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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Introducing Weirs: An Abstraction for Next Generation Streaming Workflows

In HPC applications, it is widely understood that in situ systems will play a significant role in next generation systems. The rate that next-generation leadership machines will be able to generate data will exceed the bandwidths of the planned I/O systems, leading to a need for in situ processing of the resulting data to reduce it. There have been a number of techniques proposed for in situ workflow systems; we are concerned here specifically with the needs of publish/subscribe or streaming-based approaches, which allow the in situ system to be composed of completely separate executables running concurrently on the hardware. In this paper we introduce an abstract known as a Weir. A weir is a useful mechanism to control state in a point to point streaming workflow in the absence of a third party publish subscribe system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Structural Simluation Toolkit (SST) v.12.0

The Structural Simulation Toolkit (SST) was developed to explore innovations in highly concurrent computing systems where the instruction set architecture (ISA), micro-architecture, and memory interact with the programming model and communications system. The package provides a fully modular design for extensive exploration of an individual system parameter as well as a parallel simulation environment based on message passing interface (MPI) which enable a high level of performance as well as the ability to look at large systems. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Rodrigues, ArunF.↗
DOE OSTI2023

Predictive Engineering of Interfaces and Cathodes for High-Performance All Solid-State Lithium-Sulfur Batteries

The primary goal of this project is to leverage data-driven methods and machine learning strategies to develop accurate multi-physics models for all-solid-state Li-S battery (ASLSB) materials that can capture electrochemical and transport phenomena over atomic to mesoscopic length/timescales. These models will be rigorously validated by synthesis and advanced characterization experiments. The team will leverage the predictive power of these models, alongside synthesis/characterization experiments and battery fabrication to address longstanding issues at the electrode/electrolyte interfaces in ASLSBs. The project’s proposed technology involves the following: (1) halide-doped solid sulfide electrolytes that can concurrently provide high Li + ion conductivity and suppress dendrite growth; (2) novel mesoporous cathode composed of super-P and carbon nanotubes co-infiltrated with sulfur and sulfide electrolyte, which hold potential to allow high sulfur loading and optimal ion/electron pathways; and (3) functionalization of sulfide electrolyte with ionic liquids to improve physical contact and minimize impedance at the cathode/electrolyte interface. Successful development of proposed predictive models (at multiple scales) will bridge this knowledge gap and will advance fundamental understanding of reaction chemistry, kinetics, charge transfer, and dendrite growth at electrified SSIs. This will enable predictive design of effective strategies to mitigate interfacial problems in ASSLSBs, including poor interfacial contact, interfacial impedance to Li + ion transport, and poor electron/ion conduction within cathodes. Ultimately, the fundamental knowledge gained will lead to development of high-performance ASSLSBs.

25 ENERGY STORAGE↗
DOE OSTI2015

Fermentation of dilute acid pretreated Populus by Clostridium thermocellum , Caldicellulosiruptor bescii , and Caldicellulosiruptor obsidiansis

Consolidated bioprocessing (CBP), which merges enzyme production, biomass hydrolysis, and fermentation into a single step, has the potential to become an efficient and economic strategy for the bioconversion of lignocellulosic feedstocks to transportation fuels or chemicals. In this study, we evaluated Clostridium thermocellum , Caldicellulosiruptor bescii , and Caldicellulosiruptor obsidiansis , three , thermophilic,cellulolytic, mixed-acid fermenting candidate CBP microorganisms, for their fermentation capabilities using dilute acid pretreated Populus as a model biomass feedstock. Under pH controlled, anaerobic fermentation conditions, each candidate successfully digested a minimum of 75% of the cellulose from dilute acid pretreated Populus , as indicated by an increase in planktonic cells and end-product metabolites and a concurrent decrease in glucan content. C. thermocellum , which employs a cellulosomal approach to biomass degradation, required 120 hours to achieve 75% cellulose utilization. In contrast, the non-cellulosomal, secreted hydrolytic enzyme system of the Caldicellulosiruptor sp. required 300 hours to achieve similar results. End-point fermentation conversions for C. thermocellum , C. bescii , and C. obsidiansis were determined to be 0.29, 0.34, and 0.38 grams of total metabolites per gram of loaded glucan, respectively. This data provide a starting point for future strain engineering efforts that can serve to improve the biomass fermentation capabilities of these three promising candidate CBP platforms.

09 BIOMASS FUELS↗
DOE OSTI2014

Towards real time diagnostics of Hybrid Welding Laser/GMAW

Methods are currently being developed towards a more robust system real time feedback in the high throughput process combining laser welding with gas metal arc welding. A combination of ultrasonic, eddy current, electronic monitoring, and visual techniques are being applied to the welding process. Initial simulation and bench top evaluation of proposed real time techniques on weld samples are presented along with the concepts to apply the techniques concurrently to the weld process. Consideration for the eventual code acceptance of the methods and system are also being researched as a component of this project. The goal is to detect defects or precursors to defects and correct when possible during the weld process.

42 ENGINEERING↗
DOE OSTI2015

Area 2. Use Of Engineered Nanoparticle-Stabilized CO 2 Foams To Improve Volumetric Sweep Of CO 2 EOR Processes

The goal of this project was to develop a new CO 2 injection enhanced oil recovery (CO 2 -EOR) process using engineered nanoparticles with optimized surface coatings that has better volumetric sweep efficiency and a wider application range than conventional CO 2 -EOR processes. The main objectives of this project were to (1) identify the characteristics of the optimal nanoparticles that generate extremely stable CO 2 foams in situ in reservoir regions without oil; (2) develop a novel method of mobility control using “self-guiding” foams with smart nanoparticles; and (3) extend the applicability of the new method to reservoirs having a wide range of salinity, temperatures, and heterogeneity. Concurrent with our experimental effort to understand the foam generation and transport processes and foam-induced mobility reduction, we also developed mathematical models to explain the underlying processes and mechanisms that govern the fate of nanoparticle-stabilized CO 2 foams in porous media and applied these models to (1) simulate the results of foam generation and transport experiments conducted in beadpack and sandstone core systems, (2) analyze CO 2 injection data received from a field operator, and (3) aid with the design of a foam injection pilot test. Our simulator is applicable to near-injection well field-scale foam injection problems and accounts for the effects due to layered heterogeneity in permeability field, foam stabilizing agents effects, oil presence, and shear-thinning on the generation and transport of nanoparticle-stabilized C/W foams. This report presents the details of our experimental and numerical modeling work and outlines the highlights of our findings.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Interfacial Engineering Using Covalent Organic Frameworks in Polymer Composites for High‐Temperature Electrostatic Energy Storage

Abstract The use of inorganic nanofillers has been an effective method to improve high‐temperature capacitive performance of dielectric polymers, though there are unmet challenges such as undesirable organic–inorganic compatibility, and low efficiencies and energy densities. Herein, a surface functionalization strategy using covalent organic frameworks (COFs) is employed to address such challenges in realizing high‐performing polymer composites. Specifically, core–shell structured nanoparticles, where ZrO 2 nanoparticles act as the core and a COF material forms the shell, are constructed and composited with the polyetherimide (PEI) matrix. The design leverages the high electron affinity ( E A ) of the outer COF shell to create energy traps, thereby capturing free charges and limiting electrical conduction. Concurrently, the low E A and wide bandgap of the ZrO 2 core introduce energy barriers to impede charge injection and migration. This orchestrated “energy level cascade” results in a marked reduction of leakage current and energy loss. The resulting polymer composite showcases an impressive discharged energy density of 6.21 J cm −3 at an efficiency above 90%, with a maximum discharged energy density reaching 7.43 J cm −3 at 150 °C. These performance metrics position the PEI/ZrO 2 @COF polymer composite to surpass or be on par with state‐of‐the‐art high‐temperature PEI composites and other advanced polymer dielectrics.

Xie, Zongliang↗
DOE OSTI2023

S4PST: Sustainability for Programming Systems and Tools: May Workshop Report

The US Department of Energy (DOE) Exascale Computing Project (ECP) has fostered and strengthened the use of modern software engineering practices for developing applications and libraries, and this effort has resulted in the coordinated and interoperable E4S1 and xSDK2 ecosystems. Although this approach is cost-effective, it relies on robust programming systems and tools (PST) as the underlying foundation for our HPC software. At present, our primary PST stack consists of traditional high-performance computing (HPC) languages, namely Fortran, C, C++, and the popular Python language for data analysis and AI workflows. These languages support various programming frameworks and run-time abstractions that enable parallelism and concurrency across multiple node architectures and thousands of nodes through a variety of interconnect systems. However, to accommodate users’ diverse needs, certain aspects of the HPC ecosystem are delegated to vendor-specific or third-party implementations that extend beyond a particular scientific domain. This broader scope results in a multitude of specifications and variations, which leads to a complex orchestration of many-ecosystems. Unfortunately, this complexity in the ecosystem imposes additional overhead costs on consumers during the latter stages of the development cycle. In addition to the software ecosystem challenge, the upcoming conclusion of the ECP by December 2023 has raised significant concerns within the HPC programming systems community, from both the economic and social perspectives. The ECP has implemented a management structure for software development and funding decisions across all ECP participants by following a conventional hierarchical and centralized approach. However, this structure has prompted certain considerations within the community, particularly in anticipation of the Software Sustainability initiative by the DOE’s Advanced Scientific Computing Research Program (ASCR). For the success of this new initiative, it is of utmost importance to secure consistent funding and foster close engagement with researchers and core developers of existing programming-system products. This collaboration is vital to maintaining the critical capabilities of the current software during the transition phase while proactively adapting to future technology and workforce trends. The community recognizes the significance of adapting to emerging trends and is aware of the inherent fragility of the HPC software ecosystem, particularly in relation to programming systems that cater to all users. The ability to adapt and evolve is essential to staying relevant and effectively addressing these technical, economic, and social challenges. The S4PST team, which represents one of the six ASCR Software Sustainability seedling projects, is dedicated to tackling these challenges through community-based approaches that go beyond the scope of the DOE. This involves collaboration between national laboratories with academia, non-DOE institutions, hardware and system vendors, and international partners. By fostering these partnerships, we aim to create a robust and sustainable HPC software ecosystem that can effectively meet the needs of the community. This new community effort, driven by the eight DOE labs, will take on the responsibility of guiding funding decisions for programming-systems development and maintenance with transparency and consistency across all decisions. Additionally, the team will offer common technical services to the programming systems community, irrespective of their funding situations, and facilitate community-wide incubation to proactively nurture the software ecosystem. By actively engaging with stakeholders and employing a collaborative approach, we can collectively shape the future of programming systems and ensure a robust and thriving HPC software landscape. On May 11–12, 2023, the S4PST team conducted its inaugural kick-off workshop at the Innovative Computing Laboratory (ICL) in the University of Tennessee, Knoxville, hosted by Hartwig Anzt. The workshop encompassed various sessions dedicated to presentations and discussions, with the aim of comprehending the team members’ perspectives on the vision of software sustainability. Additionally, the workshop aimed to identify the technical, economic, and social requirements for sustaining the programming-systems community in the field of HPC. This report provides a summary of the S4PST effort by highlighting five major thrust areas discussed during the workshop: (i) community, (ii) technical support, (iii) training and diversity, (iv) verification, validation and correctness, and (v) emerging technologies. It also encompasses an overview of the presentations and discussions held throughout the event, our views and potential synergies with other seedling efforts, along with the outcomes and key takeaways from our initial discussions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

An overview of the 2014 revision of ANSI/ANS-ANS-8.1-2014, 'Nuclear criticality safety in operations with Fissionable Materials Outside Reactors' - 14577

A revision to the American National Standards Institute (ANSI)/American Nuclear Society (ANS) standard, 'Nuclear Criticality Safety in Operations with Fissionable Materials Outside Reactors' [ANSI/ANS-8.1 (ANS-8.1)], was completed and published in 2014. The approved scope for the 2014 revision included two major efforts: (1) an editorial revision to clarify the meaning of the process analysis requirement (PA) and the double contingency principle recommendation (DCP) and (2) the generation of new subcritical limits for uranium and uranium compounds for enrichments less than 10 wt % {sup 235}U. After a clarification request was submitted regarding the PA and DCP in 2009, the scope of the revision became focused almost entirely on the editorial revision. With approval from the ANS-8 subcommittee chairman, the computational effort was postponed until the editorial revision could be completed. The 2014 revision of ANS-8.1 involved nuclear criticality safety experts from 14 different sites, each with many years of experience, either maintaining the standard as a working group member or as a criticality safety practitioner. Many of the represented sites had implemented the PA with the language of the DCP to ensure that process operations with fissionable materials would be subcritical. However, the early working group deliberations made it clear that the general industry focus was on the DCP rather than the PA, which requires that 'all normal and credible abnormal conditions remain subcritical'. Over the course of the revision, two new definitions and a new appendix (Appendix B) were developed to enhance understanding of the PA and DCP. The emphasis of Appendix B is on the requirement for subcriticality (PA) rather than the DCP. The phrase 'credible abnormal conditions' in the PA is broader in meaning than 'changes in process conditions,' as recommended by the DCP. This is because a single credible abnormal condition can potentially affect multiple independent process conditions, and consequently, multiple process parameters, simultaneously. The DCP is a technical practice meant to support the PA and cannot be applied to all situations. However, when it can be properly applied, the DCP technical practice, in most cases, ensures compliance with the PA because two unlikely, independent, and concurrent changes in process conditions are generally judged not to be a credible abnormal condition, as specified in the PA. This paper elaborates on the intense working group discussions over the course of the ANSI/ANS-8.1 standard revision and summarizes the modifications made to the revised standard. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Perspectives of automotive battery R&D in China, Germany, Japan, and the USA

Lithium(-ion) batteries are and will be the battery technology of choice for a wide range of applications - including electric vehicles - for several years to come. Nonetheless, to foster the transition from combustion engine vehicles to a fully electrified transportation, further progress is needed. In this regard, the annual International Conference on Advanced Lithium Batteries for Automobile Applications (ABAA) targets the intensive exchange of the involved industrial and research entities to jointly ensure the further progress of this technology. During the past meeting, ABAA-10, held in October 2017 in Chicago, IL, USA, representatives of China, Germany, Japan, and the USA provided a comprehensive overview of the current and future battery R&D activities in their countries, depicting a highly insightful survey about partially concurrent, partially complementary research and funding strategies. Here, the given presentations are provided in the Supplementary Material for this Special Perspective, while this perspective paper may serve as brief introduction to the general development in the field concerning the overall EV sales and common considerations regarding future material developments.

25 ENERGY STORAGE↗
DOE OSTI2018

Impact of Pore Fluid Chemistry on Fine-Grained Sediment Fabric and Compressibility

Fines, defined here as grains or particles, less than 75µm in diameter, exist nearly ubiquitously in natural sediment, even those classified as coarse. Macroscopic sediment properties, such as compressibility, which relates applied effective stress to the resulting sediment deformation, depend on the fabric of fines. Unlike coarse grains, fines have sizes and masses small enough to be more strongly influenced by electrical interparticle forces than by gravity. These electrical forces acting through pore fluids are influenced by pore-fluid chemistry changes. Macroscopic property dependence on pore-fluid chemistry must be accounted for in sediment studies involving subsurface flow and sediment stability analyses, as well as in engineered flow situations such as groundwater pollutant remediation, hydrocarbon migration or other energy resource extraction applications. This study demonstrates how the liquid-limit-based electrical sensitivity index can be used to predict sediment compressibility changes due to pore-fluid chemistry changes. Laboratory tests of electrical sensitivity, sedimentation and compressibility illustrate mechanisms linking micro- and macro-scale processes for selected pure, endmember fines. In conclusion, a specific application considered here is methane extraction via depressurization of gas hydrate-bearing sediment, which causes a dramatic pore-water salinity drop concurrent with sediment being compressed by the imposed effective stress increase.

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

Predictive multiscale modeling for Unidirectional Carbon Fiber Reinforced Polymers

This paper presents a predictive multiscale modeling scheme for Unidirectional (UD) Carbon Fiber Reinforced Polymers (CFRP). A bottom-up modeling procedure is discussed for predicting the performance of UD structures. UD material responses are computed from high fidelity Representative Volume Elements (RVEs). A data-driven Reduced Order Modeling approach compresses RVEs into Reduced Order Models so material responses can be computed in a concurrent fashion along with the structural level simulation. The approach presented in this paper is validated against experimental data and is believed to provide design guidance for future fiber reinforced polymers development.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Risk-Informed Safety Margins Characterization (RISMC) Pathway Technical Program Plan

Safety is central to the design, licensing, operation, and economics of nuclear power plants (NPPs). As the current Light Water Reactor (LWR) NPPs age beyond 60 years, there are possibilities for increased frequency of systems, structures, and components (SSCs) degradations or failures that initiate safety-significant events, reduce existing accident mitigation capabilities, or create new failure modes. Plant designers commonly “over-design” portions of NPPs and provide robustness in the form of redundant and diverse engineered safety features to ensure that, even in the case of well-beyond design basis scenarios, public health and safety will be protected with a very high degree of assurance. This form of defense-in-depth is a reasoned response to uncertainties and is often referred to generically as “safety margin.” Historically, specific safety margin provisions have been formulated, primarily based on “engineering judgment.” The ability to better characterize (i.e., describe and quantify) safety margin is important to improved decision making about LWR design and long-term operation. A systematic approach to characterizing safety margins and the subsequent risk informed margins management options represents a vital input to the licensee and regulatory analysis and decision making that will be involved. In addition, as research and development (R&D) in the LWRS Program and other collaborative efforts yield new data and improved scientific understanding of physical processes that govern the aging and degradation of plant SSCs (and concurrently support technological advances in nuclear reactor fuels and plant instrumentation and control systems), needs and opportunities to better optimize plant safety, economics, and performance will become known. The purpose of the Risk-Informed Safety Margins Characterization (RISMC) Pathway R&D is to support plant decisions for risk-informed margins management with the aim to improve economics, reliability, and sustain safety of current NPPs over periods of extended plant operations. The goals of the RISMC Pathway are twofold: (1) develop and demonstrate a risk-assessment method that is coupled to safety margin quantification that can be used by NPP decision makers as part of risk-informed margin management strategies; (2) create an advanced RISMC Toolkit that enables more accurate representation of NPP safety margins. The methods and tools provided by RISMC are essential to a comprehensive and integrated risk-informed margin management approach that supports effective preservation of margin for both active and passive SSCs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Fully Autonomous Multiplet Event Detection: Application to Local-Distance Monitoring of Blood Falls Seismicity

We apply a fully autonomous icequake detection methodology to a single day of high-sample rate (200 Hz) seismic network data recorded from the terminus of Taylor Glacier, ANT that temporally coincided with a brine release episode near Blood Falls (May 13, 2014). We demonstrate a statistically validated procedure to assemble waveforms triggered by icequakes into populations of clusters linked by intra-event waveform similarity. Our processing methodology implements a noise-adaptive power detector coupled with a complete-linkage clustering algorithm and noise-adaptive correlation detector. This detector-chain reveals a population of 20 multiplet sequences that includes ~150 icequakes and produces zero false alarms on the concurrent, diurnally variable noise. Our results are very promising for identifying changes in background seismicity associated with the presence or absence of brine release episodes. We thereby suggest that our methodology could be applied to longer time periods to establish a brine-release monitoring program for Blood Falls that is based on icequake detections.

42 ENGINEERING↗
DOE OSTI2017

Scalable domain decomposition solvers for stochastic PDEs in high performance computing

Stochastic spectral finite element models of practical engineering systems may involve solutions of linear systems or linearized systems for non-linear problems with billions of unknowns. For stochastic modeling, it is therefore essential to design robust, parallel and scalable algorithms that can efficiently utilize high-performance computing to tackle such large-scale systems. Domain decomposition based iterative solvers can handle such systems. And though these algorithms exhibit excellent scalabilities, significant algorithmic and implementational challenges exist to extend them to solve extreme-scale stochastic systems using emerging computing platforms. Intrusive polynomial chaos expansion based domain decomposition algorithms are extended here to concurrently handle high resolution in both spatial and stochastic domains using an in-house implementation. Sparse iterative solvers with efficient preconditioners are employed to solve the resulting global and subdomain level local systems through multi-level iterative solvers. We also use parallel sparse matrix–vector operations to reduce the floating-point operations and memory requirements. Numerical and parallel scalabilities of these algorithms are presented for the diffusion equation having spatially varying diffusion coefficient modeled by a non-Gaussian stochastic process. Scalability of the solvers with respect to the number of random variables is also investigated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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. To make advancements in all the aforementioned scientific areas, many technical aspects need to be more thoroughly studied and deeply understood in parallel discrete event simulation (PDES). The unique dynamics inherent in a discrete event modeling approach, by their very nature, intersect and influence the entire stack of the computing system, including (a) the unique nature of the instruction sets exercised in PDES workloads without a predominance of high-precision floating point operations, (b) virtual time-constrained multi-threaded execution of many logical processes per processor, (c) extremely variable and difficult to predict network traffic characteristics, (d) interfaces and inter-dependencies with machine learning and artificial intelligence codes at higher software layers, and (e) highly challenging load balancing needs, especially in effectively accounting for accelerated/extremely heterogeneous computing in current and future high-performance computing systems. Efficient and accurate parallel execution of PDES workloads is also dominated by challenges in dealing with their asynchronous concurrency fundamentally present at the model level. Conservative synchronization, optimistic/speculative synchronization, and their hybrid schemes open new questions in fundamental computer science with respect to reversibility of computation and prediction (lookahead) of behaviors inherent within model codes. On the implementation front, there are relatively few scalable, general-purpose parallel discrete event simulators in the world, and even fewer have been studied on emerging hardware platforms. To enable scientific advances using PDES, the research needs in computer science must also be pursued and met in the intersection of the algorithmic and hardware-aware aspects of scalable PDES engines. This report is aimed at capturing a computer science-oriented view of this important area of research in PDES, presenting a sample of important applications with their inherent discrete event technology elements. Needs are outlined in core areas of parallel discrete event research as well as cross-cutting directions in computer science research that positively impact scientific advancements across several important application areas. A selection of priority research opportunities in advanced computing for PDES is identified to serve as reference for key research topics and their order of importance for scientific advancements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

CILogon: A federated X.509 certification authority for cyberinfrastructure logon

SUMMARY CILogon provides a federated X.509 certification authority for secure access to cyberinfrastructure such as the Extreme Science and Engineering Discovery Environment. CILogon relies on federated authentication (Security Assertion Markup Language (OASIS, Burlington, MA (USA)) and OpenID) for determining user identities when issuing certificates. Federated authentication enables users to obtain certificates using existing identities (university, Google, etc.). Federated authentication also enables CILogon to serve a national‐scale user community without requiring a large network of registration authorities performing manual user identification. CILogon supports multiple levels of assurance and custom interfaces for specific user communities. In this article, we introduce the CILogon service and describe experiences and lessons learned from the first 3 years of operation. © 2014 The Authors. Concurrency and Computation: Practice and Experience published by John Wiley & Sons Ltd.

Basney, Jim↗
DOE OSTI2018

Modeling Mesoscale Processes of Scalable Synthesis Final Scientific/Technical Report

This is the final scientific and technical report for this award. Molecular dynamics (MD) is a powerful tool to study biomolecules at the nanoscale. One of its main limitations however is that such simulations typically require a timestep of 1 femtosecond while reactions and conformational changes typically happen on the time scale of 1 microsecond or more. This discrepancy severely restricts the impact of this method. We have developed a series of algorithms to mitigate this problem and allow predicting long-time scale events using much shorter simulations. The method is based on the concurrent adaptive sampling method. It consists in using probabilistic weights for trajectories and biasing the sampling such that rare but important trajectories, e.g., those that go over energy barriers and lead to relevant conformational changes in the molecule, are observed with much higher frequency that in a standard MD simulation. We will demonstrate below that this approach has been very successful. In collaboration with Jay Grate at PNNL we have applied this novel method to the study the triazine polymers, which can be con gured using different types of side chains in order to adopt different 3-dimensional structures. We have found novel stable con- formations and have analyzed the impact of side chain modifcations on the native folded shape of the polymer. Direct MD simulations would have been untractable for this problem. The method of replica exchange was also used successfully to calculate free energy profiles, in particular for cis-trans torsional angle changes with high energy barriers. Studying molecules at the atomistic scale is essential to design new molecules in chemical engineering, such as the triazine polymers developed by Grate, in material science to study the strength of metals for examples (e.g., dislocation dynamics), or in biochemistry to understand how proteins fold and how they interact with ligands (a key step in designing drugs). Although new hardware makes these simulations increasingly faster (e.g., GPU, Anton from DE Shaw Research), new algorithms are key to making these methods more tractable and increase their impact. At this point, because of limitations in modeling, one of the main techniques for advancing science remains to a large extent numerous and costly experiments. For exam- ple, when designing drug, where multiple variants must be screened, the ability to run tests on a computer rather than experimentally testing with high throughput methods thousands of compounds would represent a signi cant advance with broad benefits for the public at large.

36 MATERIALS SCIENCE↗