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At least 361 records · Page 20

Development of a calculation framework coupling Monte Carlo neutronics, subchannel thermal-hydraulics and 1.5D fuel thermo-mechanics

A coupled calculation system consisting of the Monte Carlo neutronic solver SERPENT and the fuel behaviour solver TRANSURANUS was extended with the sub-channel thermal-hydraulic solver SUBCHANFLOW to form a coupled calculation framework for multi-physics reactor analyses. The coupling between the 3 solvers was accomplished via a driver program written in Perl that runs the solvers, processes and transfers the output data between the solvers and monitors the convergence. While some features of the coupling are still under development, a steady-state coupled calculation resulting in convergence was performed for a single hexagonal fuel assembly to demonstrate that the base functionalities work as expected. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Remote quantum state transfer for qubits with different frequencies

A quantum communication system includes a first quantum transceiver, a second quantum transceiver, and a quantum communication mediator (QCM) system. The transceivers have different resonant frequencies or physical systems. The QCM system receives an initial quantum signal from the first quantum transceiver. The QCM system transfers a quantum state of the initial quantum signal to a first mechanical signal and then from the first mechanical signal to a first pair of optical signals by way of a first three-wave mixing process. The QCM transfers the quantum state to a second pair of optical signals from the first pair by way of a four-wave mixing process. The QCM transfers the quantum state from the second pair of optical signals to a second mechanical signal by way of a second three-wave mixing process. The QCM transfers the quantum state from the second mechanical signal to a final quantum signal by mechanical transduction.

Soh, Daniel Beom Soo↗

Process intensification approach to enhancing heat and mass transfer: Radio frequency (RF) assisted drying of paper and board

Conventional multi-cylinder drying of paper and board typically relies on both conductive drying from steam-heated cylinders and convective drying, where heated air flows over the paper web surface. Conduction primarily contributes to heat transfer, while convection is the main driver of mass transfer. However, conventional drying systems are heavily dependent on steam, usually powered by fossil fuels, and are often energy-inefficient with high levels of waste. Additionally, these surface-driven processes result in a lower percentage of energy absorption compared to the energy supplied, leading to significant energy losses. To improve this long-standing process, an experimental system was developed to investigate a process intensification approach involving the integration of Radio Frequency (RF) heating, a volumetric electromagnetic technology, alongside traditional conduction and convection drying methods. This study also emphasizes the use of sensors to continuously monitor key parameters such as moisture content, supply system temperatures, sample temperatures, air flows, and drying rates in real-time. The effect of RF as an auxiliary energy source in localized environments at varying moisture levels was explored to optimize industrial drying systems, quantify potential improvements, and provide insights for future studies. Experimental results from trials combining RF with convection and with the base case alternating conduction-convection drying processes are presented. It is shown that RF is a viable process intensification approach for paper drying improving the drying rate and energy intensity at higher moisture contents. These findings offer valuable insights for process intensification and contribute to the process development, modeling, and simulation of advanced paper drying techniques.

42 ENGINEERING↗

Highly Coupled Heterobicycle‐Fused Porphyrin Dimers: Excitonic Coupling and Charge Separation with Coordinated Fullerene, C 60

Abstract Porphyrin dimers have been widely explored and studied owing to their importance in photosynthetic systems. A vast variety of dimers linked by different groups and at different angles have been synthesized and studied; however, the means by which to synthesize rigidly fused porphyrins with direct conjugation of the chromophores remains limited. Such a class of porphyrins may possess interesting properties that unconjugated or stacked dimers may not exhibit. In this study, bisbenzimidazole‐fused porphyrin dimers and their mono‐ and bis−zinc derivatives are synthesized and characterized. As a consequence of excitonic coupling, these dimers exhibit a split Soret band irrespective of the metal ion in the porphyrin cavity. Steady‐state fluorescence and excitation spectra followed by femtosecond transient absorption spectral studies of the heterometallated dimer, (free‐base and zinc porphyrin) reveals the occurrence of efficient singlet‐singlet energy transfer (>95 % efficiency and rate constant >10 12 s −1 ) within the dyad. Further, donor‐acceptor conjugates were formed by metal‐ligand axial coordination of phenyl imidazole functionalized C 60 and were characterized by a variety of physicochemical techniques. Excited state charge separation from both singlet and triplet excited states of ZnP in the conjugates has been established. The lifetime of the final charge‐separated state was in the 30–40 μs range revealing charge stabilization. Interestingly, no charge separation in the conjugate derived from the heterometallated dimer was observed wherein excitation transfer dominated the process. The present study brings out the importance of the rigid π‐spacer connecting porphyrin dimers in governing the energy and electron transfer events when coupled with an electron acceptor.

Chemistry↗

Process intensification approach to enhancing heat and mass transfer during drying: Ultrasonic (US) assisted drying of paper and board

Drying of paper and board is conventionally achieved through alternating conduction (steam-heated cylinders) and pocket convection (heated air over the paper web surface). These conventional drying systems rely heavily on steam from fossil fuels, resulting in inefficiencies, high energy usage, and thermal losses due to surface-driven mechanisms. Here, to address these challenges, an experimental system, with in-situ drying characteristics measurements, was developed to investigate process intensification using ultrasonic-based dewatering—a volumetric, pressure-driven acoustic energy system—integrated with conventional drying. The objectives of this study are to assess the impact of ultrasonics (US) on dewatering; compare performances to conventional drying systems; identify improvements in drying rate and energy use as a function of moisture content; and gain potential insights on heat and mass transfer mechanisms during US-assisted drying. US performance was evaluated across frequencies, power levels, pulp types, and basis weights. Results show that improvements to ultrasonic applications in conjunction with convection were 30-43% in drying rate and 20-35% in drying time over continuous and intermittent applications. When combined with conduction and convection, ultrasonics yielded up to 20% improvement in both rate and time and up to 20% reduction in energy consumption. Observations support a hypothesis of extension of the constant rate period due to improved capillary flow at higher moisture content and enhancing vapor diffusion and boundary layer disruption at lower moisture contents during falling rate period. These findings will inform future modeling, simulation, design and optimization of advanced drying systems.

42 ENGINEERING↗

Design of an Additively Manufactured Recuperator With 800 °C Inlet Temperature for sCO2 Power Cycle Application

Abstract Recuperators with design temperatures at and above 800 °C can further increase the thermal efficiency of supercritical CO2 power cycles by enabling higher turbine exhaust temperatures. Mar-M247 is a well-suited nickel-based superalloy for high temperature service due to its high creep strength that prevents excessive material thickness being required for pressure containment. Additive manufacturing using a high-speed laser-directed energy deposition (L-DED) process presents a promising solution, with build trials demonstrating the ability to produce nonconventional flow channels for enhanced heat transfer. A design process is presented that includes aerothermal and mechanical evaluation to maximize performance within the constraints of the manufacturing process. A 2-D heat transfer network and pressure drop code allows prediction of flow distribution and its effect on overall thermal performance. Established literature correlations, along with CFD simulation, inform the prediction of heat transfer coefficients and friction factors for the flowpaths and enhancement features in the heat exchanger core. Mechanical evaluation using finite element analysis (FEA) modeling with the intent of the ASME Boiler & Pressure Vessel Code (BPVC) Section VIII, Div. 2 assesses the operational safety of the design. The detailed design features annular finned passages that take advantage of helical flow paths to distribute the flow from separated headers to shared heat transfer surfaces. Performance predictions for the recuperator at a 50 kW scale provide insights into the feasibility of the additively manufactured (AM) process to produce recuperators on a commercial scale that extend existing operating envelopes.

Engineering↗

Sharing is caring: An extensive analysis of parameter-based transfer learning for the prediction of building thermal dynamics

In recent years deep neural networks have been proposed as a lightweight data-driven model to capture high-dimensional, nonlinear physical processes to predict building thermal responses. However, the need of a large amount of data for the training process of deep neural networks clashes with the potential limited data availability in most existing or new buildings. Transfer learning aims to enhance the performance of a target learner exploiting knowledge from related and similar environments. This study conducted a suite of experiments that leveraged 250 data-driven models based on a synthetic dataset of a building archetype to study the influence of data availability, energy efficiency level, occupancy and climate for the transfer process of thermal dynamics. The performance of the transfer learning process was compared against a classical machine learning approach. Here, the results suggest that building thermal dynamics can be effectively transferred under the same climatic conditions, increasing performance when dealing with different occupancy schedules, efficiency levels and low data availability. Furthermore, the paper compares the performance of both transfer learning and machine learning approaches in an online fashion, to support the implementation in real-world deployment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Visible-Light-Initiated Free-Radical Polymerization by Homomolecular Triplet-Triplet Annihilation

Polymerization reactions initiated by ultraviolet light are ubiquitous in scores of industrial applications but would markedly benefit from visible-light activation to overcome stability, energy consumption, light penetration, and sample geometry limitations. The current work leverages visible-light-driven homomolecular triplet-triplet annihilation (TTA) in zinc(II) meso-tetraphenylporphyrin (ZnTPP) to initiate facile free-radical polymerization in trimethylolpropane triacrylate (TMPTA) and methyl acrylate (MA) monomers through ultrafast electron transfer quenching. Selective Q-band (S 1 ) excitation of ZnTPP in the green or yellow sensitizes TTA occurring between two 3 ZnTPP* energized chromophores, ultimately generating the highly reducing S 2 excited state on one ZnTPP molecule (E red = –2.13 V versus saturated calomel electrode, SCE). Subsequently, this S 2 state engages in electron transfer with TMPTA or MA, thereby initiating the radical polymerization process. Bimolecular electron transfer was confirmed through optically gated fluorescence upconversion. In conclusion, FT-IR and EPR spin-trapping experiments verified visible-light-initiated polymerization leading to the formation of well-defined macro- and microscopic objects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Charge transfer driven by ultrafast spin transition in a CoFe Prussian blue analogue

Photoinduced charge-transfer is an important process in nature and technology and is responsible for the emergence of exotic functionalities, such as magnetic order for cyanide-bridged bimetallic coordination networks. Despite its broad interest and intensive developments in chemistry and material sciences, the atomic-scale description of the initial photoinduced process, which couples intermetallic charge-transfer and spin transition, has been debated for decades; it has been beyond reach due to its extreme speed. In this work we study this process in a prototype cyanide-bridged CoFe system by femtosecond X-ray and optical absorption spectroscopies, enabling the disentanglement of ultrafast electronic and structural dynamics. Our results demonstrate that it is the spin transition that occurs first on the Co site within ~50 fs, and it is this that drives the subsequent Fe-to-Co charge-transfer within ~200 fs. This study represents a step towards understanding and controlling charge-transfer-based functions using light.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Product selectivity and mass transport in levulinic acid transfer hydrogenation by monolithic MIL-100, MIL-88B and ZIF-8@Pd MOFs

The diffusion processes between adsorbent and adsorbate naturally play a significant role in the efficiency and selectivity of the heterogenous catalytic process. This paper considers the importance of diffusion processes in the transfer hydrogenation reaction of levulinic acid to γ-valerolactone by MIL-88B, MIL-100, and ZIF8@Pd monolithic catalysts. Over a period of five catalytic cycles, it was shown that the Fe-based catalysts can achieve similar conversions to the ZIF-8 supported Pd, with the only current limitation being the lower aqueous stability of these MOFs. Diffusion constants were calculated using the ZLC method, with micropore diffusion limitation found for ZIF-8 and MIL-100 monolithic frameworks at 2.7 x 10 -8 and 4.6 x 10 -8 cm 2 s -1 respectively. This diffusion limitation was also confirmed by IR spectroscopy with an increasing concentration of C—H bands on the MOF substrate post-reaction. Mass transfer coefficients, also calculated by ZLC, revealed increased mass transport for the hydrophobic ZIF-8 framework, which perhaps aids in the γ-valerolactone selectivity over side products that are produced in the absence of catalytic material, as seen for MIL-88B and MIL-100 after multiple uses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Assessing horizontal gene transfer in the rhizosphere of Brachypodium distachyon using fabricated ecosystems (EcoFABs)

ABSTRACT Horizontal gene transfer (HGT) is a major process by which genes are transferred between microbes in the rhizosphere. However, examining HGT remains challenging due to the complexity of mimicking conditions within the rhizosphere. Fabricated ecosystems (EcoFABs) have been used to investigate several complex processes in plant-associated environments. Here we show that EcoFABs are efficient tools to examine and measure HGT frequency in the rhizosphere. We provide the first demonstration of gene transfer via a triparental conjugation system in the Brachypodium distachyon rhizosphere in an EcoFAB using Pseudomonas putida KT2440 as both donor and recipient bacterial strain with the donor containing a mobilizable and non-self-transmissible plasmid. We observed that the frequency of plasmid transfer in the rhizosphere is potentially dependent on the plant developmental stage and the composition and amount of root exudates. The frequency of plasmid transfer also increased with higher numbers of donor cells. We demonstrate the transfer of plasmid from P. putida to another B. distachyon root colonizer, Burkholderia sp. OAS925, showing HGT within a rhizosphere microbial community. Environmental stresses also influenced the rate and efficiency of HGT in the rhizosphere between different species and genera. This study provides a robust workflow to evaluate transfer of engineered plasmids in the rhizosphere when such plasmids are potentially introduced in a field or other plant-associated environments. IMPORTANCE We report the use of EcoFABs to investigate the HGT process in a rhizosphere environment. It highlights the potential of EcoFABs in recapitulating the dynamic rhizosphere conditions as well as their versatility in studying plant-microbe interactions. This study also emphasizes the importance of studying the parameters impacting the HGT frequency. Several factors such as plant developmental stages, nutrient conditions, number of donor cells, and environmental stresses influence gene transfer within the rhizosphere microbial community. This study paves the way for future investigations into understanding the fate and movement of engineered plasmids in a field environment.

Priya, Shweta↗

Organic Microbial Electrochemical Transistor Monitoring Extracellular Electron Transfer

Abstract Extracellular electron transfer (EET) denotes the process of microbial respiration with electron transfer to extracellular acceptors and has been exploited in a range of microbial electrochemical systems (MESs). To further understand EET and to optimize the performance of MESs, a better understanding of the dynamics at the microscale is needed. However, the real‐time monitoring of EET at high spatiotemporal resolution would require sophisticated signal amplification. To amplify local EET signals, a miniaturized bioelectronic device, the so‐called organic microbial electrochemical transistor (OMECT), is developed, which includes Shewanella oneidensis MR‐1 integrated onto organic electrochemical transistors comprising poly(3,4‐ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) combined with poly(vinyl alcohol) (PVA). Bacteria are attached to the gate of the transistor by a chronoamperometric method and the successful attachment is confirmed by fluorescence microscopy. Monitoring EET with the OMECT configuration is achieved due to the inherent amplification of the transistor, revealing fast time‐responses to lactate. The limits of detection when using microfabricated gates as charge collectors are also investigated. The work is a first step toward understanding and monitoring EET in highly confined spaces via microfabricated organic electronic devices, and it can be of importance to study exoelectrogens in microenvironments, such as those of the human microbiome.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nonthermal Ionization of Kilonova Ejecta: Observable Impacts

The characteristic rapid rise and decline at optical wavelengths of a kilonova is the product of the low ejecta mass (≲0.05 M ⊙ ) and high ejecta velocity (≳0.1c). We show that, even at very early times (≲2 days), regions of ejecta fall below critical density and temperature thresholds at which nonlocal thermodynamic equilibrium (NLTE) effects become important. Here, we present an approximate method for calculating the ionization state of the ejecta that accounts for the NLTE impact of high-energy electrons produced in the beta decay of freshly synthesized r-process elements. We find that incorporating ionization from high-energy electrons produces an “inverted” and “blended” ionization structure, where the most highly ionized species are located in the fastest moving homologous ejecta, and multiple ionization states coexist. In radiation transport calculations, the higher degree of ionization reduces line blanketing in optical bands, leading to improved agreement with the light-curve properties of AT 2017gfo, such as the duration, decay rates, brightness, and colors. Our quasi-NLTE implementation helps to alleviate tensions in kilonova modeling: for high-velocity (∼0.3 c) ejecta components, our models require less mass for a given peak brightness in optical bands, by as much as a factor of 3; our models can explain the presence of observed features associated to Sr II, W III, Se III, and Te III under conditions where LTE models would predict only neutral species; and we naturally predict the coexistence of species like Sr II and Ce III without the need for fine-tuning of the ejecta properties.

High energy astrophysics↗

Carbon Capture through Membranes - Leveraging Multiphysics Modeling, Dimensional Analysis and Machine Learning to Scale up and Optimize Devices and Processes for Decarbonization

We study the separation performance using membrane modules through dimensional analysis (DA). We formulate the main process equations to identify relevant dimensionless numbers inherent in the physics. In particular, we identify that the critical step in the separation process is mass transfer through the selective layer. Remarkably, the dimensionless feed flow (DFfeed) emerges as a crucial factor in describing this process. Not only does DFfeed directly appear in the governing equations, but it also holds a physical significance associated with the time scales for the mass transfer across the feed side and through the selective layer. Regarding the output performance variables, we consider the recovery, stage cut, productivity and purity. In this context, we profit from experimental data and CFD simulations to evaluate the separation performance of the modules when varying the input flowrate, the scale of the module, and the CO2 permeance. These datasets enable us to establish correlations between performance metrics and the dimensionless feed flow (DFfeed). Using simple power functions of DFfeed, we obtain R2 coefficients exceeding 0.99, indicating the accuracy of the correlations built in the present work. In the future, we wish to use DA to understand key transport mechanisms, predict and control module performance, and challenge the universality of these findings by testing various gas separations across different membrane modules beyond our case study.

Pedrozo, Hector A.↗

Modeling and Scaling up of Membrane Modules Leveraging Dimensional Analysis

In the current analysis, we study the separation performance using membrane modules through dimensional analysis (DA). We formulate the main process equations to identify relevant dimensionless numbers inherent in the physics. In particular, we identify that the critical step in the separation process is mass transfer through the selective layer. Remarkably, the dimensionless feed flow (DFfeed) emerges as a crucial factor in describing this process. Not only does DFfeed directly appear in the governing equations, but it also holds a physical significance associated with the time scales for the mass transfer across the feed side and through the selective layer. Regarding the output performance variables, we consider the recovery, stage cut, productivity and purity. In this context, we profit from experimental data and CFD simulations to evaluate the separation performance of the modules when varying the input flowrate, the scale of the module, and the CO2 permeance. These datasets enable us to establish correlations between performance metrics and the dimensionless feed flow. Using simple power functions of DFfeed, we obtain R2 coefficients exceeding 0.99, indicating the accuracy of the correlations built in the present work. In the future, we wish to use DA to understand key transport mechanisms, predict and control module performance, and challenge the universality of these findings by testing various gas separations across different membrane modules beyond our case study.

Pedrozo, Hector A.↗

Comprehensive Analysis of the Relative Dispersion of Droplet-Size Distributions and Their Relationships to Key Physical Fog Processes Under Different Aerosol Conditions and Evolutionary Stages

The relative dispersion of cloud and fog droplets has significant impacts on aerosol indirect effects, radiative transfer, and microphysical processes. However, previous studies have been mostly concerned with clouds, with limited studies on fog, particularly those that examine the combined influences of all key physical processes and their roles during fog evolution. As such, this study aims to conduct a comprehensive investigation by examining the relationships between relative dispersion and other microphysical variables, as well as the underlying microphysical and dynamic processes, based on field fog campaigns in polluted and clean conditions. In polluted fog, droplet concentrations are higher, leading to smaller droplets and increased dispersion. The correlation between dispersion and droplet volume-mean radius is positive in the polluted fog, but shifts to negative in clean fog. Here, we attribute the difference to various microphysical processes like aerosol activation, condensation, collision-coalescence, and entrainment-mixing. In polluted fog, high aerosol concentrations, low supersaturations, and strong turbulence (entrainment-mixing) provide suitable conditions for the simultaneous occurrence of droplet condensation and aerosol activation, resulting in a positive correlation between dispersion and volume-mean radius, especially during the fog formation stage. In contrast, during the mature stage in clean fog, condensation is dominant with weak aerosol activation leading to a negative correlation between relative dispersion and volume-mean radius. The collision-coalescence process is more active in the mature stage, increasing radii and leading to the negative correlation between dispersion and volume-mean radius. This result sheds new light on understanding the relative dispersion and mechanisms in fog under different aerosol backgrounds.

54 ENVIRONMENTAL SCIENCES↗

Toward memory-efficient melt pool monitoring: a classification framework using event-based imaging and sparse sensing technique

Vision sensors like CMOS and CCD cameras are often used for in-process monitoring of melt pools in laser-based additive and welding processes, but they require transferring large amounts of data and computational processing resources. Event-based neuromorphic imagery, on the other hand, detects only the change in pixel intensity, thus potentially reducing the data amount and latency. With an event imager, this study develops a framework for melt pool condition classification, including image construction, time scale selection, optimal pixel selection, and sparse classification, to achieve a highly memory-efficient scheme. These are based on sparse sensing techniques with singular value decomposition (SVD) and QR pivoting, the two fundamental matrix transformations for linear dimensionality reduction. The framework is then validated by classifying a controlled experiment by exciting various mode shapes of liquid gallium pools of varying depths (3, 6, and 8 mm). At 200 pixels, the classifier can reach overall accuracy of 75%, while at 2000 pixels (0.013% of the total possible pixels), the accuracy is nearly 90% (89.86%). At the same number of pixels, random selection can only achieve 46% and 67%, respectively. The memory savings of the sparsely sampled event data compared to a conventional imager is about 500 times. In addition to performance, implementation and limitations of the framework are also discussed.

42 ENGINEERING↗