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DOE OSTI2023

Direct Alcohol Fuel Cells: A Comparative Review of Acidic and Alkaline Systems

In the last 20 years, direct alcohol fuel cells (DAFCs) have been the subject of tremendous research efforts for the potential application as on-demand power sources. Two leading technologies respectively based on proton exchange membranes (PEMs) and anion exchange membranes (AEMs) have emerged: the first one operating in an acidic environment and conducting protons; the second one operating in alkaline electrolytes and conducting hydroxyl ions. In this review, we present an analysis of the state-of-the-art acidic and alkaline DAFCs fed with methanol and ethanol with the purpose to support a comparative analysis of acidic and alkaline systems, which is missing in the current literature. A special focus is placed on the effect of the reaction stoichiometry in acidic and alkaline systems. Particularly, we point out that, in alkaline systems, OH – participates stoichiometrically to reactions, and that alcohol oxidation products are anions. This aspect must be considered when designing the fuel and when making an energy evaluation from a whole system perspective.

25 ENERGY STORAGE↗

DOE OSTI2020

Self-cleaning and de-pollution efficacies of photocatalytic architectural membranes

Photocatalytic self-cleaning “cool” roofs and walls can maintain high albedos, saving building cooling energy, reducing peak power demand, and mitigating the urban heat island effect. Other environmental benefits result from their de-polluting properties. Specimens from two different photocatalytic architectural membranes and a non-photocatalytic control were exposed alongside vertically, facing west, for two years at three California sites, and retrieved quarterly for testing. Photocatalytic materials showed excellent self-cleaning performance, retaining albedos of 0.74 – 0.75. By contrast, the control material exhibited an albedo loss of up to 0.10, with appreciable soiling observed by scanning electron microscopy. De-pollution capacity was assessed by quantifying NO removal and NOx deposition rates at 60 °C. Furthermore, efficacy varied with exposure location, weather conditions, and the nature of the photocatalytic material. Seasonal effects were observed, with partial inhibition during the dry season and reactivation during the rainy season.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Predictive modeling of a subcritical pulverized-coal power plant for optimization: Parameter estimation, validation, and application

As renewable power generation deployment increases, fossil fuel plants are increasingly required to operate more flexibly. Many coal-fired power plants were originally designed to operate at base load and do not operate optimally at partial load. Predictive first-principles plant-wide models can be employed to identify opportunities for flexibility improvements and diagnose low-load operating issues. This paper describes the application of the Institute for the Design of Advanced Energy Systems Integrated Platform (IDAES) to model and optimize flexible power plant operations. The key benefits of using IDAES are that it provides an open-source, fully equation-oriented modeling framework for efficient modular model construction, reuse, and customization, together with a mathematical optimization framework leveraging powerful, state-of-the-art solvers. The process systems engineering workflow from predictive process simulation to parameter estimation, model validation, and plant optimization is applicable to a variety of existing and next-generation energy systems as well as other chemical and environmental processes. Here, to demonstrate this capability, a physics-based, steady-state model was developed to improve full- and part-load performance of the Escalante Generating Station, a 245 MWe (net) subcritical pulverized coal-fired power plant owned and operated by Tri-State Generation and Transmission Association. Specifically, sixty-nine model parameters were simultaneously estimated from several months of operating data enabling prediction of flow rates, temperatures, pressures, and steam quality throughout the plant. The validated model was leveraged by Escalante to reduce the minimum operating load from 90 MW to 50 MW by diagnosing a low-load water-hammer issue, enabling coal usage and emissions reductions during periods of low power demand. Additionally, opportunities for heat rate reduction (i.e., efficiency improvement) through a steeper sliding-pressure approach to load-following and optimization of other boiler operating variables were also identified and quantified. For example, a potential efficiency improvement of 0.7 percentage points was observed at half-load operation.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2021

Control co-design of commercial building chiller plant using Bayesian optimization

Not Available

Bhattacharya, Arnab↗

DOE OSTI2024

Levelized cost of charging of extreme fast charging with stationary LMO/LTO batteries

Extreme DC fast charging for electric vehicles (EVs) could be competitive with the internal combustion engine refueling experience and enable longer-distance travel, which could help with EV adoption and decarbonization, but these systems have high capital costs and extremely variable high-power demands. Behind-the-meter systems (BTMS) could support extreme-fast-charging (XFC) stations to increase nationwide adoption of EVs. Here, this study examines the optimal break-even levelized cost of charging (LCOC) across 96 BTMS scenarios to enable low-wait XFC stations providing 200 miles of charge in 10 min. This research simulates LCOC via synthetic XFC-capable EV loads, machine-learned battery life models from testing data, and nonlinear optimal controls, co-minimizing complex utility costs and battery replacements. An aggregate optimal BTMS design treating each EV load as equal likely gives an optimal LCOC per utility rate, the average of which is $\$$0.59/kWh. In addition, the sensitivity of optimal and off-optimal design factors, the long-life LMO/LTO chemistry, and optimized controls are analyzed. The battery control model, based on battery stressors to compare chemistries, optimizes LMO/LTO resting state of charge and cycle depth without compromising cost reduction, which enables greater flexibility in operation. The LCOC savings due to replacement reduction are small, up to $\$$0.035/kWh (6%), with an average of $\$$0.02/kWh (3.5%). Compared with gasoline stations, the aggregate XFC station design achieves comparable speed, experience of service, and cost at $\$$3.81/gal gasoline, showing that EVs can replace gasoline vehicles even for longer-distance travel.

25 ENERGY STORAGE↗

DOE OSTI2022

UV/chlorine advanced oxidation processes for degradation of contaminants in water and wastewater: A comprehensive review

Advanced oxidation processes (AOPs) have recently gained increasing attention as promising alternatives to conventional water and wastewater treatment technologies. As an AOP, there has been a growing interest in UV/chlorine due to its multiple disinfection modes and ability to maintain chlorine residuals in drinking water distribution systems. Compared to the popular UV/H 2 O 2 AOP treatment process, UV/chlorine AOP possesses several advantages including a higher radical production efficiency and a lower power demand. The process has recently been applied for the degradation of a wide range of natural and synthetic organic as well as inorganic compounds including pharmaceutical and personal care products, natural organic matter, herbicides and insecticides, taste and odor, and different types of water and wastewaters. The focus of the present work is to review and evaluate the efficiency of the UV/chlorine process on the oxidation of these pollutants. Here a critical overview is provided of the fundamentals of UV/chlorine, controlling factors of the process performance, and a comparison with other UV-based AOPs. The formation of disinfection by-products (DBPs), one of the concerns associated with UV/chlorine treatment, is discussed and strategies to tackle this obstacle are provided for future studies and applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Review of data-driven models for quantifying load shed by non-residential buildings in the United States

Shifting and shedding power demand in buildings can be cost-effective techniques for grids to function reliably and for end users to earn compensation. Grid operators reimburse customers in proportion to the quantity of load shed. Simple data-driven methods are used to quantify this shed, which is the difference between a measured load during the event and modeled "baseline" that would have occurred in absence of the event. These methods have evolved over the years and in many cases have been integrated with building physics, to make them a hybrid between physics based and empirical models. However, there is no comprehensive analysis that provides guidance to building operators, grid operators and researchers in selecting appropriate models based on their specific needs and available data. Here, this work aims to fill this gap by critically assessing the performance of baseline models put forward from the year 2000 through 2023. The literature reviewed includes reports generated by grid operators, reports from national laboratories and academic journal articles. The work outlines modeling features like the inputs, training period, estimation method, adjustments to fine tune the predictions and metrics to evaluate the performance. A comprehensive list of 50 models has been provided. For each model, the study explores the applicability of the model to weather sensitive buildings, variability in the building profile, timing of the event, and whether the building reduces energy consumption before an event. The work identifies the situations in which a particular model works and draws lessons based on evidence of performance. Finally, recommendations to aid in model selection are given.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Regulating Catalytic Properties and Thermal Stability of Pt and PtCo Intermetallic Fuel-Cell Catalysts via Strong Coupling Effects between Single-Metal Site-Rich Carbon and Pt

Developing low platinum-group-metal (PGM) catalysts for the oxygen reduction reaction (ORR) in proton-exchange membrane fuel cells (PEMFCs) for heavy-duty vehicles (HDVs) remains a great challenge due to the highly demanded power density and long-term durability. Here, this work explores the possible synergistic effect between single Mn site-rich carbon (Mn SA -NC) and Pt nanoparticles, aiming to improve intrinsic activity and stability of PGM catalysts. Density functional theory (DFT) calculations predicted a strong coupling effect between Pt and MnN 4 sites in the carbon support, strengthening their interactions to immobilize Pt nanoparticles during the ORR. The adjacent MnN 4 sites weaken oxygen adsorption at Pt to enhance intrinsic activity. Well-dispersed Pt (2.1 nm) and ordered L1 2 -Pt 3 Co nanoparticles (3.3 nm) were retained on the Mn SA -NC support after indispensable high-temperature annealing up to 800 °C, suggesting enhanced thermal stability. Both PGM catalysts were thoroughly studied in membrane electrode assemblies (MEAs), showing compelling performance and durability. The Pt@Mn SA -NC catalyst achieved a mass activity (MA) of 0.63 A mg Pt –1 at 0.9 V iR-free and maintained 78% of its initial performance after a 30,000-cycle accelerated stress test (AST). The L1 2 -Pt 3 Co@Mn SA -NC catalyst accomplished a much higher MA of 0.91 A mg Pt –1 and a current density of 1.63 A cm –2 at 0.7 V under traditional light-duty vehicle (LDV) H 2 –air conditions (150 kPa abs and 0.10 mg Pt cm –2 ). Furthermore, the same catalyst in an HDV MEA (250 kPa abs and 0.20 mg Pt cm –2 ) delivered 1.75 A cm –2 at 0.7 V, only losing 18% performance after 90,000 cycles of the AST, demonstrating great potential to meet the DOE targets.

25 ENERGY STORAGE↗

DOE OSTI2025

Convergence of Energy and IT Sectors

Today there has never been a more profound codependence and synergetic convergence, such as the one between the energy and IT sectors, and the industries will need to work together more closely to meet today’s growing data center power demands.

AI↗

DOE OSTI2026

System-Level Efficiency Study of Modular DC/DC and Fuel Cell Stack Series–Parallel Configurations

This paper presents a system-level efficiency study of modular DC/DC converter and fuel cell stack configurations under series, parallel, and series–parallel connections. The investigation considers selected DC/DC converter topologies, including isolated and non-isolated architectures, boost, non-inverting buck-boost, and resonant converters, integrated with commercially available fuel cell stacks, including the Accelera FCE150, Ballard FCgen-HPS, and Toyota TFCM2. DC/DC converter modules are evaluated in modular configurations rated at 60 kW and 90 kW and two distinct output voltage ranges, specifically 580–730V and 780–930V, examining how different interconnection schemes impact overall system efficiency. The converters are evaluated under full load (100%), partial load (66%), and light load (33%) conditions, providing a comprehensive assessment of efficiency and operational characteristics across varying power demands. Approximately two-thousand efficiency data points are obtained from laboratory prototype–level component measurements and validated design evaluations across multiple converter topologies, modular configurations, voltage ranges, and load conditions, providing a robust dataset for comparative system-level efficiency analysis. The results highlight the effects of modularity and topology selection on system-level efficiency, offering a “playbook” framework for designers to select appropriate DC/DC converter arrangements and fuel cell stack connections for series, parallel, or hybrid configurations based on efficiency considerations.

DC/DC↗

DOE OSTI2022

Multifunctional fiber-reinforced composites for passive sensing and energy harvesting with enhanced mechanical performance

Fiber-reinforced polymer composites (FRPCs) are valid alternatives to metals, especially in the aerospace industry, for their superior strength-to-weight ratio. FRPCs are generally manufactured by stacking layers of fibers and infusing them with epoxy-based adhesives to result in laminates. Such layer-by-layer structure often ensues a poor interlaminar property of the composites. Additionally, FRPCs can sustain complex damage modes because of their inherent anisotropic characteristics. For example, delamination can occur due to low-velocity impact at a subsurface level, which can result in premature catastrophic failures if undetected. Thus, structural monitoring is crucial to identify such damage. Point-based sensors (e.g., strain gauges, accelerometers, among many) can be embedded in the FRPCs for structural monitoring. However, their electrical power demand often embroils their usage. Therefore, the main objective of this research is to design and implement multifunctional composites that can simultaneously perform passive sensing and energy harvesting while exhibiting better mechanical performance. Previous research efforts have demonstrated that a continuous feed-through deposition of functional materials on fiber surfaces simultaneously enhanced the mechanical and sensing properties of the FRPCs. This study explores a similar approach to encode passive sensing and energy harvesting properties in the FRPCs by integrating ferroelectric microparticles on the fiber surfaces. Upon ensuring their superior interlaminar shear strength, sensing and energy harvesting properties were characterized through experimental studies. The outcome is a multifunctional composite fabricated by coating the fibers with functional microparticles through a high throughput, scalable, and low-cost approach that enables passive sensing, energy harvesting, and improved mechanical performance.

Gupta, Sumit↗

DOE OSTI2025

Modeling Structured Electrodes and Graded Porosity for Improving Discharge Rate Capability in Ultra-Thick Graphite|LiNi 0.6 Mn 0.2 Co 0.2 O 2 Batteries

Long-range electric vehicles (EVs) require high-energy-density batteries that also meet the power demands of high current charge and discharge. Ultra-thick (>100 μm) Lithium-ion battery electrodes are critical to enable this need, but slow ion transport in conventional uniform electrodes (UEs) reduces battery capacity at increasing charge/discharge rates. We present a 3D computational analysis on the impact of structured electrode (SE) and graded electrode (GE) geometries on the discharge rate capability of ultra-thick graphite|LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC-622) battery cells based on the footprint of a commercial EV pouch cell. SE cathodes with either a “grid” or “line” geometry and GEs with two layers of porosity were modeled. Based on the results of 230 models, we found that the electrolyte volume fraction is a key parameter that impacts capacity improvements in UEs, GEs, and SEs at 2 C–6 C discharge rates. SEs have the greatest discharge rate capability, outperforming GEs and UEs due to reduced Lithium-ion concentration gradients across the electrode thickness, which mitigates electrolyte depletion at high rates. The best SE model has a “grid” geometry with gravimetric and volumetric energy density improvements of 0.9%–4% at C/2–2 C and 18%–24% at 4 C–6 C relative to UEs.

25 ENERGY STORAGE↗

DOE OSTI2023

Data Projection of the High Temperature Electrolysis System in the Dynamic Energy Transport and Integration Laboratory using Dynamic System Scaling

For nuclear power to be flexible in a functioning Integrated Energy System (IES), excess produced heat must be stored or utilized during times of low power demand to ensure a load factor of 1 while load balancing. The Dynamic Energy Transport and Integration Laboratory (DETAIL) is one facility that is under development to emulate IES conditions on the engineering-scale, planned to conduct virtual real time operations with industry-scale facilities, and is currently testing thermal storage and high temperature electrolysis. As part of the study to develop a method to preprocess input signals or postprocess output signals between systems of different scales via Dynamical System Scaling (DSS), the current research is one of the continued efforts branching from the data projection activity conducted for the Thermal Energy Distribution System and currently engages the High Temperature Electrolysis (HTE) System in DETAIL. The HTE SOEC electrical, fluid, and thermal dynamics Figure of Merits (FOM) were identified, governing equations and closure relations were successfully scaled, and relations between FOM scaling ratios were determined. Setting the scaling objectives to reform existing data to project a data set that doubly accelerated the electrolysis process while preserving the produced amount of hydrogen was generated for the full transient. The calculated boundary conditions were inlet temperature, stack current, and inlet steam mass flow rate at 1470 K, 121.1 A, and 1.886 g/s, respectively. The research outcomes demonstrated an output signal postprocessing case accelerating the hydrogen production without changing geometry, number of cells, and partial pressures.

08 HYDROGEN↗

DOE OSTI2020

Development of FRET clusters for CBRN Detection

Advanced sensor capabilities for the simultaneous on-site detection of specific chemical, biological, and radiological/nuclear (CBRN) threats is important to significantly limit the risk of exposure to personnel and allow the rapid collection of essential scientific data and critical evidence. Commercially available sensor capabilities are generally complex, and/or require highly specific and ultra-sensitive methods that are often power demanding or require offsite post-analysis for positive detection, leaving personnel vulnerable. The goal of this project is to develop a portable sensor capable of simultaneously detecting CBRN signatures using a multiplexed Förster Resonance Energy Transfer (FRET) based sensor. FRET sensors are tailorable, specific, and highly dependent on the donor-acceptor distance. In this project, nanoparticles were functionalized with aptamers that were designed for the detection of methylphosphonate, a sarin metabolite. FRET was measured between quantum dot donors and dye and metal nanoparticle acceptors using optical spectroscopy.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2020

Algal Biomass Production via Open Pond Algae Farm Cultivation: 2019 State of Technology and Future Research

NREL’s algae state of technology benchmarking efforts focus both on front-end algal biomass production and separately on back-end conversion to fuels through NREL’s “combined algae processing” (CAP) pathway. The production model is based on outdoor long-term cultivation data, enabled by comprehensive algal biomass production trials conducted under Development of Integrated Screening, Cultivar Optimization, and Verification Research (DISCOVR) consortium efforts, driven by data furnished by Arizona State University (ASU) at the Arizona Center for Algae Technology and Innovation (AzCATI) testbed site. The CAP model is based on experimental efforts conducted under NREL R&D projects. This report focuses on front-end algal biomass production, documenting the pertinent algal biomass cultivation parameters that were input to the NREL open pond algae farm model and reports on key process sustainability indicators for the biomass production stage including annual biomass yields, facility power demand, and water consumption.

09 BIOMASS FUELS↗

DOE OSTI2020

Hybrid Electric Drivetrain Testing and Design (CRADA CRD-17-00699 Final Report)

Hybrid electric drivetrains have recently become of a great interest in the medium and heavy-duty vehicle market as it enables substantial reduction of petroleum use, vehicle level fuel use and criteria pollutant emissions. These vehicle performance improvements are not only economically beneficial for business operations relying on large fleets of vehicles, they are also paramount for curbing energy use and the negative effects of vehicle operations on the environment. Efficient Drivetrains, Inc. (EDI), acquired in July 2018 by Cummins, Inc., is a small company focused on development of medium and heavy-duty hybrid electric drivetrains. EDI has already developed the general hardware architecture of their drivetrain system, but there is still a significant effort to be done on optimizing the system in terms of control strategies and component sizing in order to maximize the benefits of the hybrid drivetrain. Historically, hybrid electric systems have proven to deliver better fuel economy in certain applications than their conventional counterparts. Particular areas of advantageous applications are vocations with kinetically intensive transient duty cycles and operations requiring some sort of power take off whose power demand is not well matched to the size of the vehicle’s main engine, thus forcing it to operate in extremely inefficient operating modes. Hybrid drivetrains can be at a disadvantage when pressed into duty cycle operation consisting of extensive steady state highway cruise due to various design compromises optimized for more transient operation. This can also lead to increase in vehicle emissions if the system is not optimized properly. Ample opportunity for extensive optimization is needed to overcome these obstacles.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2020

Hybrid Electric Drivetrain Testing and Design (CRADA CRD-17-00699 Final Report)

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Future Automotive Systems Technology Simulator (FASTSim) Validation Report - 2021

The National Renewable Energy Laboratory's Future Automotive Systems Technology Simulator (FASTSim) captures the most important factors influencing vehicle power demands and performs large-scale fuel efficiency calculations very quickly. These features make FASTSim well suited to evaluate a representative distribution of real-world fuel efficiency over a large quantity of in-use driving profiles, which have become increasingly available in recent years owing to incorporation of Global Positioning System data collection into various travel surveys and studies. In addition, by being open source, computationally lightweight, freely available, and free from expensive third-party software requirements, analyses conducted using FASTSim may be easily replicated and critiqued in an open forum. This is highly desirable for situations in which technical experts seek to reach consensus over questions about what vehicle development plans or public interest strategies could maximize fuel savings and minimize adverse environmental impacts with an evolving vehicle fleet. While FASTSim continues to be refined and improved on an ongoing basis, this report compiles available runs using versions of the tool from the past few years to provide illustrative comparisons of the model results against measured data.

33 ADVANCED PROPULSION SYSTEMS↗