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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Computer Science Research Needs for Parallel Discrete Event Simulation (PDES)

Historically, scientific computing efforts have demonstrated the clear need for, and effective use of, supercomputing with traditional time-stepped simulations. Nevertheless, there are several areas in the mission spaces of the U.S. Department of Energy and other agencies waiting to tap advanced computing research using a different, discrete event style of modeling, simulation, and analysis. These span a wide spectrum of applications including energy grid resilience, urban planning and policy, transportation science, building technologies, emergency response and planning, environmental impact analysis, computational epidemiology, Internet communications, cyber security, and cyber-physical systems, to name only a few. Even within traditional scientific applications, the role of discrete event modes of execution is increasing in the form of new event-based mathematical solvers such as quantized state integration methods and discrete-continuous hybrid system solvers. Co-design of advanced supercomputing hardware systems is another area that exploits discrete event simulation at its core for effective analyses. Complex systems, entity behaviors and interconnections play a significant role in all these applications, which are mapped to large-scale models with discrete event formulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Carbon dioxide in an ionic liquid: Structural and rotational dynamics

Ionic liquids (ILs), which have widely tunable structural motifs and intermolecular interactions with solutes, have been proposed as possible carbon capture media. In order to inform the choice of an optimal ionic liquid system, it can be useful to understand the details of dynamics and interactions on fundamental time scales (femtoseconds to picoseconds) of dissolved gases, particularly carbon dioxide (CO 2 ), within the complex solvation structures present in these uniquely organized materials. The rotational and local structural fluctuation dynamics of CO 2 in the room temperature ionic liquid 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (EmimNTf2) were investigated by using ultrafast infrared spectroscopy to interrogate the CO 2 asymmetric stretch. Polarization-selective pump probe measurements yielded the orientational correlation function of the CO 2 vibrational transition dipole. It was found that reorientation of the carbon dioxide occurs on 3 time scales: 0.91 ± 0.03, 8.3 ± 0.1, 54 ± 1 ps. The initial two are attributed to restricted wobbling motions originating from a gating of CO 2 motions by the IL cations and anions. The final (slowest) decay corresponds to complete orientational randomization. Two-dimensional infrared vibrational echo (2D IR) spectroscopy provided information on structural rearrangements, which cause spectral diffusion, through the time dependence of the 2D line shape. Analysis of the time-dependent 2D IR spectra yields the frequency-frequency correlation function (FFCF). Polarization-selective 2D IR experiments conducted on the CO 2 asymmetric stretch in the parallel- and perpendicular-pumped geometries yield significantly different FFCFs due to a phenomenon known as reorientation-induced spectral diffusion (RISD), revealing strong vector interactions with the liquid structures that evolve slowly on the (independently measured) rotation time scales. To separate the RISD contribution to the FFCF from the structural spectral diffusion contribution, the previously developed first order Stark effect RISD model is reformulated to describe the second order (quadratic) Stark effect—the first order Stark effect vanishes because CO 2 does not have a permanent dipole moment. Through this analysis, we characterize the structural fluctuations of CO 2 in the ionic liquid solvation environment, which separate into magnitude-only and combined magnitude and directional correlations of the liquid’s time dependent electric field. This new methodology will enable highly incisive comparisons between CO 2 dynamics in a variety of ionic liquid systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Operating Stresses and Their Effects on Degradation of LSM-Based SOFC Cathodes

The performance of solid oxides fuel cells (SOFCs) with four different Mn excess of lanthanum strontium manganite (LSM) -based cathodes were examined under different temperatures (1,000 °C, 900 °C), current densities (0, 380, and 760 mA cm -2 ), and cathode atmospheres (p O 2 )=0.1,0.15,0.21) for durations ranging from 58 to 1,008 h. Each yttria-stabilized zirconia (YSZ) electrolyte-supported “button” cell had a porous Ni/YSZ composite anode and a porous LSM/YSZ composite cathode. The cells’ output voltage versus time were recorded and electrochemical impedance spectroscopy (EIS) and linear sweep voltammetry (LSV) measurements were performed every 24 hours. The total area specific resistance (ASR) was calculated from these measurements. The values of ASR from both EIS and LSV were comparable between each other but lower than that from durability test. Distribution of relaxation times (DRT) analysis was performed to investigate the electrochemical processes and their corresponding relaxation frequencies as well as their attributions to the total ASR. The series resistance and parallel resistance that obtained from the equivalent circuit fit of the Nyquist plot were higher at low temperature and low p O 2 regardless of LSM compositions. The area of the peaks derived from DRT analysis increased with time during individual tests. The microstructures of the tested cells were examined using scanning electron microscopy and energy-dispersive x-ray spectroscopy (SEM/EDS). Manganese oxide particles were observed near the cathode-electrolyte interface after prolonged (1,008 h) testing in air of a cell with LSM of 11% manganese excess, and after a short test (58 h) under low oxygen (p O 2 = 0.10) in a cell with LSM of 5% manganese excess. However, the role of MnOx in cell degradation is still unknown.

08 HYDROGEN↗
DOE OSTI2022

Influence of Vane Trailing Edge Flow on the Formation of Cavity Cells and Rim Sealing

Abstract Hot gas ingestion into the turbine rim seal cavity is an important concern for engine designers. To prevent ingestion, rim seals use high-pressure purge flow; however, the penalty is that excessive use of the purge flow decreases engine thermal efficiency. In this paper, a one-stage turbine operating at engine-representative conditions was used to study the effect of steady and time-resolved under-platform cavity temperatures and pressures across a range of coolant flowrates in the presence of vane trailing edge (VTE) flow. This study correlates time-resolved pressure with time-resolved temperature to identify primary frequencies driving ingestion. At certain flowrates, the time-resolved pressures are out of phase with the temperatures, indicating ingestion. Measurements from high-frequency response pressure sensors in the rim seal and vane platform were also used to determine rotational speed and quantity of large-scale structures (cells). In a parallel effort, a computational model using Unsteady Reynolds-averaged Navier–Stokes (URANS) was applied to determine swirl ratio in the rim seal cavity and time-resolved rim sealing effectiveness. The experimental results confirm that at low purge flowrates, the VTE flow influences the unsteady flow field by decreasing pressure unsteadiness in the rim seal cavity. Results show an increase in purge flow increases the number of unsteady large-scale structures in the rim seal and decreases their rotational speed. However, VTE flow was shown to not significantly change the cell speed and count in the rim seal. Simulations point to the importance of the large-scale cell structures in influencing rim sealing unsteadiness, which is not captured in current rim sealing predictive models.

Engineering↗
DOE OSTI2022

Decoding the protein–ligand interactions using parallel graph neural networks

Abstract Protein–ligand interactions (PLIs) are essential for biochemical functionality and their identification is crucial for estimating biophysical properties for rational therapeutic design. Currently, experimental characterization of these properties is the most accurate method, however, this is very time-consuming and labor-intensive. A number of computational methods have been developed in this context but most of the existing PLI prediction heavily depends on 2D protein sequence data. Here, we present a novel parallel graph neural network (GNN) to integrate knowledge representation and reasoning for PLI prediction to perform deep learning guided by expert knowledge and informed by 3D structural data. We develop two distinct GNN architectures: $$\hbox {GNN}_{\mathrm{F}}$$ GNN F is the base implementation that employs distinct featurization to enhance domain-awareness, while $$\hbox {GNN}_{\mathrm{P}}$$ GNN P is a novel implementation that can predict with no prior knowledge of the intermolecular interactions. The comprehensive evaluation demonstrated that GNN can successfully capture the binary interactions between ligand and protein’s 3D structure with 0.979 test accuracy for $$\hbox {GNN}_{\mathrm{F}}$$ GNN F and 0.958 for $$\hbox {GNN}_{\mathrm{P}}$$ GNN P for predicting activity of a protein–ligand complex. These models are further adapted for regression tasks to predict experimental binding affinities and $$\hbox {pIC}_{\mathrm{50}}$$ pIC 50 crucial for compound’s potency and efficacy. We achieve a Pearson correlation coefficient of 0.66 and 0.65 on experimental affinity and 0.50 and 0.51 on $$\hbox {pIC}_{\mathrm{50}}$$ pIC 50 with $$\hbox {GNN}_{\mathrm{F}}$$ GNN F and $$\hbox {GNN}_{\mathrm{P}}$$ GNN P , respectively, outperforming similar 2D sequence based models. Our method can serve as an interpretable and explainable artificial intelligence (AI) tool for predicted activity, potency, and biophysical properties of lead candidates. To this end, we show the utility of $$\hbox {GNN}_{\mathrm{P}}$$ GNN P on SARS-Cov-2 protein targets by screening a large compound library and comparing the prediction with the experimentally measured data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

In Situ X-Ray Observations of Dendritic Fragmentation During Directional Solidification of a Sn-Bi Alloy

Dendrite fragmentation is an important phenomenon in microstructural development during solidification. For instance, it plays a key role in initiating the columnar-to-equiaxed transition (CET). Here, we use x-ray radiography to study dendrite fragmentation rate in a Sn-39.5 wt.% Bi alloy during directional solidification. Experiments were performed in which solidification was parallel and anti-parallel to gravity, leading to significantly different fragmentation rates. We quantify the distribution of fragmentation rate as a function of distance from the solidification front, time in the mushy zone, and volume fraction of solid. While the observed fragmentation rate can be high, there is no evidence of a CET, illustrating that it requires more than just fragmentation to occur.

Gibbs, John W.↗
DOE OSTI2017

Trace: a high-throughput tomographic reconstruction engine for large-scale datasets

Abstract Background Modern synchrotron light sources and detectors produce data at such scale and complexity that large-scale computation is required to unleash their full power. One of the widely used imaging techniques that generates data at tens of gigabytes per second is computed tomography (CT). Although CT experiments result in rapid data generation, the analysis and reconstruction of the collected data may require hours or even days of computation time with a medium-sized workstation, which hinders the scientific progress that relies on the results of analysis. Methods We present Trace, a data-intensive computing engine that we have developed to enable high-performance implementation of iterative tomographic reconstruction algorithms for parallel computers. Trace provides fine-grained reconstruction of tomography datasets using both (thread-level) shared memory and (process-level) distributed memory parallelization. Trace utilizes a special data structure called replicated reconstruction object to maximize application performance. We also present the optimizations that we apply to the replicated reconstruction objects and evaluate them using tomography datasets collected at the Advanced Photon Source. Results Our experimental evaluations show that our optimizations and parallelization techniques can provide 158× speedup using 32 compute nodes (384 cores) over a single-core configuration and decrease the end-to-end processing time of a large sinogram (with 4501 × 1 × 22,400 dimensions) from 12.5 h to <5 min per iteration. Conclusion The proposed tomographic reconstruction engine can efficiently process large-scale tomographic data using many compute nodes and minimize reconstruction times.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Lifting and Dropping VMs to Dynamically Transition Between Time- and Space-sharing for Large-Scale HPC Systems

As HPC environments increasingly integrate with edge based systems, system architectures will need to handle a broader class of workloads and scheduling requirements. One result of this shift will be the need to simultaneously support bulk-synchronous parallel (BSP) and on-demand service based applications on the same infrastructure. This in turn will require that future resource management approaches utilize both space-shared as well as time-shared resource scheduling strategies. In this work we introduce the concept of "VM-lifting'' (and its inverse "VM-Dropping'') which allows dynamically switching an HPC workload between space-shared and time-shared scheduling regimes. Our work targets co-kernel based HPC system software environments, in which multiple specialized OS kernels execute natively on dedicated physical resource partitions inside a single compute node. With VM-lifting, a native co-kernel can be migrated at runtime to and from locally hosted Virtual Machine Environments due to changing scheduling requirements of the node. This allows an HPC node to be dynamically (re-)configured as either a time-shared Infrastructure-as-a-Service (IaaS) resource or a dedicated space shared resource based on the current workload demands. We have implemented this approach in the context of the Hobbes Exascale System Software stack and have demonstrated that a node can be reconfigured with minimal impact on the running applications.

Gordon, Nick↗
DOE OSTI2017

Low- and high-order accurate boundary conditions: From Stokes to Darcy porous flow modeled with standard and improved Brinkman lattice Boltzmann schemes

The present contribution focuses on the accuracy of reflection-type boundary conditions in the Stokes–Brinkman–Darcy modeling of porous flows solved with the lattice Boltzmann method (LBM), which we operate with the two-relaxation-time (TRT) collision and the Brinkman-force based scheme (BF), called BF-TRT scheme. In parallel, we compare it with the Stokes–Brinkman–Darcy linear finite element method (FEM) where the Dirichlet boundary conditions are enforced on grid vertices. In bulk, both BF-TRT and FEM share the same defect: in their discretization a correction to the modeled Brinkman equation appears, given by the discrete Laplacian of the velocity-proportional resistance force. This correction modifies the effective Brinkman viscosity, playing a crucial role in the triggering of spurious oscillations in the bulk solution. While the exact form of this defect is available in lattice-aligned, straight or diagonal, flows; in arbitrary flow/lattice orientations its approximation is constructed. At boundaries, we verify that such a Brinkman viscosity correction has an even more harmful impact. Already at the first order, it shifts the location of the no-slip wall condition supported by traditional LBM boundary schemes, such as the bounce-back rule. For that reason, this work develops a new class of boundary schemes to prescribe the Dirichlet velocity condition at an arbitrary wall/boundary-node distance and that supports a higher order accuracy in the accommodation of the TRT-Brinkman solutions. For their modeling, we consider the standard BF scheme and its improved version, called IBF; this latter is generalized in this work to suppress or to reduce the viscosity correction in arbitrarily oriented flows. Our framework extends the one- and two-point families of linear and parabolic link-wise boundary schemes, respectively called B-LI and B-MLI, which avoid the interference of the Brinkman viscosity correction in their closure relations. The performance of LBM and FEM is thoroughly evaluated in three benchmark tests, which are run throughout three distinctive permeability regimes. The first configuration is a horizontal porous channel, studied with a symbolic approach, where we construct the exact solutions of FEM and BF/IBF with different boundary schemes. The second problem refers to an inclined porous channel flow, which brings in as new challenge the formation of spurious boundary layers in LBM; that is, numerical artefacts that arise due to a deficient accommodation of the bulk solution by the low-accurate boundary scheme. The third problem considers a porous flow past a periodic square array of solid cylinders, which intensifies the previous two tests with the simulation of a more complex flow pattern. The ensemble of numerical tests provides guidelines on the effect of grid resolution and the TRT free collision parameter over the accuracy and the quality of the velocity field, spanning from Stokes to Darcy permeability regimes. It is shown that, with the use of the high-order accurate boundary schemes, the simple, uniform-mesh-based TRT-LBM formulation can even surpass the accuracy of FEM employing hardworking body-fitted meshes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Image Gradient Decomposition for Parallel and Memory-Efficient Ptychographic Reconstruction

Ptychography is a popular microscopic imaging modality for many scientific discoveries and sets the record for highest image resolution. Unfortunately, the high image resolution for ptychographic reconstruction requires significant amount of memory and computations, forcing many applications to compromise their image resolution in exchange for a smaller memory footprint and a shorter reconstruction time. In this paper, we propose a novel image gradient decomposition method that significantly reduces the memory footprint for ptychographic reconstruction by tessellating image gradients and diffraction measurements into tiles. In addition, we propose a parallel image gradient decomposition method that enables asynchronous point-to-point communications and parallel pipelining with minimal overhead on a large number of GPUs. Our experiments on a Titanate material dataset (PbTiO3) with 16632 probe locations show that our Gradient Decomposition algorithm reduces memory footprint by 51 times. In addition, it achieves time-to-solution within 2.2 minutes by scaling to 4158 GPUs with a super-linear strong scaling efficiency at 364% compared to runtimes at 6 GPUs. This performance is 2.7 times more memory efficient, 9 times more scalable and 86 times faster than the state-of-the-art algorithm.

Wang, Xiao↗
DOE OSTI2016

A matrix-algebraic formulation of distributed-memory maximal cardinality matching algorithms in bipartite graphs

We describe parallel algorithms for computing maximal cardinality matching in a bipartite graph on distributed-memory systems. Unlike traditional algorithms that match one vertex at a time, our algorithms process many unmatched vertices simultaneously using a matrix-algebraic formulation of maximal matching. This generic matrix-algebraic framework is used to develop three efficient maximal matching algorithms with minimal changes. The newly developed algorithms have two benefits over existing graph-based algorithms. First, unlike existing parallel algorithms, cardinality of matching obtained by the new algorithms stays constant with increasing processor counts, which is important for predictable and reproducible performance. Second, relying on bulk-synchronous matrix operations, these algorithms expose a higher degree of parallelism on distributed-memory platforms than existing graph-based algorithms. We report high-performance implementations of three maximal matching algorithms using hybrid OpenMP-MPI and evaluate the performance of these algorithm using more than 35 real and randomly generated graphs. On real instances, our algorithms achieve up to 200 × speedup on 2048 cores of a Cray XC30 supercomputer. Even higher speedups are obtained on larger synthetically generated graphs where our algorithms show good scaling on up to 16,384 cores.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

A cloud computing approach to massively-parallel distributed stochastic optimization with application to geomechanical reservoir characterization

Many search strategies used to optimize parameters during hydrologic model calibration are inherently limited in that simulations must be performed sequentially in order for the algorithm to converge. As a result, the overall time required to reach a solution increases linearly with the number of steps necessary. In contrast, sampling strategies that attempt to approximate the posterior distribution of the parameters do not require the model simulations to be run in sequence and therefore invite the use of a massively parallel approach across heterogeneous computing environments. We apply a cloud computing methodology to this problem where a head node running on Amazon Web Services continuously produces candidate models that are distributed to arbitrary compute environments to run the simulation, in our case Clemson’s Palmetto cluster computer. Thus the time required to obtain a sufficient number of samples to produce an adequate approximation of the posterior distribution of the parameters is limited by the number of available compute sites. Monte Carlo sampling of the posterior space would be duplicative and inefficient, thus we combine Latin hypercube methods with genetic algorithms to ensure that no large regions of the parameter space are left unexplored, and that high probability regions are investigated thoroughly. We independently assess the fit to different types of data sets without the need to construct a single objective function. Sets of Pareto optimal models are particularly valuable when the quality and information content of data is poorly known or conceptual model errors exist in our simulation. We illustrate our approach for a problem where in situ strain data are used to calibrate the parameters of an oil reservoir in the Avant oil field in Oklahoma. We use well injection and shut-in to stress a deep (500m) confined formation, and observe the geomechanical response using borehole strainmeters installed in the shallow subsurface (30m). These data were then used to calibrate the poroelastic properties of the reservoir and caprock along with the geometry of an elliptic channel associated with the formation. Using our approach we are able to identify issues with model error as well as substantial tradeoffs that occur within the parameters.

inversion, stochastic, geomechanics, poroelastic, ↗
DOE OSTI2017

Parallel Reconstruction of Three Dimensional Magnetohydrodynamic Equilibria in Plasma Confinement Devices

Fast, accurate three dimensional reconstructions of plasma equilibria, crucial for physics interpretation of fusion data generated within confinement devices like stellarators/ tokamaks, are computationally very expensive and routinely require days, even weeks, to complete using serial approaches. Here, we present a parallel implementation of the three dimensional plasma reconstruction code, V3FIT. A formal analysis to identify the performance bottlenecks and scalability limits of this new parallel implementation, which combines both task and data parallelism, is presented. The theoretical findings are supported by empirical performance results on several thousands of processor cores of a Cray XC30 supercomputer. Parallel V3FIT is shown to deliver over 40X speedup, enabling fusion scientists to carry out three dimensional plasma equilibrium reconstructions at unprecedented scales in only a few hours (instead of in days/weeks) for the first time.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Time dependent evolution of linear kinetic Alfvén waves in inhomogeneous plasma

The propagation of linear Kinetic Alfvén waves (KAWs) in inhomogeneous magnetized plasma has been studied while including inhomogeneities in transverse and parallel directions relative to the background magnetic field. The propagation of KAWs in inhomogeneous magnetized plasma is expected to play a key role in energy transfer and turbulence generation in space and laboratory plasmas. The inhomogeneity scale lengths in both directions may control the nature of fluctuations and localization of the waves. We present a theoretical study of the localization of KAWs, variations in magnetic field amplitude in time, and variation in the frequency spectra arising from inhomogeneities. The relevance of the model to space and laboratory observations is discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Large-scale real-time signal processing in physics experiments: the ALICE TPC FPGA pipeline

For LHC Run 3, the ALICE Time Projection Chamber was upgraded to operate in continuous readout mode. Interaction rates of up to 50 kHz in Pb-Pb collisions require real-time processing of more than 3 TB s -1 of raw detector data. This requirement is met by a custom FPGA-based processing pipeline that performs the complete front-end data treatment fully in-stream, including common-mode correction, pedestal subtraction, ion-tail filtering, zero suppression, and dense data packing. A central element of the design is a highly parallel common-mode correction algorithm operating directly on the streaming data. It robustly identifies signal-free readout channels on a time-bin basis and applies pad-dependent scaling to compensate for local variations in capacitive coupling in the GEM readout. In combination with pedestal subtraction and ion-tail filtering, this enables accurate baseline restoration under extreme high-occupancy conditions, preventing signal loss while efficiently suppressing noise prior to zero suppression. The pipeline operates continuously at the full detector bandwidth and reduces the raw input rate of approximately 3 TB s -1 to about 900 GBps for Pb-Pb collisions at the target interaction rate. Overall, it represents a large-scale FPGA-based real-time signal-processing implementation for high-energy physics detector readout.

Digital signal processing (DSP)↗
DOE OSTI2026

Real-Time GPU-Accelerated OFDR With an Integrated Auxiliary Interferometer

A GPU-accelerated optical frequency domain reflectometry (OFDR) system with an improved integrated auxiliary interferometer is proposed. Unlike conventional approaches that require separate auxiliary interferometers and multiple detection channels, the proposed OFDR system embeds this functionality directly into the signal via an intentional beat component. This enables self-calibration of laser nonlinearity while maintaining a cost-effective hardware configuration. Building on this simplified configuration, the system leverages GPU acceleration with an NVIDIA RTX 4070 Ti to achieve real-time performance, delivering high-throughput signal processing for continuous OFDR interrogation. The signal processing pipeline comprises signal capture, resampling for nonlinearity compensation, and frequency shift computation, all optimized for parallel execution. Hardware benchmarking demonstrates substantial acceleration over CPU implementations, achieving up to a 45× speedup for resampling and frequency shift computations and enabling processing latencies below 30 ms. Thermal response validation is conducted under two complementary scenarios: localized heating using a water bath and cryogenic-temperature conditions using liquid nitrogen. Under localized heating, the system achieves an accuracy of 0.249 °C with a thermal sensitivity of 5.971 GHz/°C, while cryogenic-temperature validation demonstrates a frequency shift response with a sensitivity of 2.383 GHz/°C and an accuracy of 2.04 °C. The high acceleration of the proposed GPU-accelerated OFDR system and its accuracy are achieved by exploiting CUDA-based stride indexing, enabling efficient parallel segmentation and processing of large datasets without additional memory copies. The benchmarking results confirm the robustness, accuracy, and deployability of the proposed OFDR system across a wide temperature range, establishing it as a practical platform for real-time distributed fiber sensing in structurally dynamic environments.

Harb, Salah [Lawrence Berkeley National Laboratory↗
DOE OSTI2015

WE-EF-303-05: Development and Commissioning of Real-Time Imaging Function for Respiratory-Gated Spot-Scanning Proton Beam Therapy

Purpose: To realize real-time-image gated proton beam therapy (RGPT) for treating mobile tumors. Methods: The rotating gantry of spot scanning proton beam therapy has been designed to equip two x-ray fluoroscopy devices that enable real-time imaging of the internal fiducial markers during respiration. Three-dimensional position of the fiducial marker located near the tumor can be calculated from the fluoroscopic images obtained from orthogonal directions and therapeutic beam is gated only when the fiducial marker is within the predefined gating window. Image acquisition rate can be selected from discrete value ranging from 0.1 Hz to 30 Hz. In order to confirm the effectiveness of RGPT and apply it clinically, clinical commissioning was conducted. Commissioning tests were categorized to main three parts including geometric accuracy, temporal accuracy and dosimetric evaluation. Results: Developed real-time imaging function has been installed and its basic performances have been confirmed. In the evaluation of geometric accuracy, coincidence of three-dimensional treatment room coordinate system and imaging coordinate system was confirmed to be less than 1 mm. Fiducial markers (gold sphere and coil) were able to be tracked in simulated clinical condition using an anthropomorphic chest phantom. In the evaluation of temporal accuracy, latency from image acquisition to gate on/off signal was about 60 msec in typical case. In dosimetric evaluation, treatment beam characteristics including beam irradiation position and dose output were stable in gated irradiation. Homogeneity indices to the mobile target were 0.99 (static), 0.89 (w/o gating, motion is parallel to direction of scan), 0.75 (w/o gating, perpendicular), 0.98 (w/ gating, parallel) and 0.93 (w/ gating, perpendicular). Dose homogeneity to the mobile target can be maintained in RGPT. Conclusion: Real-time imaging function utilizing x-ray fluoroscopy has been developed and commissioned successfully in order to realize RGPT. Funding Support: This research was partially supported by Japan Society for the Promotion of Science (JSPS) through the FIRST Program. Conflict of Interest: Prof. Shirato has research fund from Hitachi Ltd, Mitsubishi Heavy Industries Ltd and Shimadzu Corporation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Stiff and Transparent Multilayer Thin Films Prepared Through Hydrogen-Bonding Layer-by-Layer Assembly of Graphene and Polymer [Super Stiff and Highly Transparent Multilayer Thin Films Prepared through Hydrogen-Bonding Layer-by-Layer Assembly of Graphene and Polymer]

Due to their exceptional orientation of 2D nanofillers, layer–by–layer (LbL) assembled polymer/graphene oxide thin films exhibit unmatched mechanical performance relative to any conventionally produced counterparts with similar composition. Unprecedented mechanical property improvement, by replacing graphene oxide with pristine graphene, is demonstrated in this work. Polyvinylpyrrolidone–stabilized graphene platelets are alternately deposited with poly(acrylic acid) using hydrogen bonding assisted LbL assembly. Transmission electron microscopy imaging and the Halpin–Tsai model are used to demonstrate, for the first time, that intact graphene can be processed from water to generate polymer nanocomposite thin films with simultaneous parallel–alignment, high packing density, and exfoliation. A multilayer thin film with only 3.9 vol% of highly exfoliated, and structurally intact graphene, increases the elastic modulus (E) of a polymer multilayer thin film by 322% (from 1.41 to 4.81 GPa), while maintaining visible light transmittance of ≈90%. This is one of the greatest improvements in elastic modulus ever reported for a graphene–filled polymer nanocomposite with a glassy (E > 1 GPa) matrix. In conclusion, the technique described here provides a powerful new tool to improve nanocomposite properties (mechanical, gas transport, etc.) that can be universally applied to a variety of polymer matrices and 2D nanoplatelets.

36 MATERIALS SCIENCE↗