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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Control over Conformational Landscapes of Polypeptoids by Monomer Sequence Patterning

The ability to program chain conformation and structure through control over the monomer sequence of synthetic polymers has broad implications for next-generation material design. While related problems of protein-folding and de novo design have generated accurate predictions of 3D folded chain structures, generalization to synthetic polymers remains intractable due to the requirement of large structural databases and the intrinsically disordered nature of polymer building blocks. In this work, polypeptoids, a class of peptidomimetic synthetic polymers, are utilized to build a general workflow for the study of relationships between monomer sequence and dynamic 3D chain structure in solution. Furthermore, this work demonstrates how control over the monomer sequence can alter the conformational landscape of synthetic polymers to deviate dramatically from classical chain statistics. Specifically, the distribution of end-to-end distances, as measured by double electron-electron resonance spectroscopy in dilute solvent, is systematically skewed towards shorter distances with an increasing number of hydrophobes and further refined by hydrophobe arrangement in amphiphilic polypeptoid chains.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Investigating biological nitrogen fixation via single-cell transcriptomics

The extensive use of nitrogen fertilizers has detrimental environmental consequences, and it is essential for society to explore sustainable alternatives. One promising avenue is engineering root nodule symbiosis, a naturally occurring process in certain plant species within the nitrogen-fixing clade, into non-leguminous crops. Advancements in single-cell transcriptomics provide unprecedented opportunities to dissect the molecular mechanisms underlying root nodule symbiosis at the cellular level. This review summarizes key findings from single-cell studies in Medicago truncatula, Lotus japonicus, and Glycine max. We highlight how these studies address fundamental questions about the development of root nodule symbiosis, including the following findings: (i) single-cell transcriptomics has revealed a conserved transcriptional program in root hair and cortical cells during rhizobial infection, suggesting a common infection pathway across legume species; (ii) characterization of determinate and indeterminate nodules using single-cell technologies supports the compartmentalization of nitrogen fixation, assimilation, and transport into distinct cell populations; (iii) single-cell transcriptomics data have enabled the identification of novel root nodule symbiosis genes and provided new approaches for prioritizing candidate genes for functional characterization; and (iv) trajectory inference and RNA velocity analyses of single-cell transcriptomics data have allowed the reconstruction of cellular lineages and dynamic transcriptional states during root nodule symbiosis.

Lotus japonicus↗
DOE OSTI2019

Designing Metabolic Division of Labor in Microbial Communities

ABSTRACT Microbes face a trade-off between being metabolically independent and relying on neighboring organisms for the supply of some essential metabolites. This balance of conflicting strategies affects microbial community structure and dynamics, with important implications for microbiome research and synthetic ecology. A “gedanken” (thought) experiment to investigate this trade-off would involve monitoring the rise of mutual dependence as the number of metabolic reactions allowed in an organism is increasingly constrained. The expectation is that below a certain number of reactions, no individual organism would be able to grow in isolation and cross-feeding partnerships and division of labor would emerge. We implemented this idealized experiment using in silico genome-scale models. In particular, we used mixed-integer linear programming to identify trade-off solutions in communities of Escherichia coli strains. The strategies that we found revealed a large space of opportunities in nuanced and nonintuitive metabolic division of labor, including, for example, splitting the tricarboxylic acid (TCA) cycle into two separate halves. The systematic computation of possible solutions in division of labor for 1-, 2-, and 3-strain consortia resulted in a rich and complex landscape. This landscape displayed a nonlinear boundary, indicating that the loss of an intracellular reaction was not necessarily compensated for by a single imported metabolite. Different regions in this landscape were associated with specific solutions and patterns of exchanged metabolites. Our approach also predicts the existence of regions in this landscape where independent bacteria are viable but are outcompeted by cross-feeding pairs, providing a possible incentive for the rise of division of labor. IMPORTANCE Understanding how microbes assemble into communities is a fundamental open issue in biology, relevant to human health, metabolic engineering, and environmental sustainability. A possible mechanism for interactions of microbes is through cross-feeding, i.e., the exchange of small molecules. These metabolic exchanges may allow different microbes to specialize in distinct tasks and evolve division of labor. To systematically explore the space of possible strategies for division of labor, we applied advanced optimization algorithms to computational models of cellular metabolism. Specifically, we searched for communities able to survive under constraints (such as a limited number of reactions) that would not be sustainable by individual species. We found that predicted consortia partition metabolic pathways in ways that would be difficult to identify manually, possibly providing a competitive advantage over individual organisms. In addition to helping understand diversity in natural microbial communities, our approach could assist in the design of synthetic consortia.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Computer Based Procedures for Field Workers - FY16 Research Activities

The Computer-Based Procedure (CBP) research effort is a part of the Light-Water Reactor Sustainability (LWRS) Program, which provides the technical foundations for licensing and managing the long-term, safe, and economical operation of current nuclear power plants. One of the primary missions of the LWRS program is to help the U.S. nuclear industry adopt new technologies and engineering solutions that facilitate the continued safe operation of the plants and extension of the current operating licenses. One area that could yield tremendous savings in increased efficiency and safety is in improving procedure use. A CBP provides the opportunity to incorporate context-driven job aids, such as drawings, photos, and just-in-time training. The presentation of information in CBPs can be much more flexible and tailored to the task, actual plant condition, and operation mode. The dynamic presentation of the procedure will guide the user down the path of relevant steps, thus minimizing time spent by the field worker to evaluate plant conditions and decisions related to the applicability of each step. This dynamic presentation of the procedure also minimizes the risk of conducting steps out of order and/or incorrectly assessed applicability of steps. This report provides a summary of the main research activities conducted in the Computer-Based Procedures for Field Workers effort since 2012. The main focus of the report is on the research activities conducted in fiscal year 2016. The activities discussed are the Nuclear Electronic Work Packages – Enterprise Requirements initiative, the development of a design guidance for CBPs (which compiles all insights gained through the years of CBP research), the facilitation of vendor studies at the Idaho National Laboratory (INL) Advanced Test Reactor (ATR), a pilot study for how to enhance the plant design modification work process, the collection of feedback from a field evaluation study at Plant Vogtle, and path forward to commercialize INL’s CBP system.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

A dynamic control approach for energy-efficient production scheduling on a single machine under time-varying electricity pricing

This paper proposes a dynamic control algorithm to enable an energy-aware single machine scheduling under the time-varying electricity pricing policy, in which price rates remain fixed day-to-day over the season. The key issue is to assign a set of jobs to available time periods where different electricity prices are assigned, while considering requested due dates of jobs so as to minimize total penalty costs for earliness and tardiness of jobs and total energy consumption costs, simultaneously. As the first contribution of this study, we develop a new mixed integer nonlinear programming (MINLP) model that aims at determining job arrival times and resulting earliness and tardiness of jobs and energy consumption costs for machine idle and normal processing. Second, an efficient heuristic approach based on continuous-time variable control models and algorithm is developed. The proposed heuristic adaptively changes job arrival times and due dates, which finally determine production sequence over the time periods of different electricity prices, machine turn-off, and machine idle with minimum energy consumption costs and just-in-time (JIT) penalty. Energy and JIT performance of the proposed approach is examined using real energy and machining parameters of a HAAS machine and compared to those of the metaheuristic approach. For relatively large size data groups, the proposed approach incurs about higher energy consumption costs on average, which are offset by up to lower JIT costs, resulting in lower total costs on average compared to the metaheuristic approach. Further, the proposed time-scaled heuristic algorithm yields extremely short computational time, which enables production managers to flexibly select proper production strategies and to implement them for different production environments.

42 ENGINEERING↗
DOE OSTI2021

Maize tissue culture, transformation, and genome editing

The importance of maize (Zea mays L.) to global agriculture, world economy, and food security is widely known and increasing. Current maize breeding programs are deeply integrated with recent and rapid technological advances in genome sequencing, computational biology, and new genotyping and phenotyping technologies. Transformation and genome editing capabilities are a central hub to an array of advanced molecular and breeding approaches to crop improvement. Tissue culture and somatic embryogenesis play essential and central roles in maize transformation biology. Synergistic applications of maize transformation, advanced genomics, and genome editing provide a potent interdependent triad for functional genomics research and advanced molecular breeding. Implementation of advanced capabilities to transform maize and conduct genome editing will profoundly influence the dynamics of global agriculture ushering in a new era of varietal development and molecular breeding. With over 60.9 Mha planted in 2019 alone, biotech maize accounts for 31% of the world’s maize production. Up to 10% higher yields are achieved using new varieties generated using genetic modification technologies compared to similar conventional varieties. By extension, the impact new varietal releases developed through genome editing will likely be more significant. Further, advances in transformation and genome editing technologies will facilitate an even wider applicability for the development of new varieties with increasingly complex traits. The introduction of biochemical pathways and the use of synthetic biology have become increasingly more attainable. The future is of genotype independent maize transformation and genome editing, as the working platform will impact world agriculture, global food security, and plant science well into the future.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Evaluation of the Nanometrics Centaur Digitizer

Sandia National Laboratories has tested and evaluated a new digitizer, the Centaur, manufactured by Nanometrics, Inc. This digitizer is used to record sensor output for seismic and infrasound monitoring applications. The purpose of the digitizer evaluation was to measure the performance characteristics in such areas as power, sensitivity, self-noise, dynamic range, system noise, modified noise power ration, relative transfer function, analog bandwidth, harmonic distortion, common mode, cross talk, timing tag accuracy and timing drift. The Centaur provides six channels of 24 bit digitization, three of which may be transmitted utilizing CD1.1 protocol.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

A dataset for understanding self-reported patterns influencing residential energy decisions

Household occupant behavior and decision-making dynamics substantially impact technology uptake and residential building energy performance. Although significant research underscores the importance of social science in energy studies, few public data with representative samples on household energy decision-making patterns are available. The dataset (UPGRADE-E: Understanding Patterns Guiding Residential Adoption and Decisions about Energy Efficiency) presents 9,919 responses from U.S. residents of single-family and small multifamily homes. Derived from a national-scale internet survey, the dataset contains 391 variables: demographics, building characteristics, home modifications, willingness to adopt new technologies, motivations for making changes, barriers, program participation, trusted information sources, and energy scenarios. Responses were validated via internal consistency checks and comparison with other U.S. national scale datasets. UPGRADE-E advances knowledge of household energy related decision-making, tying demographics, home modifications, and self-reported cognitive drivers together at a scale and breadth that has not been previously achieved. Policymakers and researchers at local, regional, and national levels may leverage this dataset to understand drivers influencing the adoption of key technologies in U.S. homes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Architecture Independent Integrated Early Performance and Energy Estimation

The end of Dennard’s scaling, coupled to the necessity to keep increasing computational performance in constrained power envelopes, is leading developers towards the need to opti- mize applications not only for performance, but also for energy consumption. In such a scenario, solutions that enable estimating performance and energy consumption of a program as early as possible, even during development and without the necessity to access the final target hardware, can become fundamental tools to reduce the design space, the optimization effort, and provide potential opportunities to automate the optimization process itself. In this position paper, we discuss the design of a performance and energy estimation framework based on a retargetable com- piler. Our proposed approach targets the Intermediate Repre- sentation (IR) of the LLVM compiler. The IR based approach enables, after a model is built, estimation from a host different from the target architecture, even considering dynamic infor- mation. We present the rationale behind such a framework, identify opportunities and components readily available (such as the provided static analysis, quick ways to add instrumentation for dynamic profiling, and the multiple backends), and aspects that still need further research efforts (such as more effective non-linear, or machine learning based models). We also discuss a hand-developed case study, based on a simple sparse matrix vector multiplication with a linear model, to motivate the needs for such a framework.

Estimation, Compilers, Performance Analysis↗
DOE OSTI2023

FLASH: FPGA-Accelerated Smart Switches with GCN Case Study

Some communication switches, e.g., the Mellanox SHArP and those in the IBM BlueGene clusters, are augmented to process packets at the application level with fixed-function collectives. This approach, however, lacks flexibility, which limits their applicability in diverse and dynamic workloads. Recently, a new type of programmable packet processor, which uses high-level languages, e.g., P4, has emerged as possible candidates. P4-based switches, however, fall short in certain applications, including machine learning, where capabilities not currently supported by P4 are needed. These include more complex calculation, such as sparse computation and fused multiply-accumulate, data-intensive floating point operations, data reuse, and significant memory. The problem addressed here is that such a switch augmentation needs to support: a large amount of state, significant flexible compute capability, and ease of programming, all while maintaining full functionality, including ensuring high throughput, and demonstrating utility. In this work, we propose a programmable look-aside-type accelerator that can be embedded into, or attached to, existing communication switch pipelines and that is capable of processing packets at line-rate. The proposed in-switch accelerator is based on mixing an ISA (subset of RISC-V instructions) with dataflow graphs (found in CGRAs). To augment performance, vector instructions are also supported. To facilitate usability, we have developed a complete toolchain to compile user-provided C/C++ codes to appropriate back-end instructions for configuring the accelerator. While this approach is flexible enough to support various workloads, in this paper, we consider Graph Convolutional Networks (GCNs) as a case study. Experimental results show that this approach considerably improves the performance of distributed GCN applications.

Haghi, Pouya↗
DOE OSTI2018

The 2017 Nonlinear Mechanics and Dynamics Research Institute.

The 2017 Nonlinear Mechanics and Dynamics (NOMAD) Research Institute was successfully held from June 19 to July 28, 2017. NOMAD seeks to bring together participants with diverse technical backgrounds to work in small teams to utilize an interactive approach to cultivate new ideas and approaches in engineering . NOMAD provides an opportunity for researchers - especially early career researchers - to develop lasting collaborations that go beyond what can be established from the limited interactions at their institutions or at annual conferences. A total of 17 students from around the world came to Albuquerque, New Mexico to participate in the six - week long program held at the University of New Mexico campus. The students collaborated on one of six research projects that were developed by various mentors from Sandia National Laboratories, academia, and other government laboratories. In addition to the research activities, the students attended weekly technical seminars, toured the National Museum of Nuclear Science & History, and socialized at various off - hour events including an Albuquerque Isotopes baseball game. At the end of the summer, the students gave a final technical presentation o n their research findings that was broadcast via Skype. Many of the research discoveries made at NOMAD are published as proceedings at technical conference s and have direct alignment with the critical mission work performed at Sandia.

42 ENGINEERING↗
DOE OSTI2019

Containment Chamber Systems Engineering Project

Lawrence Livermore National Laboratory (LLNL) is a leading research laboratory in material properties. The most notable facility at LLNL capable of determining equation of state data for hazardous materials is the National Ignition Facility (NIF). NIF is the most energetic laser in the world and is a very versatile system that allows for a variety of laser configurations and diagnostics. The flexibility that NIF offers makes it an attractive tool for high budget programs researching specific areas of interest. Some programs require many tests to be performed, and although NIF could be an option for performing these tests, the cost and time to perform the tests would not be feasible. Also, many of these tests would underutilize the full capacity of NIF’s lasers, and NIF does not have a dedicated light source suitable for the diagnostic requirement. The needs of these tests do not align with NIF’s capabilities. The physicists are the main stakeholders for the tests, and they require a third-generation light source to meet the desired diagnostic performance. The Dynamic Compression Sector (DCS) within the Advanced Photon Source (APS) at Argonne National Laboratory (ANL) is the facility that will meet necessary laser performance and the X-ray diagnostic performance in order to obtain the desired data. DCS does not have the capability to test hazardous material, and therefore DCS requires a method and hardware for ensuring that no hazardous material is exposed before, during, or after the test. After taking a system engineering evaluation of the need for a solution to perform laser shock experiments on hazardous materials with certain laser and X-ray characteristics, a solution is proposed that meets the requirements of each involved stakeholder. The proposed solution is to contain the targets within sealed vacuum chamber that will meet the protection requirements of each facility. The chamber would be assembled and pumped down at LLNL in facilities that can handle hazardous material. Then, the chamber would be shipped under vacuum to DCS, where the chamber will be inserted into the beam paths. DCS’s laser will enter the sealed chamber and impart a shock into the target of hazardous material while the X-ray will simultaneously image the material. Once each target has been fired, the chamber will be removed from the beam path and shipped to the proper disposal facility.

42 ENGINEERING↗
DOE OSTI2026

Lessons Learned from Ecosystem-Scale Experimental Field Studies (Workshop Report)

Efforts to understand and predict ecosystem responses to environmental change require long-term, large-scale, spatially representative experiments and observations that capture natural variability, test predictive models, and generate transferable knowledge. Such studies are indispensable for unraveling the complexities of terrestrial ecosystems and their responses to disturbances and evolving environmental conditions, while generating the data necessary for developing mechanistic models and predictive tools that inform decision-making processes. Having a rich history of designing and executing large-scale ecosystem experiments, the U.S. Department of Energy’s Environmental System Science program convened a workshop in January 2025 that brought together leaders in the field to distill critical lessons from decades of experience in large-scale experiments. The workshop aimed to (1) provide an ecosystem experiment primer for best practices, thus ensuring a high scientific return on investment for funding agencies, and (2) offer a robust framework for the design and management of future research initiatives. This report synthesizes insights and experiences from workshop participants and is structured to capture the entire research life cycle, from goal setting and design to operations, adaptive management, team dynamics, collaborations, and the often overlooked aspect of decommissioning. By synthesizing decision-making and lessons learned across diverse research approaches, the report aims to provide a template of essential factors to consider when designing successful long-term, large-scale ecosystem experiments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Probing early-time longitudinal dynamics with the Λ hyperon's spin polarization in relativistic heavy-ion collisions

Here, we systematically study the hyperon global polarization's sensitivity to the collision systems' initial longitudinal flow velocity in hydrodynamic simulations. By explicitly imposing local energy-momentum conservation when mapping the initial collision geometry to macroscopic hydrodynamic fields, we study the evolution of systems' orbital angular momentum (OAM) and fluid vorticity. We find that a simultaneous description of the $\Lambda$ hyperons' global polarization and the slope of pion's directed flow can strongly constrain the size of longitudinal flow at the beginning of hydrodynamic evolution. We extract the size of the initial longitudinal flow and the fraction of orbital angular momentum in the produced QGP fluid as a function of collision energy with the STAR measurements in the RHIC Beam Energy Scan program. We find that there is about 100-200 $\hbar$ OAM that remains in the mid-rapidity fluid at the beginning of hydrodynamic evolution. We further exam the effects of different hydrodynamic gradients on the spin polarization of $\Lambda$ and $\bar{\Lambda}$. The gradients of $\mu_B/T$ can change the ordering between $\Lambda$'s and $\bar{\Lambda}$'s polarization.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

A review on regional convection‐permitting climate modeling: Demonstrations, prospects, and challenges

Abstract Regional climate modeling using convection‐permitting models (CPMs; horizontal grid spacing <4 km) emerges as a promising framework to provide more reliable climate information on regional to local scales compared to traditionally used large‐scale models (LSMs; horizontal grid spacing >10 km). CPMs no longer rely on convection parameterization schemes, which had been identified as a major source of errors and uncertainties in LSMs. Moreover, CPMs allow for a more accurate representation of surface and orography fields. The drawback of CPMs is the high demand on computational resources. For this reason, first CPM climate simulations only appeared a decade ago. In this study, we aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic. The most important components in CPMs such as physical parameterizations and dynamical formulations are discussed critically. An overview of weaknesses and an outlook on required future developments is provided. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Improvements are evident mostly for climate statistics related to deep convection, mountainous regions, or extreme events. The climate change signals of CPM simulations suggest an increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains. In conclusion, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Putting the soil health principles to the test in Iowa

One of the most popular soil conservation campaigns is based on the USDA Natural Resource Conservation Service's Soil Health Principles (NRCS-SHPs). The NRCS-SHP program identifies four principles—maximize presence of living roots, minimize disturbance, maximize soil cover, and maximize biodiversity—with the underlying assumption that the more principles one follows, the greater improvements in soil health. Despite the popularity of the NRCS-SHPs, this underlying assumption has not been rigorously tested. To do so, we used nine long-term experiments all located in central Iowa, but with varying degree of NRCS-SHP adoption, to determine if greater adoption increases three slow-changing (maximum water holding capacity, bulk density [BD], and soil organic carbon) and three dynamic (microbial biomass carbon [MBC], potentially mineralizable carbon [PMC], and permanganate oxidizable carbon [POXC]) soil health indicators. We regressed these indicators with a soil health principle score that can scale soil management based on adoption of the NRCS-SHPs. Of the slow-changing soil properties, increased adoption of NRCS-SHPs only decreased soil BD (R2 = 0.22, p = 0.024). On the other hand, increased adoption of NRCS-SHPs strongly predicted increases in both MBC and PMC and across two sampling dates (R2 > 0.23, p < 0.015); POXC, however, did not increase with greater adoption. The consistent increases in MBC and PMC with greater adoption of NRCS-SHPs supports their usefulness as sensitive indicators of positive soil health change. Our study provides scientific evidence to support the NRCS-SHPs concept, improving its usefulness as an extension campaign, and stands as a step toward evidence-based soil conservation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Machine-learned closure of URANS for stably stratified turbulence: connecting physical timescales & data hyperparameters of deep time-series models

Stably stratified turbulence (SST), a model that is representative of the turbulence found in the oceans and atmosphere, is strongly affected by fine balances between forces and becomes more anisotropic in time for decaying scenarios. Moreover, there is a limited understanding of the physical phenomena described by some of the terms in the Unsteady Reynolds-Averaged Navier–Stokes (URANS) equations—used to numerically simulate approximate solutions for such turbulent flows. Rather than attempting to model each term in URANS separately, it is attractive to explore the capability of machine learning (ML) to model groups of terms, i.e. to directly model the force balances. We develop deep time-series ML for closure modeling of the URANS equations applied to SST. We consider decaying SST which are homogeneous and stably stratified by a uniform density gradient, enabling dimensionality reduction. We consider two time-series ML models: long short-term memory and neural ordinary differential equation. Both models perform accurately and are numerically stable in a posteriori (online) tests. Furthermore, we explore the data requirements of the time-series ML models by extracting physically relevant timescales of the complex system. We find that the ratio of the timescales of the minimum information required by the ML models to accurately capture the dynamics of the SST corresponds to the Reynolds number of the flow. The current framework provides the backbone to explore the capability of such models to capture the dynamics of high-dimensional complex dynamical system like SST flows.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Technical Note: Experimental results from a prototype high-field inline MRI-linac

Purpose: The pursuit of real-time image guided radiotherapy using optimal tissue contrast has seen the development of several hybrid magnetic resonance imaging (MRI)-treatment systems, high field and low field, and inline and perpendicular configurations. As part of a new MRI-linac program, an MRI scanner was integrated with a linear accelerator to enable investigations of a coupled inline MRI-linac system. This work describes results from a prototype experimental system to demonstrate the feasibility of a high field inline MR-linac. Methods: The magnet is a 1.5 T MRI system (Sonata, Siemens Healthcare) was located in a purpose built radiofrequency (RF) cage enabling shielding from and close proximity to a linear accelerator with inline (and future perpendicular) orientation. A portable linear accelerator (Linatron, Varian) was installed together with a multileaf collimator (Millennium, Varian) to provide dynamic field collimation and the whole assembly built onto a stainless-steel rail system. A series of MRI-linac experiments was performed to investigate (1) image quality with beam on measured using a macropodine (kangaroo) ex vivo phantom; (2) the noise as a function of beam state measured using a 6-channel surface coil array; and (3) electron contamination effects measured using Gafchromic film and an electronic portal imaging device (EPID). Results: (1) Image quality was unaffected by the radiation beam with the macropodine phantom image with the beam on being almost identical to the image with the beam off. (2) Noise measured with a surface RF coil produced a 25% elevation of background intensity when the radiation beam was on. (3) Film and EPID measurements demonstrated electron focusing occurring along the centerline of the magnet axis. Conclusions: A proof-of-concept high-field MRI-linac has been built and experimentally characterized. This system has allowed us to establish the efficacy of a high field inline MRI-linac and study a number of the technical challenges and solutions.

60 APPLIED LIFE SCIENCES↗