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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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485 records · Page 27

A First-Principles Approach to Modeling Surface Site Stabilities on Multimetallic Catalysts

The study of multimetallic alloys and the multitude of possible surface compositions have sparked a tremendous interest in engineering low-cost materials with high activity and selectivity in heterogeneous catalysis. Multimetallic systems provide complementary functionalities and an unprecedented tunability when designing catalyst formulations. However, due to their immense structural and compositional complexity, the investigation and identification of an optimal catalyst is a tedious and time-consuming process, both experimentally and theoretically. Therefore, theoretical design principles are highly desirable to accelerate the screening of catalyst structures across the vast compositional space. In this paper, we introduce a simple and general model for predicting the site stability of multimetallic surfaces and nanoparticles, which is based on physical principles. The model requires only a small set of density functional theory (DFT) calculations of metal atom binding energies on monometallic and dilute alloy surface slabs to optimize the parameters in the simple model. The resulting model allows for the quantification of the stability of any particular atom site in any conceivable chemical environment across a wide range of morphologies, sizes, and arrangements by interpolating the derived parameters from a monometallic system to a completely diluted alloyed system. Herein, we demonstrate the robustness of the model across an extensive data set of transition metal alloy surfaces and 147-atoms cuboctahedral nanoparticles (NPs) composed of IrRhRu and PtPdRu. In conclusion, our approach yields mean absolute errors of ≈0.15 (IrRhRu), 0.20 (PtPdRu), 0.19 (IrRhRu NP), and 0.26 (PtPdRu NP) eV relative to site binding energies calculated using DFT.

36 MATERIALS SCIENCE↗

Sensing Electrical Networks Securely & Economically (SENSE)

The growing adoption of distributed energy resources (DERs) like battery energy storage systems and roof top solar/PV and the rapid penetration of electric vehicles (EVs), the electric grid is undergoing a major transformation with elevated stress on legacy grid assets. Despite a lot of expenditure to address these challenges, both in dollars and manpower, utilities have not been able to receive the value that was promised. The gains have been most visible at the transmission and substation level, especially where the main objective was improving operational and economic efficiency for the utility. Improving visibility and control at a few select points enhances the existing and established paradigm of centralized command and control. With changing load patterns, load types and the overall transition to an “active grid”, the centralized control and coordination paradigm gets challenged. To address the challenges, a new architecture and mechanism is needed, one that supports decentralized control and decision making, extracting value streams at the grid edge, particularly as the changes are fueled by transitions occurring in the distribution system. To address this, a communications and data processing platform, “GAMMA” was developed and demonstrated through the project. At the heart of the platform, are distributed, intelligent edge nodes with sensing and compute capabilities, that can record and analyze information locally. They are embedded in sensors and actuators specific to different distribution system applications. Phase 1 of the project focused on developing novel sensor technology that can be used for monitoring utility pole top distribution transformers. The sensors were designed with the objective of being low-cost, communicating with the GAMMA cloud using novel “delay-tolerant” networking using Bluetooth and a secure mobile application. They were non-intrusive in nature so that they can be installed quickly in the field, resulting in overall low cost of deployment and operations. Following the successful completion of Phase 1, the team manufactured 100 units for a field demonstration in Phase 2. The field demonstration was carried out on two real feeder systems with the local utility partner. In total, 100 sensors were installed and operated over a period of 6 months in the state of Georgia. The platform is operational end to end, with the cloud infrastructure deployed on a distributed, serverless environment that can serve multiple data streams, an analytics engine and a portal to securely view the data from multiple assets. The data collected through the GAMMA Mobile Phone app showcased the viability of the novel delay tolerant networking architecture, and the data processing algorithms developed through the course of the project, were successful in extracting important information about the overall network, improving the utility’s visibility and situational awareness in the distribution feeder.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Magnetohydrodynamic Augmented Propulsion Experiment

A fundamental obstacle to routine space access is the specific energy limitations associated with chemical fuels. In the case of vertical take-off, the high thrust needed for vertical liftoff and acceleration to orbit translates into power levels in the 10 GW range. Furthermore, useful payload mass fractions are possible only if the exhaust particle energy (i.e., exhaust velocity) is much greater than that available with traditional chemical propulsion. The electronic binding energy released by the best chemical reactions (e.g., LOX/LH2 for example, is less than 2 eV per product molecule (approx. 1.8 eV per H2O molecule), which translates into particle velocities less than 5 km/s. Useful payload fractions, however, will require exhaust velocities exceeding 15 km/s (i.e., particle energies greater than 20 eV). As an added challenge, the envisioned hypothetical RLV (reusable launch vehicle) should accomplish these amazing performance feats while providing relatively low acceleration levels to orbit (2-3g maximum). From such fundamental considerations, it is painfully obvious that planned and current RLV solutions based on chemical fuels alone represent only a temporary solution and can only result in minor gains, at best. What is truly needed is a revolutionary approach that will dramatically reduce the amount of fuel and size of the launch vehicle. This implies the need for new compact high-power energy sources as well as advanced accelerator technologies for increasing engine exhaust velocity. Electromagnetic acceleration techniques are of immense interest since they can be used to circumvent the thermal limits associated with conventional propulsion systems. This paper describes the Magnetohydrodynamic Augmented Propulsion Experiment (MAPX) being undertaken at NASA Marshall Space Flight Center (MSFC). In this experiment, a 1-MW arc heater is being used as a feeder for a 1-MW magnetohydrodynamic (MHD) accelerator. The purpose of the experiment is to demonstrate that an MHD accelerator can be an effective augmentation system for increasing engine exhaust velocity. More specifically, the experiment is intended to show that electromagnetic effects are effective at producing flow acceleration whereas electrothermal effects do not cause unacceptable heating of the working fluid. The MHD accelerator was designed as an externally diagonalized segmented Faraday channel, which will be inserted into an existing 2-tesla electromagnet. This allows the external power to be connected through two terminals thereby minimizing the complexity and cost associated with powering each segment independently. The design of the accelerator and other components in the flow path has been completed and fabrication activities are underway. This paper provides a full description of MAPX including performance analysis, design, and test plans, and current status.

Litchford, Ron J.↗

Computational Fermi Level Engineering and Doping-Type Conversion of Mg:Ga 2 O 3 via Three-Step Synthesis Process

Gallium oxide (Ga 2 O 3 ) is being actively explored for electronics that can operate at high power, temperature, and frequency as well as for deep-ultraviolet optoelectronics and other applications due to its ultra-wide bandgap (UWBG) and low projected fabrication cost of large-size and high-quality crystals. Efficient n-type doping of monoclinic beta-phase of Ga 2 O 3 has been achieved, but p-type doping faces fundamental obstacles due to compensation, deep acceptor levels, and the polaron transport mechanism of free holes. However, aside from the challenges of achieving p-type conductivity, plenty of opportunity exists to engineer the position of the Fermi level for improved design of Ga 2 O 3 -based devices. We use first-principles defect theory and defect equilibrium calculations to simulate a three-step growth-annealing-quench synthesis protocol for hydrogen-assisted Mg doping in ß-Ga 2 O 3 . The simulations take into account the gas phase equilibrium between H 2 , O 2 , and H 2 O, which determines the H chemical potential. We predict Ga 2 O 3 doping-type conversion to a net p-type regime after growth under reducing conditions in the presence of H2 followed by O-rich annealing, which is a similar process to Mg acceptor activation by H removal in GaN. For equilibrium annealing with re-equilibration of compensating O vacancies, there is an optimal temperature that maximizes the Ga 2 O 3 net acceptor density for a given Mg doping level; the acceptor density is further increased in the non-equilibrium annealing scenario without re-equilibration. After quenching to operating temperature, the Ga 2 O 3 Fermi level drops below mid-gap down to about 1.5 eV above the valence band maximum, creating a significant number of uncompensated neutral Mg Ga 0 acceptors. The resulting free hole concentration in Ga 2 O 3 is very low even at elevated operating temperature (~10 8 cm -3 at 400°C) due to the deep energy level of these Mg acceptors, and hole conductivity is further impeded by the polaron hopping mechanism. However, the Fermi-level reduction and suppression of free electron density in this doping-type converted (NA>ND) Ga 2 O 3 material are important for improved designs of Ga 2 O 3 electronic devices. These results illustrate the power of computational predictions not only for new materials but also for their synthesis science.

36 MATERIALS SCIENCE↗

Federal Workplace Charging Program Guide

The 2015 Fixing America's Surface Transportation (FAST) Act authorizes the installation, operation, and maintenance of electric vehicle supply equipment (EVSE) for the purpose of recharging employees' privately owned vehicles (POVs) under the custody or control of the General Services Administration (GSA) or a Federal agency. It requires the collection of fees to recover the costs of installing, operating, and maintaining this equipment and imposes reporting requirements. This program guide reviews those requirements, excerpts the relevant language in Appendix A, and describes when and how fees may be required to cover costs of electricity, network costs, EVSE units, and installations in various scenarios. This program guide is designed to support Federal agencies developing and refining workplace charging programs for employee POVs. While it provides guidance and best practices, it does not replace agencywide policies or agency-specific legal counsel. It contains a roadmap for agency workplace charging programs and defines roles and responsibilities. This guide explains how to determine the number of POVs likely to charge at a given site and contains a sample employee survey in Appendix B. It reviews EVSE planning, including unit selection and acquisition, charger location(s), accounting for available power capacity, using existing infrastructure, and funding an incentive program. It also discusses the costs associated with EVSE acquisition, installation, and network management. These costs inform the subsequently provided information, which describes how to amortize costs to determine appropriate fees for each charging session. The final two sections of this guide address aspects of ongoing program management that the facility coordinator should consider and the reporting requirements associated with the FAST Act. The insights in this guide are applicable to all agency-owned and GSA-leased buildings or facilities offering the use of EVSE or a 120-volt receptacle for the purpose of recharging an employee's POV. However, the FAST Act requirements typically do not apply to any building or facility operated and maintained by a third-party vendor offering the use of EVSE as part of a commercial building lease unless the agency is managing the station and/or energy on behalf of the building and collecting POV fees.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Electrocatalytic water oxidation performance in an extended porous organic framework with a covalent alliance of distinct Ru sites

The rational synthesis of durable, earth-abundant efficient electrocatalysts for the oxygen evolution reaction (OER) from water is one of the most important routes for storing renewable energy and minimizing fossil fuel combustion. The prime hurdles for effectively utilizing commercial RuO 2 as (OER) electrocatalysts are its very low stability, catalyst deactivation, and high cost. In this work, we explored a Ru-integrated porous organic polymer (Ru@Bpy-POP) by a facile one-pot Friedel–Crafts alkylation strategy between redox-active (Ru(demob) 3 Cl 2 ) and a carbazole unit, which is composed of unique features including an extended framework unit, isolated active sites, and tunable electrode kinetics. Ru@Bpy-POP can serve as a bridge between a Metal–Organic Framework (MOF) and POP-based catalytic systems with a balanced combination of covalent bonds (structural stability) and open metal sites (single site catalysis). Ru@Bpy-POP, deposited on a three-dimensional nickel foam electrode support, exhibits a promising electrocatalytic OER activity with an ultra-low ruthenium loading compared to a benchmark RuO 2 catalyst, providing an overpotential of about 270 mV to reach 10 mA cm –2 in an alkaline medium. Moreover, a high current density of 248 mA cm –2 was achieved for the Ru@Bpy-POP catalyst at only 1.6 V (vs. RHE), which is much higher than 91 mA cm –2 for commercial RuO 2 . The robust, albeit highly conjugated, POP framework not only triggered facile electro-kinetics but also suppressed aggregation and metallic corrosion during electrolysis. In particular, the benefits of covalent integration of distinct Ru sites into the framework can modulate intermediate adsorption and charge density, which contributes to its exceptional OER activity. All of the critical steps involved in OER are complemented by Density Functional Theory (DFT) calculations, which suggest that electrocatalytic water oxidation proceeds from a closed-shell configuration to open-shell electronic configurations with high-spin states. Finally, these open-shell configurations are more stable than their closed-shell counterparts by 1 eV, improving the overall catalytic activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Future Battery Material Demand Analysis Based on U.S. Department of Energy R&D Targets

The U.S. Department of Energy’s Vehicle Technologies Office (VTO) supports research, development, and deployment of efficient, sustainable transportation technologies that will improve energy efficiency and fuel economy, and enable America to use less petroleum. To accelerate the development and adoption of new technologies, VTO has developed specific targets for a wide range of powertrain components, including the energy storage system. In this study, we use Autonomie, Argonne National Laboratory’s (Argonne’s) vehicle system simulation tool to evaluate future energy storage requirements (power, energy, etc.) for different vehicle classes, powertrains, component technologies and timeframes. BatPac, Argonne’s tool dedicated to energy storage pack design and costs, is then used to quantify the materials required for each pack. Market penetrations are then used to estimate the overall material demand worldwide and in the United States, with or without recycling. The results demonstrate that the positive impact of VTO research and development will lead to significant reduction in material compared to business-as-usual due to new anode and cathode designs, along with acceleration in battery cell chemistry penetrations. In terms of material demands, it is observed that lithium demand reaches about 80,000 tons (by a factor of 42–45), nickel demand reaches about 500,000 tons (by a factor of 47–56), manganese demand reaches about 30,000–50,000 tons (by a factor of 20–34), and cobalt demand reaches about 30,000 tons (by a factor of 13–28) in the future by 2050. The individual material demand per unit energy, however, decreases significantly in the future due to advances in VTO research and development activities. The increase in battery material demands is mostly driven by increased electrified vehicle fleet penetration in the markets.

25 ENERGY STORAGE↗

Fe-single atom catalysts facilitate fast electron transfer with MoS 2 /SnS 2 cathodes in lithium–sulfur batteries

Lithium–sulfur batteries (LSBs) emerge as promising next-generation energy storage systems offering cost-effectiveness, environmental friendliness, and high theoretical energy density. The practical implementation of LSBs faces significant hindrances due to the shuttle effect and sluggish redox reactions. To address these challenges, single-atom catalyst (SAC) based combination materials from d-block elements can offer increased active catalytic sites, rapid charge transfer, accelerated electron migration, and fast sulfur redox conversion kinetics of lithium polysulfides (LiPSs). In this study, we fabricated three different LSB cathodes: pure S, S@MoS 2 /SnS 2 , and S@Fe–MoS 2 /SnS 2 . These cathodes were then used to explore the cycle life, capacity, rate capability, and redox kinetic reactions of LiPSs while assessing the influence of Fe-SACs on their performance. As a result, LSBs with S@Fe–MoS 2 /SnS 2 cathodes demonstrate an extended cycle life of 1000 cycles at a C-rate of 0.2C, maintaining a capacity close to 500 mA h g −1 , the highest initial discharge capacity of 1622 mA h g −1 and 1066 mA h g −1 at 0.05C and 0.2C, and excellent rate capabilities of 708 mA h g −1 and 558 mA h g −1 at 1C and 2C, respectively. The synergistic effect of the Fe-SAC-based combination cathode (S@Fe–MoS 2 /SnS 2 ) creates plentiful adsorptive and highly active catalytic sites, resulting in substantially enhanced capacity for adsorbing soluble long-chain LiPSs. This facilitates ultra-fast redox kinetics, surpassing the performance of the S@MoS 2 /SnS 2 and pure S cathodes. In the ex situ analysis, results from powder X-ray diffraction (XRD) to observe the new phase, soft X-ray absorption spectroscopy (XAS) to investigate the electronic structure, and hard X-ray photoelectron microscopy (HAXPES) with different energies (900 eV, 2000 eV, and 6000 eV) to track the chemical-state evolution of Fe-SACs in MoS 2 /SnS 2 cathodes displayed notable electrochemical reversibility involving S 8 ⇄ LiPSs ⇄ Li 2 S conversion even after 1000 cycles. Additionally, in situ, operando Raman analysis can unveil a novel catalytic mechanism of Fe-SACs in MoS 2 /SnS 2 “facilitating rapid electron transfer” during the discharge and charge processes of LSBs involving the conversion of S 8 ⇄ long-chain LiPSs ⇄ Li 2 S 2 /Li 2 S. This study elucidates the working mechanism of Fe-SAC cathodes, offering insights into overcoming the shuttle effect and facilitating sulfur redox kinetics to advance commercial LSBs.

36 MATERIALS SCIENCE↗

Sizing battery energy storage and PV system in an extreme fast charging station considering uncertainties and battery degradation

In this paper, we present mixed integer linear programming (MILP) formulations to obtain optimal sizing for a battery energy storage system (BESS) and solar generation system in an extreme fast charging station (XFCS) to reduce the annualized total cost. The proposed model characterizes a typical year with eight representative scenarios and obtains the optimal energy management for the station and BESS operation to exploit the energy arbitrage for each scenario. Contrasting extant literature, this paper proposes a constant power constant voltage (CPCV) based improved probabilistic approach to model the XFCS charging demand for weekdays and weekends. This paper also accounts for the monthly and annual demand charges based on realistic utility tariffs. Furthermore, BESS life degradation is considered in the model to ensure no replacement is needed during the considered planning horizon. Different from the literature, this paper offers pragmatic MILP formulations to tally BESS charge/discharge cycles using the cumulative charge/discharge energy concept. McCormick relaxations and the Big-M method are utilized to relax the bi-linear terms in the BESS operational constraints. Finally, a robust optimization-based MILP model is proposed and leveraged to account for uncertainties in electricity price, solar generation, and XFCS demand. Case studies were performed to signify the efficacy of the proposed formulations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

IceCube-Gen2: the window to the extreme Universe

The observation of electromagnetic radiation from radio to γ-ray wavelengths has provided a wealth of information about the Universe. However, at PeV (10 15 eV) energies and above, most of the Universe is impenetrable to photons. New messengers, namely cosmic neutrinos, are needed to explore the most extreme environments of the Universe where black holes, neutron stars, and stellar explosions transform gravitational energy into non-thermal cosmic rays. These energetic particles havemillions of times higher energies than those produced in the most powerful particle accelerators on Earth. As neutrinos can escape from regions otherwise opaque to radiation, they allow an unique view deep into exploding stars and the vicinity of the event horizons of black holes. The discovery of cosmic neutrinos with IceCube has opened this new window on the Universe. IceCube has been successful in finding first evidence for cosmic particle acceleration in the jet of an active galactic nucleus. Yet, ultimately, its sensitivity is too limited to detect even the brightest neutrino sources with high significance, or to detect populations of less luminous sources. In thiswhite paper, we present an overview of a next-generation instrument, IceCube-Gen2, which will sharpen our understanding of the processes and environments that govern the Universe at the highest energies. IceCube-Gen2 is designed to: (a) Resolve the high-energy neutrino sky from TeV to EeV energies (b) Investigate cosmic particle acceleration through multi-messenger observations (c) Reveal the sources and propagation of the highest energy particles in the Universe (d) Probe fundamental physics with high-energy neutrinos IceCube-Gen2 will enhance the existing IceCube detector at the South Pole. It will increase the annual rate of observed cosmic neutrinos by a factor of ten compared to IceCube, and will be able to detect sources five times fainter than its predecessor. Furthermore, through the addition of a radio array, IceCube- Gen2 will extend the energy range by several orders of magnitude compared to IceCube. Construction will take 8 years and cost about $350M. The goal is to have IceCube-Gen2 fully operational by 2033. IceCube-Gen2 will play an essential role in shaping the new era of multimessenger astronomy, fundamentally advancing our knowledge of the highenergy Universe. Overall, this challenging mission can be fully addressed only through the combination of the information from the neutrino, electromagnetic, and gravitational wave emission of high-energy sources, in concert with the new survey instruments across the electromagnetic spectrum and gravitational wave detectors which will be available in the coming years.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

CubeX: A Compact X-Ray Telescope Enables Both X-Ray Fluorescence Imaging Spectroscopy and Pulsar Timing Based Navigation

This paper describes the benefits of a miniaturized X-ray telescope payload in the context of a lunar mission. The first part describes the payload in detail, the second part summarizes a small satellite mission concept that utilizes its compact form factor and performance. The CubeX instrument can be used for both X-ray fluorescence (XRF) imaging spectroscopy and X-ray pulsar timing based navigation (XNAV). Using our recent technological advances in X-ray optics and sensors, CubeX combines high angular resolution (<1 arcminutes) Miniature Wolter-I X-ray optics (MiXO) with a common focal plane consisting of high spectral resolution (<150 eV at 1 keV) CMOS X-ray sensors and a high timing resolution (< 1 usec) SDD X-ray sensor. This novel combination of the instruments enables both XRF measurements and XNAV operations without moving parts. The high angular resolution of the MiXO opens a wide range of orbital configurations for observation. Given that performance, the instrument has unprecedented small volume (~1×1×6U), mass (<6 kg), and power (<9W) requirements and opens a wide range of applications for a variety of targets and missions including NEOs and Martian moons. In this paper we illustrate one potential application for a lunar mission concept: The elemental composition of the Moon holds keys to understanding the origin and evolution of both the Moon and the Earth. X-ray fluorescence (XRF), induced either by solar X-ray flux or energetic ions, carries decisive signatures of surface elemental composition. X-ray observations, therefore, give a unique, powerful diagnostic tool for remotely determining elemental abundances including major rock forming elements such as Mg, Al, Na, Si, Fe, and Ca. Through high-resolution XRF imaging spectroscopy, CubeX searches for small patches of elusive lower crust and mantle material excavated within and around impact craters. CubeX identifies regional compositional variations and allows straightforward comparison of elemental distributions with the surface topography from LRO and the gravity data from GRAIL. The elemental compositions of the lower crust and the mantle are sensitive to the conditions of the giant impact which led to the Moon's formation and the subsequent lunar magma ocean (LMO), and thus they are key missing pieces in understanding the formation and early evolution of the Moon. In between XRF observations, CubeX also leverages the technology of high resolution X-ray imaging and time series measurements to conduct XNAV operations and evaluate their performance. Deep space navigation is a critical issue for small planetary missions. XNAV can enable low-cost autonomous deep-space navigation, and has the potential to greatly assist, or even outperform, NASA's Deep Space Network (DSN) or ESA's European Space Tracking (ESTRACK). CubeX is designed to perform sequential observations of 3-4 millisecond pulsars (MSPs) to solve the spacecraft trajectory for absolute navigation, and explore the remote sensing capability of XNAV. In the presented mission concept, the Moon's relative proximity enables a straightforward evaluation of the XNAV performance through DSN.

x-ray spectroscopy↗

Assessments of Physiology and Cognition in Hybrid-Reality Environments (APACHE) – A VR “Sandbox” for Planetary Spacewalk Research

NASA is planning to return to the Moon in the mid-2020s as a steppingstone to Mars missions in the 2030s. Spacewalks, or extravehicular activities (EVAs), performed on the Moon and Mars will differ in a variety of ways from those that have been performed in decades past. NASA has identified multiple risks to human health and performance associated with a crewed mission to Mars, especially those associated with exploration EVAs which are expected to be a primary mission activity. Crew may be expected to conduct up to 24 hours of EVA per person per week, where the likelihood of injury and/or mental mistakes are increased compared to ground-based training or current microgravity EVAs and the consequences of which can be catastrophic. Current test environments for exploration EVA research and technology development are large, costly facilities that are limited in their availability or capabilities. Spacesuit testing in a reduced gravity environment such as NASA’s Neutral Buoyancy Laboratory, while a good representation of the crew’s physical workload during exploration EVAs, typically has small datasets and is difficult to integrate physiological sensors or other types of crew performance measures. Meanwhile, scientific field-based testing such as NASA’s Desert Research and Technology Studies offers an operationally relevant environment for exploration EVAs, particularly for cognitive workload, but is also limited by small datasets, lack of a pressurized spacesuit, and obtrusive measures. The limitations of current analogs for exploration EVAs identify a need for a new test environment that can approximate both the physical and cognitive demands associated with exploration EVAs to enable rapid, controlled, and repeatable evaluations of human health and performance risks of exploration missions. In response, the Human Physiology, Performance, Protection, and Operations Laboratory (H-3PO) at NASA Johnson Space Center has developed a hybrid reality exploration EVA analog named the Assessments of Physiology And Cognition in Hybrid-reality Environments (APACHE)[ to address these limitations using a combination of virtual, physical, and hybrid reality techniques. The APACHE facility resides at NASA Johnson Space Center and serves as a large “sandbox” for EVA research and simulation. At its center is a roughly 15x20ft space surrounded by a 14” tall sandbox partially filled with lunar regolith simulant to emulate the physical feeling of walking on a planetary surface and to allow for simulated geology operations. Nearby, a curved passive treadmill (Skillmill Connect, Technogym, Fairfield, NJ) and an omnidirectional treadmill (Infinadeck, Infinadeck, Rocklin, CA) are included to enable exploration of these large virtual environments while also imposing the physical demands, representative timelines, and cognitive burdens required to navigate and traverse these distances during exploration EVA. A 6DOF motion platform is used to simulate rover operations and supports various human performance evaluations and associated risks. Lastly, APACHE can support two extravehicular (EV) crewmembers working in tandem. A computer workstation is located nearby and also supports an intravehicular (IV) crewmember as part of a full mission simulation. The IV crewmember has direct video and audio communication with the EV crew in VR to provide operational and procedural support.

Human Performance↗

Assessments of Physiology and Cognition in Hybrid-Reality Environments (APACHE)

NASA is planning to return to the Moon in the mid-2020s as a stepping stone to Mars missions in the 2030s. Spacewalks, or extravehicular activities (EVAs), performed on the Moon and Mars will differ in a variety of ways from those that have been performed in decades past. NASA has identified multiple risks to human health and performance associated with a crewed mission to Mars, especially those associated with exploration EVAs which are expected to be a primary mission activity. Crew may be expected to conduct up to 24 hours of EVA per person per week, where the likelihood of injury and/or mental mistakes are increased compared to ground-based training or current microgravity EVAs and the consequences of which can be catastrophic. Current test environments for exploration EVA research and technology development are large, costly facilities that are limited in their availability or capabilities. Spacesuit testing in a reduced gravity environment such as NASA’s Neutral Buoyancy Laboratory, while a good representation of the crew’s physical workload during exploration EVAs, typically has small datasets and is difficult to integrate physiological sensors or other types of crew performance measures. Meanwhile, scientific field-based testing such as NASA’s Desert Research and Technology Studies offers an operationally relevant environment for exploration EVAs, particularly for cognitive workload, but is also limited by small datasets, lack of a pressurized spacesuit, and obtrusive measures. The limitations of current analogs for exploration EVAs identify a need for a new test environment that can approximate both the physical and cognitive demands associated with exploration EVAs to enable rapid, controlled, and repeatable evaluations of human health and performance risks of exploration missions. In response, the Human Physiology, Performance, Protection, and Operations Laboratory (H-3PO) at NASA Johnson Space Center has developed a hybrid reality exploration EVA analog named the Assessments of Physiology And Cognition in Hybrid-reality Environments (APACHE) to address these limitations using a combination of virtual, physical, and hybrid reality techniques. The APACHE facility resides at NASA Johnson Space Center and serves as a large “sandbox” for EVA research and simulation. At its center is a roughly 15x20ft space surrounded by a 14” tall sandbox partially filled with lunar regolith simulant to emulate the physical feeling of walking on a planetary surface and to allow for simulated geology operations. Nearby, a curved passive treadmill (Skillmill Connect, Technogym, Fairfield, NJ) and an omnidirectional treadmill (Infinadeck, Infinadeck, Rocklin, CA) are included to enable exploration of these large virtual environments while also imposing the physical demands, representative timelines, and cognitive burdens required to navigate and traverse these distances during exploration EVA. A 6DOF motion platform is used to simulate rover operations and supports various human performance evaluations and associated risks. Lastly, APACHE can support two extravehicular (EV) crewmembers working in tandem. A computer workstation is located nearby and also supports an intravehicular (IV) crewmember as part of a full mission simulation. The IV crewmember has direct video and audio communication with the EV crew in VR to provide operational and procedural support. The software used in APACHE was created by the JSC Engineering Directorate, in partnership with Buendea, powered by a custom Unreal Engine 5 (UE5.3, Epic Games) project. APACHE currently utilizes the HTC Vive Pro Eye in a wireless configuration for VR simulations. There are two virtual environments that subjects can explore within APACHE, a Lunar and Martian surface. The virtual Lunar surface was created from LIDAR data of the Lunar South Pole to create roughly 16 sq km of explorable terrain. The virtual Martian surface contains roughly 400 sq km of explorable terrain derived from Mars Reconnaissance Orbiter LIDAR data of the Jezero Crater. The immersion and related cognitive burdens of conducting a planetary EVA is simulated through a series of EVA-relevant tasks performed in the VR environment, using these high-fidelity visual representations. Additionally, APACHE includes biosensor driven informatics, such as real-time heart rate monitoring and/or derived values from model simulations, for active monitoring by the EV crew and added cognitive demand. A “Wizard of Oz” control panel enables test operators to activate contingency events such as simulated spacesuit malfunctions, loss of communications, and/or limited visibility. Embedded performance measures such as accuracy, completeness, and execution time have been developed for various exploration tasks to objectively quantify crew performance during an EVA and compare impacts to performance when different environmental stressors, both physical and cognitive, are added to or removed from the simulation. Additionally, validated cognitive and operational performance measures such as the Digit Symbol Substitution Task have been recreated and embedded in VR for direct and relatively unobtrusive measurement of motor perception. The APACHE environment currently supports multiple research studies at NASA. Examples include the CHAPEA project, a series of simulated year-long missions on Mars by a 4-person crew; and the CO2 Contingency Walk Back Study, an investigation of elevated CO2 exposure on crew performance during a contingency EVA scenario. APACHE also provides a test environment to support the development of the Crew State and Risk Model, which is a collection of individualized, mathematical models of crew physical and cognitive state; and the Personalized EVA Informatics and Decision Support system, an operational tool for flight controllers, and eventually a self-reliant Martian crew, to make biomedically-informed decisions in real-time to optimize the EVA planning and execution with respect to crew health and performance. Some technical challenges associated with developing the APACHE environment, as well as current limitations, include VR limitless natural walking with a hybrid spacesuit simulator, optimizing performance for wireless PC VR streaming while maintaining a high degree of visual fidelity, and the integration of various physiological (metabolic masks) and psychometric (eye tracking) sensors with the VR headset.

Human Performance↗

Charge Management for an Inductively Charged On-Demand Battery-Electric Shuttle Service with High Penetration of Renewable Energy

This paper presents a charge management control strategy for an on-demand battery-electric shuttle van operating at the National Renewable Energy Laboratory (NREL) campus and supported by day-time inductive charging at the vehicle's waiting spot. A new control algorithm has been proposed for reducing the demand charge costs incurred from wireless charging of the on-demand shuttle. A custom controller has been developed to monitor the shuttle, wireless charger, renewable energy generation, and various loads at NREL's campus, and regulate charging behavior for demand response. The intermittent renewable generation and sporadic operation of the on-demand shuttle service contribute to a high level of uncertainty in expected campus load profile, which must be carefully managed. The control algorithm predicts energy profile to estimate the mobility needs of the vehicle and maintain uninterrupted service during operation while still minimizing peak demand. The proposed controller has been designed and optimized using a Simulink model for the entire system. Next, it has been implemented and tested in real-time on the NREL campus. Two primary vehicle-use cases, charge sustaining and charge depletion operation, are tested under different load profiles and drive cycles to assess the controller's effectiveness at reducing peak demand and therefore demand charges. The proposed controller showed robust performance under different driving scenarios with high correlation between simulated and experimental data. The results showed that proper demand response can be achieved with an average of 94% reduction of charging loads during peak demand events.

ADVANCED PROPULSION SYSTEMS,ENERGY STORAGE↗

In-situ hydrogen microstructural characterization of Si heterojunction passivation: Addressing V OC degradation and mitigation pathways

Si heterojunction (SHJ) solar cells have demonstrated record efficiency >27%, approaching the theoretical limit of ≈ 29%, primarily due to best surface/interface defect passivation provided by deposited thin layers of hydrogenated amorphous silicon (a-Si:H). Such excellent surface/interface passivation reduces recombination loss and result in >100 mV improvement of cell open circuit voltage (V OC ) to ≈ 750 mV, thus the cell efficiency. However, fielded SHJ modules exhibit loss of V OC and hence efficiency over time in years, presumably due to degradation related to a-Si:H layers. This adversely affects the technology’s market acceptance, and levelized cost of energy (LCOE). It is hypothesized that the origin of a-Si:H degradation is somehow related to the presence of weak Si–Si bonds and hydrogen in a-Si:H films. The objective of this project is to test this hypothesis by directly measuring chemical and structural changes occurring within SHJ component layers and solar cells. This is achieved by developing an innovative in-situ Fourier transform infrared (FTIR) spectrometry apparatus to monitor hydrogen microstructural changes occurring within amorphous silicon and decipher hydrogen evolution kinetics over time when samples are exposed to heat and/or light stress. These in-situ measured hydrogen microstructural changes are correlated to the changes in effective minority carrier lifetime (τ eff ), implied V OC (iV OC ), surface recombination velocity (S), and cell V OC . These mechanistic understandings will provide critical guidance to mitigate the V OC -driven degradation of SHJ solar cell performance. Passivation optimization and degradation analysis of individual SHJ component structures were achieved through systematic deposition of three symmetric structures and the completed SHJ solar cell structure. The three symmetric structures used were intrinsic a-Si:H [(i)a-Si:H] layers in a bilayer structure, intrinsic and p-type doped stacked layers [(i-p)a-Si:H] representing the front heterojunction in the SHJ cell, and intrinsic and n-typed doped stacked layers [(i-n)a-Si:H] representing the back-side back surface field (BSF) in the SHJ cell. State-of-the-art passivation qualities are demonstrated by a champion iV OC of 740 mV for the (i)a-Si:H layers, and the (i-n)a-Si:H symmetric structure. A 725 mV iV OC is observed for the (i-p)a-Si:H symmetric structure. These symmetric passivated SHJ component structures were subsequently subjected to different accelerated lifetime (ALT) stressors to identify which conditions contribute the most to iV OC degradation. Degradation of the thin (10 nm) (i)a-Si:H passivation layers without any additional overlying layers is minimal; complexity of this study arises due to unavoidable surface oxidation of (i)a-Si:H layer during most of the stress application, which is likely irrelevant for a full SHJ cell configuration with overlying protective layers. The iV OC degradation of symmetric structures is found to occur primarily at the (i-p)a-Si:H passivation stack under dark heat stress with associated hydrogen loss from the (p)a-Si:H layer. An activation energy for increase in S (defect creation) of 0.65 eV can be correlated to the activation energy of ≈ 0.4 eV for hydrogen loss from the (i-p)a-Si:H stack. This also suggests the presence of weakly bonded hydrogen in the (p)a-Si:H films, which effuses out of the film stack at such low activation energy. When light and heat stress are applied together, similar hydrogen loss from (i-p)a-Si:H stack is observed, however, does not appreciably degrade iV OC or increase S. This is an important result and departure from direct correlation between hydrogen loss and defect creation. This perhaps indicates additional defect chemistries or annealing that might be occurring in the presence of light requiring further detailed defect measurements. The full SHJ cell structure used for this project is depicted in Fig.1(d). SHJ cells with an initial V OC ≈ 700 mV were fabricated and subjected to similar ALT stress conditions. Cell V OC is found to degrade the most under dark heat stress and is confirmed by observed hydrogen migration out of the (i-p)a-Si:H stack. However, hydrogen cannot escape from the cell stack, it accumulates near the (p)a-Si:H/ITO contact interface, where ITO acts as a barrier preventing hydrogen loss. Furthermore, light-heat combined stress does not degrade V OC appreciably, confirming the occurrence of a defect annealing process.

14 SOLAR ENERGY↗

High-dimensional Data-driven Energy optimization for Multi-Modal Transit Agencies (HD-EMMA) (Final Technical Report)

Public bus transit services in the U.S. are responsible for at least 19.7 million metric tons of CO 2 emission annually. Electric vehicles (EVs) can have a much lower environmental impact than comparable internal combustion engine vehicles (ICEVs), especially in urban areas. Unfortunately, EVs are also much more expensive than ICEVs. As a result, many public transit agencies can afford only mixed fleets of transit vehicles, consisting of EVs, hybrids (HEVs), and ICEVs. Transit agencies that operate such mixed fleets of vehicles face a challenging optimization problem: these agencies need to decide which vehicles are assigned to serving which transit trips. Since the advantage of EVs over ICEVs varies depending on the route and time of day (e.g., the benefit of EVs is higher in slower traffic with frequent stops and lower on highways), the assignment can have a significant effect on energy use and, hence, environmental impact. Through this project, we have developed reference data about energy collections and constructed a set of machine learning models that can accurately predict the energy consumption for the whole fleet at the level of each trip. We have used these models to develop a scheduling and assignment strategy that can rotate the different vehicle types across the transit agencies’ routes. The optimization algorithm ensures that the vehicles are matched to trips considering weather patterns, expected congestion, and road gradients to minimize the overall energy usage. We list the key observations from our project for other practitioners below. Details are available in the report, and the list of source code and our publications are included in the appendix. 1. We have demonstrated the feasibility of collecting, merging and analyzing large volumes of high-resolution real-world telemetry data from a mixed vehicle fleet. To mitigate the inherent noise of the recorded GPS points, the team developed an algorithm that filters data and maps the points onto a street. The algorithm considers previous and subsequent location measurements and different characteristics of nearby streets to determine how likely the vehicle travels on them. Then, the team segmented the time series into disjoint contiguous samples based on adjacent road segments and repeated the outlier detection and removal. For each data point, the team added features corresponding to elevation changes within the samples, weather features, such as temperature, and traffic data, such as speed ratio between actual speed and free-flow speed. 2. We have developed two forms of machine learning models that be used to understand and analyze the energy operations of a mixed vehicle transit fleet. The micro prediction model provides estimates of instantaneous energy prediction for all types of buses (diesel, hybrid, and electric). Such a model is important in evaluating the energy impacts of real-time bus operation strategies, but it is challenging due to diversified driving cycles of transit buses. The model can help the drivers understand the impact of their driving behaviors and short-term congestions. The macro prediction models estimate average energy consumption across the whole trip considering the features: distance traveled, various road-type features, elevation change, day of the week, time of day, various weather features (temperature, humidity, etc.), and traffic features (speed ratio and jam factor). 3. We have demonstrated that it is possible to transfer the machine learning models we have developed in this project to other teams and cities by using inductive transfer learning. We also showed that the performance of the macro energy prediction models can be improved using a multi-task learning approach where the learning parameters are shared between the models being developed for different vehicle types. The advantage of this approach is improved learning performance as the models can exploit common spatio-temporal and environmental characteristics. 4. Finally, we have developed trip and vehicle assignment and scheduling algorithms that use the energy prediction models and develop a trip to vehicle type (diesel, electric, hybrid) assignment for the whole operation to reduce overall emissions and cost. We have shown through simulations that the proposed algorithms can save $\$$ 48,910 in energy costs and 175 metric tons of CO 2 emission annually for CARTA.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

WBG-Enabled Current-Source Inverters for Integrated PM Motor Drives

This project takes advantage of the special capabilities of wide-bandgap (WBG) power semiconductor devices to develop innovative power electronics in the form of new current-source inverters (CSIs) that offer promising advantages over the dominant voltage-source inverter (VSI) topology. These CSIs, in turn, are extremely well-suited for integration into the housings of permanent magnet synchronous machines (PMSMs) to form integrated motor drives (IMDs). These new IMDs offer great promise for achieving major energy savings in a wide variety of applications that benefit from adjustable-speed control, including air conditioners, laundry appliances, industrial pumps/compressors, electric vehicles, and aerospace drives. WBG devices play a critical enabling role in these new IMDs because of their transformative features including much higher switching frequencies, lower losses, and compatibility with high operating temperatures. When incorporated into new CSI-based IMDs with PM machines, these WBG switches open the door to achieving major increases in power density, drive system efficiency, and fault tolerance, as well as substantial reductions in electromagnetic interference (EMI), manufacturing cost, and temperature-induced failures. The higher operating temperature capability of WBG devices compared to conventional silicon power devices is very appealing in IMD applications because the power electronics is mounted in close proximity to the motors which typically operate at temperatures well above the maximum limits of today’s silicon-based power electronics. This project has succeeded in designing, building, and testing multiple prototype versions of this CSI-IMD that have overcome many technical challenges in order to demonstrate the impressive performance improvements that can be achieved by the WBG-enabled CSI-IMD. The preliminary demo and bench-top versions of the current-source inverter developed during the first two years of the project were critical to laying the technical foundations for the 3 kW prototype CSI-IMD unit that was successfully built and tested during the third year. This prototype CSI-IMD unit was designed to fit within the housing envelope of the original permanent magnet (PM) synchronous machine in order to meet the demanding power density requirements that were set at the beginning of the project. All of the remaining performance objectives set for the prototype CSI-IMD unit including efficiency and electromagnetic interference (EMI) were also met. The last 18 months of the project were devoted to developing further enhancements of the WBG-enabled CSI-IMD technology that better prepare it for commercial production. More specifically, an upgraded version of the prototype CSI-IMD unit was developed that moved the power electronics into the same machine housing chamber as the motor, substantially raising the thermal demands on the power electronics. Tests with five different combinations of motor enclosure types and air cooling configurations were evaluated. Importantly, this work confirmed that the power electronics can deliver its full rated power and still operate well within its maximum temperature limits even for worst-case conditions when the housing is “totally-enclosed” without any openings for air to enter or exit the enclosure, and no blower/fan is provided to blow air over the outside surface of the enclosure. Reaching the full performance and energy-savings potential of this disruptive CSI-IMD motor drive technology is highly consistent with ARPA-E’s stated mission to “enhance the economic and energy security of the United States” while also supporting its commitment to “ensure that the U.S. maintains a technological lead in developing and deploying advanced energy technologies”. Follow-on projects are under way to explore the scalability of WBG-enabled CSI-IMD technology to 100 kW (peak) electric vehicle traction drives and fault-tolerant modular motor drives for future electrified aircraft propulsion applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗