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At least 361 records · Page 20

Semi‐Continuous Ex Situ Carbon Dioxide Mineralization in Produced Water for Calcite Production

ABSTRACT The mineralization of carbon dioxide (CO 2 ) to stable carbonate products is a desirable process for carbon capture utilization and storage (CCUS). However, improving the process economics through creative use of available reactants is necessary to develop a scalable mineralization process. This study details the development of a semi‐continuous CO 2 mineralization process that uses flue gas as a point CO 2 source, produced water (PW) as an alkaline source of Ca 2+ , and NaOH effluent (potentially sourced from integration with the chlor‐alkali process. Operating at a controlled pH allowed for both complete reaction of available Ca 2+ (100% carbonation potential or 9.9 g CO 2 .L –1 PW brine) and for reproducible control of the produced calcium carbonate (CaCO 3 ) product. A full factorial design of experiments was implemented to study the effects of reaction temperature, pH, and gaseous CO 2 concentration on the mineralization and CO 2 capture rates as well as product crystalline structure and morphology. A maximum CO 2 capture rate of 0.315 ± 0.007 kg.L –1 .d –1 was achieved at 25°C and 25% CO 2 . CO 2 gas to liquid phase mass transport is believed to be the rate limiting step. With improved reactor design and optimization, the proposed semi‐continuous mineralization process shows promise for scaling to a pilot scale CO 2 capture technology.

Bennett, Quinn [Institute for Sustainable Energy &↗

Demonstrating the Potential of Adaptive LMS Filtering on FPGA-Based Qubit Control Platforms for Improved Qubit Readout in 2D and 3D Quantum Processing Units

Advancements in quantum computing underscore the critical need for sophisticated qubit readout techniques to accurately discern quantum states. This abstract presents our research intended for optimizing readout pulse fidelity for 2D and 3D Quantum Processing Units (QPUs), the latter coupled with Superconducting Radio Frequency (SRF) cavities. Focusing specifically on the application of the Least Mean Squares (LMS) adaptive filtering algorithm, we explore its integration into the FPGA-based control systems to enhance the accuracy and efficiency of qubit state detection by improving Signal-to-Noise Ratio (SNR). Implementing the LMS algorithm on the Zynq UltraScale+ RFSoC Gen 3 devices (RFSoC 4x2 FPGA and ZCU216 FPGA) using the Quantum Instrumentation Control Kit (QICK) open-source platform, we aim to dynamically test and adjust the filtering parameters in real-time to characterize and adapt to the noise profile presented in quantum computing readout signals. Our preliminary results demonstrate the LMS filter's capability to maintain high readout accuracy while efficiently managing FPGA resources. These findings are expected to contribute to developing more reliable and scalable quantum computing architectures, highlighting the pivotal role of adaptive signal processing in quantum technology advancements.

Johnson, Hans↗

Demonstrating the Potential of Adaptive LMS Filtering on FPGA-Based Qubit Control Platforms for Improved Qubit Readout in 2D and 3D Quantum Processing Units

Advancements in quantum computing underscore the critical need for sophisticated qubit readout techniques to accurately discern quantum states. This abstract presents our research intended for optimizing readout pulse fidelity for 2D and 3D Quantum Processing Units (QPUs), the latter coupled with Superconducting Radio Frequency (SRF) cavities. Focusing specifically on the application of the Least Mean Squares (LMS) adaptive filtering algorithm, we explore its integration into the FPGA-based control systems to enhance the accuracy and efficiency of qubit state detection by improving Signal-to-Noise Ratio (SNR). Implementing the LMS algorithm on the Zynq UltraScale+ RFSoC Gen 3 devices (RFSoC 4x2 FPGA and ZCU216 FPGA) using the Quantum Instrumentation Control Kit (QICK) open-source platform, we aim to dynamically test and adjust the filtering parameters in real-time to characterize and adapt to the noise profile presented in quantum computing readout signals. Our preliminary results demonstrate the LMS filter's capability to maintain high readout accuracy while efficiently managing FPGA resources. These findings are expected to contribute to developing more reliable and scalable quantum computing architectures, highlighting the pivotal role of adaptive signal processing in quantum technology advancements.

Johnson, Hans↗

Traffic Signal Control for Large-Scale Urban Traffic Networks: Real-World Experiments using Vision-Based Sensors

Effective control of traffic signals plays a critical role in ensuring smooth vehicle flow in urban areas. Expertly engineered traffic signal controllers can considerably minimize travel delays and enhance sustainability. In this paper, the team proposes the Model Predictive Control (MPC) traffic signal control strategy using real-time traffic flow data from a vision-based camera as feedback information. Also, a realistic signal timing plan that considers National Electrical Manufacturers Association (NEMA) constraints has been developed to be applied to real-world scenarios. The primary aim is to reduce the number of vehicles across all links in the controlled area, thereby optimizing traffic flow and reducing energy consumption. To validate the proposed method, several real-life experiments were conducted at 24 intersections in Chattanooga, Tennessee, by collaborating with traffic field engineers. These experiments demonstrated significant performance improvements in comparison to the existing method.

data processing↗

Autoionizing polaritons with the Jaynes-Cummings model

Intense laser pulses have the capability to couple resonances in the continuum, leading to the formation of a split pair of autoionizing polaritons. These polaritons can exhibit extended lifetimes due to interference between radiative and Auger decay channels. In this work we show how an extension of the Jaynes-Cummings model to autoionizing states quantitatively reproduces the observed phenomenology. Furthermore, this extended model allows us to study how the dressing laser parameters can be tuned to control the ionization rate of the polariton multiplet.

74 ATOMIC AND MOLECULAR PHYSICS↗

Epitaxy of Emerging Materials and Advanced Heterostructures for Microelectronics and Quantum Sciences

Abstract Epitaxy, a process to prepare crystalline materials in nanostructures and thin films, is the core technology for preparing high‐quality materials as a key enabler of next‐generation microelectronics and quantum information system. Progress in epitaxy has been expanding the choice of materials and their heterostructures beyond the combinations limited by materials compatibility. However, the improvement of material quality, physical implementation of materials with unique properties, and integration of incommensurate materials in an architecture have been the challenging issues. Emerging materials, including 2D materials and quantum materials, have opened opportunities to study epitaxy mechanisms and realize various functional devices. Acceleration of discovery and progress in epitaxy research should be accomplished by “understanding of epitaxy under various circumstances at multiple length scales” and “integration of experiments and models.” In the perspective, a basic summary of the status of epitaxially grown materials, the challenges in epitaxy research, and integration of modeling epitaxy and ultimate control of the epitaxy process with advanced characterization techniques are discussed.

Materials Science↗

Efficient BiVO 4 /CoFeO x H y photoanodes using controlled annealing and conformal linear-sweep electrocatalyst photodeposition

Although monoclinic bismuth vanadate (BiVO 4 ) is a promising photoanode for solar water splitting, its practical use is hindered by imperfect photocurrent generation/collection, low photovoltage compared to the bandgap, and corrosion side reactions that limit durability. Here, we introduce a controlled-annealing sol–gel process for BiVO 4 thin-film photoanodes along with an optimized linear-sweep-voltammetry photodeposition of CoFeO x H y cocatalysts. The resulting BiVO 4 films annealed at 550 °C exhibited a photocurrent density of 4.1 mA/cm 2 at 1.23 V RHE under 1 sun AM 1.5G solar simulation and a low onset potential of 0.26 V RHE due to high majority carrier conductivity, a crystalline bulk with reduced defects as evidenced by x-ray photoelectron spectroscopy and photoluminescence lifetime analysis, and thus enhanced photocarrier collection. However, significant degradation in performance was found due to interfacial photocorrosion. To protect the surface and speed the oxygen-evolution reaction CoFeO x H y cocatalyst layers were deposited. By varying the number of consecutive sweeps and adjusting the applied bias range, an ultra-thin (~15 nm) CoFeO x H y cocatalyst layer was uniformly grown deposited over 30 cycles on the BiVO 4 surface. The resulting BiVO 4 /CoFeO x H y yielded 4.03 mA/cm 2 at 1.23 V RHE and onset potential of 0.24 V RHE , with stable operation (~15 % loss in photocurrent at 1.23 V RHE relative to ~60 % loss in the uncatalyzed control sample). These conformal CoFeO x H y catalytic layers function simultaneously to selectively collect photoexcited holes from the BiVO 4 , catalyze the water-oxidation reaction, and protect the BiVO 4 from photodegradation.

42 ENGINEERING↗

Raman Laser-Induced Structural Modification in CVD-Grown Monolayer MoS 2 for Multi-Purposed Nanofabrication

Molybdenum disulfide (MoS 2 ) has been extensively explored to be utilized as an electronic material in a variety of device applications. In particular, the tunability of MoS 2 enhances its electrical properties making it an intriguing candidate for field-effect transistors (FETs), while also extending beyond electrical properties to structural phase engineering. Laser-induced modifications, particularly with Raman lasers, offer a straightforward method to modulate materials via thermal processes with precise patterning control and energy-level flexibility. However, most studies on the modification of MoS 2 have focused on multilayered structures or have been conducted under low-power laser conditions, leaving the feasibility of structural modifications in monolayer MoS 2 elusive. In this study, we fundamentally elucidated the effects of high-power Raman laser irradiation on the surface of chemical vapor deposition (CVD)-grown monolayer MoS 2 under ambient conditions and uncovered the underlying mechanisms of laser-induced modifications by applying intense photon energy with highly interactive reactions. Our results revealed both etching and deposition phenomena in two discernible regions, and it can be demonstrated by intensity regimes based on the spatial distribution of laser irradiance within the laser-irradiated spot. Furthermore, phase transition was found to be inhibited due to the promoted oxidation and the deposition of hydrogenated amorphous carbon (a-C:H), and p-type doping was observed, likely occurring in the region beneath the a-C:H deposition as substitutional doping on the 2H phase of MoS 2 . To compare the thermal effects, MoS 2 modifications were further analyzed using simplified heat transfer estimations. In conclusion, these findings deepen our understanding of how Raman laser irradiation modifies MoS 2 under ambient conditions, providing guidelines for optimizing its modification processes.

36 MATERIALS SCIENCE↗

A Robust Data-Driven Approach for Mechanical Serial Sectioning

Mechanical serial sectioning (MSS) provides detailed microstructural information across large length scales. By repeatedly removing thin layers of material and imaging the exposed surface, a 3D representation of a specimen’s internal structure can be constructed, enabling failure analysis and feature identification that are otherwise inaccessible via conventional 2D or nondestructive evaluation techniques. Achieving consistent and accurate material removal can be challenging due to system variability, requiring an experienced operator to manually adjust parameters, prolonging data collection times and necessitating post-processing routines to standardize the data. Here, to address these challenges, this paper presents the employment of a one-step model predictive control (MPC) framework tailored to a run-to-run (R2R) controller. The R2R-MPC controller automates the parameter selection process, improving the consistency of material removal through iterative feedback for disturbance rejection and accurate tracking of the target removal rate. Using a data-driven approach, the controller robustly adapts to changing material characteristics. The effectiveness of the R2R-MPC controller is demonstrated through simulation and experimental results and compared to previous data collection procedures.

3D Materials Science↗

High power pulse systems for surface processing

A high-power pulsed surface processing system includes insulated-gate bipolar transistors (IGBT) to replicate desirable pulse structures with high precision, at low cost, and with high reliability within a single system. The pulsed surface processing system includes a power supply, an anode and a cathode, a dual gate driver supplying power to one or more IGBT gates, and one or more capacitor banks. Pulse formation software controls the timing and duration of electrical pulses to the electrodes. A freewheeling diode protects the system from an abrupt reduction of current in the circuit. The high-power pulsed surface processing system may be used to control versatile and complex pulse structures while with precise control of instantaneous pulse powers, pulse timing, and process control. The inclusion of dual gate drivers also offers the ability for multiple pulsers to be created and “slaved” together for a wide variety of custom processes.

Tian, Hui↗

Control, Fault Management, and Grid Support Functionality of an MV AC-DC Solid State Transformer based EV Extreme Fast Charging Station

Electric vehicles (EVs) have become increasingly popular in recent times while revolutionizing the consumer and commercial transportation market. The development of charging infrastructure has become one of the priorities for increasing the adoption of EVs. Extreme fast charging (XFC) technology can reduce the so-called ’range anxiety’ of consumers as they significantly reduce the charging time. With the advent of wide band-gap (WBG) power devices and improvement in power electronic converters, medium voltage (MV) solid state transformer (SST) based XFC system has the potential to replace the traditional XFC stations because of the lower footprint, ease of installation, enhanced control feature, and better system efficiency. The control system design is one of the critical aspects of the SST development process. Careful consideration and detailed analysis are required to find out suitable control method for the SST based on its topology among different centralized and decentralized control architectures. Also, the control parameters selection and potential improvement to the transient response of the controller ought to be investigated. Another major concern of the SST is different types of internal fault which reduces the overall reliability of the XFC system. As a result, designing a robust protection system is essential. Among different fault modes, open circuit switch faults have received significant attention as an active research area because of their likelihood and severe effects on converters. Therefore, the power stages used in the XFC system require functional and accurate open circuit switch fault management methods. An equally significant aspect of this SST based XFC is its compatibility in a microgrid where there is no synchronous generator present. When the grid is not available, the XFC SSTs can provide grid forming capability and continue supplying the critical loads in islanded mode. The transition between grid connected and islanded mode, especially the grid resynchronization process has to be carefully performed for the safety of the microgrid components. The challenges posed by the aforementioned issues have inspired the work done in this dissertation. Here, a 13.2 kV, 1 MVA, AC/DC SST for the XFC system is examined and a comparative analysis is conducted to select the control architecture based on feasibility of implementation and performance. A detailed control parameter design process is demonstrated considering the sensor dynamics and delay. The selected decentralized control method is augmented by introducing a novel sensor-less load current feedforward method to provide better voltage regulation at the DC bus during a change of load. Next, in the fault management section, a hierarchical failure mode effect analysis (FMEA) is proposed to enable a systematic design of the internal fault protection of the XFC SST as there are limited examples in the literature regarding the analysis of the safety and design of the protection of a power electronic converter system. Novel open circuit switch fault management methods for the converters in the system are presented. Finally, XFC SST based MV microgrid operations in grid connected mode and islanded mode are explored. A secondary control method for grid resynchronization is presented and a design process of control parameters is shown to ensure the stability of the secondary voltage and frequency regulation.

30 DIRECT ENERGY CONVERSION↗

Electrochemical Capacitance Traces with Interlayer Spacing in Two‐dimensional Conductive Metal–Organic Frameworks

Abstract Electrically conductive metal–organic frameworks (MOFs) are promising candidates for electrochemical capacitors (EC) for fast energy storage due to their high specific surface areas and potential for redox activity. To maximize energy density, traditional inorganic pseudocapacitors have utilized faradaic processes in addition to double‐layer capacitance. Although conductive MOFs are usually comprised of redox active ligands which allow faradaic reactions upon electrochemical polarization, systematic studies providing deeper understanding of the charge storage processes and structure‐function relationships have been scarce. Here, we investigate the charge storage mechanisms of a series of triazatruxene‐based 2D layered conductive MOFs with variable alkyl functional groups, Ni 3 (HIR 3 ‐TAT) 2 (TAT=triazatruxene; R=H, Et, n ‐Bu, n ‐Pent). Functionalization of the triazatruxene core allows for systematic variation of structural parameters while maintaining in‐plane conjugation between ligands and metals. Specifically, R groups modulate interlayer spacing, which in turn shifts the charge storage mechanism from double‐layer capacitance towards pseudocapacitance, leading to an increase in molar specific capacitance from Ni 3 (HIH 3 ‐TAT) 2 to Ni 3 (HIBu 3 ‐TAT) 2 . Partial exfoliation of Ni 3 (HIBu 3 ‐TAT) 2 renders redox active ligand moieties more accessible, and thus increases the dominance of faradaic processes. Our strategy of controlling charge storage mechanism through tuning the accessibility of redox‐active sites may motivate further design and engineering of electrode materials for EC.

Su, Alice Y.↗

Electrochemical Capacitance Traces with Interlayer Spacing in Two‐dimensional Conductive Metal–Organic Frameworks

Abstract Electrically conductive metal–organic frameworks (MOFs) are promising candidates for electrochemical capacitors (EC) for fast energy storage due to their high specific surface areas and potential for redox activity. To maximize energy density, traditional inorganic pseudocapacitors have utilized faradaic processes in addition to double‐layer capacitance. Although conductive MOFs are usually comprised of redox active ligands which allow faradaic reactions upon electrochemical polarization, systematic studies providing deeper understanding of the charge storage processes and structure‐function relationships have been scarce. Here, we investigate the charge storage mechanisms of a series of triazatruxene‐based 2D layered conductive MOFs with variable alkyl functional groups, Ni 3 (HIR 3 ‐TAT) 2 (TAT=triazatruxene; R=H, Et, n ‐Bu, n ‐Pent). Functionalization of the triazatruxene core allows for systematic variation of structural parameters while maintaining in‐plane conjugation between ligands and metals. Specifically, R groups modulate interlayer spacing, which in turn shifts the charge storage mechanism from double‐layer capacitance towards pseudocapacitance, leading to an increase in molar specific capacitance from Ni 3 (HIH 3 ‐TAT) 2 to Ni 3 (HIBu 3 ‐TAT) 2 . Partial exfoliation of Ni 3 (HIBu 3 ‐TAT) 2 renders redox active ligand moieties more accessible, and thus increases the dominance of faradaic processes. Our strategy of controlling charge storage mechanism through tuning the accessibility of redox‐active sites may motivate further design and engineering of electrode materials for EC.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Layer-by-Layer Organic Solar Cells Enabled by 1,3,4-Selenadiazole-Containing Crystalline Small Molecule with Double-Fibril Network Morphology

A double-fibril network of the photoactive layer morphology is recognized as an ideal structure facilitating exciton diffusion and charge carrier transport for high-performance organic solar cells (OSCs). However, in the layer-by-layer processed OSCs (LbL-OSCs), polymer donors and small molecule acceptors (SMAs) are separately deposited, and it is challenging to realize a fibril network of pure SMAs with the absence of tight interchain entanglement as polymers. Here, in this work, crystalline small molecule donors (SMDs), named TDZ-3TR and SeDZ-3TR, were designed and introduced into the L8-BO acceptor solution, forcing the phase separation and molecular fibrilization. SeDZ-3TR showed higher crystallinity and lower miscibility with L8-BO acceptor than TDZ-3TR, enabling more driving force to favor the phase separation and better molecular fibrilization of L8-BO. On the other hand, two donor polymers of PM6 and D18 with different fibril widths and lengths were put together to optimize the fibril network of the donor layer. The simultaneously optimization of the acceptor and donor layers resulted in a more ideal double-fibril network of the photoactive layer and an impressive power conversion efficiency (PCE) of 19.38 % in LbL-OSCs.

36 MATERIALS SCIENCE↗

Spatially Enhanced Electrostatic Doping in Graphene Realized via Heterointerfacial Precipitated Metals

Forming heavily-doped regions in 2D materials, like graphene, is a steppingstone to the design of emergent devices and heterostructures. Here, a selective-area approach is presented to tune the work-function and carrier density in monolayer graphene by spatially synthesizing sub-monolayer gallium beneath the 2D-solid. The localized metallic gallium is formed via precipitation from an underlying diamond-like carbon (DLC) film that is spatially implanted with gallium-ions. By controlling the interfacial precipitation process with annealing temperature, spatially precise ambipolar tuning of the graphene work-function is achieved, and the tunning effect preserved upon cooling to ambient conditions. Consequently, charge carrier densities from ≈1.8 × 10 10 cm -2 (hole-doped) to ≈7 × 10 13 cm -2 (electron-doped) are realized, confirmed by in situ and ex situ measurements. The theoretical studies corroborated the role of gallium at the heterointerface on charge transfer and electrostatic doping of the graphene overlayer. Specifically, sub-monolayer gallium facilitates heavy n-doping in graphene. Extending this doping strategy to other implantable elements in DLC provides a new means of exploring the physics and chemistry of highly-doped 2D materials.

36 MATERIALS SCIENCE↗

Permeate fluxes from desalination of brines and produced waters: A reactive transport modeling study

The increasing interest in the use of membrane systems to desalinate inland brackish water, agricultural drainage, and industrially produced wastewater demands improved means of predicting desalination system performance under variable feedwater compositions. The interaction among water flow, solute transport, and chemical composition in these systems impacts permeate flux evolution. Here, an established multicomponent reactive transport simulator that accounts for these coupled processes is applied to compute osmotic pressure and permeate fluxes in reverse osmosis (RO) systems. The model is first validated by predicting permeate fluxes for a set of benchtop crossflow experiments subject to a range of feed flow rates and compositions, under fouling and non-fouling conditions. Results compare favorably with measured data that show that solutions with similar total dissolved solids concentrations but different compositions result in different permeate fluxes. The model is then applied to predict permeate fluxes from the desalination of produced waters using a commercial spiral wound RO module. For NaCl-dominant brines, at total dissolved salt concentrations (TDS) below about 70 g/L, permeate fluxes are inversely proportional to water mole fraction as the latter is a reasonable approximation of water activity (i.e. ideal mixing). In the case of Ca–Cl-, Na–CO3- and Na–SO4-dominant brines below about 70 g/L TDS, this relationship does not hold as well and tends to overpredict osmotic pressure and thus underpredict permeate fluxes. However, the opposite becomes true at higher TDS values for typical produced waters. The scaling potential of these waters is also computed by allowing the precipitation of minerals above their saturation limit on the RO membrane. This work demonstrates how reactive transport models developed for the analysis of waters from geological systems can be extended to improve process design, optimization, and control in desalination systems from produced waters and beyond.

Molins, Sergi↗

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

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

Desalination↗