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At least 307 records · Page 17

Phase control of austenitic chrome-nickel steel

The paper presents the results of the comparative study of the possibilities of different structural and magnetic methods for detection and visualization of the strain-induced martensitic phase in low carbon austenitic chromium-nickel steel. Results of TEM, SEM, optical microscopy, atomic and magnetic force microscopy, and magnetic measurements are presented. Amount of the magnetic strain-induced martensite was estimated. We pioneered magnetic force microscopic images of the single domain cluster distribution of the strain-induced martensite in austenite-ferrite materials.

36 MATERIALS SCIENCE↗

Statistical projections for multi-dimensional visual data exploration

When working with large, multidimensional and multivariate data, science users are frequently interested in understanding variation in data, as opposed to the actual data values. Our work focuses on exploring how a simple statistical metric, the Coefficient of Variation (or Cv), can be used in several different ways to facilitate understanding variation in large data. As a statistical measure, it offers a key advantage over more widely accepted measures like standard deviation, namely to its ability to capture local variation properties. As a multidimensional projection operator, Cv is an effective way of reducing data size while preserving the key variational signal. Visualizations produced from Cv that target conveying variation in data are highly informative, especially compared to those produced with more widely known methods. We demonstrate these ideas within the context of a two-part application case study focusing on understanding long-Term trends in the the changes in precipitation and winds in large-scale climate model ensemble output.

Nguyen, H↗

Coronary artery analysis: Computer-assisted selection of best-quality segments in multiple-phase coronary CT angiography

Purpose: The authors are developing an automated method to identify the best-quality coronary arterial segment from multiple-phase coronary CT angiography (cCTA) acquisitions, which may be used by either interpreting physicians or computer-aided detection systems to optimally and efficiently utilize the diagnostic information available in multiple-phase cCTA for the detection of coronary artery disease. Methods: After initialization with a manually identified seed point, each coronary artery tree is automatically extracted from multiple cCTA phases using our multiscale coronary artery response enhancement and 3D rolling balloon region growing vessel segmentation and tracking method. The coronary artery trees from multiple phases are then aligned by a global registration using an affine transformation with quadratic terms and nonlinear simplex optimization, followed by a local registration using a cubic B-spline method with fast localized optimization. The corresponding coronary arteries among the available phases are identified using a recursive coronary segment matching method. Each of the identified vessel segments is transformed by the curved planar reformation (CPR) method. Four features are extracted from each corresponding segment as quality indicators in the original computed tomography volume and the straightened CPR volume, and each quality indicator is used as a voting classifier for the arterial segment. A weighted voting ensemble (WVE) classifier is designed to combine the votes of the four voting classifiers for each corresponding segment. The segment with the highest WVE vote is then selected as the best-quality segment. In this study, the training and test sets consisted of 6 and 20 cCTA cases, respectively, each with 6 phases, containing a total of 156 cCTA volumes and 312 coronary artery trees. An observer preference study was also conducted with one expert cardiothoracic radiologist and four nonradiologist readers to visually rank vessel segment quality. The performance of our automated method was evaluated by comparing the automatically identified best-quality segments identified by the computer to those selected by the observers. Results: For the 20 test cases, 254 groups of corresponding vessel segments were identified after multiple phase registration and recursive matching. The AI-BQ segments agreed with the radiologist’s top 2 ranked segments in 78.3% of the 254 groups (Cohen’s kappa 0.60), and with the 4 nonradiologist observers in 76.8%, 84.3%, 83.9%, and 85.8% of the 254 groups. In addition, 89.4% of the AI-BQ segments agreed with at least two observers’ top 2 rankings, and 96.5% agreed with at least one observer’s top 2 rankings. In comparison, agreement between the four observers’ top ranked segment and the radiologist’s top 2 ranked segments were 79.9%, 80.7%, 82.3%, and 76.8%, respectively, with kappa values ranging from 0.56 to 0.68. Conclusions: The performance of our automated method for selecting the best-quality coronary segments from a multiple-phase cCTA acquisition was comparable to the selection made by human observers. This study demonstrates the potential usefulness of the automated method in clinical practice, enabling interpreting physicians to fully utilize the best available information in cCTA for diagnosis of coronary disease, without requiring manual search through the multiple phases and minimizing the variability in image phase selection for evaluation of coronary artery segments across the diversity of human readers with variations in expertise.

61 RADIATION PROTECTION AND DOSIMETRY↗

Plutonium Critical Mass Curve Comparison to Mass at Upper Subcritical Limit (USL) Using Whisper

Whisper is computational software designed to assist the nuclear criticality safety analyst with validation studies with the MCNP ® Monte Carlo radiation transport package. Standard approaches to validation rely on the selection of benchmarks based upon expert judgment. Whisper uses sensitivity/uncertainty (S/U) methods to select relevant benchmarks to a particular application or set of applications being analyzed. Using these benchmarks, Whisper computes a calculational margin. Whisper attempts to quantify the margin of subcriticality (MOS) from errors in software and uncertainties in nuclear data. The combination of the Whisper-derived calculational margin and MOS comprise the baseline upper subcritical limit (USL), to which an additional margin may be applied by the nuclear criticality safety analyst as appropriate to ensure subcriticality. A series of critical mass curves for plutonium, similar to those found in Figure 31 of LA-10860-MS, have been generated using MCNP6.1.1 and the iterative parameter study software, WORM_Solver. The baseline USL for each of the data points of the curves was then computed using Whisper 1.1. The USL was then used to determine the equivalent mass for plutonium metal-water system. ANSI/ANS-8.1 states that it is acceptable to use handbook data, such as the data directly from the LA-10860-MS, as it is already considered validated (Section 4.3 4) “Use of subcritical limit data provided in ANSI/ANS standards or accepted reference publications does not require further validation.”). This paper attempts to take a novel approach to visualize traditional critical mass curves and allows comparison with the amount of mass for which the k eff is equal to the USL (calculational margin + margin of subcriticality). However, the intent is to plot the critical mass data along with USL, not to suggest that already accepted handbook data should have new and more rigorous requirements for validation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

VISILIENCE: An Interactive Visualization Framework for Resilience Analysis using Control-Flow Graph

Soft errors have become one of the major concerns for the error resilience of HPC applications, as those errors can cause HPC applications to generate serious outcomes such as Silent Data Corruptions (SDCs). A large body of approaches has been proposed to analyze the resilience of HPC applications. However, existing studies rarely address the challenges of the analysis result perception. Specifically, resilience analysis techniques often produce a massive volume of unstructured data, making it difficult for programmers to conduct the resilience analysis due to non-intuitive raw data. Furthermore, different analysis models produce diverse results with multiple levels of details, which may create hurdles to compare and explore the resilience of HPC program execution. To this end, we present VISILIENCE, an interactive VISual resILIENCE analysis framework to allow programmers to facilitate the resilience analysis of HPC applications. In particular, VISILIENCE leverages an effective visualization approach Control Flow Graph (CFG) to present a function execution. In addition, three widely-used models for resilience analysis (i.e., Y-Branch, IPAS, and TRIDENT) are seamlessly embedded into the framework for resilience analysis and result comparison. Multiple case studies have been conducted to demonstrate the effectiveness of our proposed framework VISILIENCE.

Jiang, Hailong↗

Hierarchical Spatio-temporal Visual Analysis of Cluster Evolution in Electrocorticography Data

Here, we present ECoG ClusterFlow, a novel interactive visual analysis tool for the exploration of high-resolution Electrocorticography (ECoG) data. Our system detects and visualizes dynamic high-level structures, such as communities, using the time-varying spatial connectivity network derived from the high-resolution ECoG data. ECoG ClusterFlow provides a multi-scale visualization of the spatio-temporal patterns underlying the time-varying communities using two views: 1) an overview summarizing the evolution of clusters over time and 2) a hierarchical glyph-based technique that uses data aggregation and small multiples techniques to visualize the propagation of clusters in their spatial domain. ECoG ClusterFlow makes it possible 1) to compare the spatio-temporal evolution patterns across various time intervals, 2) to compare the temporal information at varying levels of granularity, and 3) to investigate the evolution of spatial patterns without occluding the spatial context information. Lastly, we present case studies done in collaboration with neuroscientists on our team for both simulated and real epileptic seizure data aimed at evaluating the effectiveness of our approach.

60 APPLIED LIFE SCIENCES↗

A Lagrangian analysis of pockets of open cells over the southeastern Pacific

Abstract. Pockets of open cells (POCs) have been shown to develop within closed-cell stratocumulus (StCu), and a large body of evidence suggests that the development of POCs result from changes in small-scale processes internal to the boundary layer rather than large-scale forcings. Precipitation is widely viewed as a key process important to POC development and maintenance. In this study, GOES-16 satellite observations are used in conjunction with MERRA-2 winds to track and compare the microphysical and environmental evolution of two populations of closed-cell StCu selected by visual inspection over the southeastern Pacific Ocean: one group that transitions to POCs and another comparison group (CLOSED) that does not. The high spatiotemporal resolution of the new GOES-16 data allows for a detailed examination of the temporal evolution of POCs in this region. We find that POCs tend to develop near the coast, last tens of hours, are larger than 104 km2, and often (88 % of cases) do not re-close before they exit the StCu deck. Most POCs are observed to form at night and tend to exit the StCu during the day when the StCu is contracting in area. Relative to the CLOSED trajectories, POCs have systematically larger effective radii, lower cloud drop number concentrations, a comparable conditional in-cloud liquid water path, and a higher frequency of more intense precipitation. Meanwhile, no systematic environmental differences other than boundary layer height are observed between POC and CLOSED trajectories. Interestingly, there are no differences in reanalysis aerosol optical depth between both sets of trajectories, which may lead one to the interpretation that differences in aerosol concentrations are not influencing POC development or resulting in a large number that re-close. However, this largely depends on the reanalysis treatment of aerosol–cloud interactions, and the product used in this study has no explicit handling of these important processes. These results support the consensus view regarding the importance of precipitation on the formation and maintenance of POCs and demonstrate the utility of modern geostationary remote sensing data in evaluating the POC life cycle.

54 ENVIRONMENTAL SCIENCES↗

Stress field measurements using quantitative schlieren

Quantitative schlieren analysis is extended here to optically transparent solids in quasi-static and dynamic experiments to measure stress distributions. The quasi-static experiments in polymethyl methacrylate (PMMA) compared refraction angles and stress gradients calculated from schlieren images to the analytical Flamant solution of a line load on a half-space. The quantitative schlieren measurements of the stress field in the thin sample with a load compared well to the analytical solution. The analysis method was then extended to explosive induced shock waves in PMMA. The explosive induced response of PMMA was experimentally studied using high-speed schlieren to visualize the shock propagation in conjunction with Photon Doppler Velocimetry (PDV) to record surface velocity histories. The stress state estimated from the schlieren images was compared to the stress calculated from the PDV measurements. High-speed imaging limitations caused the shock wave to not be fully resolved in the images, but was resolved in the PDV measurement. The stress state behind the shock calculated from the high-speed images followed a similar trend to the stress calculated from the PDV measurements.

Physics↗

Foveal vision reduces neural resources in agent-based game learning

Efficient processing of information is crucial for the optimization of neural resources in both biological and artificial visual systems. In this paper, we study the efficiency that may be obtained via the use of a fovea. Using biologically-motivated agents, we study visual information processing, learning, and decision making in a controlled artificial environment, namely the Atari Pong video game. We compare the resources necessary to play Pong between agents with and without a fovea. Our study shows that a fovea can significantly reduce the neural resources, in the form of number of neurons, number of synapses, and number of computations, while at the same time maintaining performance at playing Pong. To our knowledge, this is the first study in which an agent must simultaneously optimize its visual system, along with its decision making and action generation capabilities. That is, the visual system is integral to a complete agent.

60 APPLIED LIFE SCIENCES↗

Comparing nonrigid registration techniques for motion corrected MR prostate diffusion imaging

Purpose: T{sub 2}-weighted magnetic resonance imaging (MRI) is commonly used for anatomical visualization in the pelvis area, such as the prostate, with high soft-tissue contrast. MRI can also provide functional information such as diffusion-weighted imaging (DWI) which depicts the molecular diffusion processes in biological tissues. The combination of anatomical and functional imaging techniques is widely used in oncology, e.g., for prostate cancer diagnosis and staging. However, acquisition-specific distortions as well as physiological motion lead to misalignments between T{sub 2} and DWI and consequently to a reduced diagnostic value. Image registration algorithms are commonly employed to correct for such misalignment. Methods: The authors compare the performance of five state-of-the-art nonrigid image registration techniques for accurate image fusion of DWI with T{sub 2}. Results: Image data of 20 prostate patients with cancerous lesions or cysts were acquired. All registration algorithms were validated using intensity-based as well as landmark-based techniques. Conclusions: The authors’ results show that the “fast elastic image registration” provides most accurate results with a target registration error of 1.07 ± 0.41 mm at minimum execution times of 11 ± 1 s.

60 APPLIED LIFE SCIENCES↗

A combined static-dynamic single-dose imaging protocol to compare quantitative dynamic SPECT with static conventional SPECT

Background: SPECT myocardial perfusion imaging (MPI) is a clinical mainstay that is typically performed with static imaging protocols and visually or semi-quantitatively assessed for perfusion defects based upon the relative intensity of myocardial regions. Dynamic cardiac SPECT presents a new imaging technique based on time-varying information of radiotracer distribution, which permits the evaluation of regional myocardial blood flow (MBF) and coronary flow reserve (CFR). In this work, a preliminary feasibility study was conducted in a small patient sample designed to implement a unique combined static-dynamic single-dose one-day visit imaging protocol to compare quantitative dynamic SPECT with static conventional SPECT for improving the diagnosis of coronary artery disease (CAD). Methods: Fifteen patients (11 males, four females, mean age 71 ± 9 years) were enrolled for a combined dynamic and static SPECT (Infinia Hawkeye 4, GE Healthcare) imaging protocol with a single dose of {sup 99m}Tc-tetrofosmin administered at rest and a single dose administered at stress in a one-day visit. Out of 15 patients, eleven had selective coronary angiography (SCA), 8 within 6 months and the rest within 24 months of SPECT imaging, without intervening symptoms or interventions. The extent and severity of perfusion defects in each myocardial region was graded visually. Dynamically acquired data were also used to estimate the MBF and CFR. Both visually graded images and estimated CFR were tested against SCA as a reference to evaluate the validity of the methods. Results: Overall, conventional static SPECT was normal in ten patients and abnormal in five patients, dynamic SPECT was normal in 12 patients and abnormal in three patients, and CFR from dynamic SPECT was normal in nine patients and abnormal in six patients. Among those 11 patients with SCA, conventional SPECT was normal in 5, 3 with documented CAD on SCA with an overall accuracy of 64%, sensitivity of 40% and specificity of 83%. Dynamic SPECT image analysis also produced a similar accuracy, sensitivity, and specificity. CFR was normal in 6, each with CAD on SCA with an overall accuracy of 91%, sensitivity of 80%, and specificity of 100%. The mean CFR was significantly lower for SCA detected abnormal than for normal patients (3.86±1.06 vs 1.94±0. 0.67, P < 0.001). Conclusions: The visually assessed image findings in static and dynamic SPECT are subjective, and may not reflect direct physiologic measures of coronary lesion based on SCA. The CFR measured with dynamic SPECT is fully objective, with better sensitivity and specificity, available only with the data generated from the dynamic SPECT method.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Energy flow networks: deep sets for particle jets

A key question for machine learning approaches in particle physics is how to best represent and learn from collider events. As an event is intrinsically a variable-length unordered set of particles, we build upon recent machine learning efforts to learn directly from sets of features or “point clouds”. Adapting and specializing the “Deep Sets” framework to particle physics, we introduce Energy Flow Networks, which respect infrared and collinear safety by construction. We also develop Particle Flow Networks, which allow for general energy dependence and the inclusion of additional particle-level information such as charge and flavor. These networks feature a per-particle internal (latent) representation, and summing over all particles yields an overall event-level latent representation. We show how this latent space decomposition unifies existing event representations based on detector images and radiation moments. To demonstrate the power and simplicity of this set-based approach, we apply these networks to the collider task of discriminating quark jets from gluon jets, finding similar or improved performance compared to existing methods. We also show how the learned event representation can be directly visualized, providing insight into the inner workings of the model. These architectures lend themselves to efficiently processing and analyzing events for a wide variety of tasks at the Large Hadron Collider. Implementations and examples of our architectures are available online in our EnergyFlow package.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The Role of a Curved Electrode with Controllable Direction in the Radiofrequency Ablation of Liver Tumors Behind Large Vessels

Purpose: To investigate the role of a novel curved radiofrequency ablation (RFA) electrode with controllable direction in the ablation of tumors behind large hepatic vessels in ex vivo bovine and in vivo canine liver experiments. Materials and Methods: Approval from the institutional animal care and use committee was obtained. In ex vivo experiments, conventional multi-tines expandable electrodes, conventional monopolar straight electrodes and novel curved electrodes were used in the ablation of the bovine liver (n = 90). The ablated area, parallel axis, vertical axis and shape of different electrodes were compared. Then, 24 beagle dogs (10 months old, female) were used for in vivo experiments. Visual tumor targets deeply located in the portal vein were established, and ultrasound-guided liver ablation was performed with different electrodes. The ablation range, target coverage rate, percentage of normal tissue injury and damage to adjacent vessels were evaluated. The Kruskal–Wallis test and the Chi-squared test were used for statistical analysis. Results: For the ex vivo study with a 3-cm electrode, the ablation area of the multi-tines expandable electrode group (7.14 ± 0.16 cm{sup 2}) was significantly larger than that of the novel curved electrode group (5.01 ± 0.30 cm{sup 2}, P < 0.001) and the monopolar straight electrode group (5.43 ± 0.15 cm{sup 2}, P < 0.001). The results obtained with the 4-cm electrode in the three groups were in accordance with those of the 3-cm electrode. In vivo, the normal tissue damage area of the novel curved electrode group was smaller than that of the multi-tines expandable electrode group (1.10 ± 0.18 cm{sup 2} vs. 4.00 ± 0.18 cm{sup 2}, P < 0.001). The target coverage rate of the novel curved electrode group was better than that of the monopolar straight electrode group (100% vs. 80.86 ± 1.68%, P < 0.001). The hematoxylin and eosin (H&E) and TUNEL staining results showed that the ablation necrosis area was adjacent to large vessels, but the vascular wall was not significantly damaged in the novel curved electrode group. Conclusion: Our preliminary results showed that the novel curved RFA electrode with controllable direction could achieve accurate ablation for tumors behind large hepatic vessels, with a better target coverage rate and less damage to normal tissue, than conventional multi-tines expandable electrodes and monopolar straight electrodes.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Clinical Evaluation of Normalized Metal Artifact Reduction in kVCT Using MVCT Prior Images (MVCT-NMAR) for Radiation Therapy Treatment Planning

Purpose: To evaluate the metal artifacts in diagnostic kilovoltage computed tomography (kVCT) images of patients that are corrected by use of a normalized metal artifact reduction (NMAR) method with megavoltage CT (MVCT) prior images: MVCT-NMAR. Methods and Materials: MVCT-NMAR was applied to images from 5 patients: 3 with dual hip prostheses, 1 with a single hip prosthesis, and 1 with dental fillings. The corrected images were evaluated for visualization of tissue structures and their interfaces and for radiation therapy dose calculations. They were compared against the corresponding images corrected by the commercial orthopedic metal artifact reduction algorithm in a Phillips CT scanner. Results: The use of MVCT images for correcting kVCT images in the MVCT-NMAR technique greatly reduces metal artifacts, avoids secondary artifacts, and makes patient images more useful for correct dose calculation in radiation therapy. These improvements are significant, provided the MVCT and kVCT images are correctly registered. The remaining and the secondary artifacts (soft tissue blurring, eroded bones, false bones or air pockets, CT number cupping within the metal) present in orthopedic metal artifact reduction corrected images are removed in the MVCT-NMAR corrected images. A large dose reduction was possible outside the planning target volume (eg, 59.2 Gy to 52.5 Gy in pubic bone) when these MVCT-NMAR corrected images were used in TomoTherapy treatment plans without directional blocks for a prostate cancer patient. Conclusions: The use of MVCT-NMAR corrected images in radiation therapy treatment planning could improve the treatment plan quality for patients with metallic implants.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Imaging of 3D morphological evolution of nanoporous silicon anode in lithium ion battery by X-ray nano-tomography

Nanostructured silicon with its high theoretical capacity and ability to accommodate volume expansion has attracted great attention as a promising anode material for Lithium ion (Li-ion) batteries. Liquid metal dealloying method, is a novel method to create nanoporous silicon (np-Si). The assembled Li-ion batteries based on such np- Si anode can be cycled beyond 1500 cycles, in 1000 mA h/g constant capacity cycling mode with consistent performance; however, it suffers from degradation after ~ 460 cycles, while being cycled under 2000 mA h/g. To reveal the failure mechanism and differences in the morphological evolution in different capacity cycling modes in the np-Si anode, we conducted synchrotron X-ray nano-tomography studies. The three dimensional (3D) morphological evolution was visualized and quantified as a function of the number of cycles and cycling capacities. By comparing the 3D morphology under each cycling condition and correlating these 3D morphological changes with cycling-life performance, we elucidate the failure mechanism of the np-Si electrodes resulting from a mesoscopic to macroscopic deformation, involving volume expansion and gradual delamination. In particular, the shorter cycling life in higher-capacity cycling mode stems from particle agglomeration. Overall, while the nanoporous structure can accommodate the volume expansion locally, these mesoscopic and macroscopic deformations ultimately result in heterogeneous stress distribution with faster delamination. As a result, the work thus sheds the light on the importance to consider the structural evolution at the mesoscopic and macroscopic scales, while designing nano-structured energy storage materials for enhanced performances, particularly for long cycling-life durability.

25 ENERGY STORAGE↗

Automated construction of clear-sky dictionary from all-sky imager data

All-sky imagers (ASIs) have significant promise as scalable sensors for short-term solar irradiance forecasting. Many of the current computational techniques that use ASIs for this purpose rely on collections of clear-sky images indexed by time of day, solar angle, or both, called clear-sky dictionaries (CSDs). These CSDs act as baselines against which images can be compared to locate and classify clouds within the image frame. CSDs are often compiled by hand, where individuals visually inspect collections of images one at a time to find clear-sky images. This process is not scalable, and it is prone to error. This paper proposes an automated, nonparametric alternative that uses the principles of digital image processing to find clear-sky images within a set of images taken over several days. We use ground-truth measurements of the clearness index to assess the performance of our method, and we show that the images it selects accurately correspond to clear-sky images. We also compare our proposal, which is nonparametric, with a state-of-the-art parametric method. The numerical results indicate that the performance of the method proposed here is superior.

14 SOLAR ENERGY↗

Enhancing physicochemical, bioactive, and nutritional properties of sweet potatoes: Ultrasonic contact drying with slot jet nozzles compared to hot-air drying and freeze drying

Sweet potatoes are a rich source of nutrients and bioactive compounds, but their quality can be impacted by the drying process. This study investigates the impact of slot jet reattachment (SJR) nozzle and ultrasound (US) combined drying (SJR + US) on sweet potato quality, compared to freeze-drying (FD), SJR drying, and hot air drying (HAD). SJR + US drying at 50 °C closely resembled FD in enhancing quality attributes and outperformed HAD and SJR in key areas such as rehydration, shrinkage ratios, and nutritional composition. Notably, SJR + US at 50 °C produced the highest total starch (36.84 g/100 g), total dietary fiber (8.48 g/100 g), total phenolic content (158.19 mg GAE/100 g), total flavonoid content (119.08 mg QE/g), DPPH antioxidant activity (6.44 μmol TE/g), β-carotene (31.98 mg/100 g), and vitamin C (5.27 mg/100 g). It also exhibited higher glass transition temperatures (Tg: 14.49 °C), indicating better stability at room temperature. The hardness values for SJR + US samples were similar to FD, while HAD samples had the highest hardness. SJR + US at 50 °C resulted in the lowest total color changes (ΔE), indicating minimal impact on appearance. Additionally, FTIR analysis revealed that peaks in specific spectral regions indicated superior preservation of bioactive compounds in SJR + US samples compared to other methods, which was also confirmed by principal component analysis (PCA) and heatmap visualization. Overall, these findings suggest that SJR + US is an effective alternative to conventional drying techniques, significantly improving the quality of dried sweet potatoes.

Color↗

Gradient Architecture Design in Scalable Porous Battery Electrodes

Because it has been demonstrated to be effective toward faster ion diffusion inside the pore space, low-tortuosity porous architecture has become the focus in thick electrode designs, and other possibilities are rarely investigated. Here, to advance current understanding in the structure-affected electrochemistry and to broaden horizons for thick electrode designs, we present a gradient electrode design, where porous channels are vertically aligned with smaller openings on one end and larger openings on the other. With its 3D morphology carefully visualized by Raman mapping, the electrochemical properties between opposite orientations of the gradient electrodes are compared, and faster energy storage kinetics is found in larger openings and more concentrated active material near the separator. As further verified by simulation, this study on gradient electrode design deepens the knowledge of structure-related electrochemistry and brings perspectives in high-energy battery electrode designs.

25 ENERGY STORAGE↗