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At least 487 records · Page 27

Ion-capture electrodialysis using multifunctional adsorptive membranes

Technologies that can efficiently purify nontraditional water sources are needed to meet rising global demand for clean water. Water treatment plants typically require a series of costly separation units to achieve desalination and the removal of toxic trace contaminants such as heavy metals and boron. We report a series of robust, selective, and tunable adsorptive membranes that feature porous aromatic framework nanoparticles embedded within ion exchange polymers and demonstrate their use in an efficient, one-step separation strategy termed ion-capture electrodialysis. This process uses electrodialysis configurations with adsorptive membranes to simultaneously desalinate complex water sources and capture diverse target solutes with negligible capture of competing ions. Our methods are applicable to the development of efficient and selective multifunctional separations that use adsorptive membranes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Integrating Applied Energy and BER Smart Data Capabilities to Develop a DOE Data Fabric for Energy-Water R&D

Focal Area(s): 1) Data acquisition and assimilation enabled by machine learning, AI, and advanced methods including experimental/network design/optimization, unsupervised learning (including deep learning), and hardware-related efforts involving AI (e.g., edge computing). Science Challenge: DOE R&D, including DOE’s Basic Energy Research (BER)’s Environmental Systems Science Division (EESSD) program and DOE’s applied energy research (AER) programs (EERE, FE, and NE) are producers and consumers of Earth systems datasets. This white paper focuses on the first topic area from the call in relation to how crosscutting resources and innovations from DOE’s EESSD and AER can be brought to bear to mutual benefit and more efficient energy-water, Earth system data resources through improved. The overarching challenge posed by this call focuses on how DOE can directly leverage artificial intelligence (AI) to engineer a substantial (paradigm-changing) improvement in Earth System Predictability? While stemming from DOE BER’s EESSD program, this is a challenge that is faced and also being addressed by DOE’s AER programs. Over the past decade plus, FE, EERE, and NE programs have made important strides towards addressing this need. These strides are in many ways highly complementary to EESSD’s MODEX efforts. Energy water systems spanning metocean to groundwater to surface water systems all are data driven whether for basic energy or applied energy. These are remote, multi-variate, complex natural, and in many cases engineered, systems. Key needs and challenges of both EESSD and AER include developing data-focused tools to enhance data search and discovery to fill in knowledge gaps (address sparse data challenge), and rapidly transform datasets, including disparate and multi-source data. Leveraging DOE on-premise computing (HPC, exascale) infrastructure supports the computing-intensive algorithms required to execute these data acquisition and transformation processes to derive enriched knowledge and data, driving AI/ML and big data analytics for these systems. The opportunity lies in combining BER and AER efforts to provide a more robust, advanced, efficient and complete computing data fabric to address energy-water data acquisition and assimilation needs which currently pose significant impediments to AI/ML predictions and research.

54 ENVIRONMENTAL SCIENCES↗

Cold Climate Integrated Heat Pump

This paper introduces development of a residential air-source integrated heat pump for cold climates (CCIHP). The heat pump is multi-functional to meet all the home comfort demands, including space cooling, space heating, domestic water heating and energy storage. The CCIHP is an ideal solution to decarbonize northern homes via providing efficient space heating and water heating to replace natural gas. It uses a three-stage compressor and a single set of heat exchangers and valves to deliver all the functions, and thus achieve cost reduction. We developed an innovative system configuration and related controls to solve typical charge unbalance in heat pumps, accelerate charge migration and smoothen mode transition in integrated heat pumps. Laboratory investigations were conducted for individual modes and verified the control functions. Laboratory tests demonstrated that the unit delivered outstanding performance. It achieved 17.0 SEER (seasonal cooling energy efficiency rating) and 11.0 HSPF (heating seasonal performance factor). In the most efficient mode (combined space cooling and water heating mode), the unit reached a total energy efficiency of 35.0 EER and required only 25 minutes to heat a 50-gallon tank of water. The CCIHP can heat 1.7 GPM water from 58 to 125°F in a direct flow-through, when the ambient temperature is above 47°F. In a dedicated water heating mode using outdoor air source, the heat pump operated down to 17°F, achieving a COP > 2.6, and heated 50-gallon water within 1 hour.

Shen, Bo↗

Predicting Initial Trans-Membrane Pressure for Optimized Operations in UF Unit Using Random Forest

With the growing scarcity of freshwater, innovative process design mechanisms like Ultra-filtration(UF) units are increasingly gaining attention among water treatment utilities to address the rising demand. Ensuring reliable water production necessitates efficient resource utilization, minimizing downtime in UF systems. Recent advancements in machine learning (ML) have enabled the development of accurate data-driven models for Model Predictive Control (MPC), often requiring minimal prior knowledge of underlying physical processes. In this study, we present predictive regression models based on Random Forest (RF) and Auto-Regressive (AR) approaches to forecast the initial Trans-Membrane Pressure (TMP) for each filtration cycle in data generated by Direct Potable Reuse (DPR) systems. The proposed RF-based model demonstrates superior performance compared to baseline methods, including historical mean, Last Observation Carried Forward (LOCF), and naïve AR models, across various forecasting horizons in terms of root mean square (RMSE) metric. Accurate prediction of initial TMP is critical for optimizing CCRO operations, as it enables the development of robust modelling frameworks that enhance process efficiency and reliability. The demonstrated efficacy of the RF-based approach highlights its potential as a tool for real-time decision-making in water treatment systems, paving the way for advanced process optimization and sustainable water resource management.

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

Electron Beam Irradiation for Water Treatment of Per- and Polyfluoroalkyl Substances (PFAS)

Per- and polyfluoroalkyl substances (PFAS) are widely used but are now considered a water contamination risk. Fermi National Accelerator Laboratory’s IARC group has demonstrated that passing water through electron beam radiation can destroy PFAS. This project aims to develop a process to scale the system for bulk water treatment. The key is efficient radiation usage, ensuring that all water receives only the minimum dose. Software was developed for this purpose, consisting of a computational fluid dynamics model (CFD) in COMSOL, which calculates particle trajectories through the radiation area. A MATLAB script integrates the radiation dose of these particles, and statistical analysis is performed to evaluate the radiation utilization efficiency. These models are validated with a flow test where colored dye is injected and optically tracked. Radiation dose is measured by testing under an e-beam to measure the degradation of a PFAS analog.

Mueller, Scott [Northern Illinois U.]↗

Climate-Water Impacts on Interconnection-Scale Electricity System Planning

A growing literature emphasizes the importance of integrating climate change impacts into electricity system planning. Rising average temperatures can increase and shift electricity demand while reducing generator and transmission efficiency. Changes to water availability and quality can reduce the output of thermally cooled generators and hydropower. Electric power grids across the US and globally are undergoing transformational changes that present new opportunities and challenges to reliability assurance. However, electric utilities and system operators have limited internal capabilities to incorporate these effects into planning practices. This work addresses gaps in utility and system planner practices by integrating climate-water-electricity expertise from universities and U.S. Department of Energy National Laboratories with electricity system planners and stakeholders in the Western Electricity Coordinating Council (WECC). Using a highly collaborative approach, global climate model data, high-resolution hydrology models, and long-term electric sector capacity expansion tools are employed to analyze a range of climate outcomes for future electricity scenarios aligned with recent WECC planning studies. Doing so allows WECC to expand its climate-agnostic planning assessments to consider how future temperature and precipitation patterns could influence generation and transmission planning. We explore how changes to climate-water conditions can affect power plant investment and operation, system economics, and environmental impacts, providing an expanded perspective on interconnection-wide decision making under climate uncertainty.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

An experiment to detect gut monopoles

Recent advances in the development of Grand Unification Theories have led to several interesting predictions. One of these states that Grand Unification Monopoles (GUMs) exist as solutions in may nonabelian gauge theories. Another consequence of Unification is the possibility of baryon decay. The efficiency of the water tank detector in registering a Rubakov type decay will vary with both the interaction length and the GUM's velocity, expressed in terms of beta ( 0.01). The efficiency decreases at large values of because of the limited resolving time of the detector (approx. 50 ns). At lower values of Beta the time between interactions is such that the criterion of 4 events in 2 mu s can no longer be satisfied. The Rubakov experiment has now been in operation for almost 2 years with an estimated live time of 80%. During this time no candidate events have been observed leading to an estimated upper limit on the flux of 7.82 x 0.00001 m(-2) d(-1) Sr(-1). The ionization loss detection system has only recently come on line and as yet no results are available from this experiment.

Macneill, G.↗

Predicting Initial Trans-Membrane Pressure for Optimized Operations in UF Unit Using Random Forest

With the growing scarcity of freshwater, innovative process design mechanisms like Reverse Osmosis (RO) are increasingly gaining attention among water treatment utilities to address the rising demand. Ensuring reliable water production necessitates efficient resource utilization, minimizing downtime in (ultra-filtration) UF systems. Recent advancements in machine learning (ML) have enabled the development of accurate data-driven models for Model Predictive Control (MPC), often requiring minimal prior knowledge of underlying physical processes. In this study, we present predictive regression models based on Random Forest (RF) and Auto-Regressive (AR) approaches to forecast the initial Trans-Membrane Pressure (TMP) for each filtration cycle in data generated by Direct Potable Reuse (DPR) systems. The proposed RF-based model demonstrates superior performance compared to baseline methods, including historical mean, Last Observation Carried Forward (LOCF), and naïve AR models, across various forecasting horizons in terms of root mean square error (RMSE) metric. To evaluate how different classes of process variables contribute to TMP dynamics over time, we examine the feature importance of independent covariates across multiple forecast horizons. This analysis provides insight into the temporal relevance of operational and sensor-derived features, guiding control and monitoring strategies. Additionally, the impact of hyperparameter tuning on TMP prediction performance is studied for both direct and recursive RF modelling approaches across increasing forecast horizons. Accurate prediction of initial TMP is critical for optimizing RO operations, as it enables the development of robust modelling frameworks by accurately estimating membrane fouling trends, thereby enhancing process efficiency and long-term reliability. The demonstrated efficacy of the RF-based approach highlights its potential as a tool for real-time decision-making in water treatment systems, paving the way for advanced process optimization and sustainable water resource management.

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

3D-Printed Membranes with a Zwitterionic Hydrogel Coating for More Robust Oil–Water Separation

Three-dimensional (3D)-printed membranes via stereolithography (SLA) are promising in oil–water separation, which is the key in the purification of industrial oily wastewater. To achieve gravity-driven oil–water separation, the membrane material needs to be simultaneously hydrophilic/oleophobic. However, most of the state-of-the-art materials for SLA do not meet the requirement. While water-adsorbing hydrogel is simultaneously hydrophilic/oleophobic and there have been reports on 3D printing of hydrogels in biomedical applications, the hydrogel is too soft for membrane application. Here, we report a simple approach to tackle the issue: a hydrogel coating on SLA-based plastic membranes. The coating is fabricated, using [2-(methacryloyloxy) ethyl] dimethyl-(3-sulfopropyl) ammonium hydroxide as the zwitterionic monomer and acrylamide as the comonomer, via in situ polymerization on SLA-based plastic membranes. The contact angle tests and Fourier transform infrared spectrum show that such a membrane readily adsorbs water and becomes simultaneously hydrophilic/oleophobic. The oil–water separation tests indicate that the water-adsorbed membrane is highly efficient in gravity-driven oil–water separation in 31 repeating cycles. Our results indicate the great potential of 3D-printed membranes in oil–water separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Thermochemical water decomposition

At present, nearly all of the hydrogen consumed in the world is produced by reacting hydrocarbons with water. As the supply of hydrocarbons diminishes, the problem of producing hydrogen from water alone will become increasingly important. Furthermore, producing hydrogen from water is a means of energy conversion by which thermal energy from a primary source, such as solar or nuclear fusion of fission, can be changed into an easily transportable and ecologically acceptable fuel. The attraction of thermochemical processes is that they offer the potential for converting thermal energy to hydrogen more efficiently than by water electrolysis. A thermochemical hydrogen-production process is one which requires only water as material input and mainly thermal energy, or heat, as an energy input. Attention is given to a definition of process thermal efficiency, the thermodynamics of the overall process, the single-stage process, the two-stage process, multistage processes, the work of separation and a process evaluation.

Funk, J. E.↗

Advanced Electrocatalysis for Energy and Environmental Sustainability via Water and Nitrogen Reactions

Abstract Clean and efficient energy storage and conversion via sustainable water and nitrogen reactions have attracted substantial attention to address the energy and environmental issues due to the overwhelming use of fossil fuels. These electrochemical reactions are crucial for desirable clean energy technologies, including advanced water electrolyzers, hydrogen fuel cells, and ammonia electrosynthesis and utilization. Their sluggish reaction kinetics lead to inefficient energy conversion. Innovative electrocatalysis, i.e., catalysis at the interface between the electrode and electrolyte to facilitate charge transfer and mass transport, plays a vital role in boosting energy conversion efficiency and providing sufficient performance and durability for these energy technologies. Herein, a comprehensive review on recent progress, achievements, and remaining challenges for these electrocatalysis processes related to water (i.e., oxygen evolution reaction, OER, and oxygen reduction reaction, ORR) and nitrogen (i.e., nitrogen reduction reaction, NRR, for ammonia synthesis and ammonia oxidation reaction, AOR, for energy utilization) is provided. Catalysts, electrolytes, and interfaces between the two within electrodes for these electrocatalysis processes are discussed. The primary emphasis is device performance of OER‐related proton exchange membrane (PEM) electrolyzers, ORR‐related PEM fuel cells, NRR‐driven ammonia electrosynthesis from water and nitrogen, and AOR‐related direct ammonia fuel cells.

Li, Yi↗

Experimental feasibility of the airborne measurement of absolute oil fluorescence spectral conversion efficiency

Airborne lidar oil spill experiments carried out to determine the practicability of the AOFSCE (absolute oil fluorescence spectral conversion efficiency) computational model are described. The results reveal that the model is suitable over a considerable range of oil film thicknesses provided the fluorescence efficiency of the oil does not approach the minimum detection sensitivity limitations of the lidar system. Separate airborne lidar experiments to demonstrate measurement of the water column Raman conversion efficiency are also conducted to ascertain the ultimate feasibility of converting such relative oil fluorescence to absolute values. Whereas the AOFSCE model is seen as highly promising, further airborne water column Raman conversion efficiency experiments with improved temporal or depth-resolved waveform calibration and software deconvolution techniques are thought necessary for a final determination of suitability.

Hoge, F. E.↗

Tests of a 2-Stage, Axial-Flow, 2-Phase Turbine

A two phase flow turbine with two stages of axial flow impulse rotors was tested with three different working fluid mixtures at a shaft power of 30 kW. The turbine efficiency was 0.55 with nitrogen and water of 0.02 quality and 94 m/s velocity, 0.57 with Refrigerant 22 of 0.27 quality and 123 m/s velocity, and 0.30 with steam and water of 0.27 quality and 457 m/s velocity. The efficiencies with nitrogen and water and Refrigerant 22 were 86 percent of theoretical. At that fraction of theoretical, the efficiencies of optimized two phase turbines would be in the low 60 percent range with organic working fluids and in the mid 50 percent range with steam and water. The recommended turbine design is a two stage axial flow impulse turbine followed by a rotary separator for discharge of separate liquid and gas streams and recovery of liquid pressure.

Elliott, D. G.↗

Self-powered Heating: Efficiency Analysis

Conventional fuel-fired heating devices such as furnaces, boilers, and water heaters have fuel efficiency less than 100% on the basis of higher heating value. They also require electricity from the electric grid to power parasitic loads such as blowers, pumps, fans, and ignitors. The primary energy efficiency of the device accounts for both fuel used on-site and primary energy used off-site to produce electric power used by the device. This work compares conventional fuel-fired heating devices to two types of self-powered devices. A self-powered device (SPD) integrates a power cycle onboard to eliminate consumption of grid electricity. We assume that all heat rejected by the onboard power cycle is added to the process fluid, so that, compared with a conventional device, the same amount of heat is provided to the process fluid and the same amount of fuel is consumed, but grid electricity consumption is eliminated. The first SPD type is the basic one: exactly the electricity required is generated. The second type considered is the SPD with heat pump (SPD-HP), in which the power cycle generates more electricity than needed for parasitic loads, and the excess electricity is used to power a heat pump. The heat pump extracts additional heat from the ambient to boost efficiency. Both SPD and SPD-HP self-consume all the generated electricity, in contrast to combined heat and power (CHP) systems that export electricity. In this work, equations are derived to express the efficiency of three classes of heating devices: conventional (consuming grid electricity), self-powered (consuming no grid electricity), and self-powered with heat pump. The efficiency of each is derived as a function of up to six factors: (1) the fraction of combustion heat captured, (2) the rate of parasitic power consumption, (3) the fraction of electric energy dissipated as useful heat, (4) the power cycle conversion efficiency, (5) the grid efficiency, when applicable, and (6) the heat pump COP, when applicable. Scenarios are identified in which it is possible to achieve efficiency greater than 100% on a higher heating value basis. Plausible configurations using existing technology options are outlined.

Gluesenkamp, Kyle↗

Preliminary operational results from the Willard solar power system

The solar powered system located near Willard, New Mexico, generates mechanical or electrical power at a capacity of 19 kW (25 HP). The solar collection system incorporates east/west tracking parabolic trough collectors with a total aperture area of 1275 sq m (13,720 sq ft). The hot oil type thermal energy storage is sufficient for approximately 20 hours of power system operation. The system utilizes a reaction type turbine in conjunction with an organic Rankine cycle engine. Total collector field efficiency reaches a maximum of 20 percent near the winter solstice and about 50 percent during the summer. During the month of July, 1979, the system pumped 60 percent of the 35,300 cu m (28.6 acre-feet) of water delivered. Operating efficiencies for the turbine component, organic Rankine cycle engine and the complete power system are respectively 65 to 75 percent, 12 to 15 percent and 5 to 6 percent. Significant maintenance time was expended on both the collector and power systems throughout the operational period.

Fenton, D. L.↗