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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Integrated protonic ceramic electrochemical cell for sustainable energy economy using water-energy nexus framework

Reliance on fossil fuels will continue for the next decades even though there are global pushes away from it to mitigate the overarching climate challenge, most especially by its highest consumers and availability. While there is a hastening global shift away from fossil fuel, integrating its assets into this technology helps limit the risk and future losses of stranded assets and reduce the cost of investment in the new technologies. Moreover, the generation of electricity from intermittent renewable sources like solar and wind has witnessed a significant surge in recent years, leading to a pressing demand for practical energy storage systems. Electrical energy storage is anticipated to play a pivotal role in the future global energy system, facilitating load-leveling operations to support the greater integration of renewable and distributed generation. Reversible electrochemical cells (RECs) offer a promising option for addressing the fossil fuel assets integration and energy storage challenges through the interconversion between electrical and chemical energy and concurrent utilizing carbon emission. In their electrolysis mode, the RECs convert electricity into durable, storable, and portable valuable chemical fuels such as syngas and methane. Conversely, the produced chemical fuels can be used as reactants in the fuel cell mode to generate electricity on demand with minimal (hydrocarbons) or zero when H2 or NH3 is used emissions. However, a challenging goal for this type of technology remains to achieve optimal operation and high roundtrip efficiencies, which has hindered the deployment of previous electrochemical cells. This dissertation demonstrates how reversible protonic ceramic electrochemical cells (RePCECs) can be integrated with fossil fuel power plants and renewable energy sources as a potential energy storage system. In this work, integrated RePCEC systems are designed and examined using computational modeling at scales to determine appropriate system configurations and operating conditions that achieve high roundtrip efficiencies. Cell level design of the PCEC is the first approach, several cells are assembled for the stack level model that is integrated into combined cycle powerplant and solar photovoltaic for the system level model. After critical literature review, this answered the operational and integration research questions proposed to address these challenges. The designed systems perform two functions, utilizing captured CO2 and storing renewable energy through co-electrolysis of steam and CO2. The co-electrolysis reaction involves endothermic water electrolysis and exothermic methanation reaction. To enhance high roundtrip efficiency, there is a need for thermal balance and management in the electrolysis mode. This involves operating the RePCEC stack under conditions that favor methane production to balance out heat needed by water electrolysis, it crucial for the RePCEC system operation. Methanation is enhanced by low temperatures. Leveraging on fabricated BCZYYb-electrolyte RePCEC, the cell model designed revealed that the optimum temperature for methane production is 450℃ at atmospheric pressure. Thus, to achieve optimum system performance, operating in the temperature range 450-525℃ is recommended at the given configuration, combining between the optimum temperature for methane production and temperature for the optimum stack roundtrip efficiency. Configuration with carbon capture system and purge stream is the optimum configuration from the seven conceptualized and evaluated. The modeling outcomes include a thermodynamic examination of integrated RePCEC systems, calibration of cell and stack level models, and steady-state simulation and integration into a 600MW combined cycle power plant retrofitted with two two-stage membrane-based carbon capture system and a wastewater treatment and recovery unit. At 100% powerplant loading, the stack and system roundtrip efficiencies are 72% and 51.37% respectively. Adding a purge stream for produced hydrogen at the system downstream improves the efficiencies to 74 and 55.48% respectively. At atmospheric pressure and 525℃, the system model suggests that a stack roundtrip of 82% is achievable, and overall system efficiency increases by reducing the energy consumption by the balance of plant components for steam generation and storage. Economic analysis of the process gives levelized cost of methane as $2.24/MMBtu lower than the conventional production route that range between $3.46/MMBtu and $9.85/MMBtu. The lifecycle analysis shows that the global warming potential for the production of methane and hydrogen from the RePCEC system is 3.83 kg CO2 eq which is lower than 9.35 kg CO2 eq emission during steam methane reforming for hydrogen production. This answered both the environmental and economic concerns in the raised research question. The proposed RePCEC configuration and analysis carried out in this dissertation to address the surge in renewable energy and challenges with PCEC technology hold significant potential in achieving large-scale energy storage while simultaneously reducing carbon emissions. These advancements, coupled with suitable governmental policies and incentive programs, have the potential to economically disrupt the natural gas industries by using RePCEC systems for methane production, thereby making them more favorable for eventual implementation and commercialization.

25 ENERGY STORAGE↗
DOE OSTI2023

Communication-Constrained Robust Control and Learning of Grid-Connected

The electric grid of things (EGoT) promises great potential for innovative grid services by tapping into vast load flexibility. However, the unique characteristics of EGoT, being a part of the cyber-physical electric power system, present both opportunities and challenges, especially concerning supply-demand balancing, stability, and communication constraints. Traditionally, centralized control was employed to ensure balance and stability in power systems. However, with the massive influx of EGoT devices, new strategies are needed to efficiently coordinate and control these distributed devices for optimal grid operations. While some studies have explored efficiency and economic models, there remains a gap in ensuring reliability under everyday operations and resilience during extreme conditions. Addressing this gap, this project develops the technology for an Energy Service Interface (ESI) that includes novel pricing, control, learning, and distributed optimization algorithms, which will enable utilities to recruit EGoT assets for crucial grid services such as load flexibility, voltage regulation, and situation-awareness. The key novelty of the proposed technology is the careful distribution of learning and control functions across utility and EGoT asset owners such that provably efficient and resilient grid operations are attained while respecting communication and information-exchange constraints. Specifically, the project team develops machine-learning enhanced load modeling methods to allow EGoT asset owners to learn their load capability and flexibility, and develops pricing-based and decentralized learning-based control so that asset owners can coordinate to meet system-wide demand-supply balance and reliability goals. For extreme situations involving high-impact, low-probability catastrophic events (termed the “black-sky” events), the team also develops (1) a “Feeder-Operating Center-on-a-Laptop” (FOCAL) software that can assist utility personnel in leveraging EGoT assets to accelerate the service recovery of damaged feeders, and (2) distributed optimization algorithms that can coordinate the operation points of EGoT devices under severe communication constraints. The proposed technology has been extensively tested and evaluated through simulations and on a testbed. In summary, as we transition into a more interconnected and digital power grid era, our project’s findings and developments offer a pivotal step toward guaranteeing both efficiency and resilience in the face of both everyday operations and rare “black-sky” events.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Process Control and Energy Efficiency

We review the impact of control systems and strategies on the energy efficiency of chemical processes. We show that, in many ways, good control performance is a necessary but not sufficient condition for energy efficiency. The direct effect of process control on energy efficiency is manyfold: Reducing output variability allows for operating chemical plants closer to their limits, where the energy/economic optima typically lie. Further, good control enables novel, transient operating strategies, such as conversion smoothing and demand response. Indirectly, control systems are key to the implementation and operation of more energy-efficient plant designs, as dictated by the process integration and intensification paradigms. Our conclusions are supported with references to numerous examples from the literature.

42 ENGINEERING↗
DOE OSTI2020

Experimental testing of particle attrition in CSP systems at high temperature

An alternate and sustainable form of energy is CSP systems, which capture and store the sun’s energy in the form of heat. Increasing the operational temperature of CSP systems will increase the efficiency of electricity production while operating at temperatures exceeding 700 degrees Celsius also creates novel operational problems. One approach for high-temperature CSP systems is to utilize solid particles as the primary heat transfer medium. As particles flow through this system, the movement of particles creates erosion in the forms of impact, abrasion, and attrition erosion. In the real world, while all three forms of erosion will occur simultaneously, it is imperative to understand the individual effect of each erosion over the lifetime of the powerplant. Besides material erosion and long-term durability concerns, thermal cycling of the particles could also introduce changes in particle thermal performance due to alterations in particle morphology. Current research on the issue of erosion has been limited to industrial applications and does not necessarily coincide with the operating conditions in CSP systems. We focus on attrition erosion resulting from particle-to-wall and particle-to-particle interactions. Research has shown that besides material hardness affecting how fast particles break down, attrition erosion increased as the size of the particles increased due to a higher chance of collision between the particles. Particle attrition is relevant to the CSP community as it may result in material loss, change the system's thermal performance, and generation of fines which could pose an environmental hazard. In this work, we focus on developing a test set up that can isolate and measure particle attrition when subjected to conditions relevant to Gen3 CSP systems.

14 SOLAR ENERGY↗
DOE OSTI2025

Equation-Free Coarse Control of Distributed Parameter Systems via Local Neural Operators

The control of high-dimensional distributed parameter systems (DPS) remains a challenge when explicit coarse-grained equations are unavailable. Classical equation-free (EF) approaches rely on fine-scale simulators treated as black-box timesteppers. However, repeated simulations for steady-state computation, linearization, and control design are often computationally prohibitive, or the microscopic timestepper may not even be available, leaving us with data as the only resource. We propose a data-driven alternative that uses local neural operators, trained on spatiotemporal microscopic/mesoscopic data, to obtain efficient short-time solution operators. These surrogates are employed within Krylov subspace methods to compute coarse steady and unsteady-states, while also providing Jacobian information in a matrix-free manner. Krylov-Arnoldi iterations then approximate the dominant eigenspectrum, yielding reduced models that capture the open-loop slow dynamics without explicit Jacobian assembly. Both discrete-time Linear Quadratic Regulator (dLQR) and pole-placement (PP) controllers are based on this reduced system and lifted back to the full nonlinear dynamics, thereby closing the feedback loop.

93B52, 93C20, 47N70, 65J15, 65M32, 68T07, 68T20, 6↗
DOE OSTI2023

Fan and Pump Efficiency in Modelica based on the Euler Number

Simulation programs often assume constant hydraulic efficiency for fan or pump models when performance curves are unavailable. This is inaccurate because the hydraulic efficiency varies with the operation condition. It therefore consistently underestimates the power draw at off-design conditions at which the hydraulic efficiency drops. Use of a modified Euler number allows computing the hydraulic efficiency and shaft power with limited data. Others showed the validity of the modified Euler number for fan efficiency calculations. We show that it is also applicable for pumps, and present its implementation in Modelica for a fan or pump model. Here, the only input required from the user is one data point at which the hydraulic efficiency is at its maximum. The reported method is applicable regardless of the type, size, or operational region of the fan or pump. Across a sample of eighteen sets of pump data and seven sets of fan data, the errors of the computed power from interpolated data were within 15% for the range of 20% - 70% of maximum flow rate and 40% - 90% of maximum pressure rise, excluding outliers.

component model↗
DOE OSTI2022

Metal-Supported Solid Oxide Fuel Cells for Natural Gas

Solid oxide fuel cells (SOFCs) are high temperature energy conversion devices that produce electricity efficiently and sustainably. High operating temperatures required for SOFC function endow these devices with many advantages including fuel flexibility and high conversion efficiencies. Fuel flexibility, in particular, distinguishes SOFCs from other types of fuel cells that operate with clean H 2 only, and enables operation with natural gas (NG). LBNL has developed metal supported SOFCs (MS-SOFCs) with unique symmetrical architecture that offer several advantages over state of the art (SoA) ceramic SOFC models including inexpensive materials, rapid start up capability, increased mechanical strength and high tolerance to thermal cycling, Fig 1. These advantages make LBNL MS-SOFCs uniquely suited for fast start-up, portable, and mobile backup generator applications. Specifically motivating this work was a scenario of backup generators fueled by pipeline natural gas delivered from SoCalGas in the event of an electric grid shut down. This project investigates the feasibility of using MS-SOFCs with pre-reformed natural gas as well as direct on-cell reforming of simulated natural gas both with and without sulfur.

03 NATURAL GAS↗
DOE OSTI2025

Optimal Control Strategy With Efficiency and Reliability Improvement for Offshore DC Microgrids

Offshore microgrids, due to their remote location and lack of external energy support, face significant challenges in wide-range load operation and maintenance. Consequently, efficiency and reliability are critical concerns for converters in offshore dc microgrids. This article presents an optimal control strategy aimed at enhancing both efficiency and reliability. A normalized nonlinear relationship between power loss and thermal stress of a paralleled converter is first established. Based on this, a dual-objective optimization function with an active weight function as well as a system overall performance index is established. The active weight function dynamically adjusts the control priority based on converter efficiency and switching device thermal stress. Then, the optimal power-sharing strategy is derived by the Lagrange multiplier method with the proposed optimal function. Additionally, to accommodate a wide load range, an optimal selection strategy for operating converter combinations is proposed, requiring only low-bandwidth communication. Experiment verification is given to validate the effectiveness of the proposed control strategy. The experiment results demonstrate that the proposed control strategy can improve the overall performance of offshore microgrids by optimizing efficiency and reliability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

An Online Joint Optimization–Estimation Architecture for Distribution Networks

Here in this article, we propose an optimal joint optimization-estimation architecture for distribution networks, which jointly solves the optimal power flow (OPF) problem and static state estimation (SE) problem through an online gradient-based feedback algorithm. The main objective is to enable a fast and timely interaction between the OPF decisions and state estimators with limited sensor measurements. First, convergence and optimality of the proposed algorithm are analytically established. Then, the proposed gradient-based algorithm is modified by introducing statistical information of the inherent estimation and linearization errors for an improved and robust performance of the online OPF decisions. Overall, the proposed method eliminates the traditional separation of operation and monitoring, where optimization and estimation usually operate at distinct layers and different time scales. Hence, it enables a computationally affordable, efficient, and robust online operational framework for distribution networks under time-varying settings.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Production of Cf-252 and other transplutonium isotopes at Oak Ridge National Laboratory

In 1957 Glenn T. Seaborg conceived and advocated for the construction of the High Flux Isotope Reactor (HFIR) and the Transuranium Processing Plant (since then renamed the Radiochemical Engineering Development Center, or REDC) at Oak Ridge National Laboratory. There, heavily shielded hot cells, glove boxes, and laboratories allow recovery of transuranium elements produced in substantial quantities. Seaborg’s vision of HFIR and REDC producing milligram quantities of berkelium, californium, and einsteinium has been fulfilled beginning in 1966 through May 2019 with 78 production campaigns yielding a cumulative totals of 1.2 g of 249 Bk, 10.2 g of 252 Cf, 39 mg of 253 Es, and 15 pg of 257 Fm. Notably, 252 Cf is a neutron source used in many industrial applications including oil exploration; process control systems for the cement industry, coal analysis, and power production; sources to start nuclear reactors and perform nondestructive materials analyses; homeland security and national defense detection devices; and medical research. Isotopes made available through transplutonium production at HFIR/REDC have enabled scientists to study the nuclear properties and reactions, chemical properties, optical properties, and solid-state properties of transplutonium elements. Long-lived isotopes have served as targets in heavy ion accelerators to produce heavier elements leading to the discovery of 104 Rf, 105 Db, 106 Sg, 113 Nh, 114 Fl, 115 Mc, 116 Lv, 117 Ts, and 118 Og. This paper reviews the evolution of the processing flowsheets to produce, separate, and purify transplutonium isotopes, which have evolved over 50 years of operation at HFIR and REDC, and summarizes directions of future work to improve the efficiency of the production operations.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

Conducting thermal energy to the membrane/water interface for the enhanced desalination of hypersaline brines using membrane distillation

Membrane distillation (MD) is a membrane-based thermal desalination process capable of treating hypersaline brines. Standard MD systems rely on preheating the feed to drive the desalination process. However, relying on the feed to carry thermal energy is limited by a decline of the thermal driving force as the water moves across the membrane, and temperature polarization. In contrast, supplying heat directly into the feed channel, either through the membrane or other channel surfaces, has the potential of minimizing temperature polarization, increasing single-pass water recoveries, and decreasing the number of heat exchangers in the system. When solar thermal energy can be utilized, particularly if the solar heat is optimally delivered to enhance water evaporation and process performance, MD processes can potentially be improved in terms of energy efficiency, environmental sustainability, or operating costs. Here we describe an MD process using layered composite membranes that include a high-thermal-conductivity layer for supplying heat directly to the membrane-water interface and the flow channel. Here, the MD system showed stable performance with water flux up to 9 L/m 2 /hr, and salt rejection >99.9% over hours of desalinating hypersaline feed (100 g/L NaCl). In addition to bench-scale system, we developed a computational fluid dynamics model that successfully described the transport phenomena in the system.

42 ENGINEERING↗
DOE OSTI2024

Comparative study of machine learning techniques for post-combustion carbon capture systems

Computational analysis of countercurrent flows in packed absorption columns, often used in solvent-based post-combustion carbon capture systems (CCSs), is challenging. Typically, computational fluid dynamics (CFD) approaches are used to simulate the interactions between a solvent, gas, and column's packing geometry while accounting for the thermodynamics, kinetics, heat, and mass transfer effects of the absorption process. These simulations can then be used explain a column's hydrodynamic characteristics and evaluate its CO 2 -capture efficiency. However, these approaches are computationally expensive, making it difficult to evaluate numerous designs and operating conditions to improve efficiency at industrial scales. In this work, we comprehensively explore the application of statistical ML methods, convolutional neural networks (CNNs), and graph neural networks (GNNs) to aid and accelerate the scale-up and design optimization of solvent-based post-combustion CCSs. We apply these methods to CFD datasets of countercurrent flows in absorption columns with structured packings characterized by several geometric parameters. We train models to use these parameters, inlet velocity conditions, and other model-specific representations of the column to estimate key determinants of CO 2 -capture efficiency without having to simulate additional CFD datasets. We also evaluate the impact of different input types on the accuracy and generalizability of each model. We discuss the strengths and limitations of each approach to further elucidate the role of CNNs, GNNs, and other machine learning approaches for CO 2 -capture property prediction and design optimization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Recent Changes to U.S. Coal Plant Operations and Current Compensation Practices

Over the last decade, the U.S. electric power sector has gone through one of the most dramatic changes in its existence. The combination of low natural gas prices as a result of the shale gas revolution and significant reduction in construction and operating costs for renewable resources, in part due to federal tax credits such as the production tax credit and investment tax credit mainly benefitting wind and solar, respectively, has resulted in a significant shift away from coal-fired generation, and instead towards natural gas and renewable generation. Furthermore, the operating profile of existing coal-fired electric generating units has changed significantly. As new natural gas combined cycle plants have become increasingly more efficient and cheaper to operate than older existing coal-fired power plants, coal units continue to lose baseload generation share and more frequently operate as load-following, or cycling, resources. These trends are of particular importance to state public utility commissions. Functioning as economic regulators, commissions oversee investments in a reliable, efficient system while balancing emissions goals, customer demands, and other policy objectives. Changes to coal plant operations as a result of increased competition from other fuel sources may have a bearing on system reliability and economics, and therefore constitute an important area for commissions to monitor.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Theory-guided Design of Refractory MPEAs for High-Temperature, Harsh-Service Conditions

Focusing on novel materials for harsh-service environments (oxidation, corrosion, and load), durability, higher operational temperature, and direct impact on power-generation technology, the goal was, using a quantitative theory-guided design approach integrated with high-throughput synthesis and characterization for validation, to accelerate by 50% the development of high temperature, refractory-based multi-principal element alloys (MPEAs) materials platforms (with co-designed oxidation-resistant, self-healing coatings) that demonstrate phase-stable operation with desired properties at 10-20% higher temperatures in oxidizing environments over state-ofthe- art systems (like Ni-stainless steels, i.e., Haynes 282 – used in critical gas turbine applications, and refractory TZM, i.e., molybdenum-rich Mo99.4-Ti0.5-Zr0.08-C0.02 in wt%). Notably, refractory MPEAs may achieve higher operational temperatures with superior creep strength and offer 50-100% larger thermal conductivity (140-170 W/m-K) than Ni-based systems, potentially eliminating active cooling, reducing system weight, complexity, and cost. Achieving this goal addresses DOE material challenges in energy generation and efficiency (higher-temperature operation), reduced lifecycle energy (waste-heat recovery), and accelerating materials development in support of AMO’s Strategic Plan and QTR goals. DOE’s Advanced Manufacturing Office (AMO) goal of reducing industrial energy intensity and GHG emissions is addressed by development of coated refractory MPEAs exhibiting 20%+ higher operational temperature (direct increase of Carnot efficiency), higher melting temperatures (better phase stability), superior creep strength (better lifetime with creep rate lower by factor of 10), larger (50-100%) thermal conductivity (improved cooling without active cooling), reduced complexity (single-phase alloys), self-healing coating (reliable oxidation-resistance) and cost.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Temporal Characterization of Tritium Smear Activities

Tritium collection efficiency varies as a function of smear media. The use of porous smear materials leads to an increase in the measured tritium activity as a function of time when the measurement is performed with liquid scintillation counters. Operational inclusion of the efficiency differences and the time dependence of the tritium smear activity is necessary to preclude inadvertently releasing materials or areas. Thomas Jefferson National Laboratory Radiological Control Department identified a contaminated stainless steel containment vessel that previously housed a target containing more than 37 TBq of tritium. The item was systematically sectioned and surveyed to compare three smear types: water-wetted cotton swabs, water-wetted paper smears, and ethanol-wetted Styrofoam wipes (NUC-Wipes™). The total activity of each section was determined using repeated decontamination. The time dependence of the measured activity was also studied. The measured activity of both paper smears and cotton swabs showed significant time dependence. The cotton swabs also showed significantly reduced collection efficiency. Given the widespread use of both of these media in routine contamination surveys, site operational limits were derived using fitted curves for time dependence and average efficiency results. In conclusion, the use of these more restrictive limits allows for rapid measurement of tritium smears while ensuring regulatory compliance.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Color‐Stable, All‐Phosphorescent White Organic Light Emitting Diodes Using the Polariton‐Enhanced Purcell Effect

Abstract The short operational lifetimes of high efficiency phosphorescent organic blue light emitting devices (PHOLEDs) has limited their use in displays and lighting. Previously, this problem has been avoided by using less efficient fluorescent blue devices in separately biased red, green, and blue emissive elements to achieve stable full color emission. However, the operational lifetime of blue phosphorescent OLEDs has been significantly improved through the utilization of the plasmon‐exciton‐polariton‐enhanced (PEP) Purcell effect. Here, a white emitting PHOLED comprising stacked red, green, and blue elements is demonstrated that exploits PEPs to extend the operational lifetime of the blue element such that all emissive layers degrade at the same rate. The device features white light emission with an external quantum efficiency of 19.1 ± 0.4%, luminous power efficiency of 13.3 ± 0.3 lm W −1 at a luminance of 1000 cd m −2 when measured over 4π solid angle, with a color rendering index of 76 unchanged throughout the device aging to 70% of its initial luminance, T 70 . A 2.9 times enhancement in the operational lifetime of the Purcell‐enhanced device is achieved to yield T 70 = 2900 ± 100 h for an initial luminance of 1000 cd m −2 , compared to devices lacking this enhancement with T 70 = 1000 ± 100 h.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Communication breakdown: Energy efficiency recommendations to address the disconnect between building operators and occupants

As technology advances, progressive building performance goals are met with ease and occupant behavior plays an increasingly significant role in preventing building operators from achieving those goals. However, removing occupants from participating in building control and operation is counterintuitive to the purpose of building operation. Occupant-centric control (OCC) has been suggested as a means of incorporating the occupant while simultaneously reducing the negative impact their behavior can have on building performance. As a result, operators are now tasked with incorporating OCC into their daily operation. The relationship between building occupants and operators is a critical component to OCC, and balancing occupant comfort and building performance. In this paper, we present findings from an international qualitative study of building operators with a focus on the operator and occupant relationship. This paper identifies the role operators play in OCC, how these relationships develop, and how these relationships impact building operation through two key research questions: What factors influence the quality of relationships between occupants and operators? How can the relationships between operators and occupants be improved? Subsequently, these questions revealed this relationship becomes strained when building performance is prioritized over comfort, occupants are ignored or uneducated, and feedback is negative or sparse. In short: there is a disconnection between operators and occupants. Here we propose several solutions including modifying job requirements to prioritize occupant comfort, educating occupants to make autonomous decisions that are not detrimental to operation, and creating effective communication channels for instances where operator intervention is required.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

MIND-MAC: Multi-Level In-memory Quasi Non-Destructive MAC Operation in Compact 2T-nC FeRAM for Efficient DNN Accelerator

We present MIND-MAC, a compact 2T-nC FeRAM architecture that performs multi-level, quasi-non-destructive in-memory multiply–accumulate (MAC) for deep neural networks. By exploiting voltage-controlled partial domain switching in MFM capacitors and read-transistor amplification, the cell stores multi-bit weights and gates bit-serial inputs to produce an accumulated current on shared lines. We combine TCAD-extracted parasitics with experimentally calibrated ferroelectric models in SPICE to validate device-/circuit-level behavior, and validate multi-level sensing and QNRO with measurements on a fabricated 2T-3C test vehicle. An analytical system model maps MIND-MAC to a 6-GB main-memory in-memory compute (IMC) architecture and benchmarks VGG13 inference in 61.08 ms at 964.99 mJ. Results indicate high density, reduced rewrite overhead, and energy efficiency, positioning 2T-nC FeRAM as a promising IMC candidate for next-generation AI hardware.

36 MATERIALS SCIENCE↗