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At least 1,369 records · Page 76

Real-Time Sea State Estimation for Wave Energy Converter Control via Machine Learning

Wave energy converters (WECs) harness the untapped power of ocean waves to generate renewable energy, offering a promising solution to sustainable energy. An optimal WEC control strategy is essential to maximize power capture that dynamically adjusts system parameters in response to rapidly changing sea states. This study presents a novel control approach that leverages neural networks to estimate sea states from onboard WEC measurements such as position, velocity, and force. Using a point absorber WEC device as a test platform, our proposed approach estimates sea states in real-time and subsequently adjusts PID controller gains to maximize energy extraction. Simulation results across diverse sea conditions demonstrate that our strategy eliminates the need for external wave monitoring equipment while maintaining power capture efficiency. The results show that our neural network-based control technique can improve power capture by 25.6% while significantly reducing system complexity. This approach offers a practical alternative for WEC deployments where direct wave measurements are either infeasible or cost prohibitive.

PIDcontrol↗

Fiber Optic Tactical Local Network (FOTLAN)

A 100 Mbit/s FDDI (fiber distributed data interface) network interface unit is described that supports real-time data, voice and video. Its high-speed interrupt-driven hardware architecture efficiently manages stream and packet data transfer to the FDDI network. Other enhancements include modular single-mode laser-diode fiber optic links to maximize node spacing, optic bypass switches for increased fault tolerance, and a hardware performance monitor to gather real-time network diagnostics.

Bergman, L. A.↗

A high performance FDDI NIU for streaming voice, video, and data

A 100-Mbit/s FDDI network interface unit (NIU) is described that supports real-time data, voice and video. Its high-speed interrupt-driven hardware architecture efficiently manages stream and packet data transfers to the FDDI network. Other enhancements include modular single-mode laser-dioce fiber optic links to maximize node spacing, optic bypass switches for increased fault tolerance, and a hardware performance monitor to gather real-time network diagnostics.

Bergman, L. A.↗

Systems Issues Pertaining to Holographic Optical Data Storage in Thick Bacteriorhodopsin Films

The optical data storage capacity and raw bit-error-rate achievable with thick photochromic bacteriorhodopsin (BR) films are investigated for sequential recording and read- out of angularly- and shift-multiplexed digital holograms inside a thick blue-membrane D85N BR film. We address the determination of an exposure schedule that produces equal diffraction efficiencies among each of the multiplexed holograms. This exposure schedule is determined by numerical simulations of the holographic recording process within the BR material, and maximizes the total grating strength. We also experimentally measure the shift selectivity and compare the results to theoretical predictions. Finally, we evaluate the bit-error-rate of a single hologram, and of multiple holograms stored within the film.

Downie, John D.↗

Operational Analysis of Vertiport Surface Topology

Urban Air Mobility (UAM) concepts and technologies are being developed to safely enable operations of small, electric-powered or hybrid, pilot-optional, vertical-takeoff-and-landing (VTOL) passenger and cargo aircraft at vertiport facilities in urban and suburban environments. It is likely that many of the highest demand locations for vertiports will be in space constrained urban environments, requiring vertiport designs to maximize throughput within a compact surface footprint. This paper presents several generic vertiport topology design approaches and evaluates their relative surface area utilization and operational efficiency under different wind constrained configurations while meeting safety driven spacing constraints derived from heliport design standards and subject matter expert interviews.

Urban air mobility↗

Self-Navigating Robotic Assistant for Long-term Wide Area Floor Contamination Monitoring - 18213

For Routine Contamination Testing (RCT) of an operational nuclear facility or one undergoing Decontamination and Decommissioning (D and D), workers utilize specified travel corridors (enclosed hallways or areas designated with tape or rope in open spaces) to minimize the risk of spreading contamination. Radiation health technicians must continually monitor these areas for contamination to minimize worker dose and prevent its spread to uncontrolled areas. For many sites, it is impractical for the technician to adequately survey such areas. The Nuclear Robotics Group (NRG) at UT Austin has developed a self-navigating robotic platform equipped with radiation detectors to augment the technician to improve both survey coverage and frequency. While maintaining a controlled velocity and floor-to-sensor distance, the system takes radiation measurements to identify and/or localize contamination sources. Readings above background levels are reported to a remote workstation to allow technicians to then respond accordingly. The completion of these mundane tasks by a robot allows the trained technicians to focus instead on operational tasks, D and D, or responding to alarms. The robot generates a map using a Lidar range sensor with established Simultaneous Localization and Mapping (SLAM) techniques. Range data is then compared to previously generated maps for robot localization and autonomous navigation. To maximize coverage, the robot executes a Complete Coverage Path Planning (CCPP) algorithm using a static map that is discretized into cells to assure comprehensive yet efficient coverage. As the system executes the generated plan, it builds a radiation map of the area for the technician to validate and verify the results. If contamination is detected, the robot will minimize the spread of contamination by stopping, sounding an alarm, and alerting the remote technician. The proposed system allows for long-term deployment with minimal human intervention. It is robust to both highly dynamic obstacles (i.e. personnel) and low dynamic changes (i.e. temporally stored cart) in the environment. This is accomplished through continuous spatiotemporal updating of the static map, and the utilization of a supervisory controller that allows the system to reliably respond to unexpected events or states (i.e. low battery, closed door, etc.). While the supervisory controller can respond to temporary complications, the system also recognizes the environment can change slowly over time necessitating that the CCPP automatically be updated to account for observed 'permanent' changes to the environment. To do this, the robot uses intermediate probabilistic data to make intelligent planning decisions offline while still maintaining local reactive obstacle avoidance and safety features. The self-updating of the map allows the robot to run longer without the need to remake the map, leading to more consistent monitoring data and less maintenance from the human technician. This paper will review the current system hardware, the CCPP algorithm, the supervisory controller, the probabilistic algorithm for identifying permanent changes, and recent experiments at UT Austin to experimentally validate the reported sensor coverage. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

JUSTIFI: Software for Improving Performance Objectives via Energy Efficiency

With growing energy supply concerns and rising costs, energy efficiency is a critical component of industrial energy resilience and competitiveness by directly reducing energy operating costs. Energy efficiency projects in manufacturing also yield valuable benefits to other key metrics, such as improved quality, reduced maintenance costs, improved safety, decreased pollution, and enhanced productivity. However, it is difficult to receive approval for energy efficiency projects, so implementation rates are low, even when meeting capital project payback period criteria. The inclusion and quantification of non-energy benefits (NEBs) in the decision-making process for energy efficiency projects can improve the overall financial payback period while demonstrating a positive impact on the firm's key performance metrics and business strategy. Despite their significant financial and strategic value, NEBs are rarely factored into decision-making due to lack of tools to effectively identify and quantify them. Therefore, a comprehensive and integrative approach is needed for the rapidly evolving energy landscape. To address these challenges, through funding from U.S. Department of Energy, our new assessment methodology integrates common continuous improvement six sigma concepts, such as the DMAIC process, and a protocol of guiding questions, into energy efficiency assessments to identify NEBs. We have also developed open-source software, JUSTIFI, to guide users through this process, data collection, and quantification. It is designed to be used concurrently with DOE energy system analysis software suite, MEASUR. Our methodology and tools inform energy assessors, firm engineering, decision makers, and workforce seeking to increase energy resilience and to maximize benefits aligned with performance metrics.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Sub-quantum Fisher information

We report the quantum Fisher information (QFI) plays a crucial role in quantum information theory and in many practical applications such as quantum metrology. However, computing the QFI is generally a computationally demanding task. In this work we analyze a lower bound on the QFI which we call the sub-quantum Fisher information (sub-QFI). The bound can be efficiently estimated on a quantum computer for an n-qubit state using 2n qubits. The sub-QFI is based on the super-fidelity, an upper bound on Uhlmann's fidelity. We analyze the sub-QFI in the context of unitary families, where we derive several crucial properties including its geometrical interpretation. In particular, we prove that the QFI and the sub-QFI are maximized for the same optimal state, which implies that the sub-QFI is faithful to the QFI in the sense that both quantities share the same global extrema. Based on this faithfulness, the sub-QFI acts as an efficiently computable surrogate for the QFI for quantum sensing and quantum metrology applications. Finally, we provide additional meaning to the sub-QFI as a measure of coherence, asymmetry, and purity loss.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Prioritizing circular economy strategies for sustainable PV deployment at the TW scale

Global decarbonization requires an unprecedented scale-up of photovoltaic (PV) manufacturing and deployment. The material demand and eventual end of life management associated with multi-TW scale deployment poses many challenges. Circular Economy (CE) and it's associated R-Actions (Reduce, Reuse, Recycle) have been proposed to mitigate end of life management and material sourcing concerns. However, CE metrics typically focus on a single product and only consider mass, excluding energy flows. This work leverages the PV in Circular Economy (PV ICE) tool to quantify the deployment, mass, and energy impacts of R-Actions and proposed sustainable PV designs in the context of achieving energy transition deployment goals (75 TW in 2050). 13 module scenarios are established and evaluated across 6 capacity, mass and energy metrics to identify tradeoffs and priorities. We find that increasing module efficiency can reduce near-term material demands up to 30% and improve energy metrics by up to 9%. Material circularity (recycling) can minimize lifecycle wastes and reduce material demands at the cost of higher energy demands. Increasing module lifetime, including reliability improvements and reuse strategies, is effective at reducing both material (>10%) and energy demands (24%). Uniquely, lifetime improvements maximize benefits and minimize the harms across all six metrics while achieving multi-TW scale deployment.

Photovoltaics↗

Center for Energy Efficient Materials (CEEM) (Final Technical Report)

The mission of the Center for Energy Efficient Materials (CEEM) was to serve the Department of Energy and the nation as a center of excellence dedicated to advancing basic research in nano-structured materials and devices for applications to solar electricity, thermoelectric conversion of waste heat to electricity, and solidstate lighting. The foundation of CEEM was based on the unique capabilities of UCSB and its partner institutions to control, synthesize, characterize, model, and apply materials at the nanoscale for more efficient sustainable energy resources. This unique expertise was a key source of the synergy that unified the research of the Center. Although the Center’s focus was basic research, It’s longer-term objective has been to transfer new materials and devices into the commercial sector where they will have a substantial impact on the nation’s need for efficient sustainable energy resources. As one measure of the impact of the Center, two start-up companies were formed based on its research. In addition, Center participants published a total of 210 archival journal articles, of which 51 were exclusively sponsored by the DOE grant. The work of the Center was structured around four specific tasks: Organic Solar Cells, Solid-State Lighting, Thermoelectrics, and High Efficiency Multi-junction Photovoltaic devices. A brief summary of each follows – detailed descriptions are in Sections 4 & 5 of this report. Research supported through CEEM led to an important shift with respect to the choice of materials used for the fabrication of solution deposited organic solar cells. Solution deposition opens the opportunity to manufacture solar cells via economically-viable high throughput tools, such as roll to roll printing. Prior to CEEM, most organic semiconductors utilized for this purpose involved polymeric materials, which, although they can form thin films reliably, suffer from batch to batch variations due to the statistical nature of the chemical reactions that produce them. In response, the CEEM team developed well-defined molecular semiconductors that produce active layers with very high power conversion efficiencies, in other words they can convert a very high fraction of sunlight into useful electrical power. The fact that the semiconductor is formed from molecular species provides the basis for circumventing the unreliability of polymer counterparts and, as an additional bonus, allows one to attain much grater insight into the structure of the active layer. The latter is particularly important because efficient conversion is the result of a complex arrangement of two semiconductors that need to phase separate in a way akin to oil and water, but with domains that are described by nanoscale dimensions. CEEM was therefore able to provide deep insight into the influence of nanostructure, through the application of structural characterization tools and theoretical methods that describe how electrical charges migrate through the organic layer. Our research in light emitting diode (LED)-based solid state lighting (SSL) was directed at improving efficiency and reducing costs to enable the widespread deployment of economically-viable replacements for inefficient incandescent, halogen, and fluorescent-based lighting. Our specific focus was to advance the fundamental science and technology of light emitting diodes to both understand factors that limit efficiencies and to provide innovative and viable solutions to the current impediments. One of the main challenges we faced is the decrease in efficiency when LEDs are driven harder to increase light output---the so called “droop” effect. It requires large emitting surfaces to reach a desired optical output, and necessitates the use of costly heat sinks, both of which increase the cost. We successfully reduced droop by growing LED crystals having non-conventional orientations. As recognized by the award of the 2014 Nobel prize to the inventors of the nitride LEDs (one of whom was a member of CEEM), LEDs already have a large societal impact in both developed (leading to large energy savings) and developing countries (bringing light where there is no electrical grid). The improvements in efficiency sought after in the CEEM project are key to a further impact of solid state lighting by LEDs with a projected doubling in efficiency by year 2020. Direct generation of electricity from heat has enormous promise for beneficial use of waste heat. But practical power generation directly from heat requires understanding and development of new and improved materials that will be more efficient and rugged than today’s thermoelectric materials. To accomplish this goal CEEM has synthesized five distinct and promising new classes of thermoelectric materials: (a) nanoparticle arrays that are effective in maximizing electric power generation and reducing detrimental loss of heat; (b) nitride and (c) oxide thermal electric materials that are effective at high temperatures where much beneficial heat is available; (d) arrays of silicon nano-wires that integrate thermal electricity generation into silicon-based electronics and materials; and (e) chemically synthesized nanostructured compounds that are cost effective, earth abundant, and environmentally friendly. The further development of these thermoelectric sources of electricity could have revolutionary impact for society in the recovery of waste heat from sources such as power plants and automobile exhaust, where there could be significant associated energy saving. It could even, in the future, provide disruptive alternatives and replacements for today’s internal combustion engines and could enable improved all-electric propulsion by the heat from shipboard nuclear reactors. The High Efficiency Multi-junction Photovoltaics task was a UCSB/NREL collaboration which bonded sub-cells from two different compound semiconductors material systems to make high efficiency multijunction solar cells for concentrating photovoltaic applications thathave substantially higher efficiency than single substrate cells made of elemental semiconductors such as silicon. This task required the development of new cell bonding methods with excellent coupling of both photons and electrons between the sub-cells. To accomplish this, we developed (1) GaInN solar cells with enhanced performance by using quantum-well absorbers and front-surface optical texturing, (2) a hybrid "pillar-array" bond which uses an array of metal pillars for electrical coupling, and (3) a "hybrid moth-eye" optical coating which combines the benefits of nano-imprinted moth-eye coatings and traditional multilayer coatings. The technical effectiveness was assessed by measurement of the photovoltaic efficiency of solar cells made using these techniques; the ultrahigh efficiencies targeted by this work are of compelling economic value for concentrating photovoltaics.

14 SOLAR ENERGY↗

Brilliant Execution of Smart Labs: Employing Best Practices to Improve Safety and Reduce Energy for Sustainable Labs: Preprint

Laboratory buildings often dominate the energy use on research campuses, consuming three to four times the energy of a typical office building. In most cases, these facilities are defined as “mission critical,” with excessive energy use as simply an unfortunate truth that cannot be avoided without compromising safety. However, case studies indicate cost savings opportunities of up to 40% in laboratories (compared to standard practices) by employing energy efficient design strategies that also improve the safety of lab spaces (Better Buildings 2018). To help stakeholders implement improvement measures, the Smart Labs Toolkit describes a proven approach to optimizing performance of laboratories and critical control environments in new or existing facilities. The Toolkit outlines distinct phases for building a successful Smart Labs program that include: Plan, Assess, Optimize, and Manage. Each phase has specific tasks, training videos, and resources to educate users, support the efforts of key stakeholders, and maximize benefits for the organization in implementing high-performance labs. The Toolkit also includes case studies from the 17 Better Buildings Smart Labs Accelerator partners, sharing lessons learned and supporting the Smart Labs approach to safe, efficient world class science. This paper reviews the technology choices for implementing Smart Labs ventilation strategies, controls, and other efficiency measures. Better Building Smart Lab Accelerator partners provide case study examples of safety and energy-savings results of using Smart Labs approaches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Privacy by Design in Distributed Edge Systems: Innovating Secure Workflows for Smart Cities

The proliferation of distributed edge systems, such as those in smart cities, healthcare, and industrial IoT, offers unprecedented opportunities for data processing closer to its source, thereby reducing latency and enhancing efficiency. However, these systems also present significant privacy challenges due to the handling of sensitive data from multiple sources. This article explores the critical need for designing privacy-preserving workflows in distributed edge systems to ensure data security while maximizing the potential of edge computing. By examining the challenges, technological advancements, and potential of privacy-by-design approaches, we highlight the importance of integrating advanced privacy-preserving techniques like federated learning, differential privacy, homomorphic encryption, secure multi-party computation, and zero-knowledge proofs. These innovations are crucial for enhancing data security, regulatory compliance, and public trust in smart city applications, ultimately leading to safer and more efficient urban environments.

Kotevska, Olivera↗

Evaporated CdSe for Efficient Polycrystalline CdSeTe Thin-Film Solar Cells

Recent progress has shown that alloying cadmium telluride (CdTe) with cadmium selenide (CdSe) to create a CdSexTe1-x (CdSeTe) gradient region can significantly boost the performance of polycrystalline CdSeTe thin-film solar cells. However, improper CdSeTe alloying might introduce problematic band alignment and deleterious voids at the front interface, limiting the benefit maximization of this technique. Here, we show that the CdSe layers deposited by thermal evaporation result in CdSeTe cells with a higher performance than the sputtered CdSe. This is because evaporated CdSe can avoid the formation of voids at the front interface, producing improved front junction quality with suppressed front junction nonradiative recombination. The champion cell using evaporated CdSe demonstrated a power conversion efficiency (PCE) of 19.7%, much higher than 18.1% in the cell using sputtered CdSe.

cadmium selenide↗

Technique for Configuring an Actively Cooled Thermal Shield in a Flight System

Broad area cooling shields are a mass-efficient alternative to conductively cooled thermal radiation shielding. The shield would actively intercept a large portion of incident thermal radiation and transport the heat away using cryogenic helium gas. The design concept consists of a conductive and conformable surface that maximizes heat transfer and formability. Broad Area Cooled (BAC) shields could potentially provide considerable mass savings for spaceflight applications by eliminating the need for a rigid thermal radiation shield for cryogen tanks. The BAC consists of a network of capillary tubes that are thermally connected to a conductive shield material. Chilled helium gas is circulated through the network and transports unwanted heat away from the cryogen tanks. The cryogenic helium gas is pumped and chilled simultaneously using a specialized pulse-tube cryocooler, which further improves the mass efficiency of the system. By reducing the thermal environment temperature from 300 to 100 K, the radiative heat load on a cryogen tank could be reduced by an order of magnitude. For a cryogenic liquid propellant scenario of oxygen and hydrogen, the boiloff of hydrogen would be significantly reduced and completely eliminated for oxygen. A major challenge in implementing this technology on large tanks is that the BAC system must be easily scalable from lab demonstrations to full-scale missions. Also, the BAC shield must be conformable to complex shapes like spheres without losing the ability to maintain constant temperature throughout. The initial design maximizes thermal conductivity between the capillary tube and the conductive radiation shielding by using thin, corrugated aluminum foil with the tube running transverse to the folds. This configuration has the added benefit of enabling the foil to stretch and contract longitudinally. This allows the BAC to conform to the complex curvature of a cryogen tank, which is key to its success. To demonstrate a BAC shield system with minimal impact to current cryogen tank designs, the shielding must be applied after the final assembly of the tank and supporting structure. One method is to pre-fabricate the shield in long strips. A spool of corrugated aluminum foil with a thermally sunk aluminum capillary running through the center could then be simply wound around the cryogen tanks and encapsulated within the multi-layer insulation (MLI) blanket. Then, on orbit, the BAC would intercept thermal radiation coming in through the MLI and transport it away from the cryogen tanks. An optimization of the design could be done to take into account mass savings from thinner MLI blankets, eliminating solid thermal shields, and ultimately, a reduction in the required cryogen tank size.

Barkfknecht, Peter↗

Additive Runge-Kutta Schemes for Convection-Diffusion-Reaction Equations

Additive Runge-Kutta (ARK) methods are investigated for application to the spatially discretized one- dimensional convection-diffusion-reaction (CDR) equations. Accuracy, stability, conservation, and dense-output are first considered for the general case when N different Runge-Kutta methods are grouped into a single composite method. Then, implicit-explicit, (N = 2), additive Runge-Kutta (ARK(sub 2)) methods from third- to fifth-order are presented that allow for integration of stiff terms by an L-stable, stiffly-accurate explicit, singly diagonally implicit Runge-Kutta (ESDIRK) method while the nonstiff terms are integrated with a traditional explicit Runge-Kutta method (ERK). Coupling error terms of the partitioned method are of equal order to those of the elemental methods. Derived ARK(sub 2) methods have vanishing stability functions for very large values of the stiff scaled eigenvalue, z['] yields -infinity, and retain high stability efficiency in the absence of stiffness, z['] yield 0. Extrapolation-type stage- value predictors are provided based on dense-output formulae. Optimized methods minimize both leading order ARK(sub 2) error terms and Butcher coefficient magnitudes as well as maximize conservation properties. Numerical tests of the new schemes on a CDR problem show negligible stiffness leakage and near classical order convergence rates. However, tests on three simple singular-perturbation problems reveal generally predictable order reduction. Error control is best managed with a PID-controller. While results for the fifth-order method are disappointing, both the new third- and fourth-order methods are at least as efficient as existing ARK(sub 2) methods.

Kennedy, Christopher A.↗

SU-E-T-780: Use Robustness Optimization (RO) Method to Improve the Planning Efficiency for Pencil Beam Scanning Cranial Spinal Irradiation

Purpose: We evaluate the feasibility of using robustness optimization (RO) function to improve the planning efficiency of pencil beam scanning (PBS) craniospinal irradiation (CSI) with gradient matching technique. Methods: A CSI patient was planned with 2 lateral brain fields and 4 posterior fields to cover the entire spine to maximal field of 24 cm × 20 cm on a compact PBS gantry, ProteusONE. CSI plans were generated using traditional volumetric gradient dose optimization (VGDO) and robustness optimization (RO) method respectively. In traditional VGDO, besides the sectioned spine target volumes, gradient volume (GV) were generated as 4 equally spaced structures e.g. 80%, 60%, 40%, and 20% of prescription dose. In RO method, only sectioned spine target volumes with an overlap of 4cm were created. In the robustness optimization settings, 5mm uncertainty in superior and inferior direction was defined for auto gradient optimization. Dosimetric metrics of conformity number (CN), homogeneity index (HI), and maximal cord doses were compared in Raystation version 4.6.100.6. Results: In VGDO method, total 16 GV structures and five 100% dose level target structures were contoured compared to total 5 target structures in RO method which saves 30 min in contour. With the same PTV coverage (95% volume receive 30.6Gy prescription dose), maximum cord dose is 32.64Gy in VGDO and 31.94Gy in RO. HI is 1.03 and 1.04 for VGDO and RO respectively. CN is 0.93 and 0.94 for VGDO and RO respectively. Conclusions: The dosimetric comparison demonstrated both methods are equivalent in terms of plan quality. With robust optimization for CSI gradient matching, it efficiently reduces the amount of planning target contour structure by factor of 4 and thus improves the planning efficiency especially for 4 or more gradient junction area.

60 APPLIED LIFE SCIENCES↗

Lactobacillus casei as a biocatalyst for biofuel production

Abstract Microbial fermentation of sugars from plant biomass to alcohols represents an alternative to petroleum-based fuels. The optimal biocatalyst for such fermentations needs to overcome hurdles such as high concentrations of alcohols and toxic compounds. Lactic acid bacteria, especially lactobacilli, have high innate alcohol tolerance and are remarkably adaptive to harsh environments. This study assessed the potential of five Lactobacillus casei strains as biocatalysts for alcohol production. L. casei 12A was selected based upon its innate alcohol tolerance, high transformation efficiency and ability to utilize plant-derived carbohydrates. A 12A derivative engineered to produce ethanol (L. casei E1) was compared to two other bacterial biocatalysts. Maximal growth rate, maximal optical density and ethanol production were determined under conditions similar to those present during alcohol production from lignocellulosic feedstocks. L. casei E1 exhibited higher innate alcohol tolerance, better growth in the presence of corn stover hydrolysate stressors, and resulted in higher ethanol yields.

Vinay-Lara, Elena↗

Particle Acceleration in Collisionless Magnetically Arrested Disks

We present the first collisionless realization of two-dimensional axisymmetric black hole accretion consistent with a persistent magnetically arrested disk state. The accretion flow, consisting of an ion-electron disk plasma combined with magnetospheric pair creation effects, is simulated using first-principles general-relativistic particle-in-cell methods. The simulation is evolved over significant dynamical timescales during which a quasisteady accretion state is reached with several magnetic flux eruption cycles. We include a realistic treatment of inverse Compton scattering and pair production, which allows for studying the interaction between the collisionless accretion flow and pair-loaded jet. Our findings indicate that magnetic flux eruptions associated with equatorial magnetic reconnection within the black hole magnetosphere and the formation of spark gaps are locations of maximal particle acceleration. Flux eruptions, starting near the central black hole, can trigger Kelvin-Helmholtz-like vortices at the jet-disk interface that facilitate efficient mixing between disk and jet plasma in this region. Transient periods of increased pair production following magnetic flux eruptions and reconnection events are responsible for most of the highly accelerated particles.

Accretion disk & black-hole plasma↗