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At least 1,351 records · Page 75

Influences of buffer material and fabrication atmosphere on the electrical properties of CdTe solar cells

Abstract The electrical properties such as interface energy barriers, defect energy levels, and densities dictate the performance of thin film solar cells. Here, we show that these properties can be quantified in cadmium telluride (CdTe) thin‐film solar cells using admittance spectroscopy‐based techniques. Our results reveal that the electrical properties in CdTe thin‐film solar cells depend on both buffer material and the fabrication atmosphere. We find that only a negligible front contact barrier exists at the CdS/CdTe front junction regardless of the fabrication atmospheres, while an obvious front barriers are observed at the ZnMgO (ZMO)/CdTe junctions. Both CdS/CdTe and ZMO/CdTe solar cells exhibit back contact barrier. The energy level of defects is shallower in CdS/CdTe cells than in ZMO/CdTe cells. The fabrication atmosphere influences the electrical properties, i.e., an oxygen‐free atmosphere reduces the front and back barrier heights and lowers the energy level of defects. The results provide critical insights for understanding and optimizing the performance of CdTe thin‐film solar cells.

Awni, Rasha A.↗

Molar Absorptivities of U(VI), U(IV), and Pu(III) in Nitric Acid Solutions of Various Concentrations Relevant to Developing Nuclear Fuel Recycling Flowsheets

Testing of a co-decontamination (CoDCon) tributyl phosphate (TBP) based solvent extraction flowsheet is being performed to optimize conditions for achieving a target U/Pu ratio in the Pu-containing product. The flowsheet is designed to directly produce a mixture of U and Pu with a U/Pu mass ratio of 7/3. The system is monitored in real time using optical spectroscopy, which allows for control of the U/Pu ratio in the aqueous U/Pu nitrate product. On-line spectrophotometric monitoring of the aqueous stream at the reductive stripping step involves determination of U(VI), U(IV) and Pu(III) concentrations and relies on molar absorptivities of these species in nitric acid at a number of wavelengths corresponding to their peaks’ maxima. The magnitudes of these molar absorptivities are a sensitive function of nitric acid concentration and have to be determined as precisely as possible using an off-line spectrophotometry under well controlled conditions. This step (called training set acquisition) is typically performed not in a high contamination area of radiological glovebox where flow-through cells and other on-line equipment are installed but in a less aggressive environment of a radiological fume hood with much better control of stock solutions quality, dilution factors, optical absorbance scale calibration, etc. This is followed by the calibration transfer between the off-line instrument and the instrument deployed during extraction and stripping runs. This paper reports values of molar absorptivities of U(VI), U(IV), and Pu(III) in nitric acid solution of 0.5 M to 4 M concentration and compares them with available technical literature data. Results of off-line spectrophotometric analysis of selected aqueous grab samples from one of CoDCon runs show satisfactory agreement with total uranium and plutonium concentrations determined in the same samples by ICP-MS.

Sinkov, Sergey I.↗

Quantitative phenotyping of crop roots with spectral electrical impedance tomography: a rhizotron study with optimized measurement design

Background: Root systems are key contributors to plant health, resilience, and, ultimately, yield of agricultural crops. To optimize plant performance, phenotyping trials are conducted to breed plants with diverse root traits. However, traditional analysis methods are often labour-intensive and invasive to the root system, therefore limiting high-throughput phenotyping. Spectral electrical impedance tomography (sEIT) could help as a non-invasive and cost-efficient alternative to optical root analysis, potentially providing 2D or 3D spatio-temporal information on root development and activity. Although impedance measurements have been shown to be sensitive to root biomass, nutrient status, and diurnal activity, only few attempts have been made to employ tomographic algorithms to recover spatially resolved information on root systems. In this study, we aim to establish relationships between tomographic electrical polarization signatures and root traits of different fine root systems (maize, pinto bean, black bean, and soy bean) under hydroponic conditions. Results: Our results show that, with the use of an optimized data acquisition scheme, sEIT is capable of providing spatially resolved information on root biomass and root surface area for all investigated root systems. We found strong correlations between the total polarization strength and the root biomass (R 2 = 0.82) and root surface area (R 2 = 0.8). Our findings suggest that the captured polarization signature is dominated by cell-scale polarization processes. Additionally, we demonstrate that the resolution characteristics of the measurement scheme can have a significant impact on the tomographic reconstruction of root traits. Conclusion: Our findings showcase that sEIT is a promising tool for the tomographic reconstruction of root traits in high-throughput root phenotyping trials and should be evaluated as a substitute for traditional, often time-consuming, root characterization methods.

59 BASIC BIOLOGICAL SCIENCES↗

Polarons and electrical leakage in BaZrO 3 and BaCeO 3

The proton conductors barium zirconate (BaZrO 3 , or BZO), barium cerate (BaCeO 3 , or BCO), and their alloys have attracted considerable interest as solid-state electrolytes in solid-oxide fuel and electrolysis cells. However, the reasons for their non-negligible electrical conductivity, which can limit their performance, are not fully understood. To address that question, we use first-principles calculations based on density functional theory to study the properties of hole and electron polarons in BZO and BCO. We confirm that hole polarons form in both materials, slightly more favorably in BCO. Electron polarons, on the other hand, are stable only in BCO and in Ce-containing alloys; in pure BZO, electron polaron states are unfavorable relative to free carriers, though they become accessible when Ce impurities are introduced. In general, doped BZO and BCO will have negligible electron concentrations, but larger concentrations of holes and hole polarons may be present. Avoiding extreme O-rich conditions and limiting dopant concentrations are key strategies for reducing significant p -type electrical leakage. Furthermore, our results provide physical insights into the different electronic behaviors of BZO and BCO, which can be used to optimize their performance as pure ionic conductors.

08 HYDROGEN↗

A Perspective on the Impact of Group Delay Dispersion in Future Terahertz Wireless Systems

This article discusses the challenges and opportunities of managing group delay dispersion (GDD), and its relation to the performance standards of future sixth-generation (6G) wireless communication systems utilizing terahertz frequency waves. The unique susceptibilities of 6G systems to GDD are described, along with a quantitative description of the sources of GDD, including multipath, rough surface scattering, intelligent reflecting surfaces, and propagation through the atmosphere. An experimental case-study is presented that confirms previous models quantifying the impact of atmospheric GDD. Several GDD manipulation strategies are presented, illustrating their hindered effectiveness in the 6G context. Conversely, some benefits of leveraging GDD to enhance 6G systems, such as improved security and simplified hardware, are also discussed. Finally, a perspective on using photonic GDD control devices is provided, revealing quantitative benefits that may unburden existing equalization schemes. Here, the article argues that GDD will uniquely and significantly impact some 6G systems, but that its careful consideration along with new mitigation strategies, including photonic devices, will help optimize system performance. The conclusion provides a perspective to guide future research in this area.

Strecker, Karl↗

Subtle Roles of Sb and S in Regulating the Thermoelectric Properties of N-Type PbTe to High Performance

A high ZT (thermoelectric figure of merit) of ≈1.4 at 900 K for n-type PbTe is reported, through modifying its electrical and thermal properties by incorporating Sb and S, respectively. Sb is confirmed to be an amphoteric dopant in PbTe, filling Te vacancies at low doping levels (<1%), exceeding which it enters into Pb sites. It is found that Sb-doped PbTe exhibits much higher carrier mobility than similar Bi-doped materials, and accordingly, delivers higher power factors and superior ZT. The enhanced electronic transport is attributed to the elimination of Te vacancies, which appear to strongly scatter n-type charge carriers. Building on this result, the ZT of Pb 0.9875 Sb 0.0125 Te is further enhanced by alloying S into the Te sublattice. The introduction of S opens the bandgap of PbTe, which suppresses bipolar conduction while simultaneously increasing the electron concentration and electrical conductivity. Furthermore, it introduces point defects and induces second phase nanostructuring, which lowers the lattice thermal conductivity to ≈0.5 W m -1 K -1 at 900 K, making this material a robust candidate for high-temperature (500–900 K) thermoelectric applications. It is anticipated that the insights provided here will be an important addition to the growing arsenal of strategies for optimizing the performance of thermoelectric materials.

36 MATERIALS SCIENCE↗

Optimal Control of SOEC-Based Hydrogen Production Systems for Demand Response Using Deep Reinforcement Learning in Smart Grids

Solid oxide electrolysis cell (SOEC) hydrogen production technology can range in size from small, appliance-size equipment to large-scale, central production facilities that can be tied directly to renewable or non-greenhouse-gas-emitting forms of electricity production, making it an ideal resource for demand response (DR). The SOEC hydrogen production system is a complex integrated system that encompasses fluid dynamics, electrical dynamics, and electrochemical and thermal dynamics, all of which involve non-linearity and non-convexity. Proper control of the SOEC hydrogen production system is crucial to enable its participation in the DR program. Here, to overcome the difficulty of designing an explicit control law for such nonlinear systems with nonconvex optimization features in DR applications, deep reinforcement learning (DRL) is explored to achieve the optimal control of the SOEC system for DR participation. Specifically, a twin delayed deterministic policy gradient (TD3) control framework is applied to achieve optimal response performance during DR events by considering power tracking error and hydrogen production efficiency with a suitable reward function. Two case studies with grid connections for tracking different DR commands were investigated. The first case study involved operating conditions reaching the boundaries, while the second involved operating conditions within the boundaries. The results showed that the proposed DRL-based control for SOEC can track the DR signal in a timely manner while maintaining high energy efficiency.

08 HYDROGEN↗

Operando XAS and DFT Uncover Structure-Performance Relationships in Re/TiO 2 for Selective CO 2 Hydrogenation to Methanol

The conversion of CO 2 into value-added chemicals, such as methanol, offers a promising pathway toward a renewable energy future. However, a precise kinetic control and a highly selective catalyst are necessary to overcome the thermodynamic preference for CO 2 hydrogenation to methane. Rhenium-based catalysts, particularly Re/TiO 2 , demonstrate high activity and selectivity for methanol under high-pressure conditions. For example, at 100 bar and 200 °C, a methanol selectivity of 97−99% was obtained. Catalysts with 1 wt % Re and 5 wt % Re/ TiO 2 were used to study the effect of cluster sizes. At 250 °C, the 1 wt % catalyst achieves 97% selectivity at 23% conversion, whereas 5 wt % Re/TiO 2 achieves 74% selectivity at 40% conversion, corresponding to a drop in space-time yield from 65 to 16 g CH 3 OH ·g Re −1 ·h −1 , respectively. X-ray absorption spectroscopy provided insights into the structure of the active sites, while density functional theory calculations revealed the effects of cluster size on the energy barriers for H 2 activation, CH 3 OH dissociation, and CH 3 OH desorption, all of which directly influence conversion and selectivity. These results underscore the importance of balancing cluster size for optimal catalyst performance and provide insights into the design of efficient and selective catalysts for renewable methanol production.

XAS↗

Rate Theory Modeling and Simulations of Silicide Fuel at LWR Conditions

Uranium silicide (U 3 Si 2 ) fuel has higher thermal conductivity and higher uranium density, making it a promising candidate for the accident-tolerant fuel (ATF) used in light water reactors (LWRs). However, previous studies on the fuel performance of U 3 Si 2 , including both experimental and computational approaches, have been focusing on the irradiation conditions in research reactors, which usually involve low operation temperatures and high fuel burnups. Thus, it is important to examine the fuel performance of U 3 Si 2 at typical LWR conditions so as to evaluate the feasibility of replacing conventional uranium dioxide fuel with this silicide fuel material. As in-reactor irradiation experiments involve significant time and financial cost, it is appropriate to utilize modeling tools to estimate the behavior of U 3 Si 2 in LWRs based on all those available research reactor experimental references and state-of-the-art density functional theory (DFT) calculation capabilities at the early development stage. Hence, in this report, a comprehensive investigation of the fission gas swelling behavior of U 3 Si 2 at LWR conditions is introduced. The modeling efforts mentioned in this report was based on the rate theory (RT) model of fission gas bubble evolution that has been successfully applied for a variety of fuel materials at devious reactor conditions. Both existing experimental data and DFT-calculated results were used for the optimization of the parameters adopted by the RT model. Meanwhile, the fuel-cladding interaction was captured by the coupling of the RT model with simplified mechanical correlations. Therefore, the swelling behavior of U 3 Si 2 fuel and its consequent interaction with cladding in LWRs was predicted by the rate theory modeling, providing valuable information for the development of U 3 Si 2 fuel as an accident-tolerant alternative for uranium dioxide.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Additive Manufacturing with Cellulose-Based Composites: Materials, Modeling, and Applications

Recent advances in large-scale additive manufacturing (AM) with polymer-based composites have enabled efficient production of high-performance materials. Cellulose nanomaterials (CNMs) have emerged as bio-based feedstocks due to their exceptional strength and sustainability. However, challenges such as hornification and poor dispersion in polymer matrices still limit large-scale CNM–polymer composite manufacturing, requiring novel strategies. Here, this review outlines an approach starting with atomic-level simulations to link molecular composition to key parameters like bulk density, viscosity, and modulus. These simulations provide data for finite element analysis (FEA), which informs large-scale experiments and reduces the need for extensive trials. The strategy explores how atomic interactions impact the morphology, adhesion, and mechanical properties of CNM-based composites in AM processes. The review also discusses current developments in AM, along with predictions of mechanical and thermal properties for structural applications, packaging, flexible electronics, and hydrogel scaffolds. By integrating experimental findings with molecular dynamics (MD) simulations and finite element modeling (FEM), valuable insights for material design, process optimization, and performance enhancement in CNM-based AM are provided to address ongoing challenges.

36 MATERIALS SCIENCE↗

Ducted Fuel Injection And Cooled Spray Technologies For Particulate Control In Heavy-duty Diesel Engines (Final Report)

Cooled Spray (CS) and Ducted Fuel Injection (DFI) are in-cylinder technologies for diesel engines that can reduce particulate matter and soot emissions and data has been published showing that these technologies can reduce soot emissions by 75-100% for some engines at some operating conditions. However, little is known about scaling the devices for engine size. Additionally, the performance of either technology over the engine duty cycle has not been explored. This project addresses both of these points through single-cylinder engine investigations. The objectives of this project are to provide details about dimensional scaling of these devices and to demonstrate 75% PM reduction over a range of operating conditions on a single-cylinder engine. Two engines were used for this project: a 125mm bore optically accessible engine at Sandia National Laboratories and a 168mm bore metal engine at Southwest Research Institute. The optical engine was used to study the performance of DFI and CS inserts for a large injector orifice diameter injector that is characteristic of a locomotive engine and to perform scaling studies for DFI. The metal engine was used to perform scaling and alignment studies for CS and to evaluate the technology for both EGR and non-EGR engines over the engine operating map. Modifications were required for both engines to accept the prototype inserts being tested. The optical engine required a new fuel injector, cylinder head and piston so that tests could be run at the pressures and engine speeds required. Additionally, a novel rotating stage was designed for the optical engine to simplify alignment of the modules. The metal engine required a modified cylinder head to accept CS inserts and a modified piston to provide additional space around the fuel injector for the CS inserts. Tests on the optical engine showed that DFI reduces PM emissions for both small injector orifices (0.170mm diameter) and large injector orifices (0.290mm). For high load testing, the DFI modules were not as effective as at low load testing, but it was acknowledged that minimal geometric optimization was performed and more improvements may be possible. Comparing DFI to CS and conventional diesel combustion (CDC), DFI performed better than CS or CDC. The CS geometries used in these studies may not be ideal for that engine and additional modifications likely would improve performance. Tests on the metal engine showed PM reductions as high has 80% at some operating conditions with duty-cycle PM reductions of ~50% for EGR and non-EGR configurations. The CS testing on the metal engine showed that chamfering of the fuel passage inlet either through hydro-erosion or mechanical grinding provided significant improvements in the PM reduction capabilities of the insert. Additionally, alignment sensitivities were explored and the data show that the tolerance to misalignment is approximately 0.05 to 0.1mm for the inserts that were studied here. Air-fuel ratio was shown to be important in the effectiveness of the CS inserts. In several tests, it was shown that the CS inserts are more effective at reducing the PM for high-AFR operating conditions compared to low AFR conditions. In summary, multiple designs were evaluated on both engines. It was found that for the conditions and configurations studied here, a fuel passage diameter of ~2.5mm performed best overall. Significant duty-cycle PM reductions are possible using these technologies and sensitivities to AFR, alignment fuel passage diameter and inlet fuel passage shaping were explored and are reported here. More PM reduction may be possible with improved geometric design and attention to alignment practices.

02 PETROLEUM↗

Surface faceting and elemental diffusion behaviour at atomic scale for alloy nanoparticles during in situ annealing

The catalytic performance of nanoparticles is primarily determined by the precise nature of the surface and near-surface atomic configurations, which can be tailored by post-synthesis annealing effectively and straightforwardly. Understanding the complete dynamic response of surface structure and chemistry to thermal treatments at the atomic scale is imperative for the rational design of catalyst nanoparticles. Here, by tracking the same individual Pt 3 Co nanoparticles during in situ annealing in a scanning transmission electron microscope, we directly discern five distinct stages of surface elemental rearrangements in Pt 3 Co nanoparticles at the atomic scale: initial random (alloy) elemental distribution; surface platinum-skin-layer formation; nucleation of structurally ordered domains; ordered framework development and, finally, initiation of amorphization. Furthermore, a comprehensive interplay among phase evolution, surface faceting and elemental inter-diffusion is revealed, and supported by atomistic simulations. Furthermore, this work may pave the way towards designing catalysts through post-synthesis annealing for optimized catalytic performance.

36 MATERIALS SCIENCE↗

Stochastic Models for an Optimal Blending of Biomass under Cost, Quality and Uncertainty Considerations

Blending biomass materials of different physical or chemical properties provides an opportunity to passively adjust the quality of the feedstock to meet the specifications of the conversion platform. We propose a model which identifies the right mix of biomass to optimize the performance of the Thermochemical conversion process at the minimum cost. This is a chance-constraint programming (CCP) model which takes into account the stochastic nature of biomass availability and quality. The proposed CCP model takes as inputs the physical and chemical properties, and biomass availability. We use the sample average approximation (SAA) method to solve the problem. We develop a case study for South Carolina by using data provided by the Billion Ton Study. We conduct extensive numerical analysis to evaluate the quality of the solutions obtained.

09 BIOMASS FUELS↗

Fundamental Understanding of “Fresh” Lithium Nucleation and Growth in Sulfide-Based Anode-Free Solid-State Batteries: Effects of Substrate, Current Density, and Li + Supply

Understanding the electrochemical extraction and deposition of lithium (Li) from cathode is crucial for advancing anode-free solid-state batteries (AFSSBs). Herein, cryo-transmission electron microscopy (cryo-TEM) and electrochemical studies are employed to investigate how current collector surface properties, current densities, and cathode loadings influence the morphology of fresh electrochemically deposited Li and the electrochemical performance in sulfide-based AFSSBs. Cryo-TEM reveals that Cu current collectors induce irregular, dendritic Li deposits due to their lithiophobic nature and reactivity with Li 5.4 PS 4.4 Cl 1.6 (LPSC), while Ni and Au facilitate more uniform, planar-like Li growth. The morphology of the deposited Li also depends on current density: higher rates produce smaller, porous particles versus larger, denser deposits at lower rates. Importantly, for the first time, we discovered that low cathode loadings lead to poor cycling stability due to insufficient Li + supply for complete anode coverage, contrary to conventional solid-state batteries with preloaded Li metal anodes. This finding establishes a design principle where adequate cathode Li + reservoirs are essential for anode interface stability in AFSSBs. Overall, this work elucidates the interplayed effect of current collectors, current densities, and cathode loadings on Li morphology and cycle stability, offering fundamental insights into cathode-derived Li behavior and practical guidelines for optimizing AFSSBs performance through nucleation control and interface engineering.

25 ENERGY STORAGE↗

Irradiation of materials with short, intense ion pulses at NDCX-II

Here, we present an overview of the performance of the Neutralized Drift Compression Experiment-II (NDCX-II) accelerator at Berkeley Lab, and report on recent target experiments on beam-driven melting and transmission ion energy loss measurements with nanosecond and millimeter-scale ion beam pulses and thin tin foils. Bunches with around 10 11 ions, 1 mm radius, and 2–30 ns full width at half maximum duration have been created with corresponding fluences in the range of 0.1–0.7 J/cm 2 . To achieve these short pulse durations and mm-scale focal spot radii, the 1.1 MeV [megaelectronvolt (10 6 eV)] He + ion beam is neutralized in a drift compression section, which removes the space charge defocusing effect during final compression and focusing. The beam space charge and drift compression techniques resemble necessary beam conditions and manipulations in heavy ion inertial fusion accelerators. In conclusion, quantitative comparison of detailed particle-in-cell simulations with the experiment plays an important role in optimizing accelerator performance

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Fuel and Core Design Options to Overcome the Heavy Metal Loading Limit and Improve Performance and Safety of Liquid Salt Cooled Reactors

The research performed in this project addressed the issue of low heavy metal loading and the resulting reduced cycle length with increased refueling frequency, inherent to all FHR designs with solid, non-movable fuel based on TRISO particles. Studies performed here focused on AHTR type of reactor design with plate (“plank”) fuel. Proposal to FY12 NEUP entitled “Fuel and Core Design Options to Overcome the Heavy Metal Loading Limit and Improve Performance and Safety of Liquid Salt Cooled Reactors” was selected for award, and the 3-year project started in August 2012. A 4-month NCE was granted and the project completed on December 31, 2015. The project was performed by Georgia Tech (Prof. Bojan Petrovic, PI) and University of Tennessee (Prof. Ivan Maldonado, Co-PI), with a total funding of $758,000 over 3 years. In addition to two Co-PIs, the project directly engaged 6 graduate students (at doctoral or MS level) and 2 postdoctoral researchers. Additionally, through senior design projects and graduate advanced design projects, another 23 undergraduate and 12 graduate students were exposed to and trained in the salt reactor technology. We see this as one of the important indicators of the project’s success and effectiveness. In the process, 1 journal article was published (with 3 journal articles in preparation), together with 8 peer-reviewed full conference papers, 8 peer-reviewed extended abstracts, as well as 1 doctoral dissertation and 2 master theses. The work included both development of models and methodologies needed to adequately analyze this type of reactor, fuel, and its fuel cycle, as well as extensive analyses and optimization of the fuel and core design.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

$\mathrm{IH}$-$\mathrm{GAN}$: A conditional generative model for implicit surface-based inverse design of cellular structures

Variable-density cellular structures can overcome connectivity and manufacturability issues of topologically optimized structures, particularly those represented as discrete density maps. However, the optimization of such cellular structures is challenging due to the multiscale design problem. Past work addressing this problem generally either only optimizes the volume fraction of single-type unit cells but ignoring the effects of unit cell geometry on properties, or considers the geometry–property relation but builds this relation via heuristics. In contrast, we propose a simple yet more principled way to accurately model the property to geometry mapping using a conditional deep generative model, named Inverse Homogenization Generative Adversarial Network (IH-GAN). It learns the conditional distribution of unit cell geometries given properties and can realize the one-to-many mapping from properties to geometries. Here we further reduce the complexity of IH-GAN by using the implicit function parameterization to represent unit cell geometries. Results show that our method can 1) generate various unit cells that satisfy given material properties with high accuracy (R 2 -scores between target properties and properties of generated unit cells >98%) and 2) improve the optimized structural performance over the conventional variable-density single-type structure. In the minimum compliance example, our IH-GAN generated structure achieves a 79.7% reduction in concentrated stress and an extra 3.03% reduction in displacement. In the target deformation examples, our IH-GAN generated structure reduces the target matching error by 86.4% and 79.6% for two test cases, respectively. We also demonstrated that the connectivity issue for multi-type unit cells can be solved by transition layer blending.

42 ENGINEERING↗

Multipinhole SPECT helical scan parameters and imaging volume

Purpose: The authors developed SPECT imaging capability on an animal PET scanner using a multiple-pinhole collimator and step-and-shoot helical data acquisition protocols. The objective of this work was to determine the preferred helical scan parameters, i.e., the angular and axial step sizes, and the imaging volume, that provide optimal imaging performance. Methods: The authors studied nine helical scan protocols formed by permuting three rotational and three axial step sizes. These step sizes were chosen around the reference values analytically calculated from the estimated spatial resolution of the SPECT system and the Nyquist sampling theorem. The nine helical protocols were evaluated by two figures-of-merit: the sampling completeness percentage (SCP) and the root-mean-square (RMS) resolution. SCP was an analytically calculated numerical index based on projection sampling. RMS resolution was derived from the reconstructed images of a sphere-grid phantom. Results: The RMS resolution results show that (1) the start and end pinhole planes of the helical scheme determine the axial extent of the effective field of view (EFOV), and (2) the diameter of the transverse EFOV is adequately calculated from the geometry of the pinhole opening, since the peripheral region beyond EFOV would introduce projection multiplexing and consequent effects. The RMS resolution results of the nine helical scan schemes show optimal resolution is achieved when the axial step size is the half, and the angular step size is about twice the corresponding values derived from the Nyquist theorem. The SCP results agree in general with that of RMS resolution but are less critical in assessing the effects of helical parameters and EFOV. Conclusions: The authors quantitatively validated the effective FOV of multiple pinhole helical scan protocols and proposed a simple method to calculate optimal helical scan parameters.

60 APPLIED LIFE SCIENCES↗