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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Chapter 7 - CRISPR-Based Tools for Microbial Cell Factories

The development of microbial chassis for the production of a variety of biochemicals and biofuels is a growing area of research. How to efficiently manipulate genetic information to achieve optimal production of these compounds is a key area of focus in the field. In recent years, clustered regularly interspaced palindromic repeats (CRISPR) and its associated proteins (Cas) have become a popular strategy for gene editing and regulation in many organisms due to its versatility and efficacy. Here, we describe methods developed utilizing CRISPR-Cas systems for engineering microbial cell factories (e.g., bacteria and yeast) at the single gene to genome scale for mutagenesis and transcriptional regulation of target genes. Finally, we provide a perspective on the challenges and opportunities for the applications of advanced CRISPR-Cas-based tools for engineering microbial cell factories.

BIOMASS FUELS↗
DOE OSTI2021

Hydraulic architecture explains species moisture dependency but not mortality rates across a tropical rainfall gradient

Aim Intensified droughts are affecting tropical forests across the globe. However, the underlying mechanisms of tree drought response and mortality are poorly understood. Hydraulic traits and especially hydraulic safety margins (HSMs), i.e. the extent to which plants buffer themselves from thresholds of water stress, provide insights into species-specific drought vulnerability. Methods We investigated hydraulic traits during an intense drought triggered by the 2015-2016 El Niño on 27 canopy trees across three tropical forest sites with differing precipitation. We capitalized on the drought event as a time when plant water status might approach or exceed thresholds of water stress. We investigated the degree to which these traits varied across the rainfall gradient, as well as relationships amongst hydraulic traits and species-specific optimal moisture and mortality rates. Results There were no differences among sites for any measured trait. There was strong coordination among traits, with a network analysis revealing two major groups of coordinated traits. In one group there were water potentials, turgor loss point, sapwood capacitance and density, HSMs, and mortality rate. In the second group there was leaf mass per area, leaf dry matter content, hydraulic architecture (leaf area to sapwood area ratio), and species-specific optimal moisture. Conclusion These results demonstrated that while species with greater safety from turgor loss had lower mortality rates, hydraulic architecture was the only trait that explained species’ moisture dependency. Species with a greater leaf area to sapwood area ratio were associated with drier sites and reduced their transpirational demand during the dry season via deciduousness.

Hydraulic Saftey Margins, drought, tropical forest↗
DOE OSTI2026

Joint Optimization of Multimodal Transit Frequency and Shared Autonomous Vehicle Fleet Size with Hybrid Metaheuristic and Nonlinear Programming

Shared autonomous vehicles (SAVs) bring competition to traditional transit services but redesigning multimodal transit network can utilize SAVs as feeders to enhance service efficiency and coverage. This paper presents an optimization framework for the joint multimodal transit frequency and SAV fleet size problem, a variant of the transit network frequency setting problem. The objective is to maximize total transit ridership (including SAV-fed trips and subtracting boarding rejections) across multiple time periods under budget constraints, considering endogenous mode choice (transit, point-to-point SAVs, driving) and route selection, while allowing for strategic route removal by setting frequencies to zero. Due to the problem’s non-linear, non-convex nature and the computational challenges of large-scale networks, we develop a hybrid solution approach that combines a metaheuristic approach (particle swarm optimization) with nonlinear programming for local solution refinement. To ensure computational tractability, the framework integrates analytical approximation models for SAV waiting times based on fleet utilization, multimodal network assignment for route choice, and multinomial logit mode choice behavior, bypassing the need for computationally intensive simulations within the main optimization loop. Applied to the Chicago metropolitan area’s multimodal network, our method illustrates a 33.3% increase in transit ridership through optimized transit route frequencies and SAV integration, particularly enhancing off-peak service accessibility and strategically reallocating resources.

Ng, Max↗
DOE OSTI2021

Methods and Usability Enhancements in Shift for Non-LWR Applications

Several development and analysis tasks were undertaken in FY21 under the Nuclear Energy Advanced Modeling and Simulation program to enhance modeling of non light–water reactors (LWRs) with Shift. Specifically, these efforts targeted enhancements for tristructural isotropic (TRISO) fuel modeling. A new Shift user interface was developed that allows for much better usability and ease of modeling for non-LWR problems and TRISO fuel. Performance studies were conducted using an HTR-10 fuel pebble model by comparing different geometry packages in Shift, KENO-VI, and Serpent. These studies showed that the new geometry package in Shift performs well compared to Serpent for TRISO fuel modeling with consistent tracking options between both packages. The studies also identified the most critical areas of improvement for more efficiently performing Monte Carlo transport on TRISO fuel models with Shift. Tally calculations in Shift were optimized for non-LWR cross section generation and depletion calculations, and areas for further optimization and accuracy improvements were identified. Finally, initial collaboration efforts were formed between Idaho National Laboratory, Argonne National Laboratory, and the Nuclear Regulatory Commission to use Shift for Comprehensive Reactor Analysis Bundle support.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Engineering Atomically Dispersed FeN 4 Active Sites for CO 2 Electroreduction

Atomically dispersed FeN 4 active sites have exhibited exceptional catalytic activity and selectivity for the electrochemical CO 2 reduction reaction (CO2RR) to CO. However, the understanding behind the intrinsic and morphological factors contributing to the catalytic properties of FeN 4 sites is still lacking. By using a Fe-N-C model catalyst derived from the ZIF-8, we deconvoluted three key morphological and structural elements of FeN 4 sites, including particle sizes of catalysts, Fe content, and Fe-N bond structures. Furthermore, their respective impacts on the CO2RR were comprehensively elucidated. Engineering the particle size and Fe doping is critical to control extrinsic morphological factors of FeN 4 sites for optimal porosity, electrochemically active surface areas, and the graphitization of the carbon support. In contrast, the intrinsic activity of FeN 4 sites was only tunable by varying thermal activation temperatures during the formation of FeN 4 sites, which impacted the length of the Fe-N bonds and the local strains. The structural evolution of Fe-N bonds was examined at the atomic level. First-principles calculations further elucidated the origin of intrinsic activity improvement associated with the optimal local strain of the Fe-N bond.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

FIRED (Fire Events Delineation): An Open, Flexible Algorithm and Database of US Fire Events Derived from the MODIS Burned Area Product (2001–2019)

Harnessing the fire data revolution, i.e., the abundance of information from satellites, government records, social media, and human health sources, now requires complex and challenging data integration approaches. Defining fire events is key to that effort. In order to understand the spatial and temporal characteristics of fire, or the classic fire regime concept, we need to critically define fire events from remote sensing data. Events, fundamentally a geographic concept with delineated spatial and temporal boundaries around a specific phenomenon that is homogenous in some property, are key to understanding fire regimes and more importantly how they are changing. Here, we describe Fire Events Delineation (FIRED), an event-delineation algorithm, that has been used to derive fire events (N = 51,871) from the MODIS MCD64 burned area product for the coterminous US (CONUS) from January 2001 to May 2019. The optimized spatial and temporal parameters to cluster burned area pixels into events were an 11-day window and a 5-pixel (2315 m) distance, when optimized against 13,741 wildfire perimeters in the CONUS from the Monitoring Trends in Burn Severity record. The linear relationship between the size of individual FIRED and Monitoring Trends in Burn Severity (MTBS) events for the CONUS was strong (R2 = 0.92 for all events). Importantly, this algorithm is open-source and flexible, allowing the end user to modify the spatio-temporal threshold or even the underlying algorithm approach as they see fit. We expect the optimized criteria to vary across regions, based on regional distributions of fire event size and rate of spread. We describe the derived metrics provided in a new national database and how they can be used to better understand US fire regimes. The open, flexible FIRED algorithm could be utilized to derive events in any satellite product. We hope that this open science effort will help catalyze a community-driven, data-integration effort (termed OneFire) to build a more complete picture of fire.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Moderator Test Station at ORNL

Oak Ridge National Laboratory (ORNL) hosts two world-leading slow neutron sources, the Spallation Neutron Source (SNS) and the High Flux Isotope Reactor (HFIR), and is currently developing the technical design for a Second Target Station (STS) for the SNS. Upon completion of the STS project, ORNL will be uniquely positioned to optimize each of its three neutron sources, the SNS First Target Station (FTS), the STS, and HFIR, in a complementary way. Among the essential aspects of a reimagined FTS and the current STS concept are high-brightness parahydrogen moderators—moderators which are optimized for high per-unit-area neutron brightness rather than integrated-across-large-area neutron intensity. The high-brightness moderators proposed for the STS will significantly outperform the coupled moderators currently on the FTS for appropriately optimized neutron beamlines, provided the moderating hydrogen is converted to near-equilibrium levels of parahydrogen (approximately 99.8% at 20 K). The original FTS moderators, by contrast, were conservatively designed to be relatively insensitive to the exact ortho:para ratio, with a consequent loss in performance. As a result, a redesign of the FTS moderators assuming fully converted parahydrogen could result in significant performance improvements on the FTS coupled moderators, and more consistent performance over time for all hydrogen moderators. This “parahydrogen problem” is a long-standing challenge for the effective implementation of hydrogen cold moderators at high-power neutron sources. In addition, the development of new moderator concepts, whether based on previously unused materials, structured heterogeneous arrays, or even simply on changes in overall shape and size is significantly restricted at a large-scale production facility intended to use the neutron beams so produced. Accordingly, moderators for production neutron sources are often designed in a very conservative, low-risk fashion, even though this compromises the absolute neutronic performance. Advanced moderator concepts worthy of study include features that could not be tested without redesigning and redeploying the entire existing reflector, shielding, and neutron beamline installation, making such development efforts far more expensive than building a stand-alone test facility. We propose a Moderator Test Station (MTS) at the SNS with which we will verify such performance gains and test new moderator concepts. These concepts include both high-brightness and large-volume parahydrogen moderators, as well as moderators with tailored ortho:para hydrogen levels, heterogeneous moderator concepts such as the convoluted moderator or pelletized moderators, and moderators made of materials like ammonia, ethane, and oxygen clathrates, which have not been widely tested let alone deployed at neutron source facilities.

42 ENGINEERING↗
DOE OSTI2025

Project Title: Demonstration High Temperature Superconducting NonPlanar Stellarator Magnet with Advanced Manufactured Assemblies

This is the final report for the project “Demonstration High Temperature Superconducting Non- Planar Stellarator Magnet with Advanced Manufactured Assemblies”, funded by DOE, and performed by Type One Energy from September, 2020, to March 2024 involving the Fusion Technology Institute at the University of Wisconsin–Madison, the Plasma Science and Fusion Center (PSFC) at the Massachusetts Institute of Technology (MIT) and Commonwealth Fusion Systems (CFS) to design and fabricate the first non-planar HTS (REBCO) coil for a high-field stellarator based on the SPARC tokamak’s VIPER cable concept. Stellarators at high fields make high-temperature superconducting magnets necessary for a compact fusion device. But the asymmetric and non-planar nature of its components, especially the magnets make it difficult for scalable producibility. To address these challenges, two promising technologies have emerged: advanced manufacturing (AM) for the supporting plates for forming the magnets, and high-temperature superconducting (HTS) cables inside the plates. AM has advanced enough to produce stellarator components with the necessary geometric complexity, size, and the precision, leading to potentially significant reductions in production time, cost, and waste. The cost of HTS tape has decreased dramatically, and progress in HTS planar magnet development has reached a point where it can be proposed for application to complex 3D non-planar magnets. The main objective of this project is to develop, demonstrate and pre-commercialize a novel, non-planar HTS coil shape that remains superconducting to achieve production scalable reductions in time and cost and performance. The proposed technology is based on the novel concept of a precision sub-scale HTS nonplanar coil assembly. This project focuses on the design, fabrication, material optimization of cable design, and validation and demonstration of the high current carrying capability of superconducting magnets and their support in a complex 3D shape needed for application to stellarator magnetic plasma confinement. The specific objectives of this research program include: (1) The successful application of metal AM to build a precision sub-scale HTS nonplanar coil, (2) An HTS cable and cross-section design that can conform to the required nonplanar coil shape (bend radii as tight as 10-cm) and remains superconducting at an engineering current density of 1.35 kA/cm 2 at 77 K and 1 tesla at the conductor (5 kA in the cable). To achieve the above challenging goals, we have formed a multidisciplinary research team consisting of members from Type One Energy and UW-Madison, MIT PSFC and CFS with complementary skills and strong facilities. The team worked collaboratively on fundamental and applied research on the following three major technical areas: (1) Design, fabrication, and optimization of non-planar HTS Cable The ultimate goal of the project is to determine if commercial REBCO tapes and additive manufacturing can be used to fabricate high field (≥ 10T) non-planar coils with tight bending radii (≃ 100mm) and with a degradation of the critical current (Ic) smaller than 20% with respect to the expected performance. We started with shorter length cable to evaluate the scalability of the production process and eventually reached multiple turns for higher magnetic fields. Our findings suggest that a stellarator coil system of a relevant size, characterized by its asymmetric and non-planar components, can be fabricated using a formed cable in plate method. This system can be simulated using a large-scale modeling approach. The use of hybrid modeling 3 techniques will be pivotal in reducing the complexity of the model and in assessing expected performance in designs. (2) Modeling and simulation of the non-planar HTS Cable Multiphysics simulations are performed using the commercial software and are carried out in self-field conditions, involving 2D and 3D models and twisted around one slot of twist-pitched VIPER cable. Multiphysics simulations are mainly focused on the coil for the critical current evaluation, the magnetic field map, self-Lorentz forces and mechanical, and magnetothermal behavior and the quench dynamics. The detailed model and prediction of the superconducting performance of a stellarator-relevant demonstration cable from numerical simulations supports the results from the actual testing backing the results. A detailed description and results are provided in the later sections. (3) Design, fabrication, and optimization of support for the non-planar HTS Cable The team developed an additive manufactured (AM) coil positioning plate that formed into the required non-planar geometry (with bend radii as tight as 10-cm) and to acceptable tolerances required for a stellarator magnet: (+0.25-mm from ideal on dimensions of coil positioning plates and up to +1-mm from ideal for position of wound coil). The plate materials is also included in this selection process from fabrication and 3D printing perspective and commensurate with eventual application to a fusion reactor. From the cost effectiveness point of view, the HTS coil and plate has the potential to cost less than that made in conventional methods with less waste (<75% waste) reducing time (<50%) and cost (<50%), especially as the AM field matures. The application of advanced manufacturing in the construction of the support plates will also lead to cost reduction, as the cables can be easily replaced, thereby making the assembly modular. With such high primary cost and time savings, high current densities and magnetic field, the funded R&D work has validated the designs, proven the feasibility, and characterized the performance of the HTS coil and plate assembly, paving the way for a relevant-size stellarator coil system.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Machine Learning Approach for Spatiotemporal Multivariate Optimization of Environmental Monitoring Sensor Locations

Abstract Long-term environmental monitoring is critical for managing the soil and groundwater at contaminated sites. Recent improvements in state-of-the-art sensor technology, communication networks, and artificial intelligence have created opportunities to modernize this monitoring activity for automated, fast, robust, and predictive monitoring. In such modernization, it is required that sensor locations be optimized to capture the spatiotemporal dynamics of all monitoring variables as well as to make it cost-effective. The legacy monitoring datasets of the target area are important to perform this optimization. In this study, we have developed a machine-learning approach to optimize sensor locations for soil and groundwater monitoring based on ensemble supervised learning and majority voting. For spatial optimization, Gaussian process regression (GPR) is used for spatial interpolation, while the majority voting is applied to accommodate the multivariate temporal dimension. Results show that the algorithms significantly outperform the random selection of the sensor locations for predictive spatiotemporal interpolation. While the method has been applied to a four-dimensional dataset (with two-dimensional space, time, and multiple contaminants), we anticipate that it can be generalizable to higher-dimensional datasets for environmental monitoring sensor location optimization.

Siddiquee, Masudur R.↗
DOE OSTI2022

Manufacturing Science

The Manufacturing Science area of leadership spans the application of fundamental science research and development activities to understand the critical steps in manufacturing processes for the purposes of control and optimization. Although manufacturing is an applied area of research, fundamental science underpins our knowledge of both traditional and transformational manufacturing processes. For example, casting, welding, and many modern additive manufacturing processes that see wide use are broadly classified as solidification processes, with material transitioning from liquid to solid phases upon cooling from higher temperature. However, our understanding of the detailed physics involved in such processes is incomplete, and solidification remains a grand challenge for materials science. To enable adoption of transformative fabrication processes or to accelerate development of traditional ones, it is necessary to develop a detailed mechanistic understanding spanning multiple scales, starting with atomic building blocks (defects, interfaces, composition) and extending all the way up to macroscale performance in moderate and/or extreme environments.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Low-temperature sprayed SnO x nanocomposite films with enhanced hole blocking for efficient large area perovskite solar cells

Scalable fabrication of charge transport layers with high uniformity and compactness is essential for the commercialization of perovskite solar cells (PSCs). Cost-effective deposition of high-quality electron transport layers (ETLs) is a particularly important step to achieve low-cost, efficient and large-area PSCs. Here, an open-air (relative humidity of 40–50%) and low-temperature (≤100 °C) ultrasonic spray coating of tin oxide (SnO 2 ) nanocomposite films incorporating nanocrystalline SnO 2 nanoparticles in an amorphous SnO x matrix is demonstrated to fabricate large-area ETLs for planar PSCs. The optimized SnO 2 /SnO x nanocomposite exhibits significantly enhanced hole-blocking and high-power conversion efficiencies of 18% and 16% for planar PSCs with an active area of 0.2 cm 2 and 1 cm 2 , respectively. More importantly, the devices show little current–voltage hysteresis as well as good shelf-life stability by maintaining ~90% of the initial performance without encapsulation after 2500 hours storage under inert conditions. Additionally, high voltages of >6.0 V have been obtained for solar modules of 2.1 cm 2 aperture area comprising six sub-cells in series, suggesting that the low-temperature, open-air and fast spray coating is suitable and transferable to deposit large-area charge transport layers for scalable PSCs or other optoelectronic devices.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

The ORNL Moderator Test Station Science Case

Oak Ridge National Laboratory (ORNL) hosts two world-leading slow neutron sources, the Spallation Neutron Source (SNS) and the High Flux Isotope Reactor (HFIR), and is currently developing the technical design for a Second Target Station (STS) for the SNS. Upon completion of the STS project, ORNL will be uniquely positioned to optimize each of its three neutron sources, the SNS First Target Station (FTS), the STS, and HFIR, in a complementary way. Among the essential aspects of a re-imagined FTS and the current STS design are high-brightness parahydrogen moderators—moderators which are optimized for high per-unit-area neutron brightness rather than integrated-across-large-area neutron intensity. The high-brightness moderators proposed for the STS will, for the brightness metric, significantly outperform the coupled moderators currently on the FTS for appropriately optimized neutron beamlines, provided the moderating hydrogen is converted to near-equilibrium levels of parahydrogen (approximately 99.8% at 20 K). The original FTS moderators, by contrast, were conservatively designed to be relatively insensitive to the exact ortho:para ratio, with a consequent loss in performance. As a result, a redesign of the FTS moderators assuming fully converted parahydrogen could result in significant performance improvements on the FTS coupled moderators, and more consistent performance over time for all hydrogen moderators. This “parahydrogen problem” is a long-standing challenge for the effective implementation of hydrogen cold moderators at high-power neutron sources. In addition, the development of new moderator concepts, whether based on previously unused materials, structured heterogeneous arrays, or even simply on changes in overall shape and size is significantly restricted at a large-scale production facility intended to use the resulting neutron beams. Accordingly, moderators for production neutron sources are often designed in a very conservative, low-risk fashion, even though this compromises the absolute neutronic performance. Advanced moderator concepts worthy of study include features that could not be tested without redesigning and redeploying the entire existing reflector, shielding, and neutron beamline installation, making such development efforts far more expensive than building a stand-alone test facility.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Cyber risk assessment and investment optimization using game theory and ML-based anomaly detection and mitigation for wide-area control in smart grids

The electric power grid is increasingly becoming susceptible to cyber attacks that exploit vulnerabilities in the smart grid control, information, and physical layers. Successful cyber attacks can have catastrophic impacts on the social and economic well-being of any nation all over the globe. It has, thus, become imperative to secure the smart grid against such adversarial actions to ensure stable, secure, and reliable operation of the grid. The existing research and industry practices prove to be inadequate in terms of providing pragmatic and effective defense methodologies and measures for long-term cybersecurity planning and real-time cybersecurity for grid operation. For example, existing works lack models that incorporate uncertain behavior of cyber-attackers and pragmatic defense measures for cyber risk assessment and cybersecurity investment optimization which often provide unreliable and strictly qualitative solutions to these problems. At the same time, with the growing number of cyber incidents in the grid, there still exists a need to develop attack-resilient algorithms for wide-area monitoring, protection, and control (WAMPAC) applications like the wide-area voltage control systems (WAVCS) for Flexible AC Transmissions Systems (FACTS) that lack in scalable and feasible solutions from the cybersecurity perspective. This dissertation proposes novel models and methodologies for: (1) Cybersecurity planning, and (2) Cybersecurity for system operation. The cybersecurity planning is achieved through cyber risk assessment and cybersecurity resource investment optimization for long-term cybersecurity of the grid using game theory and attack-defense trees. Cybersecurity for system operation consists of development of cyber anomaly detection and mitigation algorithms for flexible AC transmission system (FACTS) controller-based wide-area voltage control systems (WAVCS) using machine learning (ML), and software defined networking-based moving target defense network routing for achieving real-time cyber-physical security for grid operations. This is followed by hardware-in-the-loop (HIL) implementation and evaluation of these attack prevention, detection, and mitigation algorithms and methodologies showcasing their feasibility in a close to real-world environment. For cybersecurity planning, a novel approach involving a combination of game theory and attack defense trees (ADT) for optimal cybersecurity resource allocation in the smart grid is proposed. This methodology involves modeling of the cyber-physical smart grid substations as ADTs, defining attacker costs, defense costs, and attack probabilities for attack access points. Using game theoretical formulation, optimal defense strategies for the defender of the system to invest cybersecurity resources in the grid are obtained. Additionally, a game-theoretic framework is developed for quantitative cyber-physical risk assessment of the grid under a dynamically changing cyber threat space and uncertain behavior of cyber attackers which is further used to optimize investments in the smart grid's cybersecurity resources. The attacker, defender, and the smart grid system are modeled while incorporating attacker-stochasticity and federal guidelines for smart grid cybersecurity. This allows quantification of threat, vulnerabilities, and attack impact of the grid for quantitative risk assessment. The defender's budget to invest in the security resources in the grid is optimized based on the strategies leading to minimum system risk. The evaluation of the proposed solutions highlight the feasibility for practical implementation of these methodologies and algorithms in the smart grid, while taking the federal requirements and guidelines for smart grid security into consideration. For achieving cybersecurity for system operation, attack prevention, detection, and mitigation algorithms and methodologies are developed specifically for FACTS-based WAVCS. Anomaly detection and mitigation in the WAVCS are achieved using algorithms based on machine learning which involves offline training and testing of ML models with CPS datasets incorporating physics-based features that allow accurate distinction between system faults and cyber attacks. For attack prevention, a methodology based on software defined network (SDN)-based moving target defense (MTD) network routing is proposed that enables prevention of Denial of Service (DoS) type attacks on the smart grid communication system. Subsequently, these methodologies and algorithms are implemented and evaluated on an HIL testbed that allows for real-time attack prevention, detection, and mitigation of emulated cyber attacks on the WAVCS in a close to real-world environment. The results show highly accurate and efficient performance of the implemented algorithms and methodologies with the smart grid system operating within the NERC's system operation limits even in the presence of DoS and data integrity cyber attacks. This work opens up future research opportunities in other directions such as (1) Expanding cybersecurity planning methodologies to real-time cyber contingency analysis with different game formulations; and (2) Applying the cybersecurity for system operation algorithms to broader categories of wide-area control applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Dynamic Decarbonization through Autonomous Physics-Centric Deep Learning and Optimization of Building Operations (Abstract only)

This project directly addresses the primary goal of Area of Interest 2 in the CRADA call: to advance optimization-based integrated energy management systems in commercial and residential buildings. Pacific Northwest National Laboratory (PNNL) and its industry partner PassiveLogic aim to accomplish this by reaching three key objectives. First, to ensure a broad impact in the building controls industry, PNNL will extend its open-source library for predictive control synthesis by augmenting its capabilities with data-driven self-learning of building models and auto-calibration of predictive controllers. The effort will focus on building use cases selected in collaboration with PassiveLogic. The team will specifically address the development of methods for data-driven adaptation of building models, investigation of model architectures that best address specific building types, and automated synthesis of differentiable predictive controllers that optimize diverse objectives. Second, PNNL will collaborate with PassiveLogic to integrate the aforementioned methods with PasiveLogic’s advanced controls platform. The collaborative integration effort will inform the developments under the first objective by providing specific data on the attainable performance of model learning on resource-constrained edge computing platforms. This software integration effort will increase the technical maturity of the developed libraries by exploring the use of software integration tools and methods. Third, PNNL and PassiveLogic will work to improve the technology readiness of the developed predictive controllers by testing their performance in relevant test environments, such as high-fidelity simulation, hardware in the loop, and actual test buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Metal‐Organic Framework (MOF) Morphology Control by Design

Abstract Exerting morphological control over metal‐organic frameworks (MOFs) is critical for determining their catalytic performance and to optimize their packing behavior in areas from separations to fuel gas storage. A mechanism‐based approach to tailor the morphology of MOFs is introduced and experimentally demonstrated for five cubic Zn 4 O‐based MOFs. This methodology provides three key features: 1) computational screening for selection of appropriate additives to change crystal morphology based on knowledge of the crystal structure alone; 2) use of additive to metal cluster geometric relationships to achieve morphologies expressing desired crystallographic facets; 3) potential for suppression of interpenetration for certain phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

An affordable platform for automated synthesis and electrochemical characterization

In recent years, self-driving laboratories (SDLs) have emerged as a powerful tool to expedite various areas of chemical research. For optimal functionality, these laboratories must be adaptable, readily modifying configurations to meet researchers' specific needs. Despite these advances, much of chemistry still depends on proprietary equipment from specialized vendors, which can be restrictive and difficult to customize for diverse lab setups. Moreover, ensuring reproducibility requires full disclosure of equipment details. In this work, we introduce an automated system featuring a cost-effective, self-designed potentiostat and a straightforward synthesis platform. We provide complete transparency by disclosing the electronic schematics of the potentiostat and the software used in the system. Our aim is to reduce the barriers to entry for SDLs and promote the principles of open science.

Pablo-García, Sergio↗
DOE OSTI2023

GAHLS: an optimized graph analytics based high level synthesis framework

The urgent need for low latency, high-compute and low power on-board intelligence in autonomous systems, cyber-physical systems, robotics, edge computing, evolvable computing, and complex data science calls for determining the optimal amount and type of specialized hardware together with reconfigurability capabilities. With these goals in mind, we propose a novel comprehensive graph analytics based high level synthesis (GAHLS) framework that efficiently analyzes complex high level programs through a combined compiler-based approach and graph theoretic optimization and synthesizes them into message passing domain-specific accelerators. This GAHLS framework first constructs a compiler-assisted dependency graph (CaDG) from low level virtual machine (LLVM) intermediate representation (IR) of high level programs and converts it into a hardware friendly description representation. Next, the GAHLS framework performs a memory design space exploration while account for the identified computational properties from the CaDG and optimizing the system performance for higher bandwidth. The GAHLS framework also performs a robust optimization to identify the CaDG subgraphs with similar computational structures and aggregate them into intelligent processing clusters in order to optimize the usage of underlying hardware resources. Finally, the GAHLS framework synthesizes this compressed specialized CaDG into processing elements while optimizing the system performance and area metrics. Evaluations of the GAHLS framework on several real-life applications (e.g., deep learning, brain machine interfaces) demonstrate that it provides 14.27× performance improvements compared to state-of-the-art approaches such as LegUp 6.2.

97 MATHEMATICS AND COMPUTING↗