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At least 1,045 records · Page 58

Efficient Energy Funneling in Quasi‐2D Perovskites: From Light Emission to Lasing

Abstract Quasi‐2D Ruddlesden–Popper halide perovskites with a large exciton binding energy, self‐assembled quantum wells, and high quantum yield draw attention for optoelectronic device applications. Thin films of these quasi‐2D perovskites consist of a mixture of domains having different dimensionality, allowing energy funneling from lower‐dimensional nanosheets (high‐bandgap domains) to 3D nanocrystals (low‐bandgap domains). High‐quality quasi‐2D perovskite (PEA) 2 (FA) 3 Pb 4 Br 13 films are fabricated by solution engineering. Grazing‐incidence wide‐angle X‐ray scattering measurements are conducted to study the crystal orientation, and transient absorption spectroscopy measurements are conducted to study the charge‐carrier dynamics. These data show that highly oriented 2D crystal films have a faster energy transfer from the high‐bandgap domains to the low‐bandgap domains (<0.5 ps) compared to the randomly oriented films. High‐performance light‐emitting diodes can be realized with these highly oriented 2D films. Finally, amplified spontaneous emission with a low threshold 4.16 µJ cm −2 is achieved and distributed feedback lasers are also demonstrated. These results show that it is important to control the morphology of the quasi‐2D films to achieve efficient energy transfer, which is a critical requirement for light‐emitting devices.

Lei, Lei↗

Model predictive control for robust quantum state preparation

A critical engineering challenge in quantum technology is the accurate control of quantum dynamics. Model-based methods for optimal control have been shown to be highly effective when theory and experiment closely match. Consequently, realizing high-fidelity quantum processes with model-based control requires careful device characterization. In quantum processors based on cold atoms, the Hamiltonian can be well-characterized. For superconducting qubits operating at milli-Kelvin temperatures, the Hamiltonian is not as well-characterized. Unaccounted for physics (i.e., mode discrepancy), coherent disturbances, and increased noise compromise traditional model-based control. This work introduces model predictive control (MPC) for quantum control applications. MPC is a closed-loop optimization framework that (i) inherits a natural degree of disturbance rejection by incorporating measurement feedback, (ii) utilizes finite-horizon model-based optimizations to control complex multi-input, multi-output dynamical systems under state and input constraints, and (iii) is flexible enough to develop synergistically alongside other modern control strategies. We show how MPC can be used to generate practical optimized control sequences in representative examples of quantum state preparation. Specifically, we demonstrate for a qubit, a weakly-anharmonic qubit, and a system undergoing crosstalk, that MPC can realize successful model-based control even when the model is inadequate. These examples showcase why MPC is an important addition to the quantum engineering control suite.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Design and Optimization of Structured Multi-Functional Trapping Catalysts for Conversion of Hydrocarbons and NOx from Diesel and Advanced Combustion Engines

Oxides of nitrogen in the form of nitric oxide (NO) and nitrogen dioxide (NO 2 ) commonly referred to as NOx, is one of the two chemical precursors that lead to ground-level ozone, a ubiquitous air pollutant in urban areas. A major source of NOx is generated by equipment and vehicles powered by diesel engines, which have a combustion exhaust that contains NOx in the presence of excess O 2 . Vehicular emission control catalysts are ineffective in eliminating CO, hydrocarbons, and NO x during engine cold-start when exhaust temperatures are below 200°C. The objective of the project was to develop and demonstrate a multi-functional, catalyzed trap that enables vehicles with advanced combustion strategies to meet Tier 3 emissions standards while achieving the 150 °C challenge for sustained co-oxidation of HCs and CO and ≥90% NO trapping and release during warmup. Specifically, the multi-functional Lean HC+NOx (LHCNT) was developed for application in the exhaust aftertreatment of conventional diesel engines and engines having low temperature combustion (LTC) regimes. Activities included the design and synthesis of adsorbents and catalysts, screening and evaluation. Passive NOx absorbers (PNA), hydrocarbon (HC) traps, and oxidation catalysts (OC) were evaluated for use in series or as integrated devices. Predictive tools were developed utilizing the characterization and analysis of these materials, and an emission system was designed and optimized utilizing the catalyst systems. Microkinetic models were developed for the PNA for the simple NO-only feed and complex feed containing CO, H 2 , and model hydrocarbons (ethylene and dodecane). A first-principles, mechanistic-based model of the PNA was developed which utilized molecular-scale estimates (density functional theory) of energy barriers, mechanistic-based kinetics and realistic treatments of the flow and transport processes. Two new oxidation catalysts were developed (PdCu alloy, mixed copper-ceria-cobalt oxide), both of which significantly lessened the detrimental inhibition by CO on hydrocarbon and NO oxidation. A method for lessening the detrimental impact of CO on PNA activity was developed that involves use of an oxidation catalyst upstream of the PNA. The SwRI Ectolab TM burner system was applied to evaluate the baseline PNA material and confirmed performance comparable to the benchflow PNA studies using simulated exhaust. Spatially-resolved mass spectrometry (SpaciMS) was used to measure the transient spatial profiles of reacting species spanning the length of a three-function LHCNT containing PNA, HCT, and OC. The findings from this study provide diesel vehicle and catalyst companies valuable information to develop more cost effective emission control catalysts which helps to expand the use of more fuel efficient diesel power. The fundamental modeling and experimental tools and findings from this project can be applied to catalyst technologies used in the energy and chemical industries. The project led to 14 publications in the peer-reviewed literature with 2 additional currently under review. Finally, the project also led to training of several doctoral students who were placed in research jobs in industry and academia. Specifically, Mugdha Ambast (UH) has joined Cummins, Kevin Gu (UVa) has joined GM, and Abhay Gupta (UH) is to join Caterpillar.

42 ENGINEERING↗

A Comprehensive Analysis of Energy and Daylighting Impact of Window Shading Systems and Control Strategies on Commercial Buildings in the United States

Commercial buildings consume approximately 1.9 EJ of energy in the United States, 50% of which is for heating, cooling, and lighting applications. It is estimated that windows contribute up to 34% of the energy used for heating and cooling. However, window retrofits are not often undertaken to increase energy efficiency because of the high cost and disruptive nature of window installation. Highly efficient window technologies would also need shading devices for glare prevention and visual comfort. An automated window shading system with an appropriate control strategy is a technology that can reduce energy demand, maintain occupant comfort, and enhance the aesthetics and privacy of the built environment. However, the benefits of the automated shades currently used by the shading industry are not well studied. The topic merits an analysis that will help building owners, designers and engineers, and utilities make informed decisions using knowledge of the impact of this technology on energy consumption, peak demand, daylighting, and occupant comfort. This study uses integrated daylight and whole-building energy simulation to evaluate the performance of various control strategies that the shading industry uses in commercial office buildings. The analysis was performed for three different vintages of medium office buildings at six different locations in United States. The results obtained show the control strategies enabled cooling energy savings of up to 40% using exterior shading, and lighting energy savings of up to 25%. The control strategies described can help building engineers and researchers explore different control methods used to control shading in actual buildings but rarely discussed in the literature. This information will give researchers the opportunity to investigate potential improvements in current technologies and their performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Plasma confinement state classification in fusion power plants: Profile reflectometer and ensemble diagnostics

As Fusion Pilot Plants (FPPs) are increasingly viewed as within reach, many engineering challenges remain. Not many diagnostics are expected to be available in a reactor environment. Survivability, maintainability, and limited port space substantially restrict the number of FPP-relevant diagnostics. One remaining challenge is developing tools and devices to extract plasma state information necessary for controlling an FPP from a limited subset of diagnostics. This work is part of an overarching project to address this challenge. The specific diagnostic subset to be used in FPPs is still under debate. We take the approach of developing machine-learning-based tools for different significant plasma state parameters, using already known FPP-viable diagnostics. Previously we developed a plasma confinement mode classifier utilizing the Electron Cyclotron Emission (ECE) diagnostic. Here, we expand on this by developing a Profile Reflectometer (PR) based classifier with 97% test accuracy, and an ensemble model that combines the ECE and PR models into a single model, achieving 99% test accuracy.

Clark, Randall [Univ. of California, San Diego, CA↗

Design and Optimization of Structured Multi-Functional Trapping Catalysts for Conversion of Hydrocarbons and NOx from Diesel and Advanced Combustion Engines

Oxides of nitrogen in the form of nitric oxide (NO) and nitrogen dioxide (NO 2 ) commonly referred to as NOx, is one of the two chemical precursors that lead to ground-level ozone, a ubiquitous air pollutant in urban areas. A major source of NOx is generated by equipment and vehicles powered by diesel engines, which have a combustion exhaust that contains NOx in the presence of excess O 2 . Vehicular emission control catalysts are ineffective in eliminating CO, hydrocarbons, and NOx during engine cold-start when exhaust temperatures are below 200°C. The objective of the project was to develop and demonstrate a multi-functional, catalyzed trap that enables vehicles with advanced combustion strategies to meet Tier 3 emissions standards while achieving the 150 °C challenge for sustained co-oxidation of HCs and CO and ≥90% NO trapping and release during warmup. Specifically, the multi-functional Lean HC+NOx (LHCNT) was developed for application in the exhaust aftertreatment of conventional diesel engines and engines having low temperature combustion (LTC) regimes. Activities included the design and synthesis of adsorbents and catalysts, screening and evaluation. Passive NOx absorbers (PNA), hydrocarbon (HC) traps, and oxidation catalysts (OC) were evaluated for use in series or as integrated devices. Predictive tools were developed utilizing the characterization and analysis of these materials, and an emission system was designed and optimized utilizing the catalyst systems. Microkinetic models were developed for the PNA for the simple NO-only feed and complex feed containing CO, H 2 , and model hydrocarbons (ethylene and dodecane). A first-principles, mechanistic-based model of the PNA was developed which utilized molecular-scale estimates (density functional theory) of energy barriers, mechanistic-based kinetics and realistic treatments of the flow and transport processes. Two new oxidation catalysts were developed (PdCu alloy, mixed copper-ceria-cobalt oxide), both of which significantly lessened the detrimental inhibition by CO on hydrocarbon and NO oxidation. A method for lessening the detrimental impact of CO on PNA activity was developed that involves use of an oxidation catalyst upstream of the PNA. The SwRI Ectolab TM burner system was applied to evaluate the baseline PNA material and confirmed performance comparable to the benchflow PNA studies using simulated exhaust. Spatially-resolved mass spectrometry (SpaciMS) was used to measure the transient spatial profiles of reacting species spanning the length of a three-function LHCNT containing PNA, HCT, and OC. The findings from this study provide diesel vehicle and catalyst companies valuable information to develop more cost effective emission control catalysts which helps to expand the use of more fuel efficient diesel power. The fundamental modeling and experimental tools and findings from this project can be applied to catalyst technologies used in the energy and chemical industries. The project led to 14 publications in the peer-reviewed literature with 2 additional currently under review. Finally, the project also led to training of several doctoral students who were placed in research jobs in industry and academia. Specifically, Mugdha Ambast (UH) has joined Cummins, Kevin Gu (UVa) has joined GM, and Abhay Gupta (UH) is to join Caterpillar.

02 PETROLEUM↗

Modulating charge transport via 2 MeV He + irradiation in VO 2

Vanadium dioxide (VO 2 ) is of interest for adaptive electronic applications such as neuromorphic neuristor devices and variable emissivity or tunable thermal control materials, thanks to its key property—a metal–insulator transition (MIT) at 68 °C that is accompanied by a dramatic change in electrical and optical properties. To improve performance in these roles, it is critical to develop approaches to engineer transport properties and the MIT behavior. While many documented techniques exist to modulate the MIT and film resistivities via lattice strain and chemical doping, less is known about the effects of ion irradiation on the intrinsic properties of VO 2 , despite the ability to control the spatial distribution of irradiation beams and the prevalence of high energy ion implantation in the semiconductor industry. The impact of irradiation of different acceleration energies on the responses of VO 2 is of specific interest, as charged particle energy generally impacts both the resulting defect profile and corresponding transport behavior. Here, we demonstrate that 2 MeV He ions at equivalent calculated displacements per atom, in two different types of films, can create remarkable changes to the nature of charge transport in VO 2 , especially in the low-temperature insulating phase. Simulation of resulting changes in electrical conductivity reveals that He ion irradiation offers a strategy to increase both oscillation frequency and the signal transmission. These results provide insights into the intentional design of defect populations to modulate transport for neuromorphic VO 2 devices.

Gurrola, Rebeca M. [Texas A & M Univ., College Sta↗

Surface engineering with oxidized Ti 3 C 2 T x MXene enables efficient and stable p-i-n-structured CsPbI 3 perovskite solar cells

All-inorganic CsPbI 3 perovskite has a near-ideal band gap, high thermal stability, and simple material composition, thus presenting a promising option for developing perovskite/Si tandem solar cells. However, CsPbI 3 undergoes a rapid phase transition under exposure to moisture and exhibits a significant performance gap relative to other perovskite compounds, particularly in the p-i-n structure favored for perovskite/Si tandems. In this work, we demonstrate highly efficient and stable p-i-n-structured CsPbI 3 perovskite solar cells by surface engineering the CsPbI 3 layer with oxidized Ti 3 C 2 T x MXene (OMXene) nanoplates via spray coatings. OMXene provides a physical barrier against moisture and improves charge separation at the perovskite-electron transporting layer interface via an enhanced electric field. Consequently, we demonstrated CsPbI 3 /OMXene-based p-i-n devices with efficiencies of 19.69% for 0.096-cm 2 cells and 14.64% for 25-cm 2 minimodules. The encapsulated minimodule showed good stability, retaining ~85% of the initial efficiency under simultaneous damp heat (85°C/85% relative humidity) and 1-sun light soaking for over 1,000 h.

14 SOLAR ENERGY↗

Synthesis of 2D layered transition metal (Ni, Co) hydroxides via edge-on condensation

Abstract Layered transition metal hydroxides (LTMHs) with transition metal centers sandwiched between layers of coordinating hydroxide anions have attracted considerable interest for their potential in developing clean energy sources and storage technologies. However, two-dimensional (2D) LTMHs remain largely understudied in terms of physical properties and applications in electronic devices. Here, for the first time we report > 20 μm α-Ni(OH) 2 2D crystals, synthesized from hydrothermal reaction. And an edge-on condensation mechanism assisted with the crystal field geometry is proposed to understand the 2D intra-planar growth of the crystals, which is also testified through series of systematic comparative studies. We also report the successful synthesis of 2D Co(OH) 2 crystals (> 40 μm) with more irregular shape due to the slightly distorted octahedral geometry of the crystal field. Moreover, the detailed structural characterization of synthesized α-Ni(OH) 2 are performed. The optical band gap energy is extrapolated as 2.54 eV from optical absorption measurements and the electronic bandgap is measured as 2.52 eV from reflected electrons energy loss spectroscopy (REELS). We further demonstrate its potential as a wide bandgap (WBG) semiconductor for high voltage operation in 2D electronics with a high breakdown strength, 4.77 MV/cm with 4.9 nm thickness. The successful realization of the 2D LTMHs opens the door for future exploration of more fundamental physical properties and device applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Constrained Deep Reinforcement Learning for Energy Sustainable Multi-UAV Based Random Access IoT Networks With NOMA

In this paper, we apply the Non-Orthogonal Multiple Access (NOMA) technique to improve the massive channel access of a wireless IoT network where solar-powered Unmanned Aerial Vehicles (UAVs) relay data from IoT devices to remote servers. Specifically, IoT devices contend for accessing the shared wireless channel using an adaptive p-persistent slotted Aloha protocol; and the solar-powered UAVs adopt Successive Interference Cancellation (SIC) to decode multiple received data from IoT devices to improve access efficiency. To enable an energy-sustainable capacity-optimal network, we study the joint problem of dynamic multi-UAV altitude control and multi-cell wireless channel access management of IoT devices as a stochastic control problem with multiple energy constraints. We first formulate this problem as a Constrained Markov Decision Process (CMDP), and propose an online model-free Constrained Deep Reinforcement Learning (CDRL) algorithm based on Lagrangian primal-dual policy optimization to solve the CMDP. Extensive simulations demonstrate that our proposed algorithm learns a cooperative policy in which the altitude of UAVs and channel access probability of IoT devices are dynamically controlled to attain the maximal long-term network capacity while ensuring energy sustainability of UAVs, outperforming baseline schemes. The proposed CDRL agent can be trained on a small network, yet the learned policy can efficiently manage networks with a massive number of IoT devices and varying initial states, which can amortize the cost of training the CDRL agent.

42 ENGINEERING↗

Direct quantification of ion composition and mobility in organic mixed ionic-electronic conductors

Ion transport in organic mixed ionic-electronic conductors (OMIECs) is crucial due to its direct impact on device response time and operating mechanisms but is often assessed indirectly or necessitates extra assumptions. Operando x-ray fluorescence (XRF) is a powerful, direct probe for elemental characterization of bulk OMIECs and was used to directly quantify ion composition and mobility in a model OMIEC, poly(3,4-ethylenedioxythiophene)-poly(styrene sulfonate) (PEDOT:PSS), during device operation. The first cycle revealed slow electrowetting and cation-proton exchange. Subsequent cycles showed rapid response with minor cation fluctuation (~5%). Comparison with optical-tracked electrochromic fronts revealed mesoscale structure–dependent proton transport. The calculated effective ion mobility demonstrated thickness-dependent behavior, emphasizing an interfacial ion transport pathway with a higher mobile ion density. The decoupling of interfacial effects on bulk ion mobility and the decoupling of cation and proton migration elucidate ion transport in conventional and emerging OMIEC-based devices and has broader implications for other ionic conductors writ large.

42 ENGINEERING↗

Advanced Manufacturing Workflows for Tokamak Internal Components

The project aim was to create a new advanced manufacturing workflow for the design and creation of an internal component in a fusion device, enabling a low-cost, rapid design and fabrication cycle. As a result, two demonstration components were manufactured, and mechanical properties for two feedstock materials were tested in the context of fusion device conditions. This work shows a technological scoping toward future manufacturing of complex components in topologies relevant to magnetic fusion devices via additive manufacturing.

42 ENGINEERING↗

Pulse-train drive system for electrostatic generators and motors

A novel motor drive system has been described for use in electrostatic generator/motor systems based on the time variation of capacity of a rotating condenser comprised of segmented rotor and stator elements. It takes advantage of the fact that the motor action of such a system depends only on the rms value of the drive pulses, which therefore can be formed simply by periodically interrupting a high-frequency ac wave train. This new circuitry simplifies the drive system and takes advantage of recent developments of devices used in the art of inversion of dc voltages to high-frequency (tens of kiloHz) ac.

42 ENGINEERING↗

Compact, high-efficiency accelerators driven by low-voltage solid-state amplifiers

A compact particle accelerator can include two or more cavities disposed along an axis of the particle accelerator, each of which is coupled to two or more drivers. The accelerator can also include a power supply coupled to the two or more drivers such that a particle beam traveling along the axis is accelerated. The power supply can be an interface with a commercial power outlet, battery power, or a combination thereof depending upon the use case. Example configurations of the accelerator include hand held or mobile devices that are capable of delivering up to and greater than a 1 MeV electron beam.

42 ENGINEERING↗

High-frequency direct current bulk capacitors with interleaved busbar packages

Presented are electrical capacitors with interleaved busbar architectures, methods for making/operating such capacitors, and electric-drive vehicles equipped with such capacitors. A bulk capacitor includes multiple capacitor devices disposed within an outer housing and operable to modify electric current transmitted between a power source and an electrical load. An interleaved busbar package is interposed between the capacitor devices and outer housing. The interleaved busbar package includes a first busbar plate that electrically connects to first terminals of the capacitor devices and defines a busbar pocket. A second busbar plate is seated within the busbar pocket and electrically connects to second terminals of the capacitor devices. The second busbar plate includes a capacitor basin that seats therein the capacitor devices. An isolator sheet is interleaved between and electrically insulates the first and second busbar plates. The capacitor devices and interleaved busbar package may be partially submerged in an epoxy endfill composition.

42 ENGINEERING↗

Ion-Depleted Microenvironments During Lithium Deposition Revealed by Operando Freezing Cryogenic Electron Microscopy

Local structures and chemistry at active electrochemical interfaces are critical to determining safety, lifetime, and energy density in lithium metal batteries and other devices, but they are challenging to characterize at the nanoscale. We address this issue by developing operando freezing cryogenic electron microscopy (cryo-EM) to preserve battery interfaces in an active state for subsequent high-resolution characterization. We find that ion-depleted microenvironments form locally in the electrolyte adjacent to the lithium deposition interface in lithium metal batteries and are linked to heterogenous growth morphologies. These depleted environments arise locally even under conditions for which ion depletion is not predicted at steady state; this provides a mechanistic explanation for why dangerous lithium morphologies can still propagate in such systems and lead to thermal runaway. Operando freezing cryo-EM thus provides a method to directly visualize nanoscale heterogeneities that arise locally at electrochemical interfaces and play key roles in device failure.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS,E↗

Los Alamos National Laboratory R&D Intern

This report details the responsibilities, outcomes, and project details of a summer R&D internship at Los Alamos National Laboratory (LANL). LANL is a multidisciplinary laboratory that focuses on current cutting-edge research in many fields such as national security, engineering, materials science, computational modeling, and advanced manufacturing. The goal of the internship project was to work with lab engineers and resources to develop an energy absorbing structure for high-velocity impact applications. The successful development of this technology and methodology would not only positively impact future project funding but also contribute to the laboratory's commitment to solve national security challenges through simultaneous excellence. Such devices would also support efforts surrounding the research and development of energy absorbing structures and would provide new vital information backed by experimentation. Different computational and modeling methods were used to design these structures, in addition to qualitative background information provided by past literature. The resultant designs were successfully tested, and the test results were successfully quantified. From these results, new computational methods were developed through python programming and modeling to predict ideal materialistic properties for these structures given a sufficiently defined application.

36 MATERIALS SCIENCE↗