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At least 37 records · Page 2

Technical, Economic, Energetic, and Environmental Evaluation of Pretreatment Strategies for Scaling Control in Brackish Water Desalination Brine Treatment

Effective pretreatment is essential for achieving long-term stable operation and high water recovery during the desalination of alternative waters. This study developed a process modeling approach for technical, economic, energetic, and environmental assessments of pretreatment technologies to identify the impacts of each technology treating brackish water desalination brine with high scaling propensity. The model simulations evaluated individual pretreatment technologies, including chemical softening (CS), chemical coagulation (CC), electrocoagulation (EC), and ion exchange (IX). In addition, combinations of these pretreatment technologies aiming at the effective reduction of key scaling constituents such as hardness and silica were investigated. The three evaluation parameters in this assessment consist of levelized cost of water (LCOW, $/m 3 ), specific energy consumption and cumulative energy demand (SEC|CED, kWh/m 3 ), and carbon dioxide emissions (CO 2 , kg CO 2-eq /m 3 ). The case study evaluated in this work was the desalination brine from the Kay Bailey Hutchison Desalination Plant (KBHDP) with a total dissolved solids (TDS) concentration of 11,000 mg/L and rich in hardness and silica. The evaluation of individual pretreatment units from the highest to lowest LCOW, SEC|CED, and CO 2 emissions in the KBHDP brine was IX > CS > EC > CC, CS > IX > EC > CC, and CC > CS > EC > IX, respectively. In the case of pretreatment combinations for the KBHDP, the EC + IX treatment combination was shown to be the best in terms of the LCOW and CO 2 emissions. The modeling and evaluation of these pretreatment units provide valuable guidance on the selection of cost-effective, energy-efficient, and environmentally sustainable pretreatment technologies tailored to desalination brine applications for minimal- or zero-liquid discharge.

14 SOLAR ENERGY↗

Closed-loop pressure retarded osmosis draw solutions and their regeneration processes: A review

Pressure-Retarded Osmosis (PRO) is an osmotic process that has been used to harvest energy from salinity gradients using a semi permeable membrane. A comparison between open-loop PRO (OLPRO) and closed-loop PRO (CLPRO) was made regarding their performance and costs. In CLPRO, where the diluted draw solution is re-concentrated in the regeneration system to be reutilized in the process, has recently received an intensive focus as the most viable configuration for a standalone power plant. The choice of the PRO draw solution in CLPRO is crucial to garner a high osmotic pressure as the key for the feasibility of the process. Here, in this review, the draw solutions are critically evaluated in the literature in terms of energy output as well as the method of regeneration used to recirculate them. A set of practical criteria has been suggested to appraise the adequacy of the solution for CLPRO application. It was concluded that NH 3 – CO 2 theoretically can produce 170 W/m 2 of power density. Inorganic draw solutes such as NaCl can generate high power density up to 87 W/m 2 . Organic draw solutes with their remarkably low reverse salt flux (RSF) have promising potential for future application in PRO. Similarly, the regeneration systems of the diluted draw solutions have also been reviewed and discussed. How the energy consumption of the regeneration process affects the feasibility of CLPRO is explained. For the specific case of osmotic heat engines (OHEs), when the energy of the regeneration process is supplied by heat waste, the range of applicability of the heat waste in CLPRO in terms of efficiency is defined and compared to Organic Rankine Cycle (ORC). The results showed that CLPRO has better efficiency than ORC for temperatures T < 80 °C, which makes it a promising process or low-grade heat energy recovery. In addition, a PRO-RO hybrid system coupled with solar power can reduce the net specific energy consumption (SEC) to 0.39 kWh/m 3 . The conditions that regeneration processes should operate under to make PRO viable are discussed in the last section. Overall, the study indicates the key factors for optimizing the performance of CLPRO process.

42 ENGINEERING↗

Water desalination through the dewpoint evaporative system

This paper presents the first numerical analysis of a novel Dew Point Desalination unit (DPD), which utilizes the phenomenon of the evaporative cooling process to minimize energy consumption. The proposed solution is based on a modular structure, which allows it to obtain any required water production capacity. The analyses for various operational parameters and various climatic conditions are based on the numerical simulations conducted using a validated mathematical model. The system performance was described with different factors, including specific energy consumption (SEC) and daily water production rate respected to 1 m^3*s^-1 of passing air stream (DWP). It is shown that the DPD system can operate in almost every climate zone, and the desalinated water production consumes less than 1.5 kWh*m^-3 of electric energy It is noted the best performance of the DPD system is achieved in the semi-arid, desert and subtropical climate zones. In these climate zones, the 2-stage DPD system allows the production of desalinated water with an electric energy consumption SEC lower than 0.5 kWh*m^-3. The additional benefit of the DPD system is its modularity. The presented DPD system stands as a module, that can be multiplied as needed to achieve the desired size of the desalination plant.

Desalination↗

Quantum optimization algorithms: Energetic implications

Since the dawn of quantum computing (QC), theoretical developments like Shor's algorithm proved the conceptual superiority of QC over traditional computing. However, such quantum supremacy claims are difficult to achieve in practice because of the technical challenges of realizing noiseless qubits. In the near future, QC applications will need to rely on noisy quantum devices that offload part of their work to classical devices. One way to achieve this is by using parameterized quantum circuits in optimization or even in machine learning tasks. The energy requirements of quantum algorithms have not yet been studied extensively. Here in this article, we explore several optimization algorithms using both theoretical insights and numerical experiments to understand their impact on energy consumption. Specifically, we highlight why and how algorithms like quantum natural gradient descent, simultaneous perturbation stochastic approximations or circuit learning methods, are at least 2x to 4x more energy efficient than their classical counterparts; why feedback-based quantum optimization is energy-inefficient; and how techniques like Rosalin can improve the energy efficiency of other algorithms by a factor of ≥2 0 x. Finally, we use the NchooseK high-level programming model to run optimization problems on both gate-based quantum computers and quantum annealers. Empirical data indicate that these optimization problems run faster, have better success rates, and consume less energy on quantum annealers than on their gate-based counterparts.

97 MATHEMATICS AND COMPUTING↗

Optimization-based modeling and analysis of brine reflux osmotically assisted reverse osmosis for application toward zero liquid discharge systems

Significant amounts of high-salinity wastewater generated by water-intensive industrial activities such as shale oil and gas production have raised serious environmental concerns in recent years. Existing and emerging desalination technologies offer promise to manage these high salinity wastewater streams while simultaneously producing fresh water that could be diverted for beneficial uses. Osmotically assisted reverse osmosis (OARO) is one such emerging desalination technology capable of handling hypersaline brines and achieving high recoveries. However, rigorous modeling and analysis is needed to evaluate the process performance, energy consumption, and treatment cost of various OARO configurations. Here, this work presents detailed modeling and analysis of brine-reflux OARO (BR-OARO) system and compares it with other commonly discussed configurations, including cascading osmotically mediated reverse osmosis (COMRO), consecutive loop OARO, and split feed counterflow RO, through a cost optimization-based framework. We analyze and compare the treatment costs, membrane area, specific energy consumption, and design parameters of the aforementioned configurations with the ultimate goal of achieving zero liquid discharge (ZLD). The results indicate that the BR-OARO system with treatment cost of 5.1 US $/m 3 of produced water with 10% salinity outperforms other configurations in terms of number of stages needed, treatment cost, membrane area, and energy consumption.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Assessing the Accuracy of Property Model Predictions for Cost Optimization of Desalination Technologies

Accurate modeling of seawater thermophysical and thermodynamic properties is critical for optimizing desalination processes. This study compares three seawater property models, a Reaktoro multicomponent model, the thermophysical seawater properties library from the Massachusetts Institute of Technology, and a simplified sodium chloride model, in the context of levelized cost of water (LCOW) minimization for reverse osmosis (RO) and mechanical vapor compression systems. Process simulations and cost optimizations reveal that although all three models yield comparable LCOW and specific energy consumption (SEC) estimates under baseline conditions, deviations among their predictions increase with salinity. Relative differences in LCOW and SEC reach up to 6% and 8%, respectively. RO results show greater variability due to differences in osmotic pressure predictions, which affect pressure constraints at high recoveries. Computational performance varies substantially; specifically, Reaktoro simulations are up to 28 times slower than empirical models due to their detailed equilibrium calculations. These results suggest that empirical models offer acceptable accuracy for routine desalination process design, while Reaktoro provides advantages in scenarios requiring detailed speciation, such as scaling or pH adjustment studies. These findings underscore the importance of selecting appropriate property models based on the modeling objective of desalination applications and motivate future work integrating thermodynamic rigor with empirical efficiency.

Physical and chemical properties↗

NASA Fixed Wing Project: Green Technologies for Future Aircraft Generation

Commercial aviation relies almost entirely on subsonic fixed wing aircraft to constantly move people and goods from one place to another across the globe. While air travel is an effective means of transportation providing an unmatched combination of speed and range, future subsonic aircraft must improve substantially to meet efficiency and environmental targets.The NASA Fundamental Aeronautics Fixed Wing (FW) Project addresses the comprehensive challenge of enabling revolutionary energy efficiency improvements in subsonic transport aircraft combined with dramatic reductions in harmful emissions and perceived noise to facilitate sustained growth of the air transportation system. Advanced technologies and the development of unconventional aircraft systems offer the potential to achieve these improvements. Multidisciplinary advances are required in aerodynamic efficiency to reduce drag, structural efficiency to reduce aircraft empty weight, and propulsive and thermal efficiency to reduce thrust-specific energy consumption (TSEC) for overall system benefit. Additionally, advances are required to reduce perceived noise without adversely affecting drag, weight, or TSEC, and to reduce harmful emissions without adversely affecting energy efficiency or noise.The paper will highlight the Fixed Wing project vision of revolutionary systems and technologies needed to achieve these challenging goals. Specifically, the primary focus of the FW Project is on the N+3 generation; that is, vehicles that are three generations beyond the current state of the art, requiring mature technology solutions in the 2025-30 timeframe

Subsonic Transports↗

Fixed Wing Project: Technologies for Advanced Air Transports

The NASA Fundamental Aeronautics Fixed Wing (FW) Project addresses the comprehensive challenge of enabling revolutionary energy efficiency improvements in subsonic transport aircraft combined with dramatic reductions in harmful emissions and perceived noise to facilitate sustained growth of the air transportation system. Advanced technologies and the development of unconventional aircraft systems offer the potential to achieve these improvements. Multidisciplinary advances are required in aerodynamic efficiency to reduce drag, structural efficiency to reduce aircraft empty weight, and propulsive and thermal efficiency to reduce thrust-specific energy consumption (TSEC) for overall system benefit. Additionally, advances are required to reduce perceived noise without adversely affecting drag, weight, or TSEC, and to reduce harmful emissions without adversely affecting energy efficiency or noise.The presentation will highlight the Fixed Wing project vision of revolutionary systems and technologies needed to achieve these challenging goals. Specifically, the primary focus of the FW Project is on the N+3 generation; that is, vehicles that are three generations beyond the current state of the art, requiring mature technology solutions in the 2025-30 timeframe.

Advanced Concepts↗

Cost optimization of low-salt-rejection reverse osmosis

Low-salt-rejection reverse osmosis (LSRRO) is an emerging membrane-based desalination technology for concentrating brines with potentially lower energy consumption and cost than thermally driven processes. We assess the technoeconomic performance of LSRRO by using an optimization model that minimizes the levelized cost of water (LCOW). We develop detailed models for the RO module and other equipment using WaterTAP (Water treatment Technoeconomic Assessment Platform), an open-source simulation and optimization software for water treatment. We improve upon previous LSRRO cost optimization studies by optimizing the salt permeability for each stage, which has significant implications for technoeconomic performance. We present the cost-optimal design, operation, and performance for three cases: 35 g/L TDS feed at 70% recovery, 70 g/L at 55%, and 125 g/L at 35%. The cost-optimal LCOW and specific energy consumption (SEC) for these cases are 0.70, 1.89, and 7.41 $/m 3 and 3.9, 8.4, and 30.4 kWh/m 3 , respectively. For each case, we use sensitivity analyses to provide guidance on key factors that impact economic viability. We also present the cost-optimal LCOW and SEC for feed concentrations between 5 and 220 g/L TDS and recoveries between 30 and 90%. So, we compare LSRRO to other high-salinity desalination technologies and find that it may be cost-competitive below feed concentrations of 125 g/L.

54 ENVIRONMENTAL SCIENCES↗

Tuning Local Atomic Structures in MoS 2 Based Catalysts for Electrochemical Nitrate Reduction

In recent years, there has been a substantial surge in the investigation of transition-metal dichalcogenides such as MoS 2 as a promising electrochemical catalyst. Inspired by denitrification enzymes such as nitrate reductase and nitrite reductase, the electrochemical nitrate reduction catalyzed by MoS 2 with varying local atomic structures is reported. Further, it is demonstrated that the hydrothermally synthesized MoS 2 containing sulfur vacancies behaves as promising catalysts for electrochemical denitrification. With copper doping at less than 9% atomic ratio, the selectivity of denitrification to dinitrogen in the products can be effectively improved. X-ray absorption characterizations suggest that two sulfur vacancies are associated with one copper dopant in the MoS 2 skeleton. DFT calculation confirms that copper dopants replace three adjacent Mo atoms to form a trigonal defect-enriched region, introducing an exposed Mo reaction center that coordinates with Cu atom to increase N 2 selectivity. Apart from the higher activity and selectivity, the Cu-doped MoS 2 also demonstrates remarkably improved tolerance toward oxygen poisoning at high oxygen concentration. Finally, Cu-doped MoS 2 based catalysts exhibit very low specific energy consumption during the electrochemical denitrification process, paving the way for potential scale-up operations.

36 MATERIALS SCIENCE↗

Machine learning modeling and model predictive control of a closed-circuit reverse osmosis system

Closed-circuit reverse osmosis (CCRO) offers a flexible and energy-efficient alternative to conventional reverse osmosis by operating in a semi-batch mode that recycles brine, enabling higher recovery rates and reduced specific energy consumption (SEC). However, developing accurate, system-level dynamic models for CCRO remains challenging due to its nonlinear, multi-phase operation and sensitivity to variable feed water conditions. Traditional modeling approaches, such as NARMAX (nonlinear autoregressive moving average with exogenous inputs), often struggle to generalize across varying inlet feed concentrations, necessitating frequent parameter re-estimation and limiting their utility for real-time control applications. To address these limitations, we developed a long short-term memory (LSTM) neural network model trained on an extensive experimental data set from a CCRO pilot plant. The model accepts three inputs, feed flow rate, recirculation flow rate, and initial feed conductivity, and predicts three key outputs: reject conductivity, feed pump power draw, and recirculation pump power draw. We validated the LSTM model against experimental data, demonstrating its ability to distinguish between different feed conductivities and adapt to variable flow rates. Subsequently, we incorporated the LSTM model within a nonlinear model predictive control (MPC) scheme and conducted closed-loop simulations to optimize the integrated SEC (iSEC). In conclusion, the results project up to a 6% reduction in iSEC by using MPC to optimize performance over the entire experiment duration, without requiring any random excitation for data collection or parameter re-estimation.

Desalination↗

De-Risking High-Recovery Brackish Water Desalination via Flow Reversal and Feed Flushing Using Techno-Economic Assessment

Novel desalination technologies have demonstrated enhanced performance and improved financial metrics over existing processes adopted by industry. Establishing quantitative performance targets is essential for achieving financial benefits over the current state of the art. Herein, we demonstrate how WaterTAP, a techno-economic assessment (TEA) tool, can be used to identify minimum performance metrics necessary to achieve financial benefit over using existing processes. This study evaluates the feasibility of increasing water recovery at the Chino Desalter I above 90 % through the addition of a third variable configuration reverse osmosis (VCRO) stage. Sensitivity analyses revealed flow reversal frequency, feed flushing volume (used as a cleaning step), and membrane lifespan are key factors influencing the financial viability of the VCRO process. The TEA analysis demonstrated that the system must achieve a recovery of 84 % and a 1-year membrane lifespan to have a breakeven LCOW, while achieving 90 % recovery can ultimately reduce the LCOW by 16 %. Notably, a trade-off between decreasing frictional losses and increased osmotic pressure across the recovery range, resulted in a stable specific energy consumption across the recovery range, enabling meaningful LCOW reductions without an energy penalty, a key finding that contrasts with conventional RO. This work demonstrates how TEA can guide system design by identifying key performance targets and exploring trade-offs, enabling data-driven decisions to de-risk innovative processes. These findings underscore the importance of leveraging TEA to evaluate scaling mitigation strategies and optimize inland desalination systems for sustainable and cost-effective operation.

14 SOLAR ENERGY↗

Hydrogen Production System Scaling Using a High-Fidelity Simulation-Optimization Framework

Proton exchange membrane (PEM) electrolyzers are widely used for hydrogen production, yet few validated, high-fidelity tools can reliably guide scale-up. Using measured performance from a 50-hour hardware-in-the-loop pilot test, a physics-based, plant-level model of a 1.25 MW PEM electrolyzer and its balance-of-plant (BoP) subsystems is developed and validated. The model couples electrochemistry and thermal/flow submodels and is calibrated against pilot test data via a genetic algorithm (GA) workflow. Validation yields a mean absolute percentage error (APE) of 0.43% for cell voltage and stack power. Two scale-out strategies are then benchmarked under a common 7-day wind-and-photovoltaic (PV) profile: (i) linear duplication of 1.25 MW blocks and (ii) shared-BoP architectures. Sharing BoP between stacks reduces BoP energy by 27% at 10 MW and 34% at 100 MW (vs. linear duplication) and improves system specific energy consumption (SEC) to 52.9 and 52.6 kWh/kg, respectively (from 54.0 kWh/kg with linear duplication). Partial-load studies (25-100% set-point) show that cumulative hydrogen production remains nearly constant down to 50% load because all cases use the same weekly renewable-energy input. Below 50%, the power cap limits how much energy can be used within 168 h, which reduces hydrogen output. The model further indicates that the practical operating optimum lies between 50% and 85% load, where efficiency gains begin to appear without significant loss in hydrogen output. Moreover, the efficiency gains at lower loads are offset by reduced production. The validated framework supports scenario-based engineering trade-off studies for large configurations (10-100 MW) and for operating policies under variable renewables.

08 HYDROGEN↗

Integrated Ion-Exchange Membrane Resin Wafer Assemblies for Aromatic Organic Acid Separations Using Electrodeionization

Aromatic acids, such as p-coumaric acid, are valuable chemical intermediates that are used in the specialty chemical industries because they are precursors to phenylpropanoid compounds. The separation of p-coumaric acid from fermentation broths is a critical step in the biochemical production process and more broadly the circular carbon economy. Electrodeionization (EDI) has been applied toward separations of low-carbon chain acids, but purifying p-coumaric acid has been challenging due to fouling and irreversible binding with ion-exchange membranes and resins. Here, we report a new membrane wafer assembly (MWA) consisting of laminated ion exchange membranes to porous ionomer-binder resin wafers for EDI. The MWAs in an EDI stack showed a 7-fold increase in p-coumaric acid capture while also using 70% less specific energy consumption when benchmarked against state-of-the-art resin wafer EDI modules. The more efficient p-coumaric acid recovery was ascribed to (i) the 38% reduction in interfacial transport resistance between the membrane and resin wafer and (ii) using imidazolium anion exchange membranes and ionomer binders in the MWA. MD simulations revealed enhanced transport rates for p-coumarate in imidazolium ionomers through π–π interactions. As a result, adopting the new MWA significantly reduced the amount of ion-exchange membranes in EDI and may lead to drastic capital cost savings.

42 ENGINEERING↗

Lithium Recovery and Conversion from Wastewater Produced by Recycling of Li-Ion Batteries via Two-Stage Electrodialysis

Electrodialysis (ED) is a membrane separation technique that has been well-established in various applications such as desalination, drinking water production, wastewater treatment, and lithium salt production. A limited number of studies have explored its application in lithium salt production, especially from secondary resources like wastewater. This study investigated a route to recover lithium from wastewater generated from the recycling of end-of-life Li-ion batteries. Two electrodialysis methods, namely standard electrodialysis (ED) and bipolar-membrane electrodialysis (BPED), were combined to concentrate lithium ions and convert them to lithium hydroxide (LiOH), a valuable product that can be fed back into the supply chain for manufacturing Li-ion batteries. Lithium (Li⁺) concentration in recycling wastewater was successfully increased by 58% using ED and converted to LiOH (>96% purity) with a further increase in Li⁺ concentration by 67% using BPED. The Coulombic efficiency of the experiments was 91.0 and 92.2%, with specific energy consumption of 1 and 2.5 kWh/kg, and a production rate of 1.01 and 0.14 kg/h/m 2 for the ED and BPED processes, respectively. In addition, preliminary techno-economic and environmental impact analyses show a significant improvement (GHG emission reduction by 77% and total energy reduction by 53%) by producing LiOH via electrodialysis compared to conventional lithium production via brine extraction. The process was assessed to be beneficial for lithium extraction from secondary resources and to enhance overall battery recycling efforts.

25 ENERGY STORAGE↗

Editors’ Choice—Molten Salt Electrolysis in Chloride Melts for Energy-Efficient Iron Metal Production

This study explores chloride molten salt electrolysis (CMSE) as a promising route for energy-efficient iron metal (Fe) production. Moderate temperature (500 °C) LiCl-KCl molten salts offer excellent thermodynamic stability, high ionic conductivity and diffusivity, and high solubility for FeCl 3 , thereby enabling efficient Fe metal extraction at high electrowinning rates. Here, we demonstrate the two essential steps for converting taconite ore into Fe metal. First, Fe 2 O 3 from taconite pellets was selectively leached in HCl yielding a high-purity FeCl 3 aqueous solution, while the gangue components settled at the bottom. Then, anhydrous FeCl 3 was electrolyzed in a LiCl-KCl eutectic molten salt at 500 °C at high current density (1 A cm −2 ) and at high Coulombic efficiency (>85%). Analysis of the electrowon Fe deposits revealed dendritic structures with purity of >99 wt%, which could be further improved to nearly 100 wt% through arc re-melting. CMSE offers low specific energy consumption (3.7 kWhr kg −1 ), competitive with H 2 -DRI and other electrolytic approaches being pursued globally. Our findings underscore the potential of CMSE as an energy-efficient route for electrosynthesis of Fe metal.

36 MATERIALS SCIENCE↗

Clean Energy Integration in Natural Gas Compressor Station Operations

Integrating renewable energy into oil and gas operations could reduce emissions and maximize higher-value use of produced hydrocarbons. In this study, analysts from the Joint Institute for Strategic Energy Analysis (JISEA) and the National Renewable Energy Laboratory (NREL) evaluated clean power technologies for a natural gas compressor station in Texas, using NREL’s REopt tool. Different configurations of distributed energy resources were evaluated based on the technologies available and the load they can satisfy, available land, and hypothetical carbon pricing. The analysis is part of a collaborative program with industry to understand site-specific energy consumption and prices in the oil and gas supply chain and determine under what conditions clean energy options are economically attractive. This work was sponsored by a consortium including Kinder Morgan, Interstate Natural Gas Association of America Foundation, Extraction Oil & Gas, Baker Hughes, and ConocoPhillips.

03 NATURAL GAS↗