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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 289 records · Page 16

Understanding extraction limits of plasma cathodes with experiment and simulation

The project is focused on computations for enhanced ionization near the exit orifice of a plasma cathode and how the cathode extraction electrode geometry and stray magnetic field structure influence available extractable current. The computational effort will take place at the Princeton Collaborative Research Laboratory (PCRF). The specific modeling platform to be utilized from PCRF is the electrostatic direct implicit particle in cell (EDIPIC) code. EDIPIC will be used to study ionization processes in the electron extraction region of the cathode. The control of electron energy is a key aspect to minimizing power losses in the plasma. Exiting electrons ionize gas leaving the orifice and in the process produce the dense plasma from which large amounts of current can be extracted. Project activities include studying processes that determine the energy distribution of the exiting electrons thus providing insight into how to optimize the source. The model will be validated and developed using experimental measurements as warranted. The familiarity and expertise of the team at PPPL with this type of plasma and the challenges posed greatly enhances the likelihood of gaining insight into the extraction sheath under the duration of the proposed activity. The effort is expected to shed a great deal of insight into electron extraction processes and pathways for optimization.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Direct observation of twisted stacking domains in the van der Waals magnet CrI 3

Van der Waals (vdW) stacking is a powerful technique to achieve desired properties in condensed matter systems through layer-by-layer crystal engineering. A remarkable example is the control over the twist angle between artificially-stacked vdW crystals, enabling the realization of unconventional phenomena in moiré structures ranging from superconductivity to strongly correlated magnetism. Here, we report the appearance of unusual 120° twisted faults in vdW magnet CrI 3 crystals. In exfoliated samples, we observe vertical twisted domains with a thickness below 10 nm. The size and distribution of twisted domains strongly depend on the sample preparation methods, with as-synthesized unexfoliated samples showing tenfold thicker domains than exfoliated samples. Cooling induces changes in the relative populations among different twisting domains, rather than the previously assumed structural phase transition to the rhombohedral stacking. The stacking disorder induced by sample fabrication processes may explain the unresolved thickness-dependent magnetic coupling observed in CrI 3 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Impedance Scan of Inverter-Based Resources and Diesel Generator for Stability Analysis: Preprint

Impedance-based methods are widely used for power system stability analysis with inverter-based resources (IBRs), e.g., assessing dynamic interactions between the power grid and an IBR, control interactions between multiple IBRs, and the sub-synchronous oscillation and damping phenomenon. Since it is difficult to get a numerical model 100% matching with the hardware IBR, using the hardware inverter directly to obtain its output impedance has become a prominent approach nowadays. Therefore, this article presents the impedance scan using hardware IBRs, and also a hardware diesel generator as it still stays with the grid before the grid completely goes to renewable. The devices under test (DuTs) for the impedance scan includes two 3-..phi.., 480 V, 60 Hz commercial grid-forming IBRs (one of 250 kVA and another of 125 kVA rating) in series with ..delta..-Y transformers, one 3-..phi.., 480 V, 60 Hz commercial grid-following IBR (of 125 kVA rating), and a 3-..phi.., 480 V, 60 Hz commercial diesel generator (of 187.5 kVA rating). Using voltage signals perturbed with sub-, inter-, and higher harmonic components, and measuring the current response, the positive-sequence impedances are computed via an offline- based post-analysis. Moreover, best-fit transfer functions are estimated that closely resemble the measured data points of the positive-sequence impedances. Based on the observations from various outcomes of the hardware experiments, this article also provides some fundamental insights on the equivalent positive- sequence impedance of a combination of multiple hardware components by comparing the estimated and the empirically computed impedances. A comparative insight on the damping capability of the DuTs using the positive-sequence impedances of the hardware is also discussed.

grid following inverter↗

Impedance Scan of Inverter-Based Resources and Diesel Generator for Stability Analysis

Impedance-based methods are widely used for power system stability analysis with inverter-based resources (IBRs), e.g., assessing dynamic interactions between the power grid and an IBR, control interactions between multiple IBRs, and the sub-synchronous oscillation and damping phenomenon. Since it is difficult to get a numerical model 100% matching with the hardware IBR, using the hardware inverter directly to obtain its output impedance has become a prominent approach nowadays. Therefore, this article presents the impedance scan using hardware IBRs, and also a hardware diesel generator as it still stays with the grid before the grid completely goes to renewable. The devices under test (DuTs) for the impedance scan includes two 3-..phi.., 480 V, 60 Hz commercial grid-forming IBRs (one of 250 kVA and another of 125 kVA rating) in series with ..delta..-Y transformers, one 3-..phi.., 480 V, 60 Hz commercial grid-following IBR (of 125 kVA rating), and a 3-..phi.., 480 V, 60 Hz commercial diesel generator (of 187.5 kVA rating). Using voltage signals perturbed with sub-, inter-, and higher harmonic components, and measuring the current response, the positive-sequence impedances are computed via an offline-based post-analysis. Moreover, best-fit transfer functions are estimated that closely resemble the measured data points of the positive-sequence impedances. Based on the observations from various outcomes of the hardware experiments, this article also provides some fundamental insights on the equivalent positive-sequence impedance of a combination of multiple hardware components by comparing the estimated and the empirically computed impedances. A comparative insight on the damping capability of the DuTs using the positive-sequence impedances of the hardware is also discussed.

current measurement↗

Optical control of integer and fractional Chern insulators

Optical control of topology, particularly in the presence of electron correlations, is an interesting topic with broad scientific and technological impact. Twisted MoTe 2 bilayer (tMoTe 2 ) is a zero-field fractional Chern insulator (FCI), exhibiting the fractionally quantized anomalous Hall effect. As the chirality of the edge states and sign of the Chern number are determined by the underlying ferromagnetic polarization, manipulation of ferromagnetism would realize control of the Chern insulator (CI)/FCI states. Here, in this work, we demonstrate control of ferromagnetic polarization, and thus the CI and FCI states, by circularly polarized optical pumping in tMoTe 2 . At low excitation power, we achieve on-demand preparation of ferromagnetic polarization by optical training, that is, electrically tuning the system from non-ferromagnetic to desirable ferromagnetic states under helicity-selective optical pumping. With increased excitation power, we further realize direct optical switching of ferromagnetic polarization at a temperature far below the Curie temperature. Both optical training and direct switching are most effective near CI and FCI states, which we attribute to a gap-enhanced valley polarization of optically pumped holes. The magnetization can be dynamically switched by modulating the helicity of optical excitation. Spatially resolved measurements further demonstrate optical writing of ferromagnetic, and thus CI (or FCI) domains. Our work realizes precise optical control of a topological quantum many-body system with potential applications in topological spintronics, quantum memories and creation of exotic edge states by programmable patterning of integer and fractionally quantized anomalous Hall domains.

ferromagnetism↗

Visual Style Elements in Human–System Interface Design for Nuclear Power Operations: Does Style Affect Performance and Preference?

As the world increasingly adopts renewable and sustainable energy systems, transitionary solutions include nuclear power, which currently provides 20% of the United States’ electricity and is the largest single source of carbon-free electricity generation. Advanced reactors are a critical component of a carbon-free mixed energy portfolio that require careful design of first-of-a-kind control rooms. The application of Human Factors Engineering (HFE) is essential for scientific and iterative testing of novel human–system interface (HSI) concepts to ensure effective, efficient, and safe plant operations. Microworlds are simulators that use simplified physics models and control systems to distill nuclear power operations into essential functions. HFE scientists used the Rancor Microworld Simulator to obtain preference and performance metrics for novel and traditional static HSI design styles. Participants comprised advanced reactor company employees and nuclear industry consultants. A mixture of quantitative and qualitative data was captured. There was a preference for the basic graphical style that included high contrast and traditional color scheme elements. No single HSI design outperformed the others, and the participants did not perform better using their preferred HSI style. We report this experiment is the first in a series of HFE testing for HSIs in advanced reactor control room development. Clear user preferences emerged for elements within static displays. The cutting-edge neumorphic style was the least preferred. Future directions include tests of dynamic displays. HFE is used in evaluating and designing HSI devices that will improve the efficiency and safety of advanced nuclear power operations.

99 GENERAL AND MISCELLANEOUS↗

On the Use of Smart Meter Data to Estimate the Voltage Magnitude on the Primary Side of Distribution Service Transformers

This paper develops a novel method to estimate the voltage magnitude on the primary side of distribution service transformers. The proposed method relies exclusively on smart meters, and therefore it is fully data-driven. This is an important feature because electric utilities have detailed models of only the primary network - that is, the network between the distribution substation and the primary side of service transformers that are installed closer to end-customer sites. The network that connects the secondary side of service transformers to end-customer sites, referred to as the secondary network, is simply represented by a lumped load. For each secondary network, the proposed method uses data acquired from only 2 smart meters: the closest and the farthest-in the sense of electrical distance - from the service transformer. As a reference to this feature, the proposed method is named SM2Vp. To our knowledge, this is the first time a method is shown to provide actionable information for realtime operation and control of power distribution grids using only two smart meters per secondary network. This is important because utilities have experienced barriers in managing and using large data sets for real-time operation and control. SM2Vp is primarily intended to provide pseudo-measurements for distribution system state estimation, but it can also be used directly for voltage control schemes. The performance of SM2Vp is demonstrated by numerical simulations carried out on three secondary network synthetic models and by using field data provided by a utility partner serving customers in southwestern California. A maximum relative error of approximately 3.9% or less is observed for the primary voltage magnitude estimates in all numerical experiments.

distribution service transformer↗

The value of wake steering wind farm flow control in US energy markets

Abstract. Wind farm flow control represents a category of control strategies for achieving wind-plant-level objectives, such as increasing wind plant power production and/or reducing structural loads, by mitigating the impact of wake interactions between wind turbines. Wake steering is a wind farm flow control technology in which specific turbines are misaligned with the wind to deflect their wakes away from downstream turbines, thus increasing overall wind plant power production. In addition to promising results from simulation studies, wake steering has been shown to successfully increase energy production through several recent field trials. However, to better understand the benefits of wind farm flow control strategies such as wake steering, the value of the additional energy to the electrical grid should be evaluated – for example, by considering the price of electricity when the additional energy is produced. In this study, we investigate the potential for wake steering to increase the value of wind plant energy production by combining model predictions of power gains using the FLOw Redirection and Induction in Steady State (FLORIS) engineering wind farm flow control tool with historical electricity price data for 15 existing US wind plants in four different electricity market regions. Specifically, for each wind plant, we use FLORIS to estimate power gains from wake steering for a time series of hourly wind speeds and wind directions spanning the years 2018–2020, obtained from the ERA5 reanalysis dataset. The modeled power gains are then correlated with hourly electricity prices for the nearest transmission node. Through this process we find that wake steering increases annual energy production (AEP) between 0.4 % and 1.7 %, depending on the wind plant, with average increases in potential annual revenue (i.e., annual revenue of production, ARP) 4 % higher than the AEP gains. For most wind plants, ARP gain was found to exceed AEP gain. But the ratio between ARP gain and AEP gain is greater for wind plants in regions with high wind penetration because electricity prices tend to be relatively higher during periods with below-rated wind plant power production, when wake losses occur and wake steering is active; for wind plants in the Southwest Power Pool – the region with the highest wind penetration analyzed (31 %) – the increase in ARP from wake steering is 11 % higher than the AEP gain. Consequently, we expect the value of wake steering, and other types of wind farm flow control, to increase as wind penetration continues to grow.

17 WIND ENERGY↗

Accelerating Next-Generation Cybersecurity R&D Using AI Workflows: BADGER Project Development

The Broadband Automation for Distributed Grid Efficiency and Resilience (BADGER) project aligns with national strategic priorities for integrating emerging wireless technologies and advancing AI-driven security. As critical infrastructure modernizes toward increasingly software-defined and interconnected systems, the ability to leverage 5G/NextG networks and AI-enabled control becomes essential. This report outlines work at the National Laboratory of the Rockies (NLR) to develop a NextG-native security architecture powered by AI-RAN concepts and evaluate workflows that enable efficient and reliable architectures. Together, these efforts position the laboratory to accelerate innovation while directly supporting national security and resilience objectives.

5G/6G↗

Active control of laser beam pointing for the Zettawatt-Equivalent Ultrashort pulse laser System: a proof-of-principle study with 16-inch optics

We present a proof-of-principle study of active beam-pointing control for the Zettawatt-Equivalent Ultrashort pulse laser System (ZEUS) using a piezo-actuated 16-inch mirror. To the best of our knowledge, this is the largest actively controlled mirror reported in a high-power laser system. A simple proportional feedback control was implemented based on a field-programmable gate array, which reduced the standard deviation of beam-pointing fluctuations by 91% to 0.075 μrad in the horizontal direction and by 78% to 0.25 μrad in the vertical direction. We also demonstrated the elimination of long-term pointing jitter caused by temperature drift using the same apparatus.

laser pointing control↗

Data-Driven Load Modeling and Forecasting of Residential Appliances

The expansion of residential demand side management programs and increased deployment of controllable loads require accurate appliance-level load modeling and forecasting. This paper proposes a conditional hidden semi-Markov model to describe the probabilistic nature of residential appliance demand. Model parameters are estimated directly from power consumption data using scalable statistical learning methods. We also propose an algorithm for short-term load forecasting as a key application for appliance-level load models. Case studies performed using granular sub-metered power measurements from various types of appliances demonstrate the effectiveness of the proposed load model for short-term prediction.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Secure Communications Concept and API Concept for Integrating XENDEE Positronix with TESLA PowerPack System at Site 300 (Final Deliverable)

The CleanStart DERMS project focuses on the management of Distributed Energy Resources (DER) for enhanced distribution grid resilience. The demonstration site has changed from Riverside Public Utility to the LLNS Site 300 DERS demonstration site. This project has so far focused only on device level controllers and local area controllers. These controllers potentially lack the ability to perform supervisory control and grid interactive control functions, essential for grid-level optimal DER management. This project seeks to close that gap in development of secure communication concept and appropriate Application Programming Interfaces (API) to enable integration with DERs, device level and local area controllers, such as Distributed Energy Resources Management System (DERMS).

24 POWER TRANSMISSION AND DISTRIBUTION↗

Idaho National Laboratory’s FY 2021 Greenhouse Gas Report

A greenhouse gas (GHG) inventory is a systematic approach to account for the production and release of certain gases generated by an institution from various emission sources. The gases of interest are those that climate science has identified as related to anthropogenic global climate change. This document presents an inventory of GHGs generated during Fiscal Year (FY) 2021 by Idaho National Laboratory (INL)—a Department of Energy (DOE) sponsored entity located in southeastern Idaho. In recent years, concern has grown about the environmental impact of GHGs. This, together with a desire to decrease harmful environmental impacts, would be enough to encourage the calculation of an inventory of the total GHGs generated at INL. Additionally, INL has a desire to see how its emissions compare with similar institutions, including other DOE national laboratories. Executive Order 13834 requires that federal agencies and institutions track and report GHG emissions where required. INL’s GHG inventory was calculated according to methodologies identified in federal GHG guidance documents using operational control boundaries. It measures emissions generated in three scopes: (1) INL emissions produced directly by stationary or mobile combustion and by fugitive emissions, (2) the share of emissions generated by entities from which INL purchased electrical power, and (3) indirect or shared emissions generated by outsourced activities that benefit INL (occurring outside INL’s organizational boundaries but are a consequence of INL’s activities). This inventory found that INL generated 81,185.05 metric tons (MT) of CO 2 equivalent (CO 2 e) emissions during FY 2021. The following conclusions were made from looking at the results of the individual contributors to INL’s FY 2021 GHG inventory: Electricity (including the associated transmission and distribution losses) is the largest contributor to INL’s GHG inventory, with over 50% of the CO 2 e emissions; Other sources with high emissions were mobile combustion (fleet fuels), employee commuting, stationary combustion (facility fuels), and waste disposal (fugitive emissions from the onsite landfill); Sources with low emissions were waste disposal (contracted disposal), fugitive emissions from refrigerants, wastewater treatment (onsite and contracted), and business ground travel (in personal and rental vehicles). This report details the methods behind quantifying INL’s GHG inventory and discusses lessons learned on better practices by which information important to tracking GHGs can be tracked and recorded. It is important to note that because this report differentiates between those portions of INL that are managed and operated by Battelle Energy Alliance, LLC (BEA) and those managed by other contractors, it includes only INL’s activities overseen by BEA. It is assumed that other contractors will provide similar reporting for those activities they manage, where appropriate.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Idaho National Laboratory’s FY 22 Greenhouse Gas Report

A greenhouse gas (GHG) inventory is a systematic approach to account for the production and release of certain gases generated by an institution from various emission sources. The gases of interest are those that climate science has identified as related to anthropogenic global climate change. This document presents an inventory of GHGs generated during fiscal year (FY) 2022 by Idaho National Laboratory (INL)—a Department of Energy (DOE) sponsored entity located in southeastern Idaho. In recent years, concern has grown about the environmental impact of GHGs. This, together with a desire to decrease harmful environmental impacts, would be enough to encourage the calculation of an inventory of the total GHGs generated at INL. Additionally, INL has a desire to see how its emissions compare with similar institutions, including other DOE national laboratories. Executive Order 14057 requires that federal agencies and institutions track and report GHG emissions where required. INL’s GHG inventory was calculated according to methodologies identified in federal GHG guidance documents using operational control boundaries. It measures emissions generated in three scopes: (1) INL emissions produced directly by stationary or mobile combustion and by fugitive emissions, (2) the share of emissions generated by entities from which INL purchased electrical power, and (3) indirect or shared emissions generated by outsourced activities that benefit INL (occurring outside INL’s organizational boundaries, but are a consequence of INL’s activities). This inventory found that INL generated 75,572.42 metric tons (MT) of CO2 equivalent (CO2e) emissions during FY 2022. The following conclusions were made from looking at the results of the individual contributors to INL’s FY 2022 GHG inventory: • Electricity (including the associated transmission and distribution losses) is the largest contributor to INL’s GHG inventory, with over 50% of the CO2e emissions. • Other sources with high emissions were mobile combustion (fleet fuels), employee commuting, stationary combustion (facility fuels), and waste disposal (fugitive emissions from the onsite landfill). • Sources with low emissions were waste disposal (contracted disposal), fugitive emissions from refrigerants, wastewater treatment (onsite and contracted), and business ground travel (in personal and rental vehicles). This report details the methods behind quantifying INL’s GHG inventory and discusses lessons learned on better practices by which information important to tracking GHGs can be tracked and recorded. It is important to note that because this report differentiates between those portions of INL that are managed and operated by Battelle Energy Alliance, LLC (BEA) and those managed by other contractors, it includes only INL’s activities overseen by BEA. It is assumed that other contractors will provide similar reporting for those activities they manage, where appropriate.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Idaho National Laboratory’s FY 2020 Greenhouse Gas Report

A greenhouse gas (GHG) inventory is a systematic approach to account for the production and release of certain gases generated by an institution from various emission sources. The gases of interest are those that climate science has identified as related to anthropogenic global climate change. This document presents an inventory of GHGs generated during fiscal year (FY) 2020 by Idaho National Laboratory (INL)—a Department of Energy (DOE) sponsored entity located in southeastern Idaho. In recent years, concern has grown about the environmental impact of GHGs. This, together with a desire to decrease harmful environmental impacts, would be enough to encourage the calculation of an inventory of the total GHGs generated at INL. Additionally, INL has a desire to see how its emissions compare with similar institutions, including other DOE national laboratories. Executive Order 13834 requires that federal agencies and institutions track and report GHG emissions where required. INL’s GHG inventory was calculated according to methodologies identified in federal GHG Guidance documents using operational control boundaries. It measures emissions generated in three scopes: (1) INL emissions produced directly by stationary or mobile combustion and by fugitive emissions, (2) the share of emissions generated by entities from which INL purchased electrical power, and (3) indirect or shared emissions generated by outsourced activities that benefit INL (occurring outside INL’s organizational boundaries, but are a consequence of INL’s activities). This inventory found that INL generated 76,494.12 metric tons (MT) of CO2 equivalent (CO 2 e) emissions during FY 2020. The following conclusions were made from looking at the results of the individual contributors to INL’s FY 2020 GHG inventory: (1) Electricity (including the associated transmission and distribution losses) is the largest contributor to INL’s GHG inventory, with over 50% of the CO 2 e emissions; (2) Other sources with high emissions were employee commuting, mobile combustion (fleet fuels), stationary combustion (facility fuels), and waste disposal (fugitive emissions from the onsite landfill); and (3) Sources with low emissions were waste disposal (contracted disposal), fugitive emissions from refrigerants, wastewater treatment (onsite and contracted), and business ground travel (in personal and rental vehicles). This report details the methods behind quantifying INL’s GHG inventory and discusses lessons learned on better practices by which information important to tracking GHGs can be tracked and recorded. It is important to note that because this report differentiates between those portions of INL that are managed and operated by Battelle Energy Alliance, LLC (BEA) and those managed by other contractors, it includes only INL’s activities overseen by BEA. It is assumed that other contractors will provide similar reporting for those activities they manage, where appropriate.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Impact of control signal phase noise on qubit fidelity

As qubit decoherence times are increased and readout technologies are improved, nonidealities in the drive signals, such as phase noise, are going to represent a growing limitation to the fidelity achievable at the end of complex control pulse sequencies. Here we study the impact on fidelity of phase noise affecting reference oscillators with the help of numerical simulations, which allow us to directly take into account the interaction between the phase fluctuations in the control signals and the evolution of the qubit state. Our method is based on the generation of phase noise realizations consistent with a given power spectral density, that are then applied to the pulse carrier in simulations, with Qiskit-Dynamics, of the qubit temporal evolution. By comparing the final state obtained at the end of a noisy pulse sequence with that in the ideal case and averaging over multiple noise realizations, we estimate the resulting degradation in fidelity, and exploiting an approximate analytical representation of a carrier affected by phase fluctuations, we discuss the contributions of the different spectral components of phase noise.

Barsotti, Agata [Pisa U.]↗

Analytical Models of Frequency and Voltage in Large-Scale All-Inverter Power Systems

Low-order frequency response models for power systems have a decades-long history in optimization and control problems such as unit commitment, economic dispatch, and wide-area control. With a few exceptions, these models are built upon the Newtonian mechanics of synchronous generators, assuming that the frequency dynamics across a system are approximately homogeneous, and assume the dynamics of nodal voltages for most operating conditions are negligible, and thus are not directly computed at all buses. As a result, the use of system frequency models results in the systematic underestimation of frequency minimum nadir and maximum RoCoF, and provides no insight into the reactive power-voltage dynamics. This paper proposes a low-order model of both frequency and voltage response in grid-forming inverter-dominated power systems. The proposed model accounts for spatial-temporal variations in frequency and voltage behavior across a system and as a result, demonstrates the heterogeneity of frequency response in future renewable power systems. Electromagnetic transient (EMT) simulations are used to validate the utility, accuracy, and computational efficiency of these models, setting the basis for them to serve as fast, scalable alternatives to EMT simulation, especially when dealing with very large-scale systems, for both planning and operational studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Flexoelectricity and New Phenomena

It is easy to miss the scientific implications of our recent work on Triboelectricity. Everyone knows that rubbing and contact can produce static electricity; less appreciated is that the thermodynamic driver has been an open question since static electricity was first observed by Thales of Miletus around 585 BC. People think they understand it, for instance one common explanation that can still be found in the current literature is that differences in the work function drives charge transfer, often called the Volta-Helmholtz hypothesis. As summarized in 1967 by Harper, this fails to explain many experimental observations, for instance that charging can occur when two pieces of the same material are rubbed against each other. We are the first to place triboelectricity on a solid foundation rooted in quantum mechanics – the flexoelectric effect. We were able to explain a significant number of previously unexplained phenomena: 1) Bipolar tribocurrents associated with stick-slip, due to the change in sign of the strain gradients. 2) A one-third power scaling of tribocurrents with indentation force. 3) Tribocharging when two identical materials are used, these being due to local variations in the asperities so there are usually local potential differences. 4) Inhomogeneous charging of insulators, related to the statistical nature of asperities. 5) An experimentally observed reversal in the sign of charge transfer for negative and positive curvature, which is related to a change in the sign of the strain gradient. Exploiting our DOE prior funded work on flexoelectricity, we obtained semi-quantitative matching to existing experimental measurements of the surface charge in triboelectric experiments. The work has been well received in the literature. The work has been the focus of a number of popular science press articles, and also formed the basis for a Podcast for children 6-10 “The Rise and Fall of Static Man” posted in December 2019 by NPR as part of their “Wow in the World” series. I was also briefly interviewed by the Chicago PBS station in January 2020. This work are significant for a wide range of energy applications; to quote from an independent source: "Triboelectric power has plenty of potential, says Wenzhuo Wu, an assistant professor of engineering at Purdue. If the basics of static electricity are better understood, we could maximize the efficiency of wind or wave power generators, Wu says. The body's own movement could be used to power internal medical devices. Imagine being able to create a roof shaped to harness the power of a raindrop — the friction of the rain passing over the surface — to generate triboelectricity, powering the building below it." This is the start of new science, some of which we already partially understand such as the role of band bending in charge transfer. We need to understand charge transfer combining elasticity, quantum mechanics, band bending and defect states. These directly involve several of the DOE Grand Challenges: "How do we control material processes at the level of electrons? How do remarkable properties of matter emerge from complex correlations of the atomic or electronic constituents and how can we control these properties? How do we characterize and control matter away—especially very far away— from equilibrium?" I will argue that this work truly falls into the class of disruptive science; it is not just a simple extension, linear science. Not everyone will accept the approach. Since we explain far more about triboelectricity than anyone before, the preponderance of evidence supports the model. The feedback I have received is that many agree with the work, to quote: "The model makes sense, says Michael McAlpine, a professor of engineering at the University of Minnesota. "It's such a simple explanation, I was surprised I didn't put my finger on that," McAlpine says." The proposal received strong reviews. It was also publicized on the Department of Energy Web Site.

16 TIDAL AND WAVE POWER↗