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At least 1,603 records · Page 89

Targeted mutagenesis with sequence–specific nucleases for accelerated improvement of polyploid crops: Progress, challenges, and prospects

Many of the world's most important crops are polyploid. The presence of more than two sets of chromosomes within their nuclei and frequently aberrant reproductive biology in polyploids present obstacles to conventional breeding. The presence of a larger number of homoeologous copies of each gene makes random mutation breeding a daunting task for polyploids. Genome editing has revolutionized improvement of polyploid crops as multiple gene copies and/or alleles can be edited simultaneously while preserving the key attributes of elite cultivars. Most genome–editing platforms employ sequence–specific nucleases (SSNs) to generate DNA double–stranded breaks at their target gene. Such DNA breaks are typically repaired via the error–prone nonhomologous end–joining process, which often leads to frame shift mutations, causing loss of gene function. Genome editing has enhanced the disease resistance, yield components, and end–use quality of polyploid crops. However, identification of candidate targets, genotyping, and requirement of high mutagenesis efficiency remain bottlenecks for targeted mutagenesis in polyploids. In this review, we will survey the tremendous progress of SSN–mediated targeted mutagenesis in polyploid crop improvement, discuss its challenges, and identify optimizations needed to sustain further progress.

60 APPLIED LIFE SCIENCES↗

Simultaneous Thermoelectric Property Measurement and Incoherent Phonon Transport in Holey Silicon

Block copolymer patterned holey silicon (HS) was successfully integrated into a microdevice for simultaneous measurements of Seebeck coefficient, electrical conductivity, and thermal conductivity of the same HS microribbon. These fully integrated HS microdevices provided excellent platforms for the systematic investigation of thermoelectric transport properties tailored by the dimensions of the periodic hole array, that is, neck and pitch size, and the doping concentrations. Specifically, thermoelectric transport properties of HS with a neck size in the range of 16-34 nm and a fixed pitch size of 60 nm were characterized, and a clear neck size dependency was shown in the doping range of 3.1 × 10 18 to 6.5 × 10 19 cm -3 . At 300 K, thermal conductivity as low as 1.8 ± 0.2 W/mK was found in HS with a neck size of 16 nm, while optimized zT values were shown in HS with a neck size of 24 nm. Finally, the controllable effects of holey array dimensions and doping concentrations on HS thermoelectric performance could aid in improving the understanding of the phonon scattering process in a holey structure and also in facilitating the development of silicon-based thermoelectric devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

RT-EZ: A Golden Gate Assembly Toolkit for Streamlined Genetic Engineering of Rhodotorula toruloides

For economic and sustainable biomanufacturing, the oleaginous yeast Rhodotorula toruloides has emerged as a promising platform for producing biofuels, pharmaceuticals, and other valuable chemicals. However, genetic manipulation of R. toruloides has been limited by its high GC content and the lack of a replicating plasmid, necessitating gene integration into the genome of the yeast. To address these challenges, we developed the RT-EZ (R. toruloides Efficient Zipper) toolkit, a versatile tool based on Golden Gate assembly, designed to streamline R. toruloides engineering with improved efficiency and flexibility. The RT-EZ toolkit simplifies vector construction by incorporating new features such as bidirectional promoters and 2A peptides, color-based screening using RFP, and sequences optimized for both Agrobacterium tumefaciens-mediated transformation (ATMT) and easy linearization, enabling straightforward selection and transformation. Notably, the RT-EZ kit can be used to construct an expression cassette with four different genes in one assembly reaction, significantly improving vector construction speed and efficiency. The utility of the RT-EZ toolkit was demonstrated through the successful synthesis of arachidonic acid in R. toruloides by coexpressing fatty acid elongases and desaturases. Furthermore, this result underscores the potential of the RT-EZ toolkit to advance synthetic biology in R. toruloides, providing a streamlined method for addressing genetic engineering challenges in the yeast.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Strongly adhesive dry transfer technique for van der Waals heterostructure

That one can stack van der Waals materials with atomically sharp interfaces has provided a new material platform of constructing heterostructures. The technical challenge of mechanical stacking is picking up the exfoliated atomically thin materials after mechanical exfoliation without chemical and mechanical degradation. Chemically inert hexagonal boron nitride (hBN) has been widely used for encapsulating and picking up vdW materials. However, due to the relatively weak adhesion of hBN, assembling vdW heterostructures based on hBN has been limited. Here, we report a new dry transfer technique. We used two vdW semiconductors (ZnPS 3 and CrPS 4 ) to pick up and encapsulate layers for vdW heterostructures, which otherwise are known to be hard to fabricate. By combining with optimized polycaprolactone (PCL) providing strong adhesion, we demonstrated various vertical heterostructure devices, including quasi-2D superconducting NbSe 2 Josephson junctions with atomically clean interface. The versatility of the PCL-based vdW stacking method provides a new route for assembling complex 2D vdW materials without interfacial degradation.

36 MATERIALS SCIENCE↗

Data for "RT-EZ: A Golden Gate Assembly Toolkit for Streamlined Genetic Engineering of Rhodotorula toruloides"

For economic and sustainable biomanufacturing, the oleaginous yeast Rhodotorula toruloides has emerged as a promising platform for producing biofuels, pharmaceuticals, and other valuable chemicals. However, genetic manipulation of R. toruloides has been limited by its high GC content and the lack of a replicating plasmid, necessitating gene integration into the genome of the yeast. To address these challenges, we developed the RT-EZ ( R. toruloides Efficient Zipper) toolkit, a versatile tool based on Golden Gate assembly, designed to streamline R. toruloides engineering with improved efficiency and flexibility. The RT-EZ toolkit simplifies vector construction by incorporating new features such as bidirectional promoters and 2A peptides, color-based screening using RFP, and sequences optimized for both Agrobacterium tumefaciens-mediated transformation (ATMT) and easy linearization, enabling straightforward selection and transformation. Notably, the RT-EZ kit can be used to construct an expression cassette with four different genes in one assembly reaction, significantly improving vector construction speed and efficiency. The utility of the RT-EZ toolkit was demonstrated through the successful synthesis of arachidonic acid in R. toruloides by coexpressing fatty acid elongases and desaturases. This result underscores the potential of the RT-EZ toolkit to advance synthetic biology in R. toruloides , providing a streamlined method for addressing genetic engineering challenges in the yeast.

gene editing↗

A Fault-oblivious Extreme-scale Execution Environment

Exascale computing systems will provide a thousand-fold increase in parallelism and a proportional increase in failure rate relative to today's machines. Systems software for exascale machines must provide the infrastructure to support existing applications while simultaneously enabling efficient execution of new programming models that naturally express dynamic, adaptive, irregular computation; coupled simulations; and massive data analysis in a highly unreliable hardware environment with billions of threads of execution. We propose a new approach to the data and work distribution model provided by system software based on the unifying formalism of an abstract file system. The proposed hierarchical data model provides simple, familiar visibility and access to data structures through the file system hierarchy, while providing fault tolerance through selective redundancy. The hierarchical task model features work queues whose form and organization are represented as file system objects. Data and work are both first class entities. By exposing the relationships between data and work to the runtime system, information is available to optimize execution time and provide fault tolerance. The data distribution scheme provides replication (where desirable and possible) for fault tolerance and efficiency, and it is hierarchical to make it possible to take advantage of locality. The user, tools, and applications, including legacy applications, can interface with the data, work queues, and one another through the abstract file model. This runtime environment will provide multiple interfaces to support traditional Message Passing Interface applications, languages developed under DARPA's High Productivity Computing Systems program, as well as other, experimental programming models. We will validate our runtime system with pilot codes on existing platforms and will use simulation to validate for exascale-class platforms. In this final report, we summarize research results from the work done at the Ohio State University towards the larger goals of the project listed above.

97 MATHEMATICS AND COMPUTING↗

Open V2X at ESIF: June 2015 - February 2017 (Final Report)

The University of Delaware (UD), and their industrial partners, have carried out testing, documentation, and standards development at ESIF. These activities are intended to help meet the objective of NREL's INTEGRATE program, to enable clean energy technologies to increase the hosting capacity of the grid, by providing grid services in a holistic manner using an open source, interoperable platform. In particular, the 'Open V2X at ESIF' project worked to facilitate standardization and interoperability for Electric Vehicle technologies, including battery electric vehicles and plug-in hybrid vehicles (hence EV) to provide grid services. This was done by interconnecting and testing EV and EVSE (charging station) hardware from different manufacturers, by developing standards and test protocols for standards, and by documenting new protocols to be proposed as standards. Contractor-supplied equipment used in the testing included Vehicle Smart Links (VSLs) installed in an EV and School Bus, single-phase and three-phase charging stations, and an optimizing aggregator (software running on a server, hence just 'Aggregator'). The Aggregator software was developed by U of Delaware and is now licensed to Nuvve Corp for commercial development, and licensed to NRG/EVgo for demonstrations. The Aggregator monitors capacity and operations of the EVs and EVSEs, dispatches them in response to requests, and reports their operations and metered power flow. In operation, as vehicles move, plug-in and unplug, the aggregator tracks the total capacity available within a defined jurisdiction or RTO (Regional Transmission Organization, synonym for ISO or TSO), and dispatches part or all of that capacity based on market or direct dispatch signals from a grid entity. The VSL is the data acquisition and control module in the resource itself (EVSE or EV), with rich communication between a single Optimizing Aggregator and many VSL (one in each resource). All requests and dispatch events are also logged by the aggregator to make the provision of grid power auditable. For these tests, the dispatch was typically a recorded signal, the VSL was in the EV or EVSE, and the recording of experimental performance was often carried out by the normal logging functions of the aggregator.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Overview of Quantum Sensing Materials and Techniques for Energy Sector Applications

The energy sector is dependent upon highly sensitive sensing devices for a wide range of applications. Variables such as temperature, pH, electromagnetic fields, and pressure must be measured with high precision, often in harsh conditions (e.g. high temperature, pressure and humidity). These sensors are deployed in infrastructure such as transformers, pipelines, mines, nuclear power plants, and other areas to ensure safe operating conditions and uninterrupted, optimized service. Moreover, new opportunities for sensors have emerged due to the expansion of smart grids/meters, driverless vehicles, and the discovery of new oil/gas deposits. The continued maturation of quantum sensors offers exciting opportunities for quantum-enhanced measurements to improve sensitivity beyond the classical limit. Here, an overview of established and emerging quantum materials and methods for sensing applications will be provided. Opportunities within the energy sector for quantum sensors will then be analyzed, including oil/gas discovery, greenhouse gas emission monitoring, pH and ion sensing, current measurements, and quantum-enhanced spectroscopy, along with barriers such as quantum sensor platform miniaturization and ruggedization. A specific project at the National Energy Technology Laboratory involving the functionalization of qubits using metal-organic frameworks for enhanced quantum sensing will then be highlighted. Here, nitrogen vacancy centers (NV) in nanodiamonds, a commercially available qubit with long coherence times and utilizable quantum properties at room temperature, are encapsulated using the metal-organic framework ZIF-8. Significantly, the ZIF-8 coating increases the longitudinal spin relaxation lifetime of the NV centers, an important parameter for spin relaxometry-based quantum sensing experiments. These results demonstrate the importance of qubit functionalization as a crucial step for rationally designing high performance quantum sensors.

Crawford, Scott↗

Practical Insights on Applying Simulation-Based Control Methods in Experimental Studies

Advanced nuclear reactors are crucial to the future of energy both in the United States and around the globe. In contrast to the current operating fleet, they are characterized as being deployable in remote locations and able to operate in semi-autonomous or autonomous fashion. This leap forward necessitates a new reactor control paradigm. Because advanced nuclear reactors are still under development in the United States, the creation of new control methods to achieve autonomous operations has been based on systems modeling and simulation. However, an important factor in successfully deploying these new control methods is the ability to seamlessly transition from simulation environments to real-world settings. Control methods tested in both simulation and experimental settings need to be investigated in the context of advanced reactor applications. This work developed a series of simple controllers for Idaho National Laboratory (INL)’s Microreactor Applications Research Validation and Evaluation (MARVEL) microreactor operating in load-following scenarios. These controllers were tested in both simulation and experimental settings, and a comparative performance analysis was performed. The simulation tests leveraged the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND) software developed in a previous stage of the current effort, along with the MARVEL Reactor Excursion and Leak Analysis Program (RELAP5-3D) and Monte Carlo N-Particle (MCNP) models. The experimental tests leveraged the COMMAND software, MARVEL models, and the U.S. Department of Energy Microreactor Program’s Microreactor Automated Control System (MACS). MACS was developed to serve as a control method testbed. It was customized to mirror the MARVEL microreactor, and COMMAND enabled MACS to emulate the physics of MARVEL. The load-following controller was developed using the simulation platform, with efforts to emulate real systems by introducing actuator saturation and noise. These factors were incrementally accounted for in the controller design. After finalizing the controller design, it was implemented with the experimental setup. The experimental conditions tested included an initial test under conditions similar to the final simulation test, and two additional scenarios. The first scenario introduced additional actuator saturation to account for equipment aging over time, which was unknown to the controller. The second scenario introduced sensor delay, a phenomenon anticipated with the use of remote operations or wireless communication in advanced reactors. These tests revealed several notable differences. While the controller performed well in simulation, it exhibited several limitations when transitioning to hardware. The main challenges involved maintaining the steady-state target power, as evidenced by larger error values between the true reactor power and setpoint power, as well as persistent oscillations in controlled reactor power. These issues could lead to unacceptable transient conditions in real reactor testing. Introducing actuator aging and stochastic delays in the experimental setup significantly impacted controller performance, resulting in increased overshoot and undershoot, and exacerbated error and oscillations previously mentioned. These findings underscore the importance of experimental testbeds for testing and validating control methods, as controllers developed using only theory and/or simulation may perform unexpectedly when applied to actual hardware. This research emphasizes the need for an experimental testbed for achieving such validation.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

ACES: Infrastructure As Code. Model Optimization and Performance Capability

Infrastructure as Code (IaC) refers to managing infrastructure (networks, physical/virtual machines, storage, and connection topology) in a descriptive model/language, rather than configuring it manually or using interactive configuration tools. Just like source code can be compiled to generate the same binary code, IaC enables generating the same environment every time it is applied. IaC is a key DevOps practice and is generally used in conjunction with continuous integration (CI) and continuous delivery (CD). In CI, all code changes are merged into a mainline branch and validated multiple times a day as developers check in their changes to the source code. In CD on the other hand, code changes are automatically packaged for a new release-to-production on a regular basis. This typically enables teams to deliver software changes much more quickly and often. Developing and managing the ACES platform using (IaC) is vital for the robust deployment and continued sustainment of this foundational computing capability. IaC and DevOps practices will help us solve many of the common challenges often encountered in developing and maintaining compute infrastructure. First, it will make the provisioning, deployment, and maintenance of the compute infrastructure across multiple environments much more efficient. Second, these processes help make the overall system much more stable by continuously testing new changes as they are introduced to the system. Third, it allows us to be much more confident of the security controls in place since they can be tested as part of the CI process and all new changes can be audited and tracked. Finally, IaC enables the ACES Platform to be adaptable to the emerging technologies due to its ability to spin up different test beds to evaluate and incorporate these technologies. This document addresses common infrastructure-management challenges, describes what happens if they are not addressed, and highlights the value of utilizing IaC to tackle them. Finally, we will provide a high-level overview of the IaC and DevOps practices being utilized by the ACES Platform team.

97 MATHEMATICS AND COMPUTING↗

High yield production of 3-hydroxypropionic acid using Issatchenkia orientalis

Biomanufacturing provides a more sustainable alternative to fossil-based chemical manufacturing. 3-Hydroxypropionic acid (3HP) is a top Department of Energy value-added chemical and precursor to bioplastics, yet cost-effective microbial production remains elusive. Here, we establish the acid-tolerant yeast Issatchenkia orientalis as a robust host for low-pH 3HP biosynthesis. Genome-scale modeling identifies the β-alanine pathway as optimal, offering the highest theoretical yield and lowest oxygen requirement. Thermodynamic analysis confirms its favorability under acidic conditions. Using sequence similarity network analysis, we discover highly active aspartate 1-decarboxylase (PAND), β-alanine-pyruvate aminotransferase (BAPAT), and 3HP dehydrogenase (YDFG), which significantly improve the pathway efficiency. Next, to further elevate the production, pathway optimization through multi-copy PAND integration, byproduct elimination (knockouts of pyruvate decarboxylase and glycerol-3-phosphate dehydrogenase), and reinforcement of aspartate flux by overexpression of pyruvate carboxylase and aspartate amino transferase improves the titer to 29 g/L in shake flasks. Fed-batch fermentation at pH 4 with low-cost corn steep liquor medium further increases the production to 92 g/L with 0.7 g/g yield and 0.55 g/L/h productivity. Techno-economic analysis indicates that such performance could potentially enable a financially viable process for sustainable acrylic acid production. This work establishes I. orientalis as a next-generation platform for cost-effective 3HP production and paves the way toward industrial commercialization.

Biotechnology↗

Understanding HPC Benchmark Performance on Intel Broadwell and Cascade Lake Processors

Hardware platforms in high performance computing are constantly getting more complex to handle even when considering multicore CPUs alone. Numerous features and configuration options in the hardware and the software environment that are relevant for performance are not even known to most application users or developers. Microbenchmarks, i.e., simple codes that fathom a particular aspect of the hardware, can help to shed light on such issues, but only if they are well understood and if the results can be reconciled with known facts or performance models. The insight gained from microbenchmarks may then be applied to real applications for performance analysis or optimization. In this paper we investigate two modern Intel x86 server CPU architectures in depth: Broadwell EP and Cascade Lake SP. We highlight relevant hardware configuration settings that can have a decisive impact on code performance and show how to properly measure on-chip and off-chip data transfer bandwidths. The new victim L3 cache of Cascade Lake and its advanced replacement policy receive due attention. Finally we use DGEMM, sparse matrix-vector multiplication, and the HPCG benchmark to make a connection to relevant application scenarios.

97 MATHEMATICS AND COMPUTING↗

Extend an innovative HPC-Compatible Multiple Temporal-spatial Resolution Concurrent Finite Element Modeling Approach to Guide Laser Powder Bed Fusion Additive

Laser power bed fusing (PBF) additive manufacturing is a key enabling technology to manufacture highly complex and integrated automotive structures. However, the geometric complexity of PBF-AM technique also leads to highly non-uniform heating and cooling rate in the manufactured part, which may cause flaw formation and produce excessive and nonuniform residual stresses, which increase quality uncertainties and manufacture issues, leading to increases in cost and energy consumption in the form of rejected parts. In this research project, we developed an innovative Multi-Spatial-Temporal-Resolution Finite Element (MUST-FE) method and completed the corresponding high performance computation (HPC) platform-based in-house code, which enables high accuracy prediction of temperature and residual stress fields for component-scale PBF-AM manufacture in efficient computation time. The MUST-FE model is calibrated and validated with a “2D pad” AlSi10Mg experiments by matching the melt pool shape and dimension, and with a “XY-cross” AlSi10Mg experiment by matching the thermal distortion and residual stress. The innovative multi-resolution and concurrent modeling approach adopted in this code ensures accuracy and computational efficiency, which will enable energy-efficient and high-yield, low-cost manufacturing of optimized, qualifiable automotive structures and contribute towards reaching technical targets outlined in AMO’s Program Plan to develop additive manufacturing systems that deliver consistently reliable parts with predictable properties.

36 MATERIALS SCIENCE↗

Designing for Zero Energy and Zero Carbon on a Multi-Building Scale Using URBANopt: Preprint

Groundbreaking efforts are necessary to mitigate contributors increasing impacts of climate change. In parallel to inventing pioneering clean energy technologies it is even more fundamental to rethink designing energy systems within a singular facility and collectively to function as a district. Facilities should not be continuously passive by just consuming; there is a need to shift to perform more dynamically. Designing for zero energy and zero carbon on a multi-building scale can uncover opportunities for building energy efficiency, decarbonization, demand flexibility, and resiliency that are not accessible at an individual building scale. This approach can be challenging without innovative tools to evaluate the multitude of possibilities. As an investigated result, we highlight the use of a campus-scale energy modeling platform - URBANopt™ - for the expansion of the National Renewable Energy Laboratory's (NREL's) South Table Mountain campus in Golden, Colorado. Programmatic growth included the design of three new all-electric, zero-energy, and zero-carbon, mixed used buildings (a combination of research laboratories and office space). This investigation is critical to NREL reaching net-zero emissions for its operational footprint, which will occur in phases over the next decade. Leveraging URBANopt's capabilities, we evaluate 1) high-performance building energy efficiency and decarbonization measures, 2) 4th generation district heating and cooling (4th GDHC) systems, 3) optimized onsite generation and energy storage assets that meet zero-energy and zero-carbon targets at minimum life-cycle costs, and 4) cost-optimal distributed energy technology mixes, dispatch strategies, and associated capacities that increase resiliency to grid outages. This work demonstrates the use and capabilities of URBANopt through a real-world case study on a multi-building scale.

community energy model↗

Design of Hopfield Networks Based on Superconducting Coupled Oscillators

The global energy shortage has driven the development of many energy-efficient computational platforms beyond Moore's law, among which brain-inspired neuromorphic computing is one of the promising solutions. Associative memory and pattern recognition are important computations solved by brain-inspired Hopfield networks. Classical Hopfield networks store memories via fixed point attractors of their dynamics. In oscillatory Hopfield networks, these attractors are replaced by periodic orbits. Here, we design an oscillatory Hopfield network based on coupled superconducting oscillators. We first employ a mathematical phase reduction approach to map networks of coupled superconducting rapid single flux quantum (RSFQ) ring oscillators to coupled Kuramoto phase-oscillator networks. We use this theory to numerically optimize the hardware's mutual inductances in order to directly match the phase-reduced superconducting oscillators to a model of phase-oscillator-based Hopfield networks. The resulting network can store multiple oscillatory phase-locked memory patterns and recover the patterns based on the initial phase conditions. As different pattern recognition tasks, or learning, require tunable connectivity strengths between the oscillatory nodes, we further employ a coupler circuit that enables tuning the coupling strength between two oscillators by applying an external flux. We demonstrate the functionality of our design through numerical simulations of a small example network with oscillators operating at 86 GHz and recognizing patterns within 10 ns. Our approach enables the learning and retrieval of dynamical memory patterns with a wide range of applications where rhythmic dynamic output is beneficial.

Cheng, Ran↗

Open source Modeling and optimization tools for Planning

Open source modeling and optimization tools for planning The existing tools and software used for planning and analysis in California are either expensive, difficult to use, or not generally accessible to a large number of participants. These limitations restrict the availability of participants for larger scale energy and grid studies in the state. The proposed initiative would build upon federal and state investments in open source software, and create and improve open source tools for use in the state planning and analysis activities. Computational analysis and simulation frameworks in development at national labs and universities can be brought forward to complement existing tools. An open source platform would provide a path for novel techniques and strategies to be brought into the larger community and reviewed by a broad set of stakeholders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

PREEMPT: Scalable Epidemic Interventions Using Submodular Optimization on Multi-GPU Systems

Preventing and slowing the spread of epidemics is achieved through techniques such as vaccination and social distancing. Given practical limitations on the number of vaccines and cost of administration, optimization becomes a necessity. Previous approaches using mathematical programming methods have shown to be effective but are limited by computational costs. In this work, we make several contributions: First, we present a new approach for intervention via maximizing the influence of vaccinated nodes on the network. We call this method \preempt. Next, we prove submodular properties associated with the objective function of our method so that it aids in construction of an efficient greedy approximation strategy. Consequently, we present a new parallel algorithm based on greedy hill climbing for \preempt, and present an efficient parallel implementation for distributed CPU-GPU heterogeneous platforms. Our results demonstrate that \preempt{} is able to achieve a significant reduction (up to 6.75$\times$) in the percentage of people infected on a city-scale network. We also show strong scaling results of \preempt{} on 128 nodes of the Summit supercomputer. Our parallel implementation is able to significantly reduce time to solution, from hours to minutes on large networks. This work represents a first-of-its-kind effort in parallelizing greedy hill climbing and applying it toward devising effective interventions for epidemics.

Minutoli, Marco↗

Ion Fast Ignition-Establishing a Scientific Basis for Inertial Fusion Energy --- Final Report

The Fast Ignition (FI) Concept for Inertial Confinement Fusion (ICF) has the potential to provide a significant advance in the technical attractiveness of Inertial Fusion Energy reactors. FI differs from conventional ?central hot spot? (CHS) target ignition by decoupling compression from heating: using a laser (or heavy ion beam or Z pinch) drive pulse (10?s of nanoseconds) to create a dense fuel and a second, much shorter (~10 picoseconds) high intensity pulse to ignite a small volume within the dense fuel. The compressed fuel is opaque to laser light. The ignition laser energy must be converted to a jet of energetic charged particles to deposit energy in the dense fuel. The original concept called for a spray of laser-generated hot electrons to deliver the energy; lack of ability to focus the electrons put great weight on minimizing the electron path. An alternative concept, proton-ignited FI, used those electrons as intermediaries to create a jet of protons that could be focused to the ignition spot from a more convenient distance. Our program focused on the generation and directing of the proton jet, and its transport toward the fuel, none of which were well understood at the onset of our program. We have developed new experimental platforms, diagnostic packages, computer modeling analyses, and taken advantage of the increasing energy available at laser facilities to create a self-consistent understanding of the fundamental physics underlying these issues. Our strategy was to examine the new physics emerging as we added the complexity necessary to use proton beams in an inertial fusion energy (IFE) application. From the starting point of a proton beam accelerated from a flat, isolated foil, we 1) curved it to focus the beam, 2) attached the foil to a superstructure, 3) added a side sheath to protect it from the surrounding plasma, and finally 4) studied the proton beam behavior as it passed through a protective end cap into plasma. We built up, as we proceeded, a self-consistent picture of the quasi-neutral plasma jet that is the proton beam that, for the first time, included the role of the hot electrons in shaping the jet. Controlling them?through design of the accelerating surface and its connection to the surrounding superstructure?is critical; their uniform spread across the proton accelerating area is vital, but their presence in the jet opposes focus; their electron flow away from the acceleration area reduces conversion efficiency but can also increase focusing ability. The understanding emerging from our work and the improved simulation tools we have developed allow designing structures that optimize proton beams for focused heating. Our findings include: ? The achievable focus of proton beams is limited by the thermal pressure gradient in the laser-generated hot electrons that drive the process. This bending can be suppressed using a controlled flow of hot electrons along the surrounding cone wall, which induces a local transverse focusing sheath electric field. The resultant (vacuum-focused) spot can meet IFE requirements. ? Confinement of laser-generated electrons to the proton accelerating area can be achieved by supporting targets on thin struts. That increases laser-to-proton conversion energy by ~50%. As noted above, confinement should not be total; necessary hot-electron leakage into the surrounding superstructure for proton focusing can be controlled by with the strut width/number. ? Proton jets are further modified as they enter the fuel through the superstructure?s end cap. They can generate currents during that transit that further focus the proton beams. We developed a new ion stopping module for LSP code that properly accounted for changes in stopping power with ionization (e.g. temperature), and will be using it in future studies. The improved understanding, new experimental platforms, and the self-consistent modeling capability allow researchers a new ability to investigate the interaction of large ion currents with warm dense matter. That is of direct importance to the creation and investigation of all aspects of warm dense matter as well as to proton-ignited FI.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗