO-C-18A-01: Advances in Model-Based 3D Image Reconstruction

Recent years have seen the emergence of CT image reconstruction techniques that exploit physical models of the imaging system, photon statistics, and even the patient to achieve improved 3D image quality and/or reduction of radiation dose. With numerous advantages in comparison to conventional 3D filtered backprojection, such techniques bring a variety of challenges as well, including: a demanding computational load associated with sophisticated forward models and iterative optimization methods; nonlinearity and nonstationarity in image quality characteristics; a complex dependency on multiple free parameters; and the need to understand how best to incorporate prior information (including patient-specific prior images) within the reconstruction process. The advantages, however, are even greater – for example: improved image quality; reduced dose; robustness to noise and artifacts; task-specific reconstruction protocols; suitability to novel CT imaging platforms and noncircular orbits; and incorporation of known characteristics of the imager and patient that are conventionally discarded. This symposium features experts in 3D image reconstruction, image quality assessment, and the translation of such methods to emerging clinical applications. Dr. Chen will address novel methods for the incorporation of prior information in 3D and 4D CT reconstruction techniques. Dr. Pan will show recent advances in optimization-based reconstruction that enable potential reduction of dose and sampling requirements. Dr. Stayman will describe a “task-based imaging” approach that leverages models of the imaging system and patient in combination with a specification of the imaging task to optimize both the acquisition and reconstruction process. Dr. Samei will describe the development of methods for image quality assessment in such nonlinear reconstruction techniques and the use of these methods to characterize and optimize image quality and dose in a spectrum of clinical applications. Learning Objectives: Learn the general methodologies associated with model-based 3D image reconstruction. Learn the potential advantages in image quality and dose associated with model-based image reconstruction. Learn the challenges associated with computational load and image quality assessment for such reconstruction methods. Learn how imaging task can be incorporated as a means to drive optimal image acquisition and reconstruction techniques. Learn how model-based reconstruction methods can incorporate prior information to improve image quality, ease sampling requirements, and reduce dose.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Rapid 3D nanoscale coherent imaging via physics-aware deep learning

Phase retrieval, the problem of recovering lost phase information from measured intensity alone, is an inverse problem that is widely faced in various imaging modalities ranging from astronomy to nanoscale imaging. The current process of phase recovery is iterative in nature. As a result, the image formation is time consuming and computationally expensive, precluding real-time imaging. Here, we use 3D nanoscale X-ray imaging as a representative example to develop a deep learning model to address this phase retrieval problem. We introduce 3D-CDI-NN, a deep convolutional neural network and differential programing framework trained to predict 3D structure and strain, solely from input 3D X-ray coherent scattering data. Our networks are designed to be “physics-aware” in multiple aspects; in that the physics of the X-ray scattering process is explicitly enforced in the training of the network, and the training data are drawn from atomistic simulations that are representative of the physics of the material. We further refine the neural network prediction through a physics-based optimization procedure to enable maximum accuracy at lowest computational cost. 3D-CDI-NN can invert a 3D coherent diffraction pattern to real-space structure and strain hundreds of times faster than traditional iterative phase retrieval methods. Our integrated machine learning and differential programing solution to the phase retrieval problem is broadly applicable across inverse problems in other application areas.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

High Speed In-situ X-ray Imaging of 3D Freeze Printing of Aerogels

3D freeze printing (3DFP) combines drop-on-demand (DOD) inkjet printing with freeze casting to fabricate lightweight and multifunctional aerogels with customized geometries. Freeze casting is an efficient and easily implemented method capable of fabricating porous, sponge-like structures for many different applications. This process enables tailoring the microstructure of the final product (i.e., pore morphology, alignment, average size distribution, etc.) by controlling the fabrication conditions and freezing kinetics. Furthermore, its combination with DOD printing provides the capability of engineering the macrostructure without relying on a mold as reported for 3D freeze-printed aerogels made from graphene, silver nanowires, and other nanocomposites. In this paper, we performed in-situ X-ray imaging to understand the inside process dynamics in 3DFP using a commercially available colloidal silica ink. We investigated the 3DFP process with the following hierarchy: first, single droplets; then, uniform lines obtained from coalescence of droplets; and finally, three consecutive lines deposited layer by layer. With the help of X-ray imaging, the importance of the balance between material deposition and freezing rates was shown in-situ by the observation inside of the freeze front following the tip of the printed line. The effects of the substrate temperature on the elimination of undesired interfacial boundaries were also shown by the observed ice crystals penetrating from lower to upper layer.

36 MATERIALS SCIENCE↗