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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 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Highly efficient reversible addition-fragmentation chain-transfer polymerization in ethanol/water via flow chemistry

Here, utilization of a flow reactor under high pressure allows highly efficient polymer synthesis via reversible addition–fragmentation chain-transfer (RAFT) polymerization in an aqueous system. Compared with the batch reaction, the flow reactor allows the RAFT polymerization to be performed in a high-efficiency manner at the same temperature. The adjustable pressure of the system allows further elevation of the reaction temperature and hence faster polymerization. Other reaction parameters, such as flow rate and initiator concentration, were also well studied to tune the monomer conversion and the molar mass dispersity (Ð) of the obtained polymers. Gel permeation chromatography, nuclear magnetic resonance (NMR), and Fourier transform infrared spectroscopies (FTIR) were utilized to monitor the polymerization process. With the initiator concentration of 0.15 mmol L –1 , polymerization of poly(ethylene glycol) methyl ethermethacrylate with monomer conversion of 52% at 100 °C under 73 bar can be achieved within 40 min with narrow molar mass dispersity (D) Ð (<1.25). The strategy developed here provides a method to produce well-defined polymers via RAFT polymerization with high efficiency in a continuous manner.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Material requirements for the adoption of unconventional silicon crystal and wafer growth techniques for high-efficiency solar cells

Silicon wafers comprise approximately 40% of crystalline silicon module cost and represent an area of great technological innovation potential. Paradoxically, unconventional wafer-growth techniques have thus far failed to displace multicrystalline and Czochralski silicon, despite four decades of innovation. One of the shortcomings of most unconventional materials has been a persistent carrier lifetime deficit in comparison to established wafer technologies, which limits the device efficiency potential. In this perspective article, we review a defect-management framework that has proven successful in enabling millisecond lifetimes in kerfless and cast materials. Control of dislocations and slowly diffusing metal point defects during growth, coupled to effective control of fast-diffusing species during cell processing, is critical to enable high cell efficiencies. As a result, to accelerate the pace of novel wafer development, we discuss approaches to rapidly evaluate the device efficiency potential of unconventional wafers from injection-dependent lifetime measurements.

14 SOLAR ENERGY↗
DOE OSTI2018

Efficiency increased to 15.2% for ultra-thin Cu(In,Ga)Se 2 solar cells

We improved the efficiency of ultra-thin (0.49-um-thick) Cu(In,Ga)Se 2 solar cells to 15.2% (officially measured). To achieve these results, we modified growth conditions from the 3-stage process but did not add post-deposition treatments or additional material layers. The increase in device efficiency is attributed to a steeper Ga gradient in the CIGS with higher Ga content near the Mo back contact, which can hinder electron-hole recombination at the interface. We discuss device measurements and film characterization for ultra-thin CIGS. Modeling is presented that shows the route to even higher efficiencies for devices with CIGS thicknesses of 0.5 um.

14 SOLAR ENERGY↗
DOE OSTI2026

Hybrid Quantum–Classical Graph Transformers for Efficient Sentiment Analysis

Quantum Machine Learning (QML) offers a promising paradigm that leverages quantum computing principles to develop efficient and expressive models for learning from complex and structured data. Recent advances in natural language processing (NLP) and artificial intelligence (AI) have demonstrated capabilities in understanding, generating, and reasoning over linguistic and multimodal information. In this work, we present the Quantum Graph Transformer (QGT), a hybrid quantum–classical architecture that extends graph transformer capabilities through quantum self-attention. The QGT models variable-length sentences as token graphs, where both the embedding encoding and the self-attention mechanisms are implemented using parameterized quantum circuits (PQCs), enabling efficient contextual learning with significantly fewer trainable parameters. We train QGT using both fully connected and 𝑘 -nearest-neighbor graph structures and evaluate it on five benchmark sentiment-classification datasets. Experimental results show that QGT consistently achieves higher or comparable accuracy to existing quantum NLP models and outperforms a Classical Graph Transformer (CGT) baseline with identical architecture, achieving 29.4 × fewer parameters while requiring 3–5 × fewer samples to reach comparable performance. These findings highlight the potential of graph-based quantum models as scalable and data-efficient architectures for natural language understanding.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Improving Cooperative Interactions Between Halogenated Aromatic Additives and Aromatic Side Chain Acceptors for Realizing 19.22% Efficiency Polymer Solar Cells

Processing additive plays an important role in the standard operation procedures for fabricating top performing polymer solar cells (PSCs) through efficient interactions with key photovoltaic materials. However, improving interaction study of acceptor materials to high performance halogenated aromatic additives such as diiodobenzene (DIB) is a widely neglected route for molecular engineering toward more efficient device performances. Here, in this work, two novel Y-type acceptor molecules of BTP-TT and BTP-TTS with different aromatic side chains on the outer positions are designed and synthesized. The resulting aromatic side chains significantly enhanced the interactions between the acceptor molecules and DIB through an arene/halogenated arene interaction, which improved the crystallinity of the acceptor molecules and induced a polymorph with better photovoltaic performances. Thus, high power conversion efficiencies (PCEs) of 18.04% and 19.22% are achieved in binary and ternary blend devices using BTP-TTS as acceptor and DIB as additive. Aromatic side chain engineering for improving additive interactions is proved to be an effective strategy for achieving much higher performance photovoltaic materials and devices.

36 MATERIALS SCIENCE↗
DOE OSTI2020

High‐Efficiency Organic Solar Cells with Wide Toleration of Active Layer Thickness

Industrial printing production of organic solar cells (OSCs) requires high power conversion efficiency (PCE) with wide toleration of active layer thickness. Herein, high‐efficiency thick‐film OSCs are demonstrated using a polymer fibril network strategy (FNS), which involves a donor polymer (PT2) that can self‐assemble into fibril nanostructure, and two nonfullerene acceptors with different crystalline properties. The fibril network can form a high‐speed hole transport channel and the addition of IDIC as a third component in active layers can improve the electron transport. As a result, the OSCs show high PCEs of ≈12% with wide toleration of active layer thickness (from 100 to 500 nm). The results indicate that FNS is a promising approach for the fabrication of highly efficient thick‐film PSCs, which can facilitate the commercialization of OSCs.

Weng, Kangkang↗
DOE OSTI2022

Scalable Two–Step Production of High–Efficiency Perovskite Solar Cells and Modules

Perovskite solar cells (PSCs) fabricated in laboratories have already achieved power conversion efficiency (PCE) comparable to market-dominant crystalline silicon solar cells. However, this promising photovoltaic technology suffers from severe loss of PCE during scaling up, limiting its progress toward commercialization. One critical question is to develop scalable, low-cost, high throughput, and well-controlled production methods to deposit high-quality perovskite films. Among various approaches, two-step sequential deposition methods have their unique advantages but have been long overlooked. This review provides an overview of two-step methods for fabricating efficient and stable perovskite solar modules (PSMs). We first discuss the mechanisms of two-step perovskite conversion and advanced engineering approaches to modulate the perovskite formation process. We survey the progress of efficient PSCs prepared by different two-step methods and compare the advantages and disadvantages of each method for scalable production of PSMs. Particularly, we highlight that the vapor-based two-step methods are promising for high-throughput in-line production of PSMs. Finally, we provide insights into the challenges and outlook of the industrialization of two-step processes for producing PSMs.

14 SOLAR ENERGY↗
DOE OSTI2023

Layer-by-Layer-Processed Organic Solar Cells with 18.02% Efficiency Enabled by Regulating the Aggregation of Bottom Polymers

The fabrication of organic solar cells (OSCs) by a layer-by-layer (LBL) method has attracted growing attention in recent years. As already known, the pre-aggregates of conjugated polymers in solution have a profound impact on their microstructure morphology in films. Herein, by simply controlling the solution temperature and annealing processes, the pre-aggregation behavior of D18 polymer in solution can be fine-tuned and the microstructure of D18 bottom layer is well manipulated. The optimized D18 bottom layer can effectively regulate L8-BO upper-layer-forming suitable networks for efficient charge transportation. In addition, a vertical phase separation with a special D/D:A/A structure (P-i-N-type component distribution) is also formed. As a result, compared to the 16.43% power conversion efficiency (PCE) of the bulk heterojunction devices, such control enables bilayer OSC devices based on the polymer D18 and L8-BO to deliver an enhanced PCE of 18.02% with simultaneously improved short-circuit current density, open-circuit voltage, and fill factor. Importantly, it is also demonstrated in these results that the LBL deposition process utilizing the pre-aggregation of polymer and its fiber-network-forming ability is a very promising approach to improve charge dynamics, suppress carrier recombination, and fabricate highly efficient OSCs.

14 SOLAR ENERGY↗
DOE OSTI2023

Seed‐Assisted Growth for Scalable and Efficient Perovskite Solar Modules

Perovskite solar modules (PSMs) have shown remarkable photovoltaic potentials, but they still suffer from large power conversion efficiency (PCE) loss on scale‐up and instability due to inferior uniformity and crystallization over large areas. Herein, the scalable production of efficient and stable PSMs using a suite of all‐scalable fabrication methods featuring a two‐step blade/dip‐coating approach to deposit the perovskite absorber layer is demonstrated. Rubidium chloride is introduced to embed (PbI 2 ) 2 RbCl complex seeds in the first‐deposited PbI 2 precursor, which assists in uniform crystallization of the perovskite layer with high crystallinity and reduced defect density over large areas. Following the optimization of RbCl additives, a champion PSM with 17.9% PCE on a 7.6 × 7.6 cm 2 substrate with a 37 cm 2 aperture area is achieved. Moreover, the RbCl‐incorporated PSMs demonstrate excellent reproducibility and stability under continuous 1 sun illumination. This work shows that the two‐step blade/dip coating is a promising method for producing high‐efficiency and stable PSMs on an industrially relevant scale.

Energy & Fuels↗
DOE OSTI2025

Efficient Quantum Gibbs Samplers with Kubo–Martin–Schwinger Detailed Balance Condition

Lindblad dynamics and other open-system dynamics provide a promising path towards efficient Gibbs sampling on quantum computers. In these proposals, the Lindbladian is obtained via an algorithmic construction akin to designing an artificial thermostat in classical Monte Carlo or molecular dynamics methods, rather than being treated as an approximation to weakly coupled system-bath unitary dynamics. Recently, Chen, Kastoryano, and Gilyén (arXiv:2311.09207) introduced the first efficiently implementable Lindbladian satisfying the Kubo–Martin–Schwinger (KMS) detailed balance condition, which ensures that the Gibbs state is a fixed point of the dynamics and is applicable to non-commuting Hamiltonians. This Gibbs sampler uses a continuously parameterized set of jump operators, and the energy resolution required for implementing each jump operator depends only logarithmically on the precision and the mixing time. In this work, we build upon the structural characterization of KMS detailed balanced Lindbladians by Fagnola and Umanità, and develop a family of efficient quantum Gibbs samplers using a finite set of jump operators (the number can be as few as one), akin to the classical Markov chain-based sampling algorithm. Compared to the existing works, our quantum Gibbs samplers have a comparable quantum simulation cost but with greater design flexibility and a much simpler implementation and error analysis. Moreover, it encompasses the construction of Chen, Kastoryano, and Gilyén as a special instance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Data-driven efficient network and surveillance-based immunization

Given a contact network and coarse-grained diagnostic information such as electronic Healthcare Reimbursement Claims (eHRC) data, can we develop efficient intervention policies from data to control an epidemic? Immunization is an important problem in multiple areas, especially epidemiology and public health. However, most existing studies rely on assuming prior epidemiological models to develop pre-emptive strategies, which may fail to adapt to the change in new epidemiological patterns and the availability of rich data such as eHRC. In practice, disease spread is usually complicated, hence assuming an underlying model may deviate from true spreading patterns, leading to possibly inaccurate interventions. Additionally, the abundance of health care surveillance data (such as eHRC) makes it possible to study data-driven strategies without too many restrictive assumptions. Therefore, such a data-driven intervention approach can help public-health experts take more practical decisions. In this work, we take into account propagation log and contact networks for controlling propagation. Furthermore, different from previous model-based approaches, our solutions are solely data driven in a sense that we develop immunization strategies directly from the network and eHRC without assuming classical epidemiological models. In particular, we formulate the novel and challenging data-driven immunization problem. To solve it, we first propose an efficient sampling approach to align surveillance data with contact networks, then develop an efficient algorithm with the provably approximate guarantee for immunization. Finally, we show the effectiveness and scalability of our methods via extensive experiments on multiple datasets, and conduct case studies on nation-wide real medical surveillance data.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Efficient Trainability of Linear Optical Modules in Quantum Optical Neural Networks

The existence of “barren plateau landscapes” for generic discrete-variable quantum neural networks, which obstructs efficient gradient-based optimization of cost functions defined by global measurements, would be surprising in the case of generic linear optical modules in quantum optical neural networks due to the tunability of the intensity of continuous variable states and the relevant unitary group having exponentially smaller dimension. We demonstrate that coherent light in m modes can be generically compiled efficiently if the total intensity scales sublinearly with m, and extend this result to cost functions based on homodyne, heterodyne, or photon detection measurement statistics, and to noisy cost functions in the presence of attenuation. Here, we further demonstrate efficient trainability of m mode linear optical quantum circuits for variational mean field energy estimation of positive quadratic Hamiltonians for input states that do not have energy exponentially vanishing with m.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Efficient learning of power grid voltage control strategies via model-based deep reinforcement learning

Here this article proposes a model-based deep reinforcement learning (DRL) method to design emergency control strategies for short-term voltage stability problems in power systems. Recent advances show promising results for model-free DRL-based methods in power systems control problems. But in power systems applications, these model-free methods have certain issues related to training time (clock time) and sample efficiency; both are critical for making state-of-the-art DRL algorithms practically applicable. DRL-agent learns an optimal policy via a trial-and-error method while interacting with the real-world environment. It is also desirable to minimize the direct interaction of the DRL agent with the real-world power grid due to its safety-critical nature. Additionally, the state-of-the-art DRL-based policies are mostly trained using a physics-based grid simulator where dynamic simulation is computationally intensive, lowering the training efficiency. We propose a novel model-based DRL framework where a deep neural network (DNN)-based dynamic surrogate model (SM), instead of a real-world power grid or physics-based simulation, is utilized within the policy learning framework, making the process faster and more sample efficient. However, having stable training in model-based DRL is challenging because of the complex system dynamics of large-scale power systems. We addressed these issues by incorporating imitation learning to have a warm start in policy learning, reward-shaping, and multi-step loss in surrogate model training. Finally, we achieved 97.5% reduction in samples and 87.7% reduction in training time for an application to the IEEE 300-bus test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Consequential improvement acquisition function for efficient multi-fidelity Bayesian optimization

Abstract Surrogate-based Bayesian optimization has been widely applied in design optimization to increase sampling efficiency. However, the cost for each evaluation of the objective function can still be very high when physical experiments or large-scale simulations are involved. Multi-fidelity Bayesian optimization is the new approach to further improve the sampling efficiency by reducing the number of expensive samples at the highest fidelity level and supplementing them with less expensive ones at low-fidelity levels. In this paper, a new consequential improvement (CI) acquisition function is proposed to allow for the simultaneous selection of the solution and the fidelity level in problems with a known hierarchy of fidelity levels. The new CI acquisition function incorporates the consequential effectiveness of objective improvement with the considerations of cost, accuracy, and validity differences between high- and low-fidelity samples in engineering practice. The new method of multi-fidelity Bayesian optimization based on the CI is demonstrated with several analytical and simulation-based design examples. In the simulation-based design optimization example, the results show that the CI acquisition function has a decisive advantage in the sampling efficiency over the other methods of multi-fidelity Bayesian optimization with simultaneous selection. The results indicate that the proposed method is particularly advantageous in solving high-dimensional problems and when large cost ratios between high- and low-fidelity evaluations exist and high-fidelity validation is mandatory. Furthermore, the method robustly avoids the prevalent issue of over sampling at low-fidelity levels.

Aydogdu, Ibrahim [Georgia Institute of Technology,↗
DOE OSTI2018

Effect of Yttrium Oxide Nanoparticles on the Diffraction Efficiency of Holographic Polymer-liquid Crystal Gratings

Electro-optical properties of the holographic and polarization holographic diffraction gratings formed in polymer-liquid crystal composites doped with Y{sub 2}O{sub 3} nanoparticles are considered. The effect of impurities on the diffraction efficiency and operated electric field is shown. The diffraction efficiency of doped holographic diffraction gratings decreases, whereas the diffraction efficiency of polarization diffraction gratings increases. Doping with nanoparticles leads to a decrease in the operated electric field.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Efficiency at Maximum Power of Dissipative Thermoelectric Generators: A Finite-time Thermodynamic Analysis

In this paper we analyze the thermodynamic efficiency expected for a fully dissipative thermoelectric generator (TEG) operating under stationary conditions at a finite rate. Although a finite-time thermodynamic analysis of TEGs has been aimed at since long time, no complete theory is available yet. The state of the art of theory is reviewed, and a simple expression for the maximum achievable efficiency of TEGs operating under fully irreversible conditions is obtained. This also sets a reference efficiency for forthcoming studies of nonstationary operation of TEGs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Efficient Removal of Metolachlor and Bacterial Community of Biofilm in Bioelectrochemical Reactors

The microbial fuel cell (MFC) provides an inexhaustible electron acceptor to generate current and enhance the degradation of organic compounds. In MFCs with metolachlor as the sole carbon source, the degradation efficiency accelerated by 98%, with 61–76% of enhancement for the degradates, ethane sulfonic acid and oxanilic acid, respectively. According to quantifying primary metabolites of deschloro and metolachlor-2-hydroxyas, dechlorination and alcoholization were deemed as antecedent steps of metolachlor bioelectrochemical degradation. The energy recovery was infeasible by sole addition of metolachlor (at 13 ± 4 °C from equivalent weight of 0.224 mg). In MFCs with metolachlor and sodium acetate as the concomitant carbon sources, the electricity generation recovered to a level comparable to the controls, instead of increasing the removal efficiency of metolachlor. These results suggest that a low-efficiently direct electron transfer occurred between electricigens and metolachlor degraders. The Illumina sequencing showed that species of Paracoccus and Aquamicrobium played a potential degradation effect, while Comamonas sp. replaced Geobacter sp. as the predominant electricigen after addition of metolachlor. This study demonstrates that MFCs could be used as a promising alternative for treatment of chloroacetanilide herbicide contaminated wastewaters by means of a rapidly established active bacterial community. .

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Repeatable and reproducible measurements of myocardial oxidative metabolism, blood flow and external efficiency using {sup 11}C-acetate PET

Background: Non-invasive approaches to investigate myocardial efficiency can help track the progression of heart failure (HF). This study evaluates the repeatability and reproducibility of {sup 11}C-acetate positron emission tomography (PET) imaging of oxidative metabolism. Methods and results: Dynamic {sup 11}C-acetate PET scans were performed at baseline and followup (47 ± 22 days apart) in 20 patients with stable HF with reduced ejection fraction. Two observers blinded to patients’ clinical data used FlowQuant{sup ®} to evaluate test–retest repeatability, as well as intra- and inter-observer reproducibility of {sup 11}C-acetate tracer uptake and clearance rates, for the measurement of myocardial oxygen consumption (MVO{sub 2}), myocardial external efficiency (MEE), work metabolic index (WMI), and myocardial blood flow. Reproducibility and repeatability were evaluated using intra-class-correlation (ICC) and Bland–Altman coefficient-of-repeatability (CR). Test–retest correlations and repeatability were better for MEE and WMI compared to MVO{sub 2}. All intra- and inter-observer correlations were excellent (ICC = 0.95-0.99) and the reproducibility values (CR = 3%-6%) were significantly lower than the test–retest repeatability values (22%-54%, P < 0.001). Repeatability was improved for all parameters using a newer PET–computed tomography (CT) scanner compared to older PET-only instrumentation. Conclusion: {sup 11}C-acetate PET measurements of WMI and MEE exhibited excellent test–retest repeatability and operator reproducibility. Newer PET–CT scanners may be preferred for longitudinal tracking of cardiac efficiency. [French] French Abstract: Contexte: Les examens non invasifs de la fonction myocardique aident à suivre la progression de l’insuffisance cardiaque. Dans ce travail, nous avons évalué la répétabilité et la reproductibilité de l’étude du métabolisme oxydatif du myocarde par imagerie tomographique à positrons avec l’acétate marqué au carbone 11. Méthodes et résultats: Une étude de base et un second examen TEP dynamique à l’ acétate marqué au carbone 11 ont été réalisés (47 ± 22 jours) chez 20 patients présentant une insuffisance cardiaque stable avec une fraction d’éjection réduite. Sans aucune connaissance des données cliniques et au moyen du programme FlowQuant®, deux observateurs ont évalué la répétabilité des TEPs de base et de leur suivi, la reproductibilité intra- et inter-observateur, l’absorption et la clearance du traceur, la mesure de la consommation d’oxygène du myocarde (MVO2), l’efficacité contractile du myocarde (MEE), l’index métabolique du travail myocardique (WMI) et le débit sanguin myocardique (MBF). La reproductibilité et la répétabilité ont été évaluées en utilisant la corrélation intra-classe (ICC) et le coefficient de répétabilité Altman (CR). Les corrélations entre les études de base et leur suivi et la répétabilité des données se sont avérées supérieures pour les paramètres MEE et WMI par rapport à MVO2. Toutes les corrélations intra- et inter-observateurs furent excellentes (ICC = 0,95-0,99). Les valeurs de reproductibilité (CR = 3-6%) furent significativement inférieures aux valeurs de répétabilité (22-54%, p <0.001). La répétabilité des paramètres mesurés s’est avérée supérieure avec un scanner TEP-TDM de nouvelle génération par rapport à l’utilisation de la TEP sans TDM Conclusion: Les mesures réalisées dans cette étude TEP 11C-acétate montre une excellent répétabilité et reproductibilité des paramètres WMI et WMI entre les examens de base et leur suivi effectués par des opérateurs différents. Les nouveaux scanners TEP-TDM devraient être préférés pour le suivi longitudinal de la fonction cardiaque. [Spanish] Spanish Abstract: Antecedentes: el abordaje no invasivo para investigar la eficiencia miocárdica puede ayudar en el seguimiento de la progresión de la insuficiencia cardíaca. Este estudio evalúa la repetibilidad y la reproducibilidad del estudio de metabolismo oxidativo con PET 11C-acetato. Métodos y resultados: Se realizaron estudios de PET 11C-acetato dinámicos al inicio y durante el seguimiento (47 ± 22 días de diferencia) en 20 pacientes con insuficiencia cardíaca estable y fracción de eyección reducida. Dos observadores cegados a los datos clínicos de los pacientes utilizaron FlowQuant® para evaluar la repetibilidad de la prueba-reprueba, así como la reproducibilidad intra e interobservador de la captación de radiotrazador 11C-acetato y sus tasas de eliminación, la medición del consumo miocárdico de oxígeno (MVO2), la eficiencia externa miocardica (EEM), el índice trabajo-metabólico (ITM) y flujo sanguíneo miocárdico (FSM). La reproducibilidad y la repetibilidad se evaluaron mediante la correlación intraclase (ICC) y el coeficiente de repetibilidad (CR) de Bland-Altman. Las correlaciones Prueba-Reprueba y la repetibilidad fueron mejores para la EEM y el ITM en comparación con el MVO2. Todas las correlaciones intra e interobservador fueron excelentes (ICC = 0.95-0.99) y los valores de reproducibilidad (CR = 3-6%) fueron significativamente menores que los valores de repetibilidad prueba-reprueba (22-54%, p <0.001). La repetibilidad fue mejor para todos los parámetros utilizando un equipo PET-TC más nuevo en comparación con un equipo PET sin CT. Conclusión: las mediciones del PET con 11C-acetato del ITM y EEM mostraron una excelente repetibilidad prueba-preprueba y reproducibilidad del operador. Los nuevos equipos PET-CT pueden ser elegidos para el seguimiento longitudinal de la eficiencia miocárdica. [Chinese] Chinese Abstract: 背景: 采用非侵入式方法来研究心肌代谢效率可以帮助追踪心力衰竭的过程。本研究评估利用碳-11 醋酸盐为 PET 显影剂行氧化代谢成像的可重复性和可再现性。 方法和结果: 纳入射血分数减低的 20 名稳定性心衰患者,对患者基线和 47±22 天随访都进行碳-11 醋酸盐 PET 扫描。为测量心肌耗氧量(MVO{sub 2}), 心肌外效率(MEE), 工作代谢指标(WMI)和心肌血流量(MBF), 两名观察者按照双盲的方法利用 FlowQuant®对碳-11 醋酸盐的摄取率和清空率进行了重复性测试以及不同观察者之间的可再现性测试。采用组内相关系数(ICC)和 Bland Altman 可重复性系数(CR)分别对可再现性和可重复性进行评估。MEE 和 WMI 的两次试验系数和可重复性优于MVO{sub 2}。所有观察者之间的相关系数都较好(ICC=0.95-0.99),可再现性系数的值(CR=3-6%)明显低于两次试验可重复性的值(22-54%, P<0.001)。相比于旧的只有 PET 的设备, 采用新型 PET-CT 扫描仪能够使所有参数的可再现性都有所提高。 结论: 碳-11醋酸盐 PET 显像测量 WMI 和 MEE 有很好的可重复性和可再现性。新的 PET-CT 扫描仪可能更适合于心脏代谢效率的长期追踪。.

62 RADIOLOGY AND NUCLEAR MEDICINE↗