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Nanometer-Scale Correlations in Aqueous Salt Solutions
The intermediate-range (1–4 nm) correlation of cations, an- ions, and water in aqueous alkaline earth salt solutions is measured using synchrotron X-ray diffraction. We differentiate from the entire solution structure factor, S(Q), a separate region at low Q (<1 °A-1) containing local diffraction maxima (pre-peaks) that indicate nanometer-scale oscillatory behavior. These features are quantitatively reproduced with classical molecular dynamics simulations. At high concentrations, the pre-peaks emerge from correlations arising from existence of small quasi close-packed lattice- like structures comprised of cation hydration spheres. We also analyze the concentration dependence of the pre-peak and discuss the overall results in light of the rich literature dealing with intermediate-range correlations underlying universal phenomena in concentrated electrolytes. The authors were supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences. Pacific Northwest National Laboratory (PNNL) is operated by Battelle for the U.S. Department of Energy under Contract No. DE-AC05-76RL01830. Computing resources were generously allocated by PNNL's Institutional Computing program. DOE Contract No. DEAC02- 06CH11357 supports operation of the Advanced Photon Source at Argonne National Laboratory.
Statistical analysis of an inter-laboratory comparison of small-scale safety and thermal testing of RDX
In this study, the Integrated Data Collection Analysis (IDCA) program has conducted a proficiency test for small-scale safety and thermal (SSST) testing of homemade explosives (HMEs). Described here are statistical analyses of the results from this test for impact, friction, electrostatic discharge, and differential scanning calorimetry analysis of the RDX Class 5 Type II standard. The material was tested as a well-characterized standard several times during the proficiency test to assess differences among participants and the range of results that may arise for well-behaved explosive materials.
Deconvoluting XPS Spectra of La-Containing Perovskites from First-Principles
Perovskite-based oxides are used in electrochemical CO 2 and H 2 O reduction in electrochemical cells due to their compositional versatility, redox properties and stability. However limited knowledge exists on the mechanisms driving these processes. Toward this understanding, herein we probe the core level binding energy shifts of water-derived adspecies (H, O, OH, H 2 O) as well as the adsorption of CO 2 on LaCoO 3 and LaNiO 3 and we correlate the simulated peaks with experimental Temperature Programmed X-ray Photoelectron Spectroscopy (TPXPS) results. We find the strong adsorption of such chemical species can affect the antiferromagnetic ordering of LaNiO 3 . The adsorption of such adspecies is further quantified through Bader and differential charge analyses. We find the higher O 1s core level binding energy peak for both LaCoO 3 and LaNiO 3 corresponds to adsorption of water-related species and CO 2 , while the lower energy peak is due to lattice oxygen. We further correlate these DFT-based core level O 1s binding energies with the TPXPS measurements to quantify the decrease of the O 1s contribution due to desorption of adsorbates and the apparent increase of the lattice oxygen (both bulk and surface) with temperature. Finally, we quantify the influence of adsorbates on the La 4d, Co 2p and the Ni 3p core level binding energy shifts. This work demonstrates how theoretically generated XPS data can be utilized to predict species-specific binding energy shifts to assist in the deconvolution of the experimental results.
Convex relaxation for Fokker–Planck equation
We propose an approach to directly estimate the moments or marginals for a high-dimensional equilibrium distribution in statistical mechanics by solving the high-dimensional Fokker–Planck equation in terms of low-order cluster moments or marginals. With this approach, we bypass the exponential complexity of estimating the full high-dimensional distribution and directly solve the simplified partial differential equations for low-order moments/marginals. Moreover, the proposed moment/marginal relaxation is fully convex and can be solved via off-the-shelf solvers. We further propose a time-dependent version of the convex programs to study non-equilibrium dynamics. In a specific setting, we show the proposed method can recover a mean-field-type equilibrium density. Numerical results are provided to demonstrate the performance of the proposed algorithm for high-dimensional systems.
Genome-Scale Analysis of Programmed DNA Elimination Sites in Tetrahymena thermophila
Genetically programmed DNA rearrangements can regulate mRNA expression at an individual locus or, for some organisms, on a genome-wide scale. Ciliates rely on a remarkable process of whole-genome remodeling by DNA elimination to differentiate an expressed macronucleus (MAC) from a copy of the germline micronucleus (MIC) in each cycle of sexual reproduction. Here we describe results from the first highthroughput sequencing effort to investigate ciliate genome restructuring, comparing Sanger long-read sequences from a Tetrahymena thermophila MIC genome library to the MAC genome assembly. With almost 25% coverage of the unique-sequence MAC genome by MIC genome sequence reads, we created a resource for positional analysis of MIC-specific DNA removal that pinpoints MAC genome sites of DNA elimination at nucleotide resolution. The widespread distribution of internal eliminated sequences (IES) in promoter regions and introns suggests that MAC genome restructuring is essential not only for what it removes (for example, active transposons) but also for what it creates (for example, splicing-competent introns). Consistent with the heterogeneous boundaries and epigenetically modulated efficiency of individual IES deletions studied to date, we find that IES sites are dramatically under-represented in the 25% of the MAC genome encoding exons. As an exception to this general rule, we discovered a previously unknown class of small (,500 bp) IES with precise elimination boundaries that can contribute the 39 exon of an mRNA expressed during genome restructuring, providing a new mechanism for expanding mRNA complexity in a developmentally regulated manner.
A Comparison of Genetic Programming Variants for Hyper-Heuristics
Modern society is faced with ever more complex problems, many of which can be formulated as generate-and-test optimization problems. General-purpose optimization algorithms are not well suited for real-world scenarios where many instances of the same problem class need to be repeatedly and efficiently solved, such as routing vehicles over highways with constantly changing traffic flows, because they are not targeted to a particular scenario. Hyper-heuristics automate the design of algorithms to create a custom algorithm for a particular scenario. Hyper-heuristics typically employ Genetic Programming (GP) and this project has investigated the relationship between the choice of GP and performance in Hyper-heuristics. Results are presented demonstrating the existence of problems for which there is a statistically significant performance differential between the use of different types of GP.
Nevada National Security Site Site-Directed Research and Development Report (FY 2018 Annual Report)
This report compiles multiple articles describing activities developed and performed under the Site-Directed Research and Development Program for the benefit the Nation during Fiscal Year 2018. Sustained investment and ongoing core innovation are the keys to successful research and development programs. These elements drive the Site-Directed Research and Development (SDRD) Program and provide solutions to some of the most challenging problems our nation and our allies face. Our Nevada enterprise, consisting of both our management and operating entity and our NNSA field office, is aggressively investing in SDRD and injecting innovation through strategic partnerships. Our partnerships with universities, industry, and our sister institutions within the National Nuclear Security Administration (NNSA) build upon our core capabilities and allow us to create innovative solutions to support our mission requirements. In 2018, we raised the investment level of SDRD for only the second time in the history of the program. Nearly at our congressionally authorized limit, SDRD has substantial resources to successfully address numerous issues. Investment is only one part of the equation; innovation is generated through collaborations that bring discovery and provide the “technical differentiation” and the return on investment we seek. This report demonstrates an enduring theme of how partnerships help us drive the best outcomes and provide the maximum impact possible, while using our resources efficiently.
New high statistics results from the MINERvA experiment Medium Energy run
The MINERvA experiment has completed its physics run using the 6 GeV, on-axis NuMI ME beam at Fermilab. The experiment received a total of 12 x 10^20 protons on target in both neutrino and antineutrino mode running. This allows MINERvA a new level of statistics in neutrino interaction measurements with the ability to measure multi-dimensional differential cross sections. In addition, in order to make the most of this jump in statistics, a new level of precision in fluxprediction has been achieved. We present results from MINERvA's Medium Energy (ME) physics program, including the new kinematic regimes that are now accessible.
Quench Detection for High-Temperature Superconductor Conductors Using Acoustic Thermometry
Detecting local heat-dissipating zones in high-temperature superconductor (HTS) magnets is a challenging task due to slow propagation of such zones in HTS conductors. For long conductor lengths, voltage-based methods may not provide a sufficient sensitivity or redundancy, and therefore nonvoltage-based detection alternatives are being sought. One of those is the recently proposed method of Eigen Frequency Thermometry (EFT), which is an active acoustic technique for a fast and nonintrusive detection of 'hot spots,' utilizing temperature dependence of the conductor elastic moduli. In this work, we demonstrate the efficiency of EFT for detecting localized heating in a 1.2-m-long sample of REBCO tape immersed in liquid nitrogen, and benchmark sensitivity of the acoustic detection with respect to voltage, hot spot temperature, and power dissipation in the conductor. Modifying the original technique for differential mode of operation enables a much improved sensitivity, and adds a hot spot localization capability. Furthermore, we adapt this technique to subscale coils wound with REBCO CORC conductor built in the framework of U.S. Magnet Development Program. A successful thermal-based detection of dissipation onset at the critical current for a two-layer canted CORC dipole assembly is discussed.
A Two-Stage Decomposition Approach for AC Optimal Power Flow
The alternating current optimal power flow (AC-OPF) problem is critical to power system operations and planning, but it is generally hard to solve due to its nonconvex and large-scale nature. Furthermore, this paper proposes a scalable decomposition approach in which the power network is decomposed into a master network and a number of subnetworks, where each network has its own AC-OPF subproblem. This formulates a two-stage optimization problem and requires only a small amount of communication between the master and subnetworks. The key contribution is a smoothing technique that renders the response of a subnetwork differentiable with respect to the input from the master problem, utilizing properties of the barrier problem formulation that naturally arises when subproblems are solved by a primal-dual interior-point algorithm. Consequently, existing efficient nonlinear programming solvers can be used for both the master problem and the subproblems. The advantage of this framework is that speedup can be obtained by processing the subnetworks in parallel, and it has convergence guarantees under reasonable assumptions. The formulation is readily extended to instances with stochastic subnetwork loads. Numerical results show favorable performance and illustrate the scalability of the algorithm which is able to solve instances with more than 11 million buses.
Brg1 modulates enhancer activation in mesoderm lineage commitment
The interplay between different levels of gene regulation in modulating developmental transcriptional programs, such as histone modifications and chromatin remodeling, is not well understood. Here, we show that the chromatin remodeling factor Brg1 is required for enhancer activation in mesoderm induction. In an embryonic stem cell-based directed differentiation assay, the absence of Brg1 results in a failure of cardiomyocyte differentiation and broad deregulation of lineage-specific gene expression during mesoderm induction. We find that Brg1 co-localizes with H3K27ac at distal enhancers and is required for robust H3K27 acetylation at distal enhancers that are activated during mesoderm induction. Brg1 is also required to maintain Polycomb-mediated repression of non-mesodermal developmental regulators, suggesting cooperativity between Brg1 and Polycomb complexes. Thus, Brg1 is essential for modulating active and repressive chromatin states during mesoderm lineage commitment, in particular the activation of developmentally important enhancers. In conclusion, these findings demonstrate interplay between chromatin remodeling complexes and histone modifications that, together, ensure robust and broad gene regulation during crucial lineage commitment decisions.
Scalability of Partial Differential Equations Preconditioner Resilient to Soft and Hard Faults [Poster]
Explore scalability of a resilient task-based domain decomposition preconditioner for elliptic PDEs. Selective reliability to study the impact of different levels of simulated SDC and hard faults. Explore interplay between the application resilience, and the role of the server-client programming model.
Quantum Computing Strategy 2026
Quantum computing (QC) is a rapidly maturing technology with the potential for revolutionary impacts on stockpile stewardship science and national security. Recent developments in fault-tolerant architectures have compressed vendor roadmaps, and predictions of a production-ready quantum computer by the mid-2030s are becoming increasingly credible. This strategy provides a roadmap for integrating QC into the Advanced Simulation and Computing (ASC) program by investing in four strategic focus areas: 1. Develop Capabilities in Mission-Relevant Quantum Applications: ASC will prioritize developing quantum-ready applications in mission areas that have shown significant promise for quantum advantage, including simulations of materials in extreme environments, nuclear dynamics, solving linear and nonlinear partial differential equations, and uncertainty quantification. These applications directly support stockpile stewardship science and modernization objectives. 2. Conduct R&D in Algorithms, Software, and Hardware: Sustained research into quantum algorithms, robust software tools, and quantum hardware is essential. ASC will develop efficient quantum algorithms; invest in quantum compilers, debuggers, and performance tools; and explore specialized quantum hardware tailored to NNSA’s unique requirements. 3. Engage with Vendors and Partners: Early and active collaboration with commercial quantum hardware vendors and academic partners is critical. Through testbeds, co-design agreements, and quantum demonstration facilities, ASC will influence hardware design, gain early access to emerging technologies, and ensure that quantum platforms evolve to meet mission needs. 4. Build Knowledge, Experience, and Workforce: Expanding and upskilling the quantum-trained workforce is essential to long-term success. This includes hiring, internal training, university outreach, and postdoctoral support to ensure ASC maintains the expertise required to operate, program, and integrate quantum systems as they become available. While quantum computing will never replace classical computing, it has the potential to solve certain problems with speed and accuracy that would be unachievable using any conceivable classical high-performance computing (HPC) system. By investing strategically in QC, ASC will help propel the emergent QC industry, maintain U.S. technological leadership, ensure mission readiness, and position itself to rapidly adopt quantum technologies as they mature.
Impact of Higher Fidelity Design Iterations on Critical System Criteria
Nuclear criticality experiments are effective at informing the performance of nuclear data libraries across many applications. This work explores the implications of refining critical experiment MCNP models from their low fidelity optimization phase to penultimate neutronic models. Specifically, this work is focused on two series of plutonium fueled experiments funded through internal programs at Los Alamos National Laboratory building off previous efforts under the EUCLID (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) collaboration. Thales, the first of the two collaborations, is a fast spectrum Ta-reflected plutonium experiment to support operations at PF-4. The second experiment are twin configurations designed to target the intermediate energy cross sections in 239 Pu. Motivation for this experiment stems from the PARallel Approach of Differential and InteGral Measurements (PARADIGM) collaboration which hopes to achieve a significant reduction in 239 Pu cross section uncertainties in the intermediate region.
Pyomo.DOE: An open-source package for model-based design of experiments in Python
Predictive mathematical models are a cornerstone of science and engineering. Yet selecting, calibrating, and validating said science-based models often remains an art in practice. Model-based design of experiments (MBDoE) provides a systematic framework to maximize information gain from experiments while minimizing time and resource costs. But MBDoE remains limited to niche application areas, in part because practitioners must integrate expertise in statistics, computational optimization, and modeling. To help reduce this barrier, we introduce Pyomo.DOE, an open-source package for MBDoE. Pyomo.DOE uses a nonlinear sensitivity analysis code k_aug to quickly approximate the Fisher information matrix and leverages a new stochastic programming abstraction. We demonstrate Pyomo.DOE with the first application of MBDoE to fixed-bed breakthrough experiments, which highlights the power of Pyomo.DOE to quantify the value of experimental modifications a priori for large-scale partial differential-algebraic equation (PDAE) models. Here we also provide a mathematical primer on MBDoE targeted at general chemical engineers.
A scalable design of experiments framework for optimal sensor placement
Here, we present a scalable design of an experiments framework for sensor placement in systems described by partial differential equations (PDEs). In particular, we aim to compute optimal sensor locations by minimizing the uncertainty of parameters estimated from Bayesian inverse problems and where the system. The resulting problem is a computationally intractable mixed-integer nonlinear program constrained by PDEs. We approach this problem with two heuristics used in compressed sensing and optimal control literature: a sparsity-inducing approach and a sum-up rounding approach. We also investigate metrics to guide the design of experiments (the total flow variance and the A-optimal design criterion) and analyze the effect of different noise structures (white and colored). Using an application in natural gas pipelines, we conclude that the sum-up rounding approach approach gives the best results and produces shrinking gaps with increasing mesh resolution. We also observe that convergence for the white noise measurement error case is slower than for the colored noise case. For A-optimal design, the solution is close to a uniform distribution of sensors along the pipeline while for the flow variance design the distribution is unstructured.
Precision Studies of Hadronic and Electro-Weak Interactions for Collider Physics (Final Report)
This project was directed toward developing precision computational tools for proton collisions at the Large Hadron Collider, focusing primarily on electroweak boson production and electroweak radiative corrections. The programs developed under this project carried the name HERWIRI, for High Energy Radiation With Infra-Red Improvements, and are the first steps in an ongoing program to develop a set of hadronic event generators based on combined QCD and QED exponentiation. HERWIRI1 applied these improvements to the hadronic shower, while HERWIRI2 will apply the electroweak corrections from the program KKMC developed for electron-positron scattering to a hadronic event generator, including exponentiated initial and final state radiation together with first-order electroweak corrections to the hard process. Some progress was also made on developing differential reduction techniques for hypergeometric functions, for application to the computation of Feynman diagrams.