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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Device-scale CFD modeling of gas-liquid multiphase flow and amine absorption for CO2 capture

In this paper we aim to develop a validated device-scale CFD model that can predict quantitatively both hydrodynamics and CO2 capture efficiency for an amine-based solvent absorber column with random Pall ring packing. A Eulerian porous-media approach and a two-fluid model were employed, in which the momentum and mass transfer equations were closed by literature-based empirical closure models. We proposed a hierarchical approach for calibrating the parameters in the closure models to make them accurate for the packed column. Specifically, a parameter for momentum transfer in the closure was first calibrated based on data from a single experiment. With this calibrated parameter, a parameter in the closure for mass transfer was next calibrated under a single operating condition. Last, the closure of the wetting area was calibrated for each gas velocity at three different liquid flow rates. For each calibration, cross validations were pursued using the experimental data under operating conditions different from those used for calibrations. This hierarchical approach can be generally applied to develop validated device-scale CFD models for different absorption columns.

Pan, Wenxiao↗
DOE OSTI2019

Device-scale computational fluid dynamics modeling of carbon dioxide absorption using encapsulated sorbents

Micro-encapsulated carbon dioxide sorbent (MECS) is considered to be a promising material for carbon capture system because of high capture rate, low fabrication cost, and efficient energy consumption. To accelerate the development of MECS technology for industrial deployment, device-scale computational fluid dynamics (CFD) simulations are performed to study hydrodynamics and CO2 absorption behavior in a conceptual fluidized bed reactor. The two-fluid model solver, built in the Multiphase Flow with Interphase eXchanges (MFIX), is adopted to solve the multiphase flow hydrodynamics by representing both fluid and solids as continuous phases. Filtered models are implemented to capture the sub-grid effects that normally cannot be directly considered because MECS particles are too small to be explicitly resolved at such a large scale. Using established CFD tools, this study aims to characterize MECS behavior and predict its carbon capture performance in a conceptual device-scale absorber. The MECS particle size and gas flow rate have significant impact on CO2 capture efficiency. The CO2 capture efficiency decreases with increasing gas flow rate. Smaller particle size lead to better gas-solid homogeneity, as a results CO2 absorption efficiency increases.

Wang, Chao (ORCID:0000000279406614)↗
DOE OSTI2017

Stretchable Lithium-Ion Batteries Enabled by Device-Scaled Wavy Structure and Elastic-Sticky Separator

Fast developments and substantial achievements have been shaping the field of wearable electronic devices, resulting in the persistent requirement for stretchable lithium-ion batteries (LIBs). Despite recent progress in stretchable electrodes, stretching full batteries, including electrodes, separator, and sealing material, remains a great challenge. Here, a simple design concept for stretchable LIBs via a wavy structure at the full battery device scale is reported. All components including the package are capable of being reversibly stretched by folding the entire pouch cell into a wavy shape with polydimethylsiloxane filled in each valley region. In addition, the stretchable, sticky, and porous polyurethane/poly(vinylidene fluoride) membrane is adopted as a separator for the first time, which can maintain intimate contact between electrodes and separator to continuously secure ion pathway under dynamic state. Commercial cathode, anode, and package can be utilized in this rationally designed wavy battery to enable stretchability. The results indicate good electrochemical performances and long-term stability at repeatable release–stretch cycles. A high areal capacity of 3.6 mA h cm -2 and energy density of up to 172 W h L -1 can be achieved for the wavy battery. The promising results of the cost-effective wavy battery with high stretchability shed light on the development of stretchable energy storages.

25 ENERGY STORAGE↗
DOE OSTI2020

Absorber Column CFD model validation against PNNL’s device-scale absorber column on the LCFS unit

Absorber column has been widely used for CO 2 capture in the coal-fired power plants. High-fidelity CFD models play an important role in absorber column design and solvents optimization, which help enhance the CO 2 capture efficiency and reduce the operation cost. This report provides a comprehensive description of the development of CFD absorber models at two different levels, the design and implementation of PNNL’s device-scale absorber column experiment, and the methodology to combine the CFD results, experiment data, and Aspen model for a better understanding of the interface area in packed column. A composite model is firstly proposed in the Discrete Element Method (DEM) packing process, which can model the complex geometry of various packing elements. This generates a realistic packing pattern and accurate packing porosity ε and specific area a p compared to the actual values for absorber column used in LCFS. Two level of CFD absorber models were developed, namely the full-size column model (FCM) to simulate the entire packed column with a focus on the wall/entrance effects, and the representative column model (RCM) to simulate a section of column with a focus on the sensitivity study of interface area. A Design of Experiment (DoE) plan was developed to guide the collection of 100 run CFD data and 12 experiment runs. The 100 CFD runs were carried out in the RCM with Pro-Pak packing and cover a wide operation range and solvent properties. Impact of influential factors on the interface area in packed column were investigated in details. The CFD interface area was then combined with the experimental data and Aspen model to infer some information of the effective contact angle in the column. The accuracy and uncertainties in the interface area and contact angle can be quantified.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Electrochemical ion insertion from the atomic to the device scale

Electrochemical ion insertion involves coupled ion–electron transfer reactions, transport of guest species and redox of the host. The hosts are typically anisotropic solids with 2D conduction planes but can also be materials with 1D or isotropic transport pathways. These insertion compounds have traditionally been studied in the context of energy storage but also find extensive applications in electrocatalysis, optoelectronics and computing. Recent developments in operando, ultrafast and high-resolution characterization methods, as well as accurate theoretical simulation methods, have led to a renaissance in the understanding of ion-insertion compounds. In this Review, we present a unified framework for understanding insertion compounds across timescales and length scales ranging from atomic to device levels. Using graphite, transition metal dichalcogenides, layered oxides, oxyhydroxides and olivines as examples, we explore commonalities in these materials in terms of point defects, interfacial reactions and phase transformations. We illustrate similarities in the operating principles of various ion-insertion devices, ranging from batteries and electrocatalysts to electrochromics and thermal transistors, with the goal of unifying research across disciplinary boundaries.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Al-alkyls as acceptor dopant precursors for atomic-scale devices

Atomically precise ultradoping of silicon is possible with atomic resists, area-selective surface chemistry, and a limited set of hydride and halide precursor molecules, in a process known as atomic precision advanced manufacturing (APAM). It is desirable to expand this set of precursors to include dopants with organic functional groups and in this work we consider aluminium alkyls, to expand the applicability of APAM. We explore the impurity content and selectivity that results from using trimethyl aluminium and triethyl aluminium precursors on Si(001) to ultradope with aluminium through a hydrogen mask. Comparison of the methylated and ethylated precursors helps us understand the impact of hydrocarbon ligand selection on incorporation surface chemistry. Combining scanning tunneling microscopy and density functional theory calculations, we assess the limitations of both classes of precursor and extract general principles relevant to each.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Device Scale Modeling of Solvent Absorption using MFIX-TFM

Recent climate change is largely attributed to greenhouse gases (e.g., carbon dioxide, methane) and fossil fuels account for a large majority of global CO 2 emissions. That said, fossil fuels will continue to play a significant role in the generation of power for the foreseeable future. The extent to which CO 2 is emitted needs to be reduced, however, carbon capture and sequestration are also necessary actions to tackle climate change. Different approaches exist for CO 2 capture including both post-combustion and pre-combustion technologies, oxy-fuel combustion and/or chemical looping combustion. The focus of this effort is on post-combustion solvent-absorption technology. To apply CO 2 technologies at commercial scale, the availability and maturity and the potential for scalability of that technology need to be considered. Solvent absorption is a proven technology but not at the scale needed by typical power plant. The scale up and down and design of laboratory and commercial packed bed reactors depends heavily on the specific knowledge of two-phase pressure drop, liquid holdup, the wetting efficiency and mass transfer efficiency as a function of operating conditions. Simple scaling rules often fail to provide proper design. Conventional reactor design modeling approaches will generally characterize complex non-ideal flow and mixing patterns using simplified and/or mechanistic flow assumptions. While there are varying levels of complexity used within these approaches, none of these models resolve the local velocity fields. Consequently, they are unable to account for important design factors such as flow maldistribution and channeling from a fundamental perspective. Ideally design would be aided by development of predictive models based on truer representation of the physical and chemical processes that occur at different scales. Computational fluid dynamic (CFD) models are based on multidimensional flow equations with first principle foundations. CFD models can include a more accurate physical description of flow processes and be modified to include more complex behavior. Wetting performance and spatial liquid distribution inside the absorber are recognized as weak areas of knowledge requiring further investigation. CFD tools offer a possible method to investigating such topics and gaining a better understanding of their influence on reactor performance. This report focuses first on describing a hydrodynamic model for countercurrent gas-liquid flow through a packed column and then on the chemistry, heat and mass transfer specific to CO 2 absorption using monoethanolamine (MEA). The indicated model is implemented in MFIX, a CFD open source software package. The user defined functions needed to build this model are described in detail along with the keywords for the corresponding input file. A test case is outlined along with a few results. The example serves to briefly illustrate the developed CFD tool and its potential capability to investigate solvent absorption.

09 BIOMASS FUELS↗
DOE OSTI2018

Device-scale CFD study for mass transfer coefficient and effective mass transfer area in packed column

Carbon dioxide (CO 2 ) is a significant contributor of greenhouse gases emissions responsible for global warming. The fossil-fueled power plant is one of the major sources of CO 2 emission worldwide and needs to be mitigated. Post-combustion carbon capture by chemical absorption can be a promising technology to reduce CO 2 emission from power plants. The absorption is carried out via countercurrent flow in the packed columns. Although monoethanolamine (MEA) is a popular solvent, it has also limitations such as high volatility of solvent, corrosivity that leads to product degradation and damage to apparatuses, low CO 2 loading capacity, etc. Therefore, alternate solvents are being explored as prospective materials for carbon capture. A water-lean solvent, CO 2 binding organic liquids (CO2BOL), is currently being developed as a prospective material in carbon capture at the Pacific Northwest National Laboratory. Since the development of the material is at the primitive stage, it needs extensive investigation before industrial deployments. Hydrodynamics and mass transfer phenomena in the packed column using CO 2 BOL is unknown. Computational fluid dynamics (CFD) can be a useful tool to understand these phenomena in the packed column. Before employing the extensive CFD investigations, one needs to carefully validate CFD predictions for accurate flow predictions. This report demonstrates the validation of multiphase flow simulations against the experimental results for both structured and random packed columns. The reactive multiphase flow simulations using volume of fluid method were conducted at a wide range of liquid loads and contacts angles. The effective area is one of the critical factors dictating interphase mass transfer due to chemical reactions. Accordingly, CFD-predicted effective areas were compared with the experimental results of Tsai et al. [1] for Mellapak 250.Y structured packing. Both results matched well at different liquid loads in the presence of fast chemical kinetics using caustic solvents. Further, reactive multiphase flow simulations were also conducted in pall ring random packing to compute effective areas in the presence of fast chemical reactions. The CFD-predicted effective area compared well with correlation developed by Song et al. [2]. With successful validations, the current simulation framework can be further used for prediction of hydrodynamics and mass transfer phenomena using CO 2 BOL solvents in the packed column. Subsequently, it would be helpful in design optimization of a packed column. In addition to validation of the CFD model, this report also explains the mechanism for enhanced liquid side mass transfer for a structured packed column as compared to the wetted wall column.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2016

Operando x-ray photoelectron emission microscopy for studying forward and reverse biased silicon p-n junctions

Significant progress in the understanding of surfaces and interfaces of materials for new technologies requires operando studies, i.e., measurement of chemical, electronic, and magnetic properties under external stimulus (such as mechanical strain, optical illumination, or electric fields) applied in situ in order to approach real operating conditions. Electron microscopy attracts much interest, thanks to its ability to determine semiconductor doping at various scales in devices. Spectroscopic photoelectron emission microscopy (PEEM) is particularly powerful since it combines high spatial and energy resolution, allowing a comprehensive analysis of local work function, chemistry, and electronic structure using secondary, core level, and valence band electrons, respectively. Here we present the first operando spectroscopic PEEM study of a planar Si p-n junction under forward and reverse bias. The method can be used to characterize a vast range of materials at near device scales such as resistive oxides, conducting bridge memories and domain wall arrays in ferroelectrics photovoltaic devices.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Modeling and Design of the Triton OWC System (Final Report)

Two versions of the Triton Oscillating Water Column type device will be modeled in WEC Sim. First, a model of a wave-tank scale device which can be tuned and validated against tank test data. Second, a model of the deployment-scale device will be constructed following the method of the tank-scale device to ensure that relevant physics are captured. In the latter case, the geometry, PTO architecture, and other design details are not yet finalized, so the model will serve as a platform for design iteration as time and budget allows. A subset of this iteration will be automated using existing WEC-Sim capabilities. A primary focus of this work will be familiarizing Triton personnel with the WEC-Sim workflow and model details so that the model of the deployment device can continue to be enhanced after project end.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Machine learning coupled multi-scale modeling for redox flow batteries

The reaction distribution in macro or device-scale has been studied for redox flow batteries. The reaction distribution on electrode pore-scale structure however is not well understood, lacking especially on how the reaction distribution on the pore-scale may impact the overall performance of a flow battery. This study introduces for the first time a framework of a multi-scale model that provides understanding of the relationship between the pore-scale electrode structure reaction and the device-scale electrochemical reaction uniformity within the flow battery. A reduced order model is constructed based on 128 pore-scale simulations, which provide a quantitative relationship between the battery operation conditions (inlet velocity, current density, inlet concentration) and the surface reaction uniformity for the pore-scale sample. The multi-scale framework upscales this pore-scale surface reaction uniformity to device-scale combined uniformity. Based on the multi-scale model, a time-varying optimization of the inlet velocity is established, leading to significant reduction on pump power consumption with targeted surface reaction uniformity. The multi-scale model establishes the critical link between the micro-structure of a flow battery component and its performance at the macro-scale, therefore providing rationale for further operational or material optimization.

flow batteries, machine learning, multi-scale mode↗
DOE OSTI2020

Classical Optimizers for Noisy Intermediate-Scale Quantum Devices

We present a collection of optimizers tuned for usage on Noisy Inter-mediate-Scale Quantum (NISQ) devices. Optimizers have a range of applications in quantum computing, including the Variational Quantum Eigensolver (VQE) and Quantum Approximate Optimization (QAOA) algorithms. They have further uses in calibration, hyperparameter tuning, machine learning, etc. We employ the VQE algorithm as a case study. VQE is a hybrid algorithm, with a classical minimizer step driving the next evaluation on the quantum processor. While most results to date concentrated on tuning the quantum VQE circuit, our study indicates that in the presence of quantum noise the classical minimizer step is a weak link and a careful choice combined with tuning is required for correct results. We explore state-of-the-art gradient-free optimizers capable of handling noisy, black-box, cost functions and stress-test them using a quantum circuit simulation environment with noise injection capabilities on individual gates. Our results indicate that specifically tuned optimizers are crucial to obtaining valid science results on NISQ hardware, as well as projecting forward on fault tolerant circuits.

Lavrijsen, Wim↗
DOE OSTI2021

Towards quantum simulations in particle physics and beyond on noisy intermediate-scale quantum devices

We review two algorithmic advances that bring us closer to reliable quantum simulations of model systems in high-energy physics and beyond on noisy intermediate-scale quantum (NISQ) devices. The first method is the dimensional expressivity analysis of quantum circuits, which allows for constructing minimal but maximally expressive quantum circuits. The second method is an efficient mitigation of readout errors on quantum devices. Both methods can lead to significant improvements in quantum simulations, e.g. when variational quantum eigensolvers are used. This article is part of the theme issue ‘Quantum technologies in particle physics’.

Science & Technology - Other Topics↗
DOE OSTI2017

Local-Scale Simulations of Nucleate Boiling on Micrometer Featured Surfaces: Preprint

A high-fidelity computational fluid dynamics (CFD)-based model for bubble nucleation of the refrigerant HFE7100 on micrometer-featured surfaces is presented in this work. The single-fluid incompressible Navier-Stokes equations, along with energy transport and natural convection effects are solved on a featured surface resolved grid. An a priori cavity detection method is employed to convert raw profilometer data of a surface into well-defined cavities. The cavity information and surface morphology are represented in the CFD model by geometric mesh deformations. Surface morphology is observed to initiate buoyancy-driven convection in the liquid phase, which in turn results in faster nucleation of cavities. Simulations pertaining to a generic rough surface show a trend where smaller size cavities nucleate with higher wall superheat. This local-scale model will serve as a self-consistent connection to larger device scale continuum models where local feature representation is not possible.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

A General Approach for Lab‐to‐Manufacturing Translation on Flexible Organic Solar Cells

Abstract The blossoming of organic solar cells (OSCs) has triggered enormous commercial applications, due to their high‐efficiency, light weight, and flexibility. However, the lab‐to‐manufacturing translation of the praisable performance from lab‐scale devices to industrial‐scale modules is still the Achilles' heel of OSCs. In fact, it is urgent to explore the mechanism of morphological evolution in the bulk heterojunction (BHJ) with different coating/printing methods. Here, a general approach to upscale flexible organic photovoltaics to module scale without obvious efficiency loss is demonstrated. The shear impulse during the coating/printing process is first applied to control the morphology evolution of the BHJ layer for both fullerene and nonfullerene acceptor systems. A quantitative transformation factor of shear impulse between slot‐die printing and spin‐coating is detected. Compelling results of morphological evolution, molecular stacking, and coarse‐grained molecular simulation verify the validity of the impulse translation. Accordingly, the efficiency of flexible devices via slot‐die printing achieves 9.10% for PTB7‐Th:PC 71 BM and 9.77% for PBDB‐T:ITIC based on 1.04 cm 2 . Furthermore, 15 cm 2 flexible modules with effective efficiency up to 7.58% (PTB7‐Th:PC 71 BM) and 8.90% (PBDB‐T:ITIC) are demonstrated with satisfying mechanical flexibility and operating stability. More importantly, this work outlines the shear impulse translation for organic printing electronics.

Meng, Xiangchuan↗
DOE OSTI2016

Smarter Grid Solutions | National Renewable Energy Laboratory: Active Management Integration: June 2015 - November 2016

This report presents the project results for the NREL INTEGRATE demonstration project: Active Network Management (ANM) Integration. Consistent with the INTEGRATE program's objective of increasing the grid's clean energy hosting capacity and providing grid services in a holistic manner, the project demonstrated the use of ANM to enable very high penetrations of solar PV and wind energy systems. Results obtained using a representative North American distribution system showed ANM's autonomous distributed control doubled the interconnected wind and solar systems by managing thermal and voltage constraints in real-time. These generators flexibly interconnected to the grid via ANM's end-to-end control architecture, and were managed and coordinated with other smart distributed energy resources (DER; e.g. EVs, battery ESS, controllable load) to unlock the grid's dynamic hosting capacity. As a smart grid application to standardize grid integration of diverse renewable generation sources, ANM provides the industry with a scalable, cost-effective alternative to traditional transmission and distribution (T&D) reinforcements. This project considered three use cases of the application of ANM: a Smart Home demonstration of ANM control of residential scale devices (PV, EV, and battery ESS); a Smart Campus demonstration of high penetration megawatt-scale DER (PV, EVs, battery ESS, and controllable load) behind a single point-of-common-coupling (PCC), and a Smart Distribution demonstration that combined prior use cases along with additional community/utility-scale DER at very high aggregate penetration levels. The Smart Distribution use case provided an integrated perspective of ANM across all distribution grid DER device scales (incorporating aggregated Smart Homes and the Smart Campus) in order to showcase how these devices can support smart grid services to manage DER related constraints in a safe and reliable manner; and likewise how ANM integrates with grid modernization initiatives. The ANM system was deployed in NREL's Energy Systems Integration Facility (ESIF), and project industry advisors attended an on-site demonstration and a set of workshops in order to review project outcomes and evaluate the relevance of ANM for increasing the grid hosting capacity. The outcomes of this effort include an assessment of opportunities for field deployment of ANM to address existing interconnection challenges, as well as consolidating project advisor suggestions for investment in ANM and potential future pilots for more advanced schemes.

24 POWER TRANSMISSION AND DISTRIBUTION↗