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At least 73 records · Page 4

Reversible Methane Electrochemical Reactors as Efficient Energy Storage for Fossil Power

The overall objective of the project was to conduct a comprehensive Research & Development (R&D) program to demonstrate the suitability and future advancement and integration of reversible methane protonic ceramic electrochemical reactors (PCERs) as an efficient Energy Storage System (ESS) with fossil fuel power plants. Fundamental process and system models are developed to conduct a preliminary conceptual study and investigate the power plant system integration requirements, performance requirements, and technical and non-technical gaps for eventual implementation at system level. Technology maturation requirements is also investigated through identifying the critical technical elements and networking with industrial technology developers and end-users.

08 HYDROGEN

AOI [1] Advanced Manufacturing of Ceramic Anchors with Embedded Sensors for Process and Health Monitoring of Coal Boilers

Researchers at West Virginia University (WVU) developed methods to fabricate and test ceramic anchors with an embedded sensor technology for monitoring the health and processing conditions within pulverized coal (PC) and fluidized-bed combustion (FBC) boiler systems. The technology included the development of advanced manufacturing processes for 2D/3D printing electroceramic (conductive ceramic) sensor designs within the ceramic anchor microstructure during the manufacturing process. This advanced manufacturing process would allow for the precise control of local microstructure and composition in order to engineer layer-by-layer any protective and electrically active materials within the refractory anchor. This 3D printing technology would permit the rapid and controlled design of the refractory microstructure and embedded sensor design throughout the volume of the ceramic anchor. The work also included a method to interconnect the sensors to boiler shell through the anchor clamp, where the sensor signals will be processed by low-power electronics and transmitted wirelessly to a central processing hub. The end-goal of the program was to produce a ceramic anchor sensor system which would be ready for implementation within a coal boiler, and/or other similar refractory liner systems (such as that in the glass and metal manufacturing areas). The project objectives were to: 1) Define the chemical and microstructural stability, in addition to the electrical properties, of oxide and non-oxide ceramic composites to be embedded within the ceramic anchor compositions that may operate up to 1400ºC; 2) Develop and implement the 2D/3D printing technology to pattern and control the microstructure of the ceramic anchor and embedded sensor circuits; 3) Develop an interconnect technology which will permit easy installation of the ceramic anchors and signal collection at the boiler shell; 4) Develop low power analog electronics and wireless communication hardware to efficiently collect the sensor signal at each processing unit and transmit data to a central hub for data analysis; 5) Demonstrate the smart ceramic anchor system for temperature and liner fracture within a high-temperature processing unit, such as a boiler furnace or glass melting furnace floor/wall liner.

20 FOSSIL-FUELED POWER PLANTS

Thermodynamic modeling of countercurrent chemical looping reverse water gas shift process for redox material screening

The reverse water gas shift (RWGS) reaction is a key pathway for CO 2 utilization, particularly within Power-to-X process chains aimed at sustainable fuel and chemical production. Countercurrent chemical looping (CL-RWGS) using non-stoichiometric oxides can overcome equilibrium limitations of conventional RWGS reactors, enabling significantly higher CO 2 conversions. However, modeling the limiting performance of such systems is challenging due to their multiphase nature and coupled spatial and temporal variation in chemical composition. In this work, we present a discretized batch equilibrium model that simulates CL-RWGS reactors as a series of localized equilibrium exchanges between gas and solid elements. The model is numerically stable, computationally efficient, and free of kinetic source terms, making it well-suited for parametric studies and system-level integration. It is validated against established convection–diffusion models and shown to predict reasonable upper bounds on experimental results. Application of the model to a range of oxygen carrier materials identifies cerium–zirconium solid solutions, particularly Ce 0.80 Zr 0.20 O 2 , as a promising class offering superior oxygen storage characteristics compared to state-of-the-art La 0.6 Sr 0.4 FeO 3 . This framework provides a robust platform for materials screening, reactor sizing, and performance optimization in chemical looping systems. The model implementation is available as open-source software to support further research and development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Control Strategies and Validation in the Hybrid Optimization and Performance Platform (HOPP)

The Hybrid Optimization and Performance Platform (HOPP) is a tool that simulates hybrid power plants in various configurations, and also calculates the financial feasibility of these plants. This report outlines an overview of HOPP and the energy storage dispatch strategies available. It then presents three case studies which demonstrate different applications of HOPP. The first case looks at the profitability of hybrid power plants in different locations in the USA. The second case examines the availability of hybrid power plants to provide energy reliability services. The third case presents a plant that produces both hydrogen and electricity, and demonstrates a dispatch strategy that chooses the most profitable energy vector based on price signals. The next section shows the validation of HOPP on operational data, using data from both unit-scale and utility-scale power plants. This validation process demonstrated that HOPP can simulate the power output of both wind and solar PV plants at both scales with comparable fidelity to an existing commercial software tool. Finally, HOPP is applied in a field test which applies an optimal dispatch strategy to a physical battery in a unit-scale hybrid plant at NREL. HOPP's optimal dispatch strategy, applied in a real-world setting, improved this hybrid plant's ability to meet a load signal while minimizing operational costs.

14 SOLAR ENERGY

Advancing Additive Manufacturing Through Artificial Intelligence–Powered, High-Throughput, Nondestructive Characterization and Process Optimization

This Cooperative Research and Development Agreement (CRADA) between Oak Ridge National Laboratory (ORNL) and ZEISS Industrial Metrology has demonstrated the transformative potential of artificial intelligence (AI)-enabled x-ray computed tomography (XCT) to accelerate the qualification and certification of additively manufactured (AM) parts. At the core of this effort is Simurgh, an AI-powered XCT reconstruction framework jointly advanced by ORNL and ZEISS that integrates computer-aided design (CAD) models, physics-based simulations, and deep learning to overcome the long-standing challenges of metal artifact correction, long scan durations, and limited flaw detectability in dense and geometrically complex components. Simurgh enables high-throughput, high-quality 3D reconstruction from sparse and fast scans, which reduces XCT acquisition times by more than an order of magnitude and simultaneously improves defect detection limits by up to fourfold compared with industry-standard approaches. This capability reduces scan costs by more than 50%, lowers labor overhead, and makes XCT characterization economically viable for routine industrial use. By enabling reliable flaw detection in minutes rather than hours, Simurgh facilitates real-time feedback loops for process parameter optimization, which was highlighted in a recent npj Computational Materials (a Nature journal) issue. In the published study, more than 100 alloy coupons were characterized within a single day. This work represents a tenfold acceleration in the development of novel AM alloys and processes compared with conventional workflows. The ZEISS collaboration has also demonstrated the scalability of Simurgh to diverse application domains, including aerospace, nuclear, automotive, and biomedical components; in these applications, ensuring structural integrity is paramount. By drastically reducing barriers to XCT adoption, this partnership has laid the foundation for digital twins and data-driven certification pipelines and directly addressed bottlenecks in qualifying new materials and designs. Together, ORNL and ZEISS have shown that Simurgh advances the state of the art in nondestructive evaluation and aligns with the broader mission of enabling Industry 4.0 manufacturing ecosystems, in which intelligent, cost-effective, rapid quality assurance is integral to accelerating innovation and ensuring safety in critical applications.

36 MATERIALS SCIENCE

Advancing Additive Manufacturing Through Artificial Intelligence–Powered, High-Throughput, Nondestructive Characterization and Process Optimization

This Cooperative Research and Development Agreement (CRADA) between Oak Ridge National Laboratory (ORNL) and ZEISS Industrial Metrology has demonstrated the transformative potential of artificial intelligence (AI)-enabled x-ray computed tomography (XCT) to accelerate the qualification and certification of additively manufactured (AM) parts. At the core of this effort is Simurgh, an AI-powered XCT reconstruction framework jointly advanced by ORNL and ZEISS that integrates computer-aided design (CAD) models, physics-based simulations, and deep learning to overcome the long-standing challenges of metal artifact correction, long scan durations, and limited flaw detectability in dense and geometrically complex components. Simurgh enables high-throughput, high-quality 3D reconstruction from sparse and fast scans, which reduces XCT acquisition times by more than an order of magnitude and simultaneously improves defect detection limits by up to fourfold compared with industry-standard approaches. This capability reduces scan costs by more than 50%, lowers labor overhead, and makes XCT characterization economically viable for routine industrial use. By enabling reliable flaw detection in minutes rather than hours, Simurgh facilitates real-time feedback loops for process parameter optimization, which was highlighted in a recent npj Computational Materials (a Nature journal) issue. In the published study, more than 100 alloy coupons were characterized within a single day. This work represents a tenfold acceleration in the development of novel AM alloys and processes compared with conventional workflows. The ZEISS collaboration has also demonstrated the scalability of Simurgh to diverse application domains, including aerospace, nuclear, automotive, and biomedical components; in these applications, ensuring structural integrity is paramount. By drastically reducing barriers to XCT adoption, this partnership has laid the foundation for digital twins and data-driven certification pipelines and directly addressed bottlenecks in qualifying new materials and designs. Together, ORNL and ZEISS have shown that Simurgh advances the state of the art in nondestructive evaluation and aligns with the broader mission of enabling Industry 4.0 manufacturing ecosystems, in which intelligent, cost-effective, rapid quality assurance is integral to accelerating innovation and ensuring safety in critical applications.

36 MATERIALS SCIENCE

FARM supervisory capabilities for thermal energy storage

The FARM (Feasible Actuator Range Modifier) module is a component of the RAVEN-based FORCE framework for the analysis of Integrated Energy Systems (IES). FARM aids HERON in the solution of the power dispatch problem by evaluating feasible set-point signals to be issued to the control systems of the different IES unit components. Set-points need to satisfy limits on both production variables (i.e., the variables to be optimized such as the electrical power, etc.) and process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.). To enforce all these limits, a two-stage approach is adopted. First, the power dispatcher algorithm in HERON module estimates set-points that meet the constraints on the production variables, e.g., power levels and power ramp rate limits. These constraints are called explicit constraints. Then, if necessary, FARM adjusts these set-points to ensure the respect of the limits on the process variables of interest, given the knowledge of the system dynamics acquired through machine learning algorithms. These constraints are called implicit constraints. From this standpoint, FARM constitutes a bridge between the HERON power dispatcher that adopts a simplified description of the IES unit (low-resolution physics) and the HYBRID high-fidelity models (high-resolution physics). In this report, an overview of the major capabilities of the latest release of FARM is provided, along with a summary of the tool demonstration campaign conducted at the Dynamic Energy Technology and Integration Laboratory (DETAIL) facility. These results assess the performance of the control system architecture embedding FARM both as a Validator of the HERON power dispatcher and as a real time Supervisory control scheme. Additionally, the report outlines the areas that FARM might benefit from, along with proposed solutions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS

DeSelenator: A Se-Removal Process for Environmental Decontamination of Wastewaters from Coal-Burning Power Plants

Selenium may become a toxic contaminant of freshwater systems when released into the environment through industrial wastewaters from mining, coal-burning power plants, or oil refining. Efficient and cost-effective Se-removal technologies are therefore necessary to reduce Se concentrations in these wastewaters to below the regulatory discharge limits. In this study, we have demonstrated an effective process that removes Se, mostly as selenate anions, from wastewaters generated by coal-burning power plants. This process, dubbed DeSelenator, leverages the high concentration of sulfate relative to selenate in the wastewater and the propensity of these oxyanions to cocrystallize with benzene-bis-iminoguanidinium (BBIG) cations into extremely insoluble salts (on par with BaSO 4 ). The SO 4 2− /SeO 4 2− cocrystallization with BBIG removes over 90% of S and Se from the wastewater. Following removal of the precipitate by filtration, the filtrate is passed over an anion-exchange resin that further reduces selenium concentration to 5 ppb, the EPA’s regulatory limit for freshwater systems. Finally, the effluent is passed over an activated carbon column, which removes 99.8% of the residual BBIG ligand remaining after crystallization, allowing for the safe discharge of the treated water into the environment. The Se-removal process was first optimized in the lab at the bench scale and then tested in the field at the Tennessee Valley Authority’s Bull Run coal-burning power plant. A technoeconomic assessment found the cost of water treatment with DeSelenator is on par with that of the active biological method, which is currently considered a state-of-the-art Se-removal technology.

anions

Uncertainty Estimation and Anomaly Detection in Chiral Effective Field Theory Studies of Key Nuclear Electroweak Processes

Chiral effective field theory (χEFT) is a powerful tool for studying electroweak processes in nuclei. I discuss χEFT calculations of three key nuclear electroweak processes: primordial deuterium production, proton-proton fusion, and magnetic dipole excitations of 48 Ca. Further, this article showcases χEFT’s ability to quantify theory uncertainties at the appropriate level of rigor for addressing the different precision demands of these three processes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

Alternatives to MARVEL Power Conversion – Comparison of Stirling Engine Thermal Efficiency and Design to other Power Conversion Cycles

The Microreactor Applications, Research, Validation, and Evaluation (MARVEL) Reactor is a small liquid-metal thermal reactor that will be built at the Idaho National Laboratory to demonstrate design and operating processes for microreactors, microgrid integration, and process heat applications. Power conversion in the MARVEL design is provided by Stirling engines, which have disadvantages in nuclear environments. Compared to Stirling engine performance, some alternative power cycles can increase power production when coupled to a liquid-metal thermal reactor In this paper, the thermal efficiency of MARVEL’s power production with Stirling engines is compared to the thermal efficiency of power production with MARVEL and alternative power cycles. Those cycles include a superheated Rankine cycle, open and closed Brayton cycles, and a supercritical carbon dioxide cycle. All cycles (except the Stirling engines) were modeled with an intermediate helium loop to meet MARVEL’s principal design criteria. All models are simple designs with conservative assumptions for consistent comparison. Detailed optimization will depend largely on reactor location and application, and the relative merit of each cycle is discussed for different environmental conditions. The study informs significant early decisions on power cycle design and economic

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS

Flux-Switching Machine Based All-Electric Power Train for Future Aircraft

This research investigates a flux-switching motor with superconducting and cryogenically cooled windings, aimed at achieving exceptionally high power densities. In addition to the motor’s topology and superconducting windings, it was found that power density could be further enhanced by incorporating superconducting shields on the rotor at the interpole locations. The resulting publications and patented technology outline the design process. A motor power density of 64 kW/kg—including housing materials—was achieved for a 1 MW design, surpassing the performance of existing motors. An electronic drive was also developed, achieving a power density of 47 kW/kg. This includes the mechanical structure of the drivetrain, for which a detailed CAD model was created, resulting in an overall drivetrain power density of 27 kW/kg.

33 ADVANCED PROPULSION SYSTEMS

Alternatives to MARVEL Power Conversion -- Comparison of Stirling Engine Thermal Efficiency and Design to Other Power Conversion Cycles

PRESENTATION for CONFERENCE PAPER: The Microreactor Applications, Research, Validation, and Evaluation (MARVEL) Reactor is a small liquid-metal thermal reactor that will be built at the Idaho National Laboratory to demonstrate design and operating processes for microreactors, microgrid integration, and process heat applications. Power conversion in the MARVEL design is provided by Stirling engines, which have disadvantages in nuclear environments. Compared to Stirling engine performance, some alternative power cycles can increase power production when coupled to a liquid-metal thermal reactor. In this paper, the thermal efficiency of MARVEL’s power production with Stirling engines is compared to the thermal efficiency of power production with MARVEL and alternative power cycles. Those cycles include a superheated Rankine cycle, open and closed Brayton cycles, and a supercritical carbon dioxide cycle. All cycles (except the Stirling engines) were modeled with an intermediate helium loop to meet MARVEL’s principal design criteria. All models are simple designs with conservative assumptions for consistent comparison. Detailed optimization will depend largely on reactor location and application, and the relative merit of each cycle is discussed for different environmental conditions. The study informs significant early decisions on power cycle design and economics for deployment of advanced microreactors as they move from theory and concept to execution.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS

Human-Centered and Explainable Artificial Intelligence in Nuclear Operations

Nuclear power plants in the United States are critical to the nation’s energy security, accounting for 20% of all electricity produced for the power grid. As energy needs grow, 100 gigawatts of additional nuclear power will be necessary by 2050, more than double the current capacity. Realizing this target requires cutting-edge technology like artificial intelligence (AI) and machine learning (ML) that can bring about significant increases in the level of automation. Human-centered AI (HCAI) is a combination of human-centered design (human factors, human-in-the-loop, etc.) with AI/ML to help produce an efficient and reliable system with full consideration for human engagement. This paper provides a comprehensive and novel discussion of HCAI considerations in nuclear power, introducing unique applications for the existing fleet as well as new advanced reactor designs. We include real-life use cases of AI applications to work management processes at nuclear power sites and highlight lessons learned for HCAI.

Hall, Anna

Fluor Solvent Evaluation and Testing New Scope: Techno-economic Assessment of EEMPA Solvent for CO 2 Separations from Natural Gas Combined Cycle Power Plant

In this project, a techno-economic analysis (TEA) and sensitivity studies were conducted to assess the PNNL’s leading water-lean CO 2 capture solvent, EEMPA, for capture CO 2 from a natural gas combined cycle (NGCC) power plant at different levels of capture rate. Process models for the NGCC power plant, integrated with EEMPA carbon capture processes, were developed in Aspen Plus V14 using the most up-to-date property package for EEMPA-H 2 O-CO 2 system. The TEA evaluated EEMPA carbon capture process at normal capture rates (90%, 95% and 97%) against Case B32B (Cansolv) described in NETL Rev4a baseline report, and at higher capture rates aimed at achieving zero or negative emissions from the power plant (400 ppmv, 200 ppmv, and 100 ppmv CO 2 in exhaust gas), compared to typical Direct Air Capture (DAC) technologies. A manuscript was drafted for peer-reviewed publication. The results suggested that the carbon capture cost reaches a minimum of $\$$53.7/tonne CO 2 at 90% capture rate. Compared to Cansolv, one of the industrial benchmarks, EEMPA demonstrates 2-4% cost savings at capture rates up to 95%, but minimal savings at higher capture rate. The water lean-solvent system proves economically attractive for achieving moderate negative emissions (about 200 ppmv CO 2 in exhaust gas, and equivalent to 50% CO 2 removal from air) for NGCC flue gas, with marginal capture costs comparable to direct air capture (DAC) technologies. A sensitivity analysis results reveal that its economic advantage, unaffected by EEMPA price due to low solvent loss and degradation rate. However, the marginal carbon capture cost exceeds $\$$1,000/tonne CO 2 when transitioning from moderate to extreme negative emissions (100 ppmv CO 2 in exhaust gas), suggesting that water-lean solvents may not be economically competitive with other DAC technologies for removing more than 75% CO 2 from air. In addition, initial connection was established with Technology Center Mongstad (TCM) for a potential pilot testing proposal. However, detailed modeling and proposal preparation was not conducted due to the delay of non-disclosure agreement.

20 FOSSIL-FUELED POWER PLANTS

EV Charging Infrastructure Energization An Overview of Approaches for Simplifying and Accelerating Timelines to Processing EV Charging Load Service Requests

The United States has seen significant growth in electric vehicle (EV) adoption, leading to increased demand for EV charging infrastructure. Over the past decade, EV charging infrastructure site developers, site hosts, and electric distribution utilities have navigated the process to integrate chargers onto the electric grid. Site developers and site hosts have raised the alarm that the integration process for high-powered EV charging projects does not meet the needs of the EV market for timeliness or cost. High-powered charging stations typically require a load service request or an agreement with the local utility to connect to the grid. The process of energizing a new high-powered charging site can be complex and time-consuming, often taking up to 2 years. This timeline is the result of current utility energization processes having been designed for construction projects that take longer to build (i.e., buildings). The specific challenges stem from various factors, including compartmentalization in application processes, the integration of EV charging process approvals with other distributed energy resources (DERs), and the need to ensure grid reliability. The energization process needs to evolve to meet the growing demand for high-powered EV charging. This white paper compiles information gathered through various conversations with key stakeholders, including utilities, utility regulators, EV charging operators, site developers, and authorities having jurisdiction (AHJ) as well as through an extensive literature review. This document identifies the challenges and provides potential solutions to streamline the process of connecting EV charging infrastructure to the power grid in the United States, serving as a starting point for future conversations around these solutions. The solutions noted in this white paper require collaborative efforts among utilities, regulators, and EV charging infrastructure developers to streamline the grid connection process for EV charging infrastructure. They are broadly organized into four areas: 1. Increase data access and transparency: Develop automated load service request tools, integrate hosting capacity and load service request analyses, incorporate EV adoption forecasts, and provide transparency on the processing queue. 2. Improve energization processes and timing: Create fast-track options based on prescreening criteria, provide flexibility or phased approvals in the load service request/interconnection process, build internal knowledge within utilities about EV charging technologies, and provide standardized workforce training. 3. Promote economic efficiency: Right size distribution components to accurately reflect the load requirements of EV charging infrastructure, make proactive investments in grid infrastructure based on EV adoption forecasts and growth projections, and consider energy equity and environmental justice factors such as equitable access to EV charging when planning infrastructure. 4. Improve grid reliability and resilience: Use load management/power control systems (PCS) at EV charging stations, adopt and implement harmonized standards for communication protocols and information models between the EV charging and grid control infrastructure, and address cybersecurity considerations by implementing robust security measures and standards for EV charging infrastructure—with particular emphasis on clarifying the security requirements for the interface to the grid. The objective of the solutions proposed in this white paper is to accelerate the timeline and decrease costs associated with connecting EV charging infrastructure to the grid. Electric utilities, utility regulators, EV charging infrastructure developers, and site hosts will first need to understand which solutions are available in their service territory, and if warranted, which combination of solutions would support their specific needs. Through the successful implementations of solutions at scale detailed here, industry will demonstrate a new and innovative ecosystem where timely deployment and energization of EV charging infrastructure with greater grid resiliency and reliability is a reality.

24 POWER TRANSMISSION AND DISTRIBUTION

Process Design and Techno-Economic Analysis of the Modular Staged Pressurized Oxy-Combustion (SPOC) Power Plant for Biomass

This work describes the process design and techno-economic analysis (TEA) of the modular SPOC power plant for biomass firing and coal-biomass co-firing. Two Rankine cycles were considered: a supercritical steam cycle (242 bar, 593°C, 593°C) with 550 MWe net output and a subcritical cycle (166 bar, 566°C, 566°C) with 200 MWe net output. For both cases, 95% carbon capture was modeled, and hybrid poplar biomass was chosen to generate carbon-negative power. In addition, the supercritical 500 MWe case included a 25% biomass co-firing (carbon neutral) case. For both cycles, a 100% Powder River Basin coal firing case was used for comparison purposes. In the SPOC process, oxygen is produced via a cryogenic air separation unit (ASU) and the heat generated from the compression of air is integrated into the steam cycle and utilized for boiler feed water pre-heating. Unique to the SPOC process, the boilers are pressurized and arranged in a series-parallel configuration, with minimized flue gas recirculation. The flue gas is cooled and scrubbed in the direct-contact cooler (DCC) column, and the moisture in the flue gas is condensed, leaving the bottom of the DCC at a sufficiently high temperature such that it can be used for boiler feed water pre-heating, improving plant thermal efficiency. Following drying and purification, CO2 in the flue gas is at the purity required for storage or utilization. The performance data were obtained from process modelling via Aspen Plus®. The stream data from Aspen Plus® were used as an input for the AACE Class 5 cost study. Ultimately, the capital costs, Levelized Cost of Electricity (LCOE), and cost of CO2 captured and avoided were obtained. The HHV efficiency of the carbon negative 550 MWe supercritical SPOC case (34.8%) was clearly above those reported by NETL for the BECCS baseline cases of supercritical pulverized coal with capture (B12B, 31.5%) and the 49% biomass co-firing case with capture (PA3, 29.2%). The HHV efficiency of the carbon-negative subcritical plant is also higher than the subcritical baseline PC plant with capture (case B11B.95) presented by NETL (32% vs 29.7%). The LCOE for the SPOC 100% biomass case was similar to the LCOE for the BECCS 49% biomass with carbon capture case ($147/MWh), and the SPOC carbon neutral case LCOE was lower ($110/MWh) than the cost for the NETL baseline SC coal firing case with 90% carbon capture ($114/MWh).

Magalhaes, Duarte

Integrated Radio Frequency and Ultrasonics with Conventional Processes for Efficient Water Removal in Pulp and Paper and Other Biomaterial Applications

Conventional drying processes used in the pulp and paper industry primarily involve lengthy, surface based, multi-cylinder conductive and convective drying with low thermal efficiencies and often use some fossil-based energy. Integration of cross cutting, electrically-powered, volumetric drying process intensification technologies based on Radio Frequency (RF) and acoustics (Ultrasonics) (US) will directly impart energy into the biomaterials resulting in improved energy efficiency and throughput. Integration of RFUS-based drying technology is expected to enable U.S. manufacturing industry to reduce capital and operating costs, energy consumption, and carbon emissions while increasing energy efficiency and throughput, improving product quality and sustainability, and helping preserve U.S. manufacturing jobs. The hybrid drying approach incorporates directed radio frequency (RF) and ultrasonic (US) energy with conventional conduction, diffusion and convective heat and mass transfer overcoming the limitations of the conventional drying processes and that meets/exceeds the minimum goals. We have shown the effective removal of free and bound water in the biomaterials by leveraging the synergies of RF and US technologies integrated with conventional manufacturing processes.

42 ENGINEERING

Towards Net-Zero: Nuclear-Assisted Waste Biomass to Liquid Fuel in Eastern Idaho

A nuclear assisted carbon negative hybrid energy process that enables production of synthetic bio-crude oil and biochar from Eastern Idaho waste biomass is proposed. The process integrates nuclear powered electricity with high temperature steam electrolysis and biomass hydropyrolysis. The bio-crude oil is of sufficient composition and blended with traditional crude oil at a refinery. Hydrogen from the electrolyzer is pressurized and inserted into the pyrolyzer. Non condensable gases generated in the hydropyrolysis process are burned with oxygen from the electrolyzer to produce heat for the electrolyzer, biomass dryer, and pyrolyzer. The biochar is returned to the soil via fertilizer application and remains there for thousands of years. Since the total process uses nuclear generated electricity, the carbon in the biochar is ultimately sequestered from the atmosphere, thus making the process carbon negative. Using Eastern Idaho wheat or barley straw, this hybrid energy process has the potential to provide an alternative petroleum source. Two options exist for the system design: 1) send electricity from the nuclear plant and straw to a chemical processing plant to produce the bio-crude and biochar, 2) construct the biomass processing facility near the nuclear plant to allow use of nuclear-generated process heat to drive the chemical. Process model description and results are discussed. The process is sized to produce gasoline and diesel at the rate that the INL uses every day for fleet usage.

09 BIOMASS FUELS