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At least 667 records · Page 37

Function allocation for humans and automation in the context of team dynamics

Within Human Factors Engineering, a decision-making process called function allocation (FA) is used during the design life cycle of complex systems to distribute the system functions, often identified through a functional requirements analysis, to all human and automated machine agents (or teammates) involved in controlling the system. Most FA methods make allocation decisions primarily by comparing the capabilities of humans and automation, but then also by considering secondary factors such as cost, regulations, and the health and safety of workers. The primary analysis of the strengths and weaknesses of humans and machines, however, is almost always considered in terms of individual human or machine capabilities. Yet, FA is fundamentally about teamwork in that the goal of the FA decision-making process is to determine what are the optimal allocations of functions among agents. Given this framing of FA, and the increasing use of and sophistication of automation, there are two related social psychological issues that current FA methods need to address more thoroughly. First, many principles for effective human teamwork are not considered as central decision points or in the iterative hypothesis and testing phase in most FA methods, when it is clear that social factors have numerous positive and negative effects on individual and team capabilities. Second, social psychological factors affecting team performance and can be difficult to translate to automated agents, and most FA methods currently do not account for this effect. The implications for these issues are discussed.

Automation↗

System Engineers and Decisions: It?s All about Knowledge

In order to guarantee that a system meets adequate levels of reliability and availability, system performances are continuously monitored and analyzed thanks to the technological advancements driving the Industry 4.0 revolution. An Industry 4.0 approach is typically based on advanced statistical, big data mining, machine learning, and internet-of-things methods designed to detect anomalies in the behavior of system, detect the most likely failure modes, and provide indications to system engineers on when maintenance activities should be performed before system performance are deemed unacceptable (which can be generated by diagnostic and prognostic methods). However, these analyses, which are designed to automatize and increase the efficacy of the system maintenance program, require large amount of data which can come in various forms: numeric, textual, images, sounds etc. Such data constitutes the historic knowledge benchmark to track system performances and support system engineer decisions. Here we claim that data is not sufficient to support this kind of analyses when applied to systems characterized by complex architectures and behaviors. Robust system engineer decisions require the ability to understand the system operational context that lies behind the observed data elements. In this respect, system models are in fact necessary to “put data in context” and capture relationships between data elements. Industry 4.0 methods require in fact contextual knowledge as a basis upon which hypotheses can be generated and assumptions tested. In our view, for complex systems, model-based system engineering (MBSE) models can afford this contextual knowledge, as they are typically used to describe systems architecture and dynamic behaviors. System knowledge is here intended as the blending of collected data and system architecture which takes the form of a “knowledge graph”. A knowledge graph is a database which consists of a large set of nodes (in our case an entity can be either a data or an MBSE element) which are linked to each other. The types of nodes and links follow a pre-defined topology, sometimes also refers as an ontology, that is designed to fit the actual decisions that needs to be performed. We show here how a knowledge graph can be defined to support system engineer maintenance decisions and how the same graph can be built based on system MBSE models and pre-processed data from numeric (through anomaly detections and diagnostic methods) and textual elements (through technical language processing TLP).

97 - MATHEMATICS AND COMPUTING↗

Managing systematic errors in the NBSR thermal power calorimetric measurements - 214

There has been a calorimetric misbalance between the primary and secondary loops of the National Bureau of Standards Reactor (NBSR) since the installation of a set of new heat exchangers in the early 90's. The NBSR's primary and secondary process instrumentation were investigated to resolve the underlying causes. The main issue was found to be the immersion length of the thermowells, resulting in non-exemplary process measurements. Furthermore, thermal insulation on various temperature sensors was found to be degraded. Hence, the following were found to be inconsistent: the heat exchanger output temperatures, previously-used differential temperature sensors, reactor inlet sensor, and the reactor outlet temperature indications. Therefore, thermodynamic analyses using these sensor measurements were inconclusive. Secondly, the discrepancy between primary and secondary loops and the gradual inconsistency between primary side sensors went largely unnoticed. We implemented sustainable, state-of-the-art upgrades to resolve systematic errors in the NBSR reactor thermal process instrumentation. Several digital upgrades were completed, along with detailed 50.59 reviews. Redundancy, defense-in-depth, reliability, diversity and accuracy of the thermal monitoring system was established by implementing an inclusive engineering approach by analyzing the sensors as a whole system instead of individual assessments. The upgrades produced two important outcomes. First, the long-term existing calorimetric discrepancy between the primary and secondary loops was resolved. Secondly, excellent agreement was achieved within the primary process measurement instrumentation, resulting in reliable and stable thermal power assessment. We will present lessons learned performing instrumentation upgrades and our future enhancement plans in process monitoring for the NBSR reactor. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Securing the Clean Energy Transition with Cyber-Informed Engineering

The Bipartisan Infrastructure Law kick-started a surge in clean energy investments in the United States. Securing these systems and their supporting infrastructure from the outset is imperative, starting from the conceptual design and continuing through the entire engineering lifecycle. Cyber-Informed Engineering is an ideal approach to seamlessly integrate the necessary advanced control capabilities and adaptive protection systems, especially considering the trend towards cloud-based infrastructure and process controls. Learn more about CIE at https://www.energy.gov/ceser/articles/cyber-informed-engineering-bridge-between-cyber-and-critical-infrastructure-securing.

14 SOLAR ENERGY↗

Automatic Imagery Data Analysis for Proactive Computer-Based Workflow Management during Nuclear Power Plant Outages

This report is being submitted for the task “Final Report” of DOE NEUP Project 15-8121 “Automatic Imagery Data Analysis for Proactive Computer-Based Workflow Management during Nuclear Power Plant Outages.” Typical nuclear power plant (NPP) outages always involve thousands of maintenance and refueling activities and a large number of workers in limited workspaces, while having tight schedules and zero-tolerance for accidents. During an outage, thousands of workers will be working in various workspaces across the NPP. High outage costs and expensive delays (approximately 1.5 million dollars of loss per day of delay) in NPP maintenance demand tight outage schedules. In packed workspaces, an automatic system that monitors human behaviors in real-time and provides insights about current and pending schedule deviations from the plan is critical for ensuring: 1) effective collaboration among workers and worker teams from different trades; 2) less waste of time and resources due to the lack of situational awareness; and 3) proactive outage project control. The overall goal of this project is to test the hypothesis that real-time imagery-based object tracking and spatial analysis, as well as human behavior modeling of outage participants, will significantly improve the efficiency of outage control while lowering the rates of accidents and incidents. Three objectives of this project are: 1) Establish real-time object tracking and spatiotemporal analysis methods that automatically assess the productivity of field activities and detect anomalous spatiotemporal relationships among activities that cause inefficiencies and risks; 2) Establish realtime human tracking and human factor modeling methods for automatically diagnosing unexpected actions of and interactions between outage participants, those which cause inefficient collaborations between Advanced Outage Control Center (AOCC), satellite outage centers, NPP workers, and maintenance service providers; and 3) Test the proposed automated object tracking, human behavior modeling, and spatiotemporal analysis methods in outage control case studies in order to characterize the effectiveness of automated imagery-data-driven methods in proactively improving the efficiency and safety of workflows in outage coordination and risk management. Recent studies of detailed human behavior monitoring on construction sites have examined the potential of applying advanced computer vision algorithms in detecting and tracking anomalous workers (i.e., workers who do not wear hard hats or safety vests) for ensuring job site safety. Some studies of human factor studies revealed the importance of modeling detailed interactions between individuals within and across teams in better understanding the impact of human in proactive project control. Other studies in the construction domain have developed computational simulation frameworks that formalize detailed spatiotemporal interactions between tasks in order to simulate the impacts of individual tasks on the performance of workflows. While integrated analyses that combine human factor assessment, as well as image processing and simulation, are in demand for effective decision-making, limited studies have examined the potential of such integrated analyses in NPP outage control. This research project has examined an automatic outage monitoring and control system that integrates human factor analysis, computer vision techniques, and simulation methods in order to enable engineers to better understand the interactions between humans, resources, and workflows during outage processes. The project aims at providing NPP maintenance agencies insights into more efficient use of limited resources in extending the life of a nuclear plant, as well as reducing waste while ensuring sufficient generation of electricity. This study is significant for the safety of nuclear plants, sustainable electricity generation for livable communities, and cost savings for maintaining electricity infrastructures in the United States.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Hanford Immobilized Low-Activity Waste Transportation System Testing Results - 20043

The immobilized low-activity waste (ILAW) transportation system is a first-of-a-kind system that is being designed and tested to transport ILAW glass-filled containers from Hanford's Waste Treatment and Immobilization Plant (WTP) Low-Activity Waste (LAW) Facility to the Integrated Disposal Facility (IDF) burial trench for permanent disposal. A prototype design and fabrication of one transport trailer and four engineered ILAW pallets was completed in mid-2018. Prototype qualification testing to verify adequacy of the design was completed in 2019 by Washington River Protection Solutions (WRPS) and affiliate ATKINS SNC-Lavalin Group. Prototype testing was completed to advance design maturation across all operational and facility interfaces, and under adverse environmental and operating conditions, including thermal assessment of the system at peak projected temperatures. Test design, observation, and feedback was well represented and supported by all ILAW Transportation System interfacing organizations: WTP constructor Bechtel National, Inc.; IDF operator CH2M (CHPRC); transportation contractor Mission Support Alliance (MSA); the U. S. Department of Energy Richland Operations Office (DOE/RL) and Office of River Protection (DOE/ORP); and Washington State Department of Ecology. This paper presents the results of prototype qualification testing and opportunities for design improvements based on testing. Changes to the final design as a result of prototype testing include improvements in safety, ergonomics, operational flexibility, and As-Low-As-Reasonably-Achievable (ALARA) applications. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

System Modeling of the HTTR and Economic Dispatch Model of the Secondary System

High Temperature Gas-cooled Reactors (HTGRs) can be used for the generation of electricity and their process heat can be used to improve the efficiency of chemical processes such as hydrogen production. The JAEA-operated High-Temperature engineering Test Reactor (HTTR-GT/H2) is exploring using the reactor for electricity and hydrogen production. A RELAP5-3D model of the HTTR-GT/H2 secondary system has been developed using design information. The various components and heat exchangers in the secondary system were modeled and results were compared to the design conditions. The results for the sole-power generation mode were shown to fit the design conditions very well. The largest temperature difference was on the order of 7 K, and the largest pressure difference was on the order of 0.05 MPa. The results for the hydrogen cogeneration mode did not match the design conditions nearly as well. The largest temperature difference was about 39 K and the largest pressure difference was about 0.27 MPa at the compressor outlet. The larger differences for the hydrogen cogeneration mode are attributed to the various complex components and the flow being split in the secondary loop. A transient reduction in heat removal capability of the secondary system was investigated. Reactor temperatures are anticipated to rise as a result. The core reactivity response due to this increase in temperature is investigated and is expected to add negative reactivity to the reactor. An economic dispatch model was developed for a nuclear-driven iodine-sulfur cycle system to determine hydrogen sale prices that would make such a system profitable. The study focuses on the development of the economic model and the role that input data plays on final calculated values. It was found that the input electricity prices, whether using historical data or a host of synthetic time histories, produce significantly different breakeven hydrogen sale prices. As such, great care should be used in these economic dispatch analyses to select reasonable input assumptions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Development of an Optimal Variable-Pitch Controller for Floating Axial-Flow Marine Hydrokinetic Turbines

This article discusses the development of an optimal variable-pitch controller for floating, axial-flow marine turbines. Recently, OpenFAST, an open-source wind turbine modeling tool, has been extended to model marine turbines. A controller is necessary to simulate marine turbines for different load cases using OpenFAST, which greatly impacts the performance of the energy system. Previous studies have designed controllers using a linearized model of the marine turbine, which can be time-consuming and require the expertise of a control engineer. In this study, we use an automated approach that uses generic models of the marine turbine to identify the controller gains, which can expedite the process of designing a controller. Using an optimizer to identify the control system parameters can additionally improve the controller's performance. The optimal controller tuned using such an approach results in a 20% reduction in the tower-base damage equivalent loading and better tracking of the rated generator speed and power.

axial flow↗

Implementation and Tuning of Batched Cholesky Factorization and Solve for NVIDIA GPUs

Many problems in engineering and scientific computing require the solution of a large number of small systems of linear equations. Due to their high processing power, Graphics Processing Units became an attractive target for this class of problems, and routines based on the LU and the QR factorization have been provided by NVIDIA in the cuBLAS library. This work addresses the situation where the systems of equations are symmetric positive definite. The paper describes the implementation and tuning of the kernels for the Cholesky factorization and the forward and backward substitution. Targeted workloads involve the solution of thousands of linear systems of the same size, where the focus is on matrix dimensions from 5 by 5 to 100 by 100. Due to the lack of a cuBLAS Cholesky factorization, execution rates of cuBLAS LU and cuBLAS QR are used for comparison against the proposed Cholesky factorization in this work. Execution rates of forward and backward substitution routines are compared to equivalent cuBLAS routines. Comparisons against optimized multicore implementations are also presented. Superior performance is reached in all cases.

Computer Science↗

Chromoanagenesis in plants: triggers, mechanisms, and potential impact

Chromoanagenesis is a single catastrophic event that involves, in most cases, localized chromosomal shattering and reorganization, resulting in a dramatically restructured chromosome. First discovered in cancer cells, it has since been observed in various other systems, including plants. In this review, we discuss the origin, characteristics, and potential mechanisms underlying chromoanagenesis in plants. Here, we report that multiple processes, including mutagenesis and genetic engineering, can trigger chromoanagenesis via a variety of mechanisms such as micronucleation, breakage–fusion–bridge (BFB) cycles, or chain-like translocations. The resulting rearranged chromosomes can be preserved during subsequent plant growth, and sometimes inherited to the next generation. Because of their high tolerance to genome restructuring, plants offer a unique system for investigating the evolutionary consequences and potential practical applications of chromoanagenesis.

59 BASIC BIOLOGICAL SCIENCES↗

Early Fault Detection in Nuclear Systems: A Digital Engineering Approach

Nuclear energy systems present unique challenges in terms of ensuring safety, reliability, and efficiency during their design and operation. Early fault detection is critical for mitigating risks and fostering system resilience. However, current methods often fall short at identifying faults during early stages, potentially leading to costly delays and safety risks. The present work proposes a comprehensive digital engineering approach that leverages digital twins, digital threads, model-based systems engineering, artificial intelligence, and immersive extended reality to support early fault detection in nuclear systems. Through a series of case studies, we highlight specific gaps in the fault detection mechanisms of traditional nuclear design and operation processes, then demonstrate a suite of solutions we are working to implement to address these shortcomings in similar projects. Our findings suggest that a digital engineering approach to design and operation can significantly improve fault detection, ultimately leading to reductions in risk.

42 - ENGINEERING↗

Software Quality Metrics for Geant4: An Initial Assessment - Paper 122

In the context of critical applications, such as shielding and radiation protection, ensuring the quality of simulation software they depend on is of utmost importance. The assessment of simulation software quality is crucial both to determine its adoption in experimental applications and to guarantee reproducibility of outcome over time. Geant4 is a simulation system used in a wide range of experimental applications, some of which, such as radiation protection and biomedical studies, may involve critical use cases and would especially profit from an objective assessment of the software quality. In this study, we present the first results from an ongoing analysis of Geant4 code based on established software metrics from the perspective of software engineering. The analysis evaluates the current status of the code to quantify its characteristics with respect to documented quality standards; further appraisals concern evolutions over a series of release distributions. The quantitative assessment of the software is initially focused on a subset of Geant4 packages, which play a key role in scientific applications and are representative of different software development processes. We describe the chosen software metrics that map the entities of a software system to numeric values through mathematical definitions, quantifying software attributes ranging from functionality to maintainability. To measure such metrics, we exploited a set of software metrics tools, i.e. programs that implement a set of software metrics definitions. They allow software engineers to assess a software system by extracting the required attributes from the software and providing the corresponding metric values. To correlate software metrics values in a well-defined way, we used software quality standard models, such as the ISO/IEC 9126 standard, which aggregate numerical values to aid quality analysis and assessment. With this work we aim to create a baseline for evaluating correlations between software quality embedded in the Geant4 development process and simulation observables produced by Geant4-based applications. Furthermore, we intend to highlight what metrics are most effective at evaluating radiation transport software quality. We are confident that the result will provide constructive guidance both to improve key software tools, such as Geant4, and to estimate their contribution in risk analysis concerning sensitive applications. The remainder of this paper is structured as follows. We first discuss the approach adopted to fulfil our assessment. Then, we present the setup of our experiments and the way we collected data. We provide an initial interpretation of a subset of data resulting from measurements made on the selected Geant4 packages. As the analysis is still ongoing at the time of submitting this abstract, some results will be documented in the final paper and in the conference presentation. With this work we aim to create a proper Geant4 data set for evaluating its software characteristics and identifying both strengths and weaknesses. In this initial study, we considered the geometry and processes packages, which play a major role in most simulation applications. The data analysis is in progress at the time of writing; its complexity is related to the differences among software metrics tools, to the large amount of data to be evaluated and to the pioneering character of this project. We are confident that the results will provide valuable indications for the Geant4 user community and constructive guidance to improve key Geant4 packages. Other Monte Carlo codes could profit from the methodology developed in this pilot project for similar assessments of their software quality. At the end of this study, we intend to create a baseline for evaluating correlations between software quality embedded in the Geant4 development process and simulation observables produced by Geant4-based applications. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗

Interfacial engineering of solution-processed Ni nanochain-SiO{sub x} (x < 2) cermets towards thermodynamically stable, anti-oxidation solar selective absorbers

Cermet solar thermal selective absorber coatings are an important component of high-efficiency concentrated solar power (CSP) receivers. The oxidation of the metal nanoparticles in cermet solar absorbers is a great challenge for vacuum-free operation. Recently, we have demonstrated that oxidation is kinetically retarded in solution processed, high-optical-performance Ni nanochain-SiO{sub x} cermet system compared to conventional Ni-Al{sub 2}O{sub 3} system when annealed in air at 450–600 °C for several hours. However, for long-term, high-temperature applications in CSP systems, thermodynamically stable antioxidation behavior is highly desirable, which requires new mechanisms beyond kinetically reducing the oxidation rate. Towards this goal, in this paper, we demonstrate that pre-operation annealing of Ni nanochain-SiO{sub x} cermets at 900 °C in N{sub 2} forms the thermodynamically stable orthorhombic phase of NiSi at the Ni/SiO{sub x} interfaces, leading to self-terminated oxidation at 550 °C in air due to this interfacial engineering. In contrast, pre-operation annealing at a lower temperature of 750 °C in N{sub 2} (as conducted in our previous work) cannot achieve interfacial NiSi formation directly, and further annealing in air at 450–600 °C for >4 h only leads to the formation of the less stable (metastable) hexagonal phase of NiSi. Therefore, the high-temperature pre-operation annealing is critical to form the desirable orthorhombic phase of NiSi at Ni/SiO{sub x} interfaces towards thermodynamically stable antioxidation behavior. Remarkably, with this improved interfacial engineering, the oxidation of 80-nm-diameter Ni nanochain-SiO{sub x} saturates after annealing at 550 °C in air for 12 h. Additional annealing at 550 °C in air for as long as 20 h (i.e., 32 h air annealing at >550 °C in total) has almost no further impact on the structural or optical properties of the coatings, the latter being very sensitive to any interfacial changes due to the localized surface plasmon resonances of the metal nanostructures. This phenomenon holds true for Ni nanoparticle diameter down to 40 nm in Ni-SiO{sub x} system, where the optical response remains stable for 53 h at 550 °C in air. The oxidation vs. time curve also shows saturation behavior deviating from the kinetic Deal-Grove oxidation model. These results strongly suggest a promising approach to thermodynamically stable, anti-oxidation Ni/SiO{sub x} cermet absorbers via interfacial engineering.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Acoustic Travel-Time Tomography for Wind Energy

New remote sensing technologies for direct observation of the atmospheric flow in the proximity of operating wind turbines are necessary for the advancement of wind turbine design, wind plant control, and the validation of high-fidelity numerical models; fundamental goals of the DOE Wind Energy Technology Office's (WETO's) A2e program. Modern remote sensing technologies for commercial and research applications rely on the backscatter of light or sound waves, which limits spatial and temporal resolution and cannot produce reliable flow estimates near solid bodies or reflective surfaces. Acoustic tomography (AT) is an innovative sensing technology based on fundamental thermodynamic properties of the atmosphere and an inverse algorithm that can reconstruct both velocity and temperature fields within a network of acoustic transducers. AT relies on the direct travel path of acoustic signals between speakers and microphones in the network and can achieve much higher resolutions than conventional backscatter technologies. For wind energy R&D applications, AT represents an extremely economical option over other remote sensing technologies, integrating mature and commonly available acoustic and signal processing hardware. This report is intended as an update on the development of the AT array on the NREL Flatirons Campus (FC) and includes a brief review of the instrumentation, the calibration of equipment, signal processing, and resulting flow field estimates. Designs for future AT systems and applications are detailed in this report, including summaries of new capabilities, engineering and theoretical challenges, and anticipated costs help to outline future directions for AT technology R\&D. The potential for application of AT to utility-scale turbines is also discussed. Investing in the development of the proposed instrument will establish AT as a transformational RS technique that represents a significant advance in measurement instrumentation, enabling new fundamental insights into the structure of the atmospheric boundary layer and supporting applications for wind energy, pollution transport, and resource characterization. AT is also an extremely economical option over other RS instruments, integrating mature and commonly available acoustic and signal processing hardware.

17 WIND ENERGY↗

Integrating Cyber-Informed Engineering into Enterprise Risk Management

This document supports the application of Cyber-Informed Engineering (CIE) within the context of Enterprise Risk Management (ERM) to enhance cyber-resilience. It highlights that many critical infrastructure organizations use ERM to manage business risks and emphasizes the importance of evaluating critical systems and assets. The proposed approach can be adopted independently of formal ERM processes and offers a starting point for integrating CIE alongside existing or new ERM practices. Both CIE and ERM are iterative, and their alignment fosters continuous improvement and supports the engineering and operations cultures of an organization.

42 ENGINEERING↗

BETO 2021 Peer Review: Algae Biotechnology Partnership - Technology Area Session: Advanced Algae Systems

Development of advanced genetic and genomic tools for targeted algal metabolic engineering pursuits will be integral to achieving target biomass productivity and, ultimately, the BETO goal of cost-competitive biofuels derived from algal biomass by 2022. However, at present, broad-host-range tool development is currently hindered by strain-specific negative regulatory mechanisms. Indeed, the biological processes controlling algal transcription and translation are subject to complex host regulation, which often presents hurdles for targeted genetic engineering strategies. Advanced genetic approaches offer a means to rewire these regulatory systems and/or introduce novel functionality into algal biocatalysts. Synthetic systems biology approaches also present a means to construct novel genetic regulatory networks and rewire natural biological systems to establish an “orthogonal central dogma,” wherein non-native control elements are introduced into or evolved in host microbes for bypass of host control. To this end, the Algae Biotechnology Partnership aims to develop advanced genetic editing tools and synthetic and orthogonal genetic regulatory systems to enable universal metabolic engineering strategies in top-candidate deployment algal strains. Successful development will ultimately open the door for targeted strain-engineering strategies, aimed at maximizing algal outdoor biomass production, composition, and strain robustness.

biocatalysis↗

Engineering Robust Production Microbes for Large-Scale Cultivation

Systems biology and synthetic biology are increasingly utilized to review and modulate complex biological systems. As such, many issues arising during scaling-up microbial production processes can be addressed using these methods. We review differences between laboratory-scale cultures and larger-scale processes to provide a perspective on those strain characteristics that are especially important during scaling. Systems biology has been used to examine a range of microbial systems for their response in bioreactors to fluctuations in nutrients, dissolved gases, and other stresses. Synthetic biology has been used both to assess and modulate strain response, and to engineer strains to improve production. We discuss these approaches and tools in the context of their use in engineering robust microbes for applications in large-scale production.

59 BASIC BIOLOGICAL SCIENCES↗

Crystalline Nanoporous Frameworks: a Nanolaboratory for Probing Excitonic Device Concepts.

Electro-optical organic materials hold great promise for the development of high-efficiency devices based on exciton formation and dissociation, such as organic photovoltaics (OPV) and organic light-emitting devices (OLEDs). However, the external quantum efficiency (EQE) of both OPV and OLEDs must be improved to make these technologies economical. Efficiency rolloff in OLEDs and inability to control morphology at key OPV interfaces both reduce EQE. Only by creating materials that allow manipulation and control of the intimate assembly and communication between various nanoscale excitonic components can we hope to first understand and then engineer the system to allow these materials to reach their potential. The aims of this proposal are to: 1) develop a paradigm-changing platform for probing excitonic processes composed of Crystalline Nanoporous Frameworks (CNFs) infiltrated with secondary materials (such as a complimentary semiconductor); 2) use them to probe fundamental aspects of excitonic processes; and 3) create prototype OPVs and OLEDs using infiltrated CNF as active device components. These functional platforms will allow detailed control of key interactions at the nanoscale, overcoming the disorder and limited synthetic control inherent in conventional organic materials. CNFs are revolutionary inorganic-organic hybrid materials boasting unmatched synthetic flexibility that allow tuning of chemical, geometric, electrical, and light absorption/generation properties. For example, bandgap engineering is feasible and polyaromatic linkers provide tunable photon antennae; rigid 1-5 nm pores provide an oriented, intimate host for triplet emitters (to improve light emission in OLEDs) or secondary semiconducting polymers (creating a charge-separation interface in OPV). These atomically engineered, ordered structures will enable critical fundamental questions to be answered concerning charge transport, nanoscale interfaces, and exciton behavior that are inaccessible in disordered systems. Implementing this concept also creates entirely new dimensions for device fabrication that could both improve performance, increase durability, and reduce costs with unprecedented control of over properties. This report summarizes the key results of this project and is divided into sections based on publications that resulted from the work. We begin in Section 2 with an investigation of light harvesting and energy transfer in a MOF infiltrated with donor and acceptor molecules of the type typically used in OPV devices (thiophenes and fullerenes, respectively). The results show that MOFs can provide multiple functions: as a light harvester, as a stabilizer and organizer or the infiltrated molecules, and as a facilitator of energy transfer. Section 3 describes computational design of MOF linker groups to accomplish light harvesting in the visible and facilitate charge separation and transport. The predictions were validated by UV-visible absorption spectroscopy, demonstrating that rational design of MOFs for light-harvesting purposes is feasible. Section 4 extends the infiltration concept discussed in Section to, which we now designate as "Molecule@MOF" to create an electrically conducting framework. The tailorability and high conductivity of this material are unprecedented, meriting publication in the journal Science and spawning several Technical Advances. Section 5 discusses processes we developed for depositing MOFs as thin films on substrates, a critical enabling technology for fabricating MOF-based electronic devices. Finally, in Section 6 we summarize results showing that a MOF thin film can be used as a sensitizer in a DSSC, demonstrating that MOFs can serve as active layers in excitonic devices. Overall, this project provides several crucial proofs-of- concept that the potential of MOFs for use in optoelectronic devices that we predicted several years ago [ 3 ] can be realized in practice.

Allendorf, Mark D.↗