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DOE OSTI2024

Neural Networks for Prediction of Complex Chemistry in Water Treatment Process Optimization

Water chemistry plays a critical role in the design and operation of water treatment processes. Detailed chemistry modeling tools use a combination of advanced thermodynamic models and extensive databases to predict phase equilibria and reaction phenomena. The complexity and formulation of these models preclude their direct integration in equation-oriented modeling platforms, making it difficult to use their capabilities for rigorous water treatment process optimization. Neural networks (NN) can provide a pathway for integrating the predictive capability of chemistry software into equation-oriented models and enable optimization of complex water treatment processes across a broad range of conditions and process designs. Herein, we assess how NN architecture and training data impact their accuracy and use in equation-oriented water treatment models. We generate training data using PhreeqC software and determine how data generation and sample size impact the accuracy of trained NNs. The effect of NN architecture on optimization is evaluated by optimizing hypothetical black-box desalination processes using a range of feed compositions from USGS brackish water data set, tracking the number of successful optimizations, and testing the impact of initial guess on the final solution. Our results clearly demonstrate that data generation and architecture impact NN accuracy and viability for use in equation-oriented optimization problems.

Dudchenko, Alexander V↗

DOE OSTI2025

Acetate as a Platform for Carbon-Negative Production of Renewable Fuels and Chemicals (Final Technical Report)

This project was an industrial-academic collaboration between experts at the University of Wisconsin-Madison, the University of Kentucky, and LanzaTech, a world leader in the use of gas fermentation to sustainably produce fuels and chemicals. The project developed technologies to create an integrated process for converting carbon dioxide and renewable hydrogen into molecules that can be blended with liquid transportation fuels or used in an array of chemical applications. The project was motivated by the Program Objectives of eliminating carbon dioxide release in the production of chemicals by integrating the unique and efficient capabilities of two microorganisms into a single process. The first microbe, an acetogen, produces acetate from carbon dioxide and hydrogen while the second microbe upgrades acetate from acetogen fermentation permeates to higher-value chemical products. The carbon dioxide released in the upgrading process is recycled internally to produce more acetate. As such, the process can be designed to operate with zero carbon dioxide release and net positive carbon dioxide capture. The process has the potential to provide an alternative paradigm to the current bioeconomy – one in which acetate is the primary energy carrier instead of sugars. Our process by-passes photosynthesis and the barriers created by biomass as primary chemical feedstock. As such, the process can be scaled to meet existing sources of carbon dioxide emissions and located anywhere renewable hydrogen can be provided. Our work developed microorganisms with optimized metabolism for producing acetate and other microorganisms with improved conversion of acetate to dodecanol and dodecyl-acetate. We developed synthetic biology tools for a promising non-model bacterium that could enhance metabolic engineering efforts to convert acetate to chemical products. We conducted protein engineering studies to improve the activity of key enzymes involved in our metabolic pathways. We conducted a full technoeconomic analysis that set technical targets for each strain to meet economic goals. We identified key technical barriers in our process and proposed strategies to overcome them.

09 BIOMASS FUELS↗

DOE OSTI2024

Reaction engineering: a lost (and found) art for a decarbonized future [Slides]

The heart (or, perhaps more appropriately, the stomach) of any chemical manufacturing process is the reactor, where chemical and physical transformations occur under precisely controlled conditions. For traditional industrial processes, the design, optimization and operation of chemical reactors are extremely well developed, drawing upon the principles of chemistry, physics, calculus and economics. However, new-age process concepts proposing to use "exotic" reactors and/or sustainable inputs (e.g., renewable carbon resources, electrons, photons, plasma) face a dearth of well documented reaction engineering principles & design practices that eclipses their rapid adoption. This presentation features two vignettes of (the return of) reaction engineering in sustainable process science, first in the valorization of lignin from biomass, and second in understanding multimodal catalyst deactivation in industrial-scale reactors within the Catofin process for propane dehydrogenation. Overall, this seminar seeks to educate student researchers on practical means of advancing laboratory reactor technologies towards commercial practice.

09 BIOMASS FUELS↗

DOE OSTI2022

High Yield, Economical and Environmentally Benign Production of Rare Earth Elements from Coal Ash [Abstract]

Fly ash stored in landfills and ponds across the United States is an attractive, abundant domestic resource for the cost-effective recovery of rare earth elements (REE) and other critical minerals (CM). Physical Sciences Inc. (PSI) and its team members, Winner Water Services (WWS) and University of Kentucky/Center for Applied Energy Research (UK/CAER) successfully executed a multiphase program that developed and demonstrated pilot plant operations for cost-effective and environmentally-friendly production of rare earth element oxide (REO) concentrates, and the critical minerals scandium and aluminum (in the forms of salts or oxide products). We constructed and operated a sub-scale (0.5 kg/day) micropilot facility to demonstrate the key physical and chemical processing operations, predict yields, and troubleshoot process bottlenecks. The project team then designed, constructed and operated two decoupled pilot plant operations: (1) an operational pilot plant for physical separation processes with a capacity of 0.4 metric tons per day (tpd) where we optimized processes to produce selected ash fractions as the feedstock for chemical processing as well as valuable byproducts such as cement substitute, cenospheres, magnetic ash and secondary fuel carbon, and (2) an operational pilot plant for chemical processing with a capacity of 0.5 tpd that developed optimized processes for the production of: (a) REO concentrates, (b) critical minerals recovery (Sc, Al), and (c) beneficiated ash as valuable byproduct suitable for cement applications.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2025

Process and environmental safety of thermochemical conversion of biomass

Biomass presents a promising opportunity for converting waste into valuable energy, fuels, and chemicals through various thermochemical processes, including hydrothermal carbonization, hydrothermal liquefaction, pyrolysis, gasification, and combustion. However, these processes operate under extreme conditions, introducing significant safety hazards that necessitate meticulous management to prevent accidents. This review discusses potential hazards, risk mitigation strategies, and safety management practices, emphasizing the importance of integrated safety measures into the design and operation of these processes. It also highlights the critical need for robust safety engineering and environmental management strategies tailored to each thermo-chemical process. As these processes transition from laboratory to industrial scale, there is an imperative to develop a clear and concise pathway for emerging industries to achieve regulatory compliance, achieve safety certification, and enable effective stewardship of potential fugitive emissions. By addressing safety and environmental concerns, stakeholders can optimize economic benefits, rural development, and achieve sustained domestic energy generation benefits offered by biomass conversion technologies. Further research on plant design optimization, operational safety, environmental evaluation standardization, and innovative waste management solutions will support the safe and effective scaling of these technologies, ultimately contributing to sustainable management and resource recovery.

09 - BIOMASS FUELS↗

DOE OSTI2022

Building Initial Dynamic System Models for Digital Twins of the Cryogenic Moderator System at the ORNL Spallation Neutron Source

This work describes the initial development of dynamic system models of the cryogenic moderator system (CMS) of the Spallation Neutron Source (SNS) at ORNL as a part of the ORNL LDRD funded project Building TRANSFORM to Accelerate Digital Twin Applications for Nuclear Systems, LOIS 10563. The goal of the work is to start the dynamic system modeling effort with the end goal of using them for real-time applications as digital twins. The CMS is a cryogenic liquid hydrogen flow loop that provides moderation of the neutrons that are generated by the SNS. For optimal neutron production, the CMS needs to maintain a steady and controlled density of cryogenic hydrogen in the moderator section thus requiring precise temperature and pressure control. Due to the varied time scales and system characteristics, control of the system is complex, and diagnostics are also difficult. Difficulty in accessing the flow loop during operations, limited instrumentation and unknown design details of the equipment combine to make the case for having sophisticated digital twin models of the system. Operationally the CMS also provides a strong use case for digital twins due to the constant need of optimization and for troubleshooting/diagnostics. The large amount of data collected which are freely available for using in building the model and verifying and validating the model also makes it a great candidate for a proof-of-concept for digital twins. The project extends ORNL's capacity of development and implementation of the open-source dynamic system modeling tool TRANSFORM for engineering design and digital twin/real-time applications. Specific system configuration data for the CMS have been gathered and an initial dynamic model was created in the TRANSFORM library using Dymola as the solution platform. Models of increasing complexity are created to demonstrate the need for a multi-layered approach in digital twin modeling depending on the scale and phenomena being focused on. The dynamic modeling is shown to bring the dynamic operational aspects to the design process for systems as well as serve as a digital twin to the hardware and allow for models to be tuned and compared against real time operational data. These aims should help to push forward strategic goals of application of digital twins and increase the impact of ORNL systems modeling capabilities with TRANSFORM/Modelica for various advanced energy systems.

42 ENGINEERING↗

DOE OSTI2024

Optimal Design and Operation of a Solvent-Sorbent Hybrid Capture Process for Minimizing the Cost of High Capture

High capture can cause a significant increase in energy penalty if the appropriate technology/technologies are not utilized. The optimal technology for bulk capture is not necessarily the optimal technology for polishing capture (i.e., high extent of capture from the flue gas with very low partial pressure of CO2). This work investigates the use of MEA for bulk capture with the polishing capture being accomplished by a functionalized metal organic framework (MOF).

Kasturi, Pooja↗

DOE OSTI2025

A DATA EFFICIENT SPARSE MODELING FRAMEWORK FOR POWER ESTIMATION IN WATER TREATMENT SENSING OPERATIONS

With increasing freshwater scarcity, advanced process design mechanisms such as Closed-Circuit Reverse Osmosis (CCRO) and Digital/Physical Twin systems are gaining traction in water treatment and reuse operations. While digital and physical twin models enable improved system insight and control, their development is often expensive and computationally intensive, requiring large volumes of synthetic or experimental data to characterize underlying process dynamics. This work introduces a sparse surrogate modeling framework to estimate power consumption from measured flow and pressure variables, along with their nonlinear polynomial and interaction expansions. To ensure model reliability and reduce overfitting, a two-stage pipeline is proposed. First, a dynamic data filtering algorithm is employed to remove uninformative observations and transient operational states. Second, a sparse penalized regression technique is applied to select a minimal set of parsimonious features. The proposed model achieves high sparsity, retaining only 7 out of 34 candidate features (≈79.41% sparsity) while delivering a root mean square error (RMSE) of 0.072 on the test dataset.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗

DOE OSTI2026

Designing a Robust MEA-Based Post-Combustion Carbon Capture Process with Capture Rate Guarantees

This work presents an application of the nonlinear two-stage robust optimization solver PyROS to the model-based design and operation of a monoethanolamine scrubbing process for CO2 capture under epistemic uncertainty. Through this application, risk-averse process designs are successfully obtained for CO2 capture targets ranging from 90% to over 99%. In particular, the risk-averse solutions for CO2 capture targets of up to 98% are shown to be only marginally more expensive than their nominally optimal counterparts. Thus, the results demonstrate the utility of recently developed nonlinear robust optimization approaches for the solution of large-scale chemical process models under uncertainty.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2024

Modeling Analysis of Ball-Milling Process for Battery-Electrode Synthesis

The mechanical alloying process is a promising method for synthesizing electrode materials for batteries owing to its benefits such as the ability to produce nanostructured, high-performing electrode alloys, no adverse effects on the solid electrolyte for solid-state batteries, stable production of thick electrodes, simple processing steps, and low processing costs. It is gaining intensive attention in the battery industry as one of the best methods to replace the conventional wet-slurry-solvent method, and its application is rapidly increasing these days. However, the operation is currently conducted purely based on trial-and-error methods without fully utilizing the features of its functions. Here, this may be attributed to a lack of understanding of the effect of operating parameters on the alloying process and final products. Surprisingly, there is a scarcity of the literature conducting fundamental research to comprehend the underlying physics of the entire mechanical alloying process, resulting in a significant knowledge gap. To address this knowledge gap, extensive research was conducted. The existing literature on mechanical alloying was reviewed to comprehend the current state of understanding and to discuss the direction for future research. Mathematical expressions were developed to create physics-based models capable of capturing the entire mechanical alloying process, including milling kinetics and defect-enhanced phase evolution. These methods were then applied to investigate the impact of operating parameters such as milling frequency, initial mole ratio of the alloyed materials, density of grinding balls, and energy required for the powders to become amorphous (i.e., the amorphization energy threshold). This research aimed not only to comprehend the direct effects of these operating parameters but also to unveil the physics underlying the ball-milling process. The results of our study can serve as crucial information for the battery industry in designing or operating the ball-milling process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Component innovations for lower cost mechanical vapor compression

Despite significant capital and operating costs, mechanical vapor compression (MVC) remains the preferred technology for challenging brine concentration applications. Here, this work seeks to assess the dependence of MVC costs on feedwater salinity and desired water recovery and to quantify the value of improved component performance or reduced component costs for reducing the levelized cost of water (LCOW) of MVC. We built a cost optimization model coupling thermophysical, heat and mass transfer, and technoeconomic models to optimize and identify low cost MVC system designs as a function of feedwater salinity and water recovery. The LCOW ranges over 3.6 to 6.1 $\$$/m 3 for seawater feed salinities of 25–150 g/kg and water recoveries of 40–80 %. We then perform sensitivity analysis on parameter inputs to isolate irreducible costs and determine high value component innovation targets. The LCOW was most sensitive to evaporator material costs and performance, including the overall heat transfer coefficient in the evaporator. Process and material innovations such as polymer-composite evaporator tubes that reduce evaporator costs by 25 % without reducing heat transfer performance by more than 10 % would result in MVC cost reductions of 8 %.

42 ENGINEERING↗

DOE OSTI2025

Energy efficiency in industrial drying: A hybrid ultrasonic system with a novel dynamic optimization framework

Drying processes are among the most energy-consuming operations in industrial and manufacturing settings, demanding strategic selection, design, and control for enhanced efficiency. Advancing drying technologies is critical for improving sustainability, lowering energy use, reducing carbon emissions, and minimizing waste. This study explores two innovative strategies aimed at transforming drying processes into sustainable, low-carbon systems by reducing energy consumption, minimizing waste, and maintaining a strong emphasis on preserving product quality. The first strategy showcases a sub-pilot scale hybrid ultrasonic-convective dryer for agrifood products. This technology, powered by electricity (process electrification), integrates non-thermal ultrasonic dehydration with convective heating and is presented as a sustainable and energy-efficient solution that enhances eco-friendly practices. The second strategy involves introducing and implementing a novel, multiobjective, mixed integer dynamic optimization technique to determine the optimal time-dependent process parameter values for the drying operation. This optimization technique yields operating conditions that are piecewise constant in time aiming to maximize the energy efficiency of the hybrid ultrasonic-convective dryer while ensuring strict adherence to product quality constraints. By adopting the hybrid ultrasonic-convective dryer, a notable 35% improvement in energy efficiency was achieved compared to conventional hot-air drying systems for drying apple slices. The proposed optimization framework further enhanced energy efficiency by nearly 14% over the most efficient process on the identical testbed, under static operating conditions. The reported enhancements have been experimentally validated. Regarding drying time (thereby improving production yield), the developed hybrid ultrasonic-convective dryer demonstrates as much as a 41% reduction in total processing time, which is further optimized by an additional 10% using our proposed optimization framework. The research outcomes have profound implications for the design and operation of drying systems, encompassing crucial aspects such as process electrification, cost-effectiveness, energy savings, time efficiency, product yield, product quality, and process automation.

Dynamic optimization↗

DOE OSTI2023

Operation and Process Control Development for a Pilot-Scale Leaching and Solvent Extraction Circuit Recovering Rare Earth Elements From Coal-Based Sources

The US Department of Energy in 2010 has identified several rare earth elements as critical materials to enable clean technologies. As part of ongoing research in REEs (rare earth elements) recovery from coal sources, the University of Kentucky has designed, developed and is demonstrating a ¼ ton/hour pilot-scale processing plant to produce high-grade REEs from coal sources. Due to the need to control critical variables (e.g. pH, tank level, etc.), process control is required. To ensure adequate process control, a study was conducted on leaching and solvent extraction control to evaluate the potential of achieving low-cost REE recovery in addition to developing a process control PLC system. The overall operational design and utilization of Six Sigma methodologies is discussed. Further, the application of the controls design, both procedural and electronic for the control of process variables such as pH is discussed. Variations in output parameters were quantified as a function of time. Data trends show that the mean process variable was maintained within prescribed limits. Future work for the utilization of data analysis and integration for data-based decision-making will be discussed.

coal, rare earth elements, pilot plant, automation↗

DOE OSTI2026

Adsorption-based direct air capture using hierarchical porous composites prepared via confined-space crystallization

Capturing CO₂ at trace concentration remains a critical challenge in sustainable carbon management via adsorption, as conventional adsorbents suffer from low CO₂ selectivity, poor moisture tolerance, and energy-intensive regeneration requirements. Here, we report a hierarchical Ba²⁺-exchanged silicoaluminophosphate (Ba²⁺-CSAPO-34) composite synthesized via confined-space crystallization within an activated carbon matrix. Comprehensive characterization revealed a confined nucleation mechanism and the successful incorporation of Ba²⁺ active sites within the SAPO-34 framework, achieved via a two-step liquid ion-exchange protocol. The core-shell architecture combines the selective CO₂ binding of Ba²⁺-functionalized SAPO-34 with the hydrophobic protection of the carbon shell. Fixed-bed adsorption tests demonstrated strong CO₂ binding (at 500-2500 ppm), no roll-up, and effective suppression of water affinity, while maintaining high selectivity even at 90% relative humidity. A phenomenological adsorption model, validated against dynamic breakthrough data, accurately predicted dynamic adsorption behavior under real-world operating conditions, enabling rational process design for direct air capture (DAC) and closed-loop life support systems. Furthermore, these results establish Ba²⁺-CSAPO-34 as a scalable, moisture-resistant adsorbent that addresses key limitations in trace CO₂ capture, advancing practical implementation of carbon removal technologies.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2022

Simulating a solar parabolic trough collector plant used for industrial process heat using an optimized operating scheme that utilizes flexible heat integration

This study focuses on the modeling and simulation of a novel design and operation of a solar industrial process heat (SIPH) plant that uses a parabolic trough collector system for generating process heat. The SIPH plant incorporates flexible heat integration (FHI) by having two options for heat sinks as well as a flexible collection temperature for the heat transfer fluid. Leveraging the degrees of freedom created by FHI allows an optimized operating scheme to be created which maximizes the solar heat delivered to the industrial processes. Yearly results for a 27 MW-t plant located in Salt Lake City, UT are simulated for a base case and a case utilizing optimized FHI. For the main process temperature case presented, FHI increases the total solar share by 13.0% and reduces the levelized cost of heat of the SIPH plant by 10.4% relative to the base case. Furthermore, three case study days are presented which highlight how FHI maximizes solar share, specifically during mornings, afternoons, and days with intermittent solar conditions. An environmental analysis is also performed showing that the SIPH plant can reduce harmful emissions by 15.4% for the base case and 17.4% for the FHI case compared to a plant that only utilizes a natural gas furnace for process heat. Overall, the work thoroughly explores an effective operating scheme for a SIPH plant, helping to make it more economical and environmentally beneficial.

14 SOLAR ENERGY↗

DOE OSTI2026

Process Optimization and Real-Time Control of Synergistic Microalgae Cultivation and Wastewater Treatment (Final Technical Report)

The overarching goal of this work was to accelerate the commercialization of high productivity, mixed community microalgal treatment technologies for the synergistic treatment of wastewater and the production of biofuel feedstocks. This project addressed a critical barrier to the financial viability and energy efficiency of algal wastewater treatment: an inability to design and operate high-rate processes that reliably achieve target effluent qualities, areal productivities, and biochemical compositions (lipid, protein, carbohydrate content) despite fluctuations in wastewater composition, weather, and microbial communities. Key outcomes from this work include an optimized and controlled Advanced Biological Nutrient Recovery (ABNR) design as well as a suite of open-source tools that include a calibrated and validated algae process simulator in QSDsan and a novel low-cost, real-time microbial monitoring tool. These tools can be leveraged by other algal cultivation and wastewater treatment technology developers in future work.

09 BIOMASS FUELS↗

DOE OSTI2025

ENVIRONMENTAL DEGRADATION OF HARD AND SOFT MAGNETIC MATERIALS IN GASEOUS AND SUPERCRITICAL CO2 ENVIRONMENTS

It may be beneficial to use hermetic designs for supercritical CO2 (sCO2) cycles machinery as they would eliminate CO2 leakage through shaft end seals. This would reduce CO2 emissions and operating costs for makeup of lost process fluid. Those designs may replace traditional oil-lubricated bearings with actively controlled magnetic bearings operating at high temperatures in the process fluid environment (to reduce the need for active cooling). This paper investigates the material degradation of various types of magnets in CO2. Included are several permanent and soft magnetic materials (Alnico 9C, Alnico 5-7C, and 18-T550 grade SmCo, and Hiperco 50) with or without coatings (nickel plating or C5 coating). The materials were exposed to: (1) flowing gaseous CO2 at 1,022 °F (550 °C) and atmospheric pressure in a furnace and (2) sCO2 at 842 °F (450 °C) and 1,500 psi (103 bar) in an autoclave. The preliminary mass change measured after total exposures of 1,000 hours and 2,000 hours are included.

supercritical CO2, magnetic material↗

DOE OSTI2022

Removal of Bond Sodium from Full-Length Unirradiated Fermi-1 Blanket Elements and Assembly via Melt-Drain-Evaporate Process

Equipment was designed, fabricated, tested, and operated in an inert atmosphere radiological glovebox at Idaho National Laboratory to demonstrate the removal of bond sodium from full-length unirradiated Fermi-1 radial blanket elements and an entire radial blanket assembly using a Melt-Drain-Evaporate process. A series of three runs was performed with individual and multiple radial Fermi-1 blanket elements, and a fourth run was conducted with an entire Fermi-1 radial blanket assembly. After each run, the depleted uranium alloy slugs in every element slid out of its cladding, mechanically exhibiting the effectual absence of bond sodium. Quantitative and further qualitative analyses of the treated Fermi-1 material revealed the substantive, if not complete, absence of sodium metal in blanket element components. Indeed, entire columns of depleted uranium alloy slugs and associated cladding from select treated elements were separately contacted with water to react with residual sodium metal on the element surfaces, forming hydrogen gas. Samples of the resultant gas were analyzed to quantify the hydrogen concentration, which correlated to a residual sodium metal content for the treated element. Accordingly, no detectable sodium metal (<7 µg) was found on the surfaces of multiple depleted uranium alloy slugs after removal from its cladding. Detectable sodium metal, ranging from 14 to 30 µg, was found on the surfaces of one separated column of slugs and two separated full-length cladding segments. Each element originally contained ~25 g of bond sodium, resulting in quantitative sodium metal removal efficiencies of =99.9998%. The remaining separated uranium alloy slugs and cladding segments from the four runs were piece-wise immersed in alcohol while videorecording possible gas bubble formation as an additional qualitative analysis for residual sodium metal on treated surfaces, which identified the predominant absence of sodium reactivity on the balance of treated Fermi-1 blanket material. The results of this demonstration substantiate a path forward for treatment and disposal of 34 metric tons heavy metal of irradiated sodium-bonded Fermi-1 blanket material currently stored at Idaho National Laboratory.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗