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At least 865 records · Page 48

Understanding Carbon Dioxide Transfer in Direct Methanol Fuel Cells Using a Pore-Scale Model

Abstract The gas flow of carbon dioxide from the catalyst layer (CL) through the microporous layer (MPL) and gas diffusion layer (GDL) has great impacts on the water and fuel management in direct methanol fuel cells (DMFCs). This work has developed a liquid–vapor two-phase model considering the counter flow of carbon dioxide gas, methanol, and water liquid solution in porous electrodes of DMFC. The model simulation includes the capillary pressure as well as the pressure drop due to flow resistance through the fuel cell components. The pressure drop of carbon dioxide flow is found to be about two to three orders of magnitude higher than the pressure drop of the liquid flow. The big difference between liquid and gas pressure drops can be explained by two reasons: volume flowrate of gas is three orders of magnitude higher than that of liquid; only a small fraction of pores (<5%) in hydrophilic fuel cell components are available for gas flow. Model results indicate that the gas pressure and the mass transfer resistance of liquid and gas are more sensitive to the pore size distribution than the thickness of porous components. To buildup high gas pressure and high mass transfer resistance of liquid, the MPL and CL should avoid micro-cracks during manufacture. Distributions of pore size and wettability of the GDL and MPL have been designed to reduce the methanol crossover and improve fuel efficiency. The model results provide design guidance to obtain superior DMFC performance using highly concentrated methanol solutions or even pure methanol.

Electrochemistry↗

High- and Mid-Fidelity Modeling Comparison for a Floating Marine Turbine System

There is a lack of suitable numerical tools, particularly open-source tools, that can be used for designing and optimizing marine turbine systems. The National Renewable Energy Laboratory has added features to their widely used mid-fidelity wind turbine modeling code, OpenFAST, to enable modeling of axial-flow marine turbines. This necessitated the addition of several physical effects relevant to marine turbines that are neglected for wind turbines. These include buoyancy, added mass and inertial loads, wave-current superposition, and changes to the coordinate systems. This updated version of OpenFAST allows for the modeling of both fixed and floating marine turbines at a speed comparable to real time. While efficient for large sets of load cases and design studies, mid-fidelity codes make simplifying assumptions that may impact their accuracy. High-fidelity computational fluid dynamics (CFD) simulations can capture more flow effects with fewer assumptions and provide detailed body pressure mapping and flow-field information. It is important to compare predictions between mid-fidelity and high-fidelity codes, both to verify the models and to understand the limitations. A floating marine turbine system was modeled both with OpenFAST and with the commercial CFD code STAR-CCM+. The CFD model used a three-dimensional unsteady Reynolds-averaged Navier-Stokes solver for a volume-of-fluid numerical wave and current tank. The blade-resolved simulations used the sliding-interface technique for the spinning rotor and an overset grid to accommodate the rigid-body motion of the floating system. The mooring system was modeled with a custom coupling of the CFD solver with the open-source code MoorDyn. This improves upon the existing quasi-static catenary solver in STAR-CCM+, which lacks seabed contact or line-to-line connections. Simulation results for a floating marine turbine are compared between OpenFAST and CFD, highlighting the capabilities of the mid-fidelity code and identifying the areas where a high-fidelity approach is needed.

CFD↗

MBMS1.0: An Open-Source Code for Modeling and Simulation of Membrane-Based Dehumidification and Energy Recovery

Membrane-based dehumidification is currently being considered as a promising solution for the building application due to its low cost and very limited energy consumption. Developing a simple and efficient open-source code simulation tool is important for boosting the optimization and evaluation of such device in HVAC community. This paper reports a first-order physics based model which accounts for the fundamental heat and mass transfer of humid-air vapor at feed side to flow stream at permeate side. The current model comprises two membrane mass transfer submodels (i.e. microstructure model and performance map model); and it adopts a segment-by-segment methodology for discretizing heat and mass transfer governing equations. The model is capable of simulating both dehumidifiers and energy recovery ventilators with parallel-flow cross-flow, and counter-flow configurations. The model was validated with the measurements at appropriate device. The practices in dehumidification and energy recovery exchangers are also discussed. The model and open-source codes are expected to become a solid fundament for developing a more comprehensive and accurate membrane-based dehumidification in the future.

Gao, Zhiming↗

Data for "Enhancing Lipid Production in Plant Cells through Automated High-Throughput Genome Engineering and Phenotyping"

Plant bioengineering is a time-consuming and labor-intensive process with no guarantee of achieving desired traits. Here, we present a fast, automated, scalable, high-throughput pipeline for plant bioengineering (FAST-PB) in maize (Zea mays) and Nicotiana benthamiana. FAST-PB enables genome editing and product characterization by integrating automated biofoundry engineering of callus and protoplast cells with single-cell matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). We first demonstrated that FAST-PB could streamline Golden Gate cloning, with the capacity to construct 96 vectors in parallel. Using FAST-PB in protoplasts, we found that PEG2050 increased transfection efficiency by over 45%. For proof-of-concept, we established a reporter-gene-free method for CRISPR editing and phenotyping via mutation of high chlorophyll fluorescence 136. We show that diverse lipids were enhanced up to 6-fold using CRISPR activation of lipid controlling genes. In callus cells, an automated transformation platform was employed to regenerate plants with enhanced lipid traits through introducing multigene cassettes. Lastly, FAST-PB enabled high-throughput single-cell lipid profiling by integrating MALDI-MS with the biofoundry, protoplast, and callus cells, differentiating engineered and unengineered cells using single-cell lipidomics. These innovations massively increase the throughput of synthetic biology, genome editing, and metabolic engineering and change what is possible using single-cell metabolomics in plants.

AI/ML↗

Field Performance of Commercial Building Load Flexibility Using Model Predictive Control

Model Predictive Control (MPC) applied to buildings is starting to see some commercial adoption by companies. However, it is hard to estimate if relative energy cost savings are enough to justify the cost of MPC implementation with few reported demonstrations. In small commercial and residential buildings, a one size-fits-all solution can help reduce implementation costs, while in very large buildings or districts the potential energy cost savings magnitude can cover more tailored solutions. This estimation becomes harder for medium to large commercial buildings, where a one-size-fits-all solution cannot be adopted and potential energy cost savings might not be sufficient to cover a tailored solution. Therefore, value propositions in addition to energy efficiency alone can make MPC technology more attractive through additional energy cost savings. One such value proposition is load shifting in response to dynamic electricity prices. On this aspect, MPC is a key technology to unlock building thermal mass for energy flexibility in response to electric grid conditions. This study shows the experimental results of MPC control of an office building in Berkeley, where different dynamic electricity price profiles were used in the MPC objective function to shift the building load and to calculate hypothetical electricity costs. Results show potential 50% cost savings with respect to the existing controller with the dynamic price scenario.

Zanetti, Ettore↗

A Machine Learning Model for Predicting Composition of Catalytic Coprocessing Products from Molecular Beam Mass Spectra

Demand for the development of an automated and integrated refining process for biofuels has increased in recent years due to the lack of generalized process inspection tools. In bio-oil upgrading processes, all process variables are maintained based on the offline specification of intermediates and products. A lack of real-time product specifications in batch-wise monitoring can cause process failure and wasted resources. Therefore, there is a need for a fast and accurate intermediates/product specification tool that can be used for real-time specification to reduce waste and mitigate the risk of process failure. Here, to address this gap, we developed a machine learning (ML) model for predicting speciated bio-oil composition, including paraffin, iso-paraffins, olefins, naphthene, and aromatics. The model is trained using the mass spectra from upgraded products collected in the vapor phase before condensation and predicts the composition of the condensed product. Training ML models using raw mass spectra is challenging due to numerous overlapped peaks originating from different parent compounds. With this in mind, we propose a protocol that (i) transforms raw mass spectra to chemistry-inspired predefined features and (ii) trains decision tree-based models using these features. Our results show that the random forest model was robust against overfitting and had the highest accuracy compared to other models. Moreover, a stochastic ablation method determined the eight most significant features while maximizing the accuracy. Our protocol facilitates real-time compositional analysis of upgraded bio-oils and thus real-time process monitoring. Additionally, this protocol enables the rational design of efficient catalysts and the determination of optimal process conditions.

09 BIOMASS FUELS↗

Regeneration of anion-exchange resins for cyclic selenium removal from industrial wastewaters

Application of ion exchange for the removal of selenium (Se) oxyanions from industrial wastewaters is often limited by ineffective regeneration of the ion-exchange resins, particularly in complex systems containing competing ions, such as coal-ash leachate containing high-sulfate concentrations and heavy metal ions. Here, in this study, it was first demonstrated that while conventional regeneration with sodium chloride (NaCl) is effective for simulated wastewater, with ∼80% efficiency, NaCl fails to regenerate resin loaded with real industrial wastewater, achieving less than 20% efficiency. To overcome this challenge, a two-step regeneration process was investigated using a sodium carbonate (Na 2 CO 3 ) solution for elution, followed by a NaCl solution for restoration. Compared to the one-step NaCl regeneration, this integrated process restored more than 80% of the resin's capacity with real industrial wastewaters. Beyond demonstrating regeneration performance, this research emphasizes fundamental mechanistic interpretations of the observed regeneration behavior across different water matrices and experimental conditions. Particularly, accounting for pH-dependent carbonate speciation, it is proposed that the elution step exploits the resin's strong affinity for divalent carbonate ions to displace strongly bound contaminants, while the subsequent restoration step relies mainly on the mass action effects of chloride ions to regenerate the resin sites. The protocol was optimized to achieve rapid regeneration (<10 min) using moderate chemical concentrations (0.5 M) in treating real leachate. In batch cyclic experiments, Se regeneration reached nearly complete recovery after five consecutive sorption and desorption cycles, while in the fixed-bed system, the regeneration efficiency remained at approximately 80% after five cycles.

Anion-exchange resin↗

Particle Handling in Particle-Based Pumped Thermal Energy Storage

A particle-based pumped thermal electricity storage system stores high-temperature heat (~1000 degrees C) in low-cost silica sand and generates power through an efficient power cycle. Central to this system is a counterflow direct-contact gas/particle fluidized-bed heat exchanger, which can significantly improve the heat exchange process due to the large heat transfer surface area of particles. To showcase a lab-scale 10- to 20-kWe heat exchange process with particles heating up to 300 degrees C, a comprehensive hydrodynamic analysis of the fluidization condition inside the heat exchanger was conducted. The heat exchanger was designed to target for heat exchange process of 10-20 kW and accommodate an air mass flow rate of 0.3-0.7 kg/s. The fluidization condition was set to maintain stable bubbling fluidization, thereby maximizing the particle-to-air heat transfer. An air distributor was designed to equally distribute air over the bed, which can avoid defluidized zones in the heat exchanger. Additionally, particle handling systems including L-valves, screw conveyors, and pneumatic conveyors were developed for the prototype heat exchanger, efficiently conveying high-temperature particles at 0.2-0.5 kg/s. This work lays the foundation for scaling up the system and integrating it into larger energy storage applications, demonstrating its potential for efficient, high-temperature thermal energy storage and power generation.

25 ENERGY STORAGE↗

Production and Catalytic Upgrading of 2,3-Butanediol Fermentation Broth into Sustainable Aviation Fuel Blendstock and Fuel Properties Measurement

With the increasing demand for sustainable supplies of aviation fuel and need to address climate change, new conversion technologies are needed to efficiently process biomass, produce high quality jet fuel blendstock, and meet carbon emission targets. This study demonstrates the synthesis, conditioning, and catalytic upgrading of 2,3-butanediol (BDO) fermentation broth into a jet fuel blendstock candidate. A high-titer 2,3-BDO fermentation broth (i.e., ~90 g/L) was produced at a 100-L scale and pretreated via nanofiltration to decrease the impurities level in the broth from 4.6 to 0.6 wt%. A novel process for catalytic upgrading of aqueous 2,3-BDO into a jet fuel blendstock candidate was developed, and each step was efficiently demonstrated. The catalytic steps include 1) 2,3-BDO dehydration into methyl ethyl ketone (MEK) over AlPO4, 2) MEK conversion into olefins over Zn1Zr10Ox, 3) oligomerization of olefins over a zeolite beta, and 4) hydrogenation over platinum/carbon. Both the model feed and real 2,3-BDO fermentation broth were tested for upgrading 2,3-BDO to MEK. With the real feed, a continuous loss of conversion (i.e., >50% loss over ~140 h time-on-stream [TOS]) was partly attributed to reversible deactivation from coking species. However, the conversion remained stable with the model feed, which demonstrates the efficiency of the first step for converting aqueous 2,3-BDO (10 wt% in water). For upgrading MEK to olefins, high selectivity to olefins (i.e., 82.5%) was obtained at high conversion levels (i.e., 93-98%) with stable conditions being achieved for > 70-hours TOS. Oligomerization of light olefins, which was demonstrated for > 270 h TOS, mainly led to the formation of dimers (C8-10) and trimers (C13-14). The oligomerized product was hydrogenated and distilled to recover the jet fraction (35 mass% or 40.9% carbon based yield), which consists mostly of desired isoalkanes (31.7 wt%), n-alkanes (24.5 wt%), and cycloalkanes (29.6 wt%). While some improvement is still needed to meet ASTM D7566 specifications for viscosity and final boiling point temperature, freezing point, density, aromatics content, and sulfur content of the jet blendstock candidate were within acceptable ranges, thus highlighting the potential of this process for production of jet fuel blendstock.

ADVANCED PROPULSION SYSTEMS,BIOMASS FUELS↗

Transport–Friendly Microstructure in SSC–MEA: Unveiling the SSC Ionomer–Based Membrane Electrode Assemblies for Enhanced Fuel Cell Performance

The significant role of the cathodic binder in modulating mass transport within the catalyst layer (CL) of fuel cells is essential for optimizing cell performance. This investigation focuses on enhancing the membrane electrode assembly (MEA) through the utilization of a short-side-chain perfluoro-sulfonic acid (SSC-PFSA) ionomer as the cathode binder, referred to as SSC-MEA. This study meticulously visualizes the distinctive interpenetrating networks of ionomers and catalysts, and explicitly clarifies the triple-phase interface, unveiling the transport-friendly microstructure and transport mechanisms inherent in SSC-MEA. The SSC-MEA exhibits advantageous microstructural features, including a better-connected ionomer network and well-organized hierarchical porous structure, culminating in superior mass transfer properties. Relative to the MEA bonded by long-side-chain perfluoro-sulfonic acid (LSC-PFSA) ionomer, noted as LSC-MEA, SSC-MEA exhibits a notable peak power density (1.23 W cm –2 ), efficient O 2 transport, and remarkable proton conductivity (65% improvement) at 65 °C and 70% relativity humidity (RH). These findings establish crucial insights into the intricate morphology-transport-performance relationship in the CL, thereby providing strategic guidance for developing highly efficient MEA.

25 ENERGY STORAGE↗

Active magnetic regenerative cooling with smaller magnets

Magnetocaloric heat pumping near room temperature, a.k.a. magnetic cooling, relies on the active regenerator cycle to achieve functional temperature spans and realize economic and societal benefits promised by this emerging solid-state cooling technology. The cycle itself depends upon synchronizing oscillating flow of a heat transfer fluid through a solid porous active material matrix, or the refrigerant, with periods when the refrigerant is in the highest available (field-on) and in nearly zero (field-off) magnetic fields to accomplish heat transfer. With this in mind, in this work we analyze varying flow and magnetic field wave forms and the timing between when the fluid is pumped and when the magnetic field is turned on and off. We demonstrate that the volume and the cost of permanent magnet generating the field changes can be cut nearly in half with little to no effect on the device temperature span and cooling power normalized by the refrigerant mass.

36 MATERIALS SCIENCE↗

Thermodynamic control on the decomposition of organic matter across different electron acceptors

The increasing availability of high-resolution characterization of natural organic matter (OM) data has shifted the paradigm of lumped descriptions of OM components and potential microbial activities. Our recent development of a substrate-explicit thermodynamic model uniquely enables incorporating complex OM pools to formulate biogeochemical reaction models based on their elemental compositions. While this previous work facilitates prediction of aerobic respiration of complex OM, it is equally imperative to consider the role of non-oxygenic electron acceptors in regulating OM turnover and the fate of carbon. In this study, we significantly expand our previous model by flexibly incorporating both detailed OM chemistry and electron acceptors other than oxygen. Here, our modeling analysis has revealed substantial variations in the energy status of OM molecules across different soils, which drive the co-occurrence of different electron-accepting processes. We demonstrated the effectiveness of the proposed model using a consistency check with experimental data. Through systematic evaluation of the impact of diverse chemical inputs (both electron donors and acceptors) on OM decomposition, the new model also revealed how key microbial growth parameters such as carbon use efficiency (CUE) and reaction rates vary across different electron-accepting processes. Our model provides a unified framework integrating thermodynamic and kinetic constraints on microbial metabolic activities. It complements traditional kinetic models, which are often designed solely to capture mass fluxes. We conclude that thermodynamic modeling emerges as a powerful tool for describing the mechanisms underlying the interplay between microbial growth and OM chemistry and cycling across different electron acceptors, enhancing our ability to project complex ecosystem behaviors in dynamic environments.

59 BASIC BIOLOGICAL SCIENCES↗

Shear Alfvén Waves Driven by Magnetic Reconnection as an Energy Source for the Aurora Borealis

Previous studies have concluded that the Hall magnetic field structures generated during magnetic reconnection are carried away by kinetic Alfvén waves. Here, we apply a kinetic simulation with an ion/electron mass ratio closer to its natural value and find that open boundary conditions and much reduced damping rates permit the shear Alfvén waves (SAWs) to become the main carrier of wave energy. Further, for magnetotail reconnection, these SAWs provide efficient transport of wave energy, enhancing the energy input for the Aurora Borealis by orders of magnitude above previous estimates.

58 GEOSCIENCES↗

Narrow-band high-lying excitons with negative-mass electrons in monolayer WSe2

Monolayer transition-metal dichalcogenides (TMDCs) show a wealth of exciton physics. Here, we report the existence of a new excitonic species, the high-lying exciton (HX), in single-layer WSe 2 with an energy of ~3.4 eV, almost twice the band-edge A-exciton energy, with a linewidth as narrow as 5.8 meV. The HX is populated through momentum-selective optical excitation in the K-valleys and is identified in upconverted photoluminescence (UPL) in the UV spectral region. Strong electron-phonon coupling results in a cascaded phonon progression with equidistant peaks in the luminescence spectrum, resolvable to ninth order. Ab initio GW-BSE calculations with full electron-hole correlations explain HX formation and unmask the admixture of upper conduction-band states to this complex many-body excitation. These calculations suggest that the HX is comprised of electrons of negative mass. The coincidence of such high-lying excitonic species at around twice the energy of band-edge excitons rationalizes the excitonic quantum-interference phenomenon recently discovered in optical second-harmonic generation (SHG) and explains the efficient Auger-like annihilation of band-edge excitons.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Contribution of sewage to occurrence of phosphodiesterase-5 inhibitors in natural water

Phosphodiesterase-5 inhibitors (PDE-5i, such as Sildenafil, Tadalafil and Vardenafil, mainly prescribed to treat erectile dysfunction) and their generic drug equivalents have been widely marketed and consumed in Korea. From the concentrations detected in wastewater, we could deduce that relatively large amounts of PDE-5i were consumed without a legal prescription. Thus, PDE-5i’s presence in the environment via sewage is unavoidable, and their environmental fate within a sewage treatment plant (STP) should be evaluated. In this study, we investigated the occurrence of three PDE-5i analogs in the influent and effluent of two STPs and the receiving water bodies. The PDE-5i concentration in total reached 62 ± 12 (STP#1) and 88 ± 37 ng L -1 (STP#2) in the sewage influent; about 70% of it was Sildenafil in both STPs. However, they were hardly removed by the STPs as the removal efficiency of the STPs was less than 10% ± 5%. Therefore, the pharmaceuticals were detected in the receiving water (lower than 7 ng L -1 as a total amount) and the concentration slightly increased downstream of the STPs. A simple mass balance model applied for the compounds in the STP effluent and receiving water bodies also confirmed that the discharged PDE-5i were quite persistent. Lastly, we identified temporal and regional patterns in the consumption of the drugs from daily variations of PDE-5i in the influent to these two STPs. For instance, the levels of PDE-5i in the sewage significantly increased on weekends (from Friday to Saturday), and especially in the area where adult-entertainment businesses are common. We estimated that the amount of PDE-5i consumption in this area was 31% higher than that in the area with fewer nightlife spots. Considering that they are pharmaceutically active and resistant to treatment processes within an STP, it is advised that a regular monitoring and management program for PDE-5i should be developed to prevent the discharge of the pharmaceuticals into the water environment.

54 ENVIRONMENTAL SCIENCES↗

A technique for studying (n,p) reactions of astrophysical interest using radioactive beams with SECAR

The formation of nuclei in slightly proton-rich regions of the neutrino-driven wind of core-collapse supernovae could be attributed to the neutrino-p process (νp-process). As it proceeds via a sequence of (p,γ) and (n,p) reactions, it may produce elements in the range of Ni and Sn, considering adequate conditions. Recent studies identify a number of decisive (n,p) reactions that control the efficiency of the νp-process. The study of one such (n,p) reaction via the measurement of the reverse (p,n) in inverse kinematics was performed with SECAR at NSCL/FRIB. Proton-induced reaction measurements, especially at the mass region of interest, are notably difficult since the recoils have nearly identical masses as the unreacted projectiles. Such measurements are feasible with the adequate separation level achieved with SECAR, and the in-coincidence neutron detection. Adjustments of the SECAR system for the first (p,n) reaction measurement included the development of new ion beam optics, and the installation of the neutron detection system. The aforementioned developments along with a discussion on the preliminary results of the p(58Fe,n)58Co reaction measurement are presented.

Tsintari, P↗

Investigating Electro-Nuclear Interactions in a New Dark Matter Search

Electro-nuclear (EN) interactions are interactions in which an incident electron collides with a nucleus, scattering the electron and creating byproduct particles. Such interactions are of interest to neutrino physicists, who use EN interactions to inform model building of neutrino-nucleus interactions. The Light Dark Matter Experiment (LDMX) is a small-scale, fixed-target, electron beam experiment which seeks to probe for dark matter and mediator particle production in the sub-GeV mass region. The 8GeV LDMX electron beam will serve as an opportunity to study electro-nuclear interactions in their final states in the multi-GeV region. LDMX’s missing energy trigger however, will not be sufficient to efficiently capture EN interactions. An additional trigger needs to be created. Using simulated background events, including EN interactions, for the LDMX experiment, a trigger on momentum was developed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Intensification and Integration of Hydrogen and Ammonia Production

In this project the Colorado School of Mines developed a more efficient method for on-site and on-demand generation of high purity hydrogen from ammonia for hydrogen fueling stations. Used primarily as a fertilizer, ammonia is the world’s highest volume commodity chemical. Having 17.6% hydrogen by mass, it also shows potential as a hydrogen carrier and carbon-free fuel. The team developed new technology to generate fuel cell quality hydrogen from ammonia using a catalytic membrane reactor (CMR). In addition, during the project we pivoted to use this CMR technology for the production of NH3/H2 mixtures for use in clean combustion applications. We demonstrated that these mixtures may serve as a drop-in replacement for conventional hydrocarbons such as natural gas. This project entails development of new catalysts, new membranes, and their innovative integration. This project helped generate >$4M in follow on funding at Mines, and resulted in the formation of a clean tech startup, Blaze Energy Technologies, which has licensed IP developed in this project and is working to commercialize this technology.

08 HYDROGEN↗