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At least 451 records · Page 25

The current status of high temperature electrochemistry-based CO 2 transport membranes and reactors for direct CO 2 capture and conversion

The concept of direct CO 2 capture and conversion has attracted significant interest from industries and academia in recent decades due to its potential to address the current grand challenge of global warming/climate change, rapid depletion of fossil fuels and realization of a future carbon neutral ecosystem. The incumbent benchmark technology for CO 2 capture is the post-combustion flue-gas “amine washing”, which is energy intensive and costly for large-scale commercial implementation. The CO 2 conversion technologies, on the other hand, are still at their infancy with many technical challenges to overcome, but primarily being explored in laboratory-scale, low-temperature, solution-based and high-temperature, solid-oxide-based electrochemical cells with renewable electricity perceived as the energy input. In this article, we provide a comprehensive overview on an emergent class of high-temperature electrochemical CO 2 transport membranes that can capture and convert CO 2 into valuable chemicals in single catalytic reactor fashion. The review starts with the chemistry and transport theory of three basic types of membranes purposely designed for different CO 2 feedstocks and downstream conversions. A range of key functional materials used in these membranes and their microstructural/electrochemical properties important to the CO 2 transport are then thoroughly discussed in conjunction with the effects of surface modifications and operating conditions. Several types of combined CO 2 capture and conversion catalytic reactors based on these membranes are also assessed with a focus on their working principles, system configurations and performance demonstrations. Finally, challenges and prospective of these electrochemical CO 2 transport membranes and their associated conversion reactors are candidly discussed for future development.

10 SYNTHETIC FUELS↗

Impact of Selected High-Performance Fuel Blends on Three-Way Catalyst Light Off under Synthetic Spark-Ignition Engine-Exhaust Conditions

The U.S. Department of Energy funded Co-Optimization of Fuels and Engines initiative aims to simultaneously develop advanced engines along with high-performance fuels to reduce petroleum consumption. The engine exhaust of spark-ignited light-duty vehicles contains pollutants such as nitrogen oxides, carbon monoxide (CO), and non-methane organic gases. When operated above their “light-off” temperature, three-way catalysts (TWCs) efficiently control the emissions of these pollutants from the vehicle exhaust. However, below the catalyst light-off temperature, during cold start, the TWCs are not effective. Thus, the stringent environmental regulations necessitate cold-start compliance of advanced engines operating on novel fuels for commercialization. Exhaust composition strongly impacts the effectiveness of TWCs. Hence, ensuring that the high-performance fuels under consideration do not have detrimental effects on current emissions control technology is necessary. To mitigate cold-start emissions, a low light-off temperature of the fuel on the TWC is desirable. As real-world fuels are multicomponent blends, we conducted investigations into the light-off behavior of representative fuel mixtures on a three-mode redox-aged commercial TWC under synthetic engine-exhaust conditions. The high-performance fuels in this study included 10–30% volumetric levels of ethanol, isobutanol, diisobutylene, and an aromatic mixture. Each of these high-performance fuel components was mixed into a gasoline surrogate blendstock for oxygenate blending (BOB). Our results showed that aromatics and alkenes in the surrogate BOB inhibit low-temperature reactivity of alkanes, alcohols, and CO on the TWC and dominate the blend light-off behavior. All the high-performance fuel blends had a very similar light-off behavior to the surrogate gasoline BOB, indicating that blending up to 30% (by vol.) of high-performance blendstocks in a gasoline base fuel can potentially reduce greenhouse gas emissions through improved engine efficiency and petroleum displacement without jeopardizing the ability to meet emissions regulations. While some high-performance blendstocks demonstrated lower light-off temperatures than a surrogate gasoline blend, taking advantage of the higher catalytic reactivity of these blendstocks to reduce cold-start emissions would require reducing the aromatic content in petroleum-based market fuels.

33 ADVANCED PROPULSION SYSTEMS↗

Untapped Benefits of Porous Liquids for Gas Capture: Low-Energy Regeneration

Current liquid-phase gas capture materials incur high operational costs due to energy-intensive regeneration processes, creating an industrial need for alternative materials that retain engineering benefits while reducing energy requirements. Porous liquids (PLs), liquid-phase materials with permanent internal porosity, have emerged as promising replacements with excellent gas absorption capacity and selectivity. Despite these benefits, evaluation of regeneration in PLs remains rare. In this Perspective, we evaluate the effects of solvent interactions, mass transport, and binding site formation that control PL regeneration. While conventional regeneration methods exist in PLs, the diversity of PL compositions allows for novel regeneration processes including light irradiation via use of photosensitive azobenzene-based cages, isostatic compression to collapse internal pore structures, and localized heating via sonication for gas desorption. In conclusion, the wide variability in porous host materials that generate the internal porosity in PLs facilitates innovative low-energy regeneration pathways, positioning them as a transformative solution in separation technologies.

gas capture↗

Reshaping the Quantum Arrow of Time

While the microscopic laws of physics are often symmetric under time reversal, most natural processes that we observe are not. The emergent asymmetry between typical and time-reversed processes is referred to as the arrow of time. In quantum physics, an arrow of time emerges when a sequence of measurements is performed on a system. We introduce quantum control tools that can yield dynamics more consistent with time flowing backward than forward. The control tools are based on the explicit construction of a Hamiltonian that can replicate the stochastic trajectories of a monitored quantum system. Such a Hamiltonian can reverse the effect of monitoring and, via a feedback process, generate trajectories consistent with a reversed arrow of time. It can also be used to simulate the backward-in-time dynamics of an open quantum system. Finally, we design a feedback-driven continuous measurement engine powered by the energy pumped into the system by the monitoring process. We show that the engine can operate under experimentally realizable conditions with feedback delay and finite-efficiency measurements.

Entropy production↗

System and method for optimal load and source scheduling in context aware homes

A controller for controlling energy consumption in a home includes a constraints engine to define variables for multiple appliances in the home corresponding to various home modes and persona of an occupant of the home. A modeling engine models multiple paths of energy utilization of the multiple appliances to place the home into a desired state from a current context. An optimal scheduler receives the multiple paths of energy utilization and generates a schedule as a function of the multiple paths and a selected persona to place the home in a desired state.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Energy and exergy analysis of multi-stage vacuum membrane distillation integrated with mechanical vapor compression

Membrane distillation (MD) is a promising candidate for desalinating hypersaline brine, but its poor energy efficiency has remained a major barrier for widespread application. One possible solution to this issue is to recover the latent heat in the process. In this work, a multi-stage vacuum MD (MSVMD) was integrated with a mechanical vapor compressor (MVC) to enhance the latent heat recovery, and the energetic and exergetic performance of this integrated process was examined. A comprehensive energy and exergy analysis is provided to compare MSVMD and MSVMD-MVC processes for desalination of hypersaline brine. This analysis was conducted by examining the effect of the compression ratio on the energetic and exergetic performance, and the findings are reported in terms of specific thermal energy consumption (STEC), specific electricity consumption (SEC), and exergetic efficiency. The energy analysis shows that thermal energy consumption can be reduced as the compression ratio increases, due to the enhancement of latent heat recovery. The MSVMD-MVC process can be operated in a steady-state condition, without the need for thermal heat input; with STEC and SEC of 0 and 49 kWh/m 3 at the feed temperature of 50 °C and MVC compression ratio of 2.14. Moreover, exergy analysis demonstrates the efficacy of the eNRTL model in exergy calculation. Exergy destruction can be greatly reduced by increasing the compression ratio to an optimal value. For high salinity brine (124 g/L), MSVMD-MVC achieved a higher exergetic efficiency of 6.85%, compared to 2.42% in MSVMD. Furthermore, the result suggests that the application of MVC can intensify the energy efficiency and exergetic efficiency of the MSVMD system, although this process cannot outperform the current desalination technologies from the standard primary energy point of view.

42 ENGINEERING↗

A generalized platform for artificial intelligence-powered autonomous enzyme engineering

Proteins are the molecular machines of life with numerous applications in energy, health, and sustainability. However, engineering proteins with desired functions for practical applications remains slow, expensive, and specialist-dependent. Here we report a generally applicable platform for autonomous enzyme engineering that integrates machine learning and large language models with biofoundry automation to eliminate the need for human intervention, judgement, and domain expertise. Requiring only an input protein sequence and a quantifiable way to measure fitness, this automated platform can be applied to engineer a wide array of proteins. As a proof of concept, we engineer Arabidopsis thaliana halide methyltransferase (AtHMT) for a 90-fold improvement in substrate preference and 16-fold improvement in ethyltransferase activity, along with developing a Yersinia mollaretii phytase (YmPhytase) variant with 26-fold improvement in activity at neutral pH. This is accomplished in four rounds over 4 weeks, while requiring construction and characterization of fewer than 500 variants for each enzyme. This platform for autonomous experimentation paves the way for rapid advancements across diverse industries, from medicine and biotechnology to renewable energy and sustainable chemistry.

59 BASIC BIOLOGICAL SCIENCES↗

Reinforcement learning based automated history matching for improved hydrocarbon production forecast

History matching aims to find a numerical reservoir model that can be used to predict the reservoir performance. An engineer and model calibration (data inversion) method are required to adjust various parameters/properties of the numerical model in order to match the reservoir production history. In this study, we develop deep neural networks within the reinforcement learning framework to achieve automated history matching that will reduce engineers’ efforts, human bias, automatically and intelligently explore the parameter space, and remove the need of large set of labeled training data. To that end, a fast-marching-based reservoir simulator is encapsulated as an environment for the proposed reinforcement learning. The deep neural-network-based learning agent interacts with the reservoir simulator within reinforcement learning framework to achieve the automated history matching. Reinforcement learning techniques, such as discrete Deep Q Network and continuous Deep Deterministic Policy Gradients, are used toth, used to train the learning agents. The continuous actions enable the Deep Deterministic Policy Gradients to explore more states at each iteration in a a learning episode; consequently, a better history matching is achieved using this algorithm as compared to Deep Q Network. For simplified dual-target composite reservoir models, the best history-matching performances of the discrete and continuous learning methods in terms of normalized root mean square errors are 0.0447 and 0.0038, respectively. Furthermore, our study shows that continuous action space achieved by the deep deterministic policy gradient drastically outperforms deep Q network.

42 ENGINEERING↗

Extended convex hull-based distributed optimal energy flow of integrated electricity-gas systems

Integrated electricity and gas systems are constructed to facilitate the gas-fired generation, and the distributed operation of these integrated systems have received much attention due to the increased emphasis on data security and privacy between different agencies. This paper proposes an extended convex hull based method to address optimal energy flow problems for the integrated electricity and gas systems in a distributed manner. First, a multi-block electricity-gas system model is constructed by dividing the whole system into N blocks considering both physical and regional differences. This multi-block model is then convexified by replacing the nonconvex gas transmission equation with the extended convex hull-based constraints. The Jacobi-Proximal alternating direction method of multipliers algorithm is adopted to solve the convexified model and minimize its operation cost. Finally, the feasibility of the optimal solution for the convexified model is checked, and a sufficient condition is developed. If the sufficient condition is satisfied, the optimal solution for the original nonconvex problem can be recovered from that for the convexified problem. Simulation results demonstrate that the proposed method is tractable and effective in obtaining feasible optimal solutions for multi-block optimal energy flow problems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The role of current and emerging technologies in meeting Japan’s mid- to long-term carbon reduction goals

Using Japan as a proxy for a developed nation, we investigated the role of existing and nascent technologies in curbing carbon emissions. We simulated possible pathways to meeting 2030 and 2050 emission targets within the Japanese electricity supply sector using a single-region model in The Integrated MARKAL-EFOM System (TIMES). Critically, our simulations incorporate novel technologies like hydrogen electrolysers, carbon capture, photochemical water splitting, and emerging photovoltaic cells, assess long-term impacts up to the year 2100, and include life-cycle emissions and learning curves for parameters such as investment cost, efficiency, and emission coefficients. Results indicate that a hybrid approach, using nuclear power and hydrogen from renewable energy-based electrolysis, is cost-effective and provides long-term emission reduction along with energy security. Finally, nuclear, wind, solar, and hydrogen from renewables emerge as key emission reduction technologies, while natural gas with carbon capture plays a minor role in achieving emission reduction targets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Hydrokinetic energy conversion using flow induced oscillations of single-cylinder with large passive turbulence control

Various types of flow-induced oscillations (FIOs) have been implemented in development of marine hydrokinetic (MHK) energy converters. With passive turbulence control (PTC), energy harvesting starts at a flow speed of about 0.5 m/s. However, there is worldwide MHK energy available in even slower currents. In the present study, the effect of damping on FIO and power extraction is investigated for a converter with large turbulence stimulation (PTC) consisting of straight strips with a height of 15% of the cylinder diameter and placed symmetrically on the cylinder surface. The oscillating amplitude decreases, as the damping ratio increases, with unchanged sinusoidal pattern of the displacement time-history. The frequency ratio is also affected by damping especially in the VIV initial branch and transition region between VIV and galloping. An important flow characteristic of the large-PTC cylinder is that a recirculation region is formed behind the PTC, causing appreciable disturbance to the flow past the cylinder. Power can be harvested in the whole FIO range and the harnessed power maximum appears at the largest inflow velocity tested. However, the optimum of harnessing efficiency is located at the beginning of the VIV upper branch. The gap between VIV and galloping is bridged when large PTC is used, eliminating the drop in power and efficiency even at higher damping, which would be a weakness of regular-PTC cylinder for energy harvesting. Finally, the mechanism behind the variation of harnessing efficiency with inflow velocity and damping ratio is revealed, and the optimality criterion for the converter design is discussed.

16 TIDAL AND WAVE POWER↗

Enhanced flow boiling heat transfer on chromium coated zircaloy-4 using cold spray technique for accident tolerant fuel (ATF) materials

Flow boiling heat transfer tests were conducted to evaluate the Critical Heat Flux (CHF) and Heat Transfer Coefficient (HTC) of conventional and accident tolerant fuel (ATF) cladding materials, i.e., bare Zircaloy-4 (Zr4), and Zircaloy-4 coated with Chromium using physical vapor deposition (PVD) (Zr4-Cr-PVD) and cold spray process (Zr4-Cr-CS), respectively. The tests were performed on a single heater rod with a uniform heat flux profile, at the atmospheric pressure, inlet temperature (24 °C) and mass flow rate (750 kg/m 2 s). HTC’s were increased by 5.2% and 3.3% on Zr4-Cr-CS compared to bare Zr4 and Zr4-Cr-PVD. Improved HTCwas attributed to the increased void fraction and high roughness (Ra = 532 nm) of the Zr4-Cr-CS. In detail, the micro-cavities, which act as bubble seeds, were entirely distributed on the Zr4-Cr-CS, and these micro-cavities generated smaller and faster bubbles, thus the void fraction increased by 10.9% compared to bare Zr4. HTC is improved by these smaller and faster bubbles which can remove heat from the heater rod surface more efficiently. To identify the exact location of CHF, the surface temperature profile was measured using advanced fiber-optic sensors which have high temporal/spatial resolution (distance between point to point: ~2.5 mm, frequency ~100 Hz). CHF occurred at 80–95% along the heated length and showed an 11.6% reduction on Zr4-Cr-CS compared to bare Zr4. We hypothesize the CHF reduction was caused by the lower wettability of the Zr4-Cr-CS which reduces the liquid supply to the surface, and vigorous bubble accumulation owing to high void fraction near the outlet, which results in early formation of the vapor film. During the post-CHF quenching phase, the rougher Zr4-Cr-CS showed larger cooling rates compared to the bare Zr4 and Zr4-Cr-PVD, preventing of oxidation by chromium layer. In conclusion, we demonstrate that the high roughness on the Zr4-Cr-CS increased the number of micro-cavities on the surface, resulting in 5.2% increase in HTC and improvement in the quenching heat transfer performance whereas CHF was 11.6% reduced compared to bare Zr4. Overall statistically there is little effect in the coating with regards to CHF and slight improvement in HTC.

42 ENGINEERING↗

A deep insight on the coal ash-to-slag transformation behavior during the entrained flow gasification process

Recent research provided deep insight on the coal ash-to-slag transformation characterization during the entrained flow gasification process, with experimentation on a 40 kg/hr (dry basis) coal-fed opposed multi-burner (OMB) entrained flow gasifier and simulation via FactSage™ software. A general mechanism is presented to relate the gasifier design temperature, ash fluid temperature, and operating temperature with the degree of the slag polymerization. The change of the high temperature zone, the corresponding particle residence time in the high temperature zone, and syngas composition have obvious effects on the slag mineral transformation behavior. Mineral types formed on the wall of the gasifier chamber were mainly anorthite (CaAl 2 Si 2 O 8 ), aluminum oxide (Al 2 O 3 ), and calcium sulfide (CaS). These minerals transformed to anorthite and diopside (CaMgSi 2 O 6 ) at the slag hole zone, while the minerals at the lock hopper were anorthite, orthoclase (KAlSi 3 O 8 ), quartz (SiO 2 ), gypsum (CaSO 4 ), calcite (CaCO 3 ), and halite (NaCl). FactSage™ predicted minerals as anorthite, diopside, orthoclase, and albite (NaAlSi 3 O 8 ), etc., where the slag temperature was below the ash fluid temperature and when the ratios of CO/CO 2 and (CO + H 2 )/CO 2 were lower than 1.0 and 2.0, respectively. By simulation, residual carbon was found to be the dominant factor over syngas composition to cause mineral transformation, and this was verified experimentally. The Ca-based crystals, typically anorthite, was shifted to diopside, near the slag hole zone, and a linear relationship was found between the content ratios of diopside/(anorthite + diopside), CaO/SiO 2 , and (CaO + MgO)/SiO 2 . A dimensionless number, θ, was defined to characterize the changing chemical composition and the degree of slag polymerization, with temperature deviation from the design condition. Three zones of θ were identified and related to the deviation between the actual gasification condition from the design condition. Finally, a low slag polymerization degree corresponded with a higher temperature deviation between the actual condition and design condition, and this proved that increased residual carbon content and changing iron valence state increased the mineral types when the slag temperature was below the ash fluid temperature.

01 COAL, LIGNITE, AND PEAT↗

A screening model for predicting injection well pressure buildup and plume extent in CO 2 geologic storage projects

We present a new screening model for predicting injection well pressure buildup and CO 2 plume migration for CO 2 geologic sequestration projects. The model requires only limited information and is quite accurate when compared to detailed simulation results. Such models can assist project developers during the early days of project planning (e.g., for 45Q related projects), and also help regulators perform simple checks against detailed numerical models. The screening model consists of two correlations: one for injectivity index in terms of the slope of the CO 2 fractional flow curve, and the second for total storage efficiency within the footprint of plume as a function of gravity number and slope of the CO 2 fractional flow curve. Using these two correlations, as well as a knowledge of some basic reservoir characteristics and estimates of fluid properties from standard correlations, the injection-well pressure buildup and CO 2 plume extent in the formation can be readily estimated. Finally, the new correlations show a good match with the results of the underlying simulations, and also provide good agreement with independent calculations for two example problems.

42 ENGINEERING↗

High-throughput oxygen chemical potential engineering of perovskite oxides for chemical looping applications

Chemical looping (CL) represents a versatile, emerging strategy for sustainable chemical and energy conversion. Designing metal oxide oxygen carriers with suitable redox properties remains one of the most critical challenges to CL due to the considerably different thermodynamic property requirements for different applications. Here, taking SrFeO 3–δ as a base-structure, this study seeks to rationally substitute its A- and/or B-site cations to tailor the equilibrium oxygen partial pressure over 20 orders of magnitude. 2401 Sr x A 1–x Fe y B 1–y O 3–δ perovskite-phase structures were investigated using high-throughput density functional theory (DFT) and 227, 273 high-entropy perovskites were screened via machine learning (ML). This significantly expands the materials design space. While most of the compositions predicted are new and nonobvious, 19 previously reported oxygen carriers, with excellent redox properties, were correctly identified by the algorithm. Moreover, we experimentally demonstrated 15 new oxygen carriers with superior redox performance. These results support the effectiveness of the high-throughput approaches for accelerated materials discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mean-field control for efficient mixing of energy loads

In this work, we pose an engineering challenge of controlling an ensemble of energy devices via coordinated, implementation-light, and randomized on/off switching as a problem in nonequilibrium statistical mechanics. We show that mean-field control with nonlinear feedback on the cumulative consumption, assumed available to the aggregator via direct physical measurements of the energy flow, allows the ensemble to recover from its use in the demand response regime, i.e., transition to a statistical steady state, significantly faster than in the case of the fixed feedback. Moreover when the nonlinearity is sufficiently strong, one observes the phenomenon of “super-relaxation,” where the total instantaneous energy consumption of the ensemble transitions to the steady state much faster than the underlying probability distribution of the devices over their state space, while also leaving almost no devices outside of the comfort zone.

25 ENERGY STORAGE↗

The Potential to Improve the Value of U.S. Geothermal Electricity Generation Through Flexible Operations

Geothermal power plants have typically been operated as baseload plants. The recent expansion of wind and solar power generation creates a potential opportunity to increase the value of geothermal generation through flexible operations. In recent years, California’s wholesale electricity markets have exhibited frequent, short-term periods of negative pricing, indicating that additional flexibility would be valued in the market. Here, we examine local nodal hourly price records at all geothermal plants located in the western United States. We describe how the frequency and temporal characteristics of negative pricing episodes have changed over recent years. Based on these price series, we calculate the value of multiple strategies of flexible operations. Additionally, we use the estimates of future prices, developed through a capacity-expansion model and a dispatch model, to explore how the value of such flexible operations might change along with further penetration of variable renewable power sources. Based on the historical pricing records, we find that simple curtailment of operations during negative pricing episodes could increase the average energy value by 1–2 dollars per MWh and that allowing for increased production during limited high-priced hours, in addition to curtailment during negative priced hours, could potentially double the increase in value (up to 4 dollars per MWh). The forward-looking simulations indicate reduced values of flexibility from geothermal power despite higher penetrations of variable renewable energy. This result highlights the possibility that increasing flexibility options throughout the system may counteract the influence of increased variable renewable energy deployment.

15 GEOTHERMAL ENERGY↗

"A" is for Ammonia: Why and How Fertilizer May Power the Planet [Slides]

Ammonia (chemical formula NH3) is so pervasive in our history that human beings simply wouldn't exist without it: 4 billion people on this planet are fed by food grown using ammonia fertilizer, but this powerful molecule consumes nearly 2% of the world's energy supply to be produced at an industrial scale. This talk will first explore the energy challenges of ammonia's current means of industrial production, followed by a new vision for its synthesis using only renewable electricity, air and water, and opportunities to use ammonia as a hydrogen source. Fertilizer may one day fuel more than just our mouths.

08 HYDROGEN↗