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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Diagnosis of the Marine Low Cloud Simulation in the NCAR Community Earth System Model (CESM) and the NCEP Global Forecast System (GFS)-Modular Ocean Model v4 (MOM4) coupled model

We present a diagnostic analysis of the marine low cloud climatology simulated by two state-of-the-art coupled atmosphere-ocean models: the NCAR Community Earth System Model (CESM) and the NCEP Global Forecasting System (GFS). In both models, the shallow convection and boundary layer turbulence parameterizations have been recently updated: both models now use a mass-flux scheme for the parameterization of shallow convection, and a turbulence parameterization capable of handling Stratocumulus (Sc)-topped Planetary Boundary Layers (PBLs). For shallow convection, both models employ a convective trigger function based on the concept of convective inhibition and both include explicit convective overshooting/penetrative entrainment formulation. For Sc-topped PBL, both models treat explicitly turbulence mixing and cloud-top entrainment driven by cloud-top radiative cooling. Our focus is on the climatological transition from Sc to shallow Cumulus (Cu)-topped PBL in the subtropical eastern oceans. We show that in the CESM the coastal Sc-topped PBLs in the subtropical Eastern Pacific are well-simulated but the climatological transition from Sc to shallow Cu is too abrupt and happens too close to the coast. By contrast, in the GFS coupled simulation the coastal Sc amount and PBL depth are severely underestimated while the transition from Sc to shallow Cu is ³delayed² and offshore Sc cover is too extensive in the subtropical Eastern Pacific. We discuss the possible connections between such differences in the simulations and differences in the parameterizations of shallow convection and boundary layer turbulence in the two models.

Xiao, Heng↗
DOE OSTI2021

BETO 2021 Peer Review - WBS 4.1.2.32: Bioeconomy Scenario Analysis

The Bioeconomy Scenario Analysis project uses systems thinking and analysis to assess current and/or prospective techno-economics, research and development, deployment strategies, policy, and market conditions and their impact on the potential development trajectories of the bioenergy industry over time. Results from this project include identification of opportunities and constraints to industrial development, quantification of multiple metrics (energy, economic, environmental) and informing researchers, decision makers, and industry of the steps needed for a sustainable, nationwide biofuels industry. Analyses from this project enable the creation of a bioenergy industry by (1) inciting policy-makers to explore scenarios for nationwide biofuels production, identifying policy actions consistent with pathways for growth; (2) improving industry’s understanding of industry growth potential under different technology and investment conditions, better targeting their development efforts; and (3) providing universities and other interested stakeholders with tools and analyses that can be adapted to meet research and teaching objectives, connecting students with careers that build the industry. One of the many modeling tools used in this project, the Biomass Scenario Model (BSM) is a publicly-available, unique, validated, state-of-the-art, award-winning, fourth-generation model of the domestic biofuels supply chain which explicitly focuses on how and under what conditions biofuel technologies might be deployed to contribute to the U.S. transportation energy sector. We use models like the BSM to examine the implications of policies and incentives as well as their potential side-effects. The BSM uses a system-dynamics simulation to model dynamic interactions and transitions across the supply chain; it tracks the deployment of biofuels given industrial learning and the reaction of the investment community in the context of land availability, projected oil markets, consumer demand for biofuels, and government policies over time. Under expected market conditions, analyses using the BSM suggest that the biofuels industry may require significant external actions in the early years to thrive. Interventions that accelerate the industrial learning process (e.g. operation of pre-commercial and commercial facilities) have been identified as having strong influence in starting the growth of a commercial biofuel industry. Policies which are coordinated across the whole supply chain in BSM foster the growth of the biofuels industry and production of tens of billions of gallons of biofuels may occur under sufficiently favorable conditions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

DRIPS: A framework for dimension reduction and interpolation in parameter space

Reduced-order models are often used to describe the behavior of complex systems, whose simulation with a full model is too expensive, or to extract salient features from the full model’s output. We introduce a new model-reduction framework DRIPS (dimension reduction and interpolation in parameter space) that combines the offline local model reduction with the online parameter interpolation of reduced-order bases (ROBs). The offline step of this framework relies on dynamic mode decomposition (DMD) to build a low-rank linear surrogate model, equipped with a local ROB, for quantities of interest derived from the training data generated by repeatedly solving the (nonlinear) high-fidelity model for multiple parameter points. The online step consists of the construction of a parametric reduced-order model for each target/test point in the parameter space, with the interpolation of ROBs done on a Grassman manifold and the interpolation of reduced-order operators done on a matrix manifold. The DMD component enables DRIPS to model (typically low-dimensional) quantities of interest directly, without having to access the (typically high-dimensional and possibly nonlinear) operators in a high-fidelity model that governs the dynamics of the underlying high-dimensional state variables, as required in projection-based reduced-order modeling. A series of numerical experiments suggests that DRIPS yields a model reduction, which is computationally more efficient than the commonly used projection-based proper orthogonal decomposition; it does so without requiring a prior knowledge of the governing equation for quantities of interest. Furthermore, for the nonlinear systems considered, DRIPS is more accurate than Gaussian-process interpolation (Kriging).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Quasi-Static Time-Series PV Hosting Capacity Methodology and Metrics

Distributed photovoltaic systems (DPV) can cause adverse grid impacts, including voltage or thermal violations. The installed capacity at which violations first occur and above which would require system upgrades is called the hosting capacity. Current methods for determining hosting capacity tend to be conservative by either only considering infrequent worst-case snapshots in time and/or only capturing coarse time and spatial resolution. Additionally, current hosting capacity methods do not accurately capture the time-dependence making them unable to capture the behavior of voltage regulating equipment and of some advanced controls mitigations. This can trigger delays from unnecessary engineering analysis or deter solar installations in areas that are actually suitable. We propose a quasi-static-time-series (QSTS) based PV hosting capacity methodology to address these issues. With this approach, we conduct power flow analysis over the course of a full year, to capture time-varying parameters and control device actions explicitly. We show that this approach can more fully capture grid impacts of DPV than traditional methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Quasi-Static Times Series PV Hosting Capacity Methodology and Metrics: Preprint

Distributed photovoltaic systems (DPV) can cause adverse grid impacts, including voltage or thermal violations. The installed capacity at which violations first occur and above which would require system upgrades is called the hosting capacity. Current methods for determining hosting capacity tend to be conservative by either only considering infrequent worst-case snapshots in time and/or only capturing coarse time and spatial resolution. Additionally, current hosting capacity methods do not accurately capture the time-dependence making them unable to capture the behavior of voltage regulating equipment and of some advanced controls mitigations. This can trigger delays from unnecessary engineering analysis or deter solar installations in areas that are actually suitable. We propose a quasi-static-timeseries (QSTS) based PV hosting capacity methodology to address these issues. With this approach, we conduct power flow analysis over the course of a full year, to capture time-varying parameters and control device actions explicitly. We show that this approach can more fully capture grid impacts of DPV than traditional methods.

14 SOLAR ENERGY↗
DOE OSTI2016

Double and triple-harmonic RF buckets and their use for bunch squeezing in AGS

For the past several years we have merged bunches in AGS in order to achieve the desired intensity per bunch prior to injection into RHIC. The merging is done on a flat porch at or above AGS injection energy. Because the merges involve the reduction of the RF harmonic number by a factor of 2 (for a 2 to 1 merge) and then a factor of 3 (for a 3 to 1 merge), one requires RF frequencies 6hf s , 3hf s , 2hf s and hf s , where f s is the revolution frequency on the porch and h = 4 is the fundamental harmonic number. The standard AGS RF cavities cannot operate at the lowest frequencies 2hf s and hf s ; these are provided by two modified cavities. Upon completion of the merges, the bunches are sitting in harmonic h buckets. In order to be accelerated they need to be squeezed into harmonic 3h buckets. This is accomplished by producing a double-harmonic bucket in which harmonics h and 2h act in concert, and then a triple-harmonic bucket in which harmonics h, 2h, and 3h act in concert. Simulations have shown that the squeeze presents an acceptance bottleneck which limits the longitudinal emittance that can be put into the harmonic 3h bucket. In this note the areas of the double and triple-harmonic buckets are calculated explicitly, and it is shown that these go through a minimum as the RF voltages are raised to the desired values. Several RF voltage ranges are examined, and the acceptance bottleneck is determined for each of these. Finally, the acceptance bottleneck for Au77+ bunches in AGS is calculated for several RF voltage ranges. The main result is that the RF voltages for the low-frequency harmonic h and 2h cavities both must be at least 22 kV in order to achieve an acceptance of 0:6 eV s per nucleon. If the harmonic h and 2h voltages are 15 and 22 kV, respectively, then the acceptance is reduced to 0:548 eV s per nucleon.

43 PARTICLE ACCELERATORS↗
DOE OSTI2015

Biomass Scenario Model: BETO Analysis Platform Peer Review; NREL (National Renewable Energy Laboratory)

The Biomass Scenario Model (BSM) is a unique, carefully validated, state-of-the-art fourth-generation model of the domestic bioenergy supply chain which explicitly focuses on policy issues and their potential side effects. It integrates resource availability, behavior, policy, and physical, technological, and economic constraints. The BSM uses system-dynamics simulation to model dynamic interactions across the supply chain; it tracks the deployment of biofuels given technological development and the reaction of the investment community to those technologies in the context of land availability, the competing oil market, consumer demand for biofuels, and government policies over time. It places a strong emphasis on the behavior and decision-making of various economic agents. The model treats the major infrastructure-compatible fuels. Scenario analysis based on the BSM shows that the biofuels industry tends not to rapidly thrive without significant external actions in the early years of its evolution. An initial focus for jumpstarting the industry typically has strongest results in the BSM in areas where effects of intervention have been identified to be multiplicative. In general, we find that policies which are coordinated across the whole supply chain have significant impact in fostering the growth of the biofuels industry and that the production of tens of billions of gallons of biofuels may occur under sufficiently favorable conditions.

09 BIOMASS FUELS↗
DOE OSTI2015

Condition‐based exciter model complexity reduction for improved transient stability simulation

A reduced model approach to decrease computational complexity in power system transient stability simulation is presented. This study investigates conditions that make fast modes active or inactive using practical power system examples. Modes in the original system where fast dynamics do not appear can be neglected, allowing simulation steps to be increased without numerical stability issues. During a transient simulation, the proposed method switches dynamically between the original exciter model and the reduced one, depending on the switching criterion presented. A high level of accuracy is achieved and computational efficiency is increased. Case studies with the Western Electricity Coordinating Council system are provided to validate the performance of the proposed method.

Kim, Soobae↗
DOE OSTI2013

Thermal transpiration through single walled carbon nanotubes and graphene channels

Thermal transpiration through carbon nanotubes (CNTs) and graphene channels is studied using molecular dynamics (MD) simulations. The system consists of two reservoirs connected by a CNT. It is observed that a flow is developed inside the CNT from the low temperature reservoir to the high temperature reservoir when the two reservoirs are maintained at different temperatures. The influence of channel size and temperature gradient on the mean velocity is analysed by varying the CNT diameter and the temperature of one of the reservoirs. Larger flow rate is observed in the smaller diameter CNTs showing an increase in the mean velocity with increase in the temperature gradient. For the flow developed inside the CNTs, slip boundaries occur and the slip length is calculated using the velocity profile. We examine the effect of fluid-wall interaction strength (ε{sub fw}), diffusivity (D), and viscosity of the fluid (μ) on the temperature induced fluid transport through the CNTs. Similar investigations are also carried out by replacing the CNT with a graphene channel. Results show that the mean velocity of the fluid atoms in the graphene channel is lower than that through the CNTs. This can be attributed to the higher degree of confinement observed in the CNTs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Demonstration of RELAP5-3D for transient analysis of a dual coolant lead lithium fusion blanket concept

Our research aims to build a multiphysics framework for transient analysis of the Dual- Coolant Lead-Lithium (DCLL) blanket design of the proposed Fusion Nuclear Science Facility (FNSF) for all Onticipated Operational Occurrences (AOOs) using Reduced Order Models (ROMs). This paper presents an assessment of using RELAP5-3D for transient thermal-hydraulic blanket analysis of the DCLL design. Preliminary validation studies for the RELAP5-3D properties were conducted using a representative vertical flow loop model and a comparison study using experimental data from the thermal convection corrosion loops at ORNL. These studies inspected the thermal hydraulic response of Lead-Lithium Eutectic (PbLi) systems within the RELAP5-3D code; mainly pressure drop and heat transfer, as compared to analytical calculations and experimental data. The Magnetohydrodynamic (MHD) pressure drop effect for liquid metal under the effects of a uniform magnetic field was implemented into our models using an equivalent forms loss coefficient based on the phasic momentum equations. We verified our implementation of MHD pressure drop within RELAP5-3D using a systematic approach consisting of two studies. Models were developed to perform comparison studies based on experimental data from the Argonne Liquid metal EXperiment (ALEX) facility and the Magnetohydrodynamic PbLi Experiment (MaPLE) facility. Using the developed validation basis, we built a simplified DCLL channel model within RELAP5-3D, inspected MHD pressure drop and performed transient temperature analysis. The DCLL channel model used radial heating data from the International Thermonuclear Experimental Reactor (ITER) which was normalized to the FNSF design. Here, a representative startup transient was performed using a relative power curve from the initial ramp up of a long-term power pulse of the Tore Supra reactor. This study demonstrated that RELAP5-3D ROMs are capable of accurate transient analysis of the DCLL blanket. We have since utilized MCNP to develop heating profiles based on the FNSF design and are working toward implementing them into our DCLL model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Phase-field simulation of domain size effect on dielectric and piezoelectric responses in K 0.5 Na 0.5 NbO 3 epitaxial thin films with superdomain structures

Size effects of mesoscale ferroelectric domains on the macroscopic dielectric and piezoelectric responses in domain-engineered bulk piezocrystals have been extensively studied for more than two decades. However, less is known about the domain size effects in ferroelectric epitaxial thin films, especially for films consisting of low-symmetry ferroelectric phases and exhibits hierarchical superdomain structures. Herein, using phase-field simulations, we systemically evaluate the effective out-of-plane dielectric and piezoelectric coefficients, κ$^{*}_{33}$ and d$^{*}_{33}$, as a function of the domain periods for two types of superdomain structures in ferroelectric K 0.5 Na 0.5 NbO 3 epitaxial thin films. In one type of the superdomain structures, we find that more than 70% increase of κ$^{*}_{33}$ and nearly 20% increase of d$^{*}_{33}$ can be achieved by tuning the domain period by a few tens of nanometers. Dissimilar behaviors are found when the domain period varies along different lateral directions, suggesting anisotropic domain size effects in thin films. By analyzing the local dielectric and piezoelectric responses from each domain variants and domain walls, we reveal that the domain size effect is governed by the variation of out-of-plane polarization inside the domains. Moreover, we also demonstrate enhanced domain size effects by modulating the misfit strains and temperature to approach the polymorphic phase boundaries, suggesting tunability of the size effect by doping and strain engineering. Furthermore, our results reveal multimodal domain size dependence of dielectric and piezoelectric responses in low-symmetry ferroelectric epitaxial thin films, implying that domain size engineering can be used to tune macroscopic properties of thin-film ferroelectrics, similar to their bulk counterparts.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Port of New York and New Jersey Drayage Electrification Analysis

The National Renewable Energy Laboratory (NREL) evaluated the potential for drayage electrification in the Port of New York and New Jersey (PoNYNJ), with a focus on operators: Harbor Freight Transport (HF), Safeway Trucking (SWT), and International Motor Freight Inc (IMF). This report summarizes the data collection and electrification evaluation of all three drayage operators, includes detailed operational data, and identifies the performance requirements for battery electric tractors (BETs) and corresponding infrastructure operated within the context of PoNYNJ drayage operation. This report also details a methodology to evaluate opportunities, strategies, and challenges associated with future expansions of BETs in meeting PANYNJ emissions goals. The Port Authority has established a goal of achieving Net Zero carbon emissions by 2050 across all facilities, including from tenant and stakeholder sources such as drayage trucks. NREL used real-world performance data collected on the three PoNYNJ drayage operations, along with modeling and analysis tools to compare BET to diesel trucks. From March to July 2021, NREL collected 1Hz vehicle and engine data from 46 drayage trucks at the three operators totaling nearly 121,000 miles of operation, providing enough information to assess vehicle operations for electrification potential. A Future Automotive Systems Technology Simulator (FASTSim) electric truck powertrain model was validated using PoNYNJ data and scenarios were run to evaluate drayage truck electrification requirements over the real-world cycles. The first scenario examined BET viability with minimal changes to existing operations. This assumes the trucks charge when stopped for two hours or longer, have a functional battery size of 375 kWh, and can charge at 270 kilowatts (kW) average which are the specification of the commercially available Freightliner eCascadia. The second scenario looked at what operational, charging infrastructure, and BET technology changes would be needed to fully electrify. Finally, detailed analysis was run on charging rate structure to understand operational costs to the fleets. The studied drayage trucks averaged 5.1 MPG, spent roughly 9% of their energy at idle, and drove an average of 140 miles per day with a maximum daily distance of 573 miles. The FASTSim model results indicate a comparable BET would use 417 kWh of energy per day on average accounting for cargo weight, which is close to the full usable capacity of the eCascadia currently available on the market. Based on the daily average operating data, partial fleet electrification is possible with current technology. However, some specific days of operation would require over 1,600 kWh of energy due to longer distances traveled by the trucks and more intense operation. Trucks used for long distance and intense operation cannot be readily electrified with current technology without operational changes. Full adoption of BETs could reduce CO 2 emissions from these fleets by roughly 75% today, eliminating 76 metric tons of CO 2 (MTCO 2 ) per vehicle each year, which equates to 24,100 MTCO 2 per year for all three operators. Commercially available direct current fast chargers (DCFC) have charge rates up to 350 kW. Based on the average daily modeled energy use for each operator, current industrial rate structures, and the assumption of 350 kW peak charging, full drayage electrification would increase electricity consumption. In addition, peak demand usage would increase with unmanaged charging along with cost of electricity having a direct impact on cost per mile for electric vehicles. The resulting cost per mile for BETs along with comparable cost per mile for conventional diesel trucks are also examined at $\$$4.00 per gallon of diesel. It will be important for PANYNJ and the drayage operators within the PoNYNJ to consider these load impacts to their existing electrical infrastructure and devise operational strategies that avoid coincident charging of vehicles to mitigate demand charges. Despite these electricity cost increases, savings from reductions in diesel consumption will help offset the costs of this increased electricity consumption. However, prices of both electricity and diesel are subject to change based on various factors meaning the realized savings will vary over time. This shows BETs could be cost-competitive on an energy cost per mile basis for all scenarios while diesel is above $\$$3.00/gal. Further, if diesel prices dropped to the 15-year low of $2.33/gal, it would still be cost competitive to operate the EVs with electricity costs of 16.3 ¢/kWh or less.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

R-Adaptivity to Enable Compression of Elementary Computations in Extreme-Scale Finite Element Simulators

Modern computing systems are capable of exascale calculations, which are revolutionizing the development and application of high-fidelity numerical models in computational science and engineering. While these systems continue to grow in processing power, the available system memory has not increased commensurately, and electrical power consumption continues to grow. A predominant approach to limit the memory usage in large-scale applications is to exploit the abundant processing power and continually recompute many low-level simulation quantities, rather than storing them. However, this approach can adversely impact the throughput of the simulation and diminish the benefits of modern computing architectures. We present three novel contributions to reduce the memory burden while maintaining, and sometimes improving, performance in simulations based on finite element discretizations. The first contribution develops dictionary-based data compression schemes that detect and exploit the structure of the discretization, due to redundancies across the finite element mesh. While these schemes are shown to reduce memory requirements by more than 99% on meshes with large numbers of identical mesh cells, there are applications where this structure does not exist. The second contribution leverages a recently developed augmented Lagrangian optimization algorithm to enable r-adaptivity for meshes with the goal of enhancing the redundancies in the mesh. The third contribution extends these methods to patch-based linear solvers and preconditioners by compressing local matrices. Numerical results demonstrate the effectiveness of the proposed methods to detect, enhance and exploit mesh structure on a suite of examples inspired by large-scale applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Dynamic Characteristic Identification

This paper introduces a dynamic system parameter extraction using experimental data and a known characteristic equation for a single degree of freedom system. The efficacy of curve fitting to determine mass, damping, and stiffness for simulated underdamped, critically damped, and overdamped systems is explored. Two methods are explored to obtain these characteristics using a step response approach in the time domain or a transfer function and dynamic stiffness approach in the frequency domain for simulated systems. Commonly available software, MATLAB, is used for curve fitting. An examination of the effect of inaccurate seeds, or starting values, for mass, damping, and stiffness is included.

Jordan, Clay↗
DOE OSTI2022

Simulation-based assessment on stochastic load scheduling for building cooling systems

Here, to fill knowledge gaps related to stochastic load scheduling, we performed a comprehensive evaluation of the stochastic load scheduling for building cooling systems. Specifically, we studied the common uncertain variables in the load scheduling process for building cooling systems and categorized those variables based on their dynamic patterns. We then developed a generic stochastic load scheduling framework and applied it to building cooling systems that served a simulated community. This community consists of 100 heterogeneous houses and serves as a virtual testbed for evaluating the performance of stochastic load scheduling. In this evaluation, we considered representatives of uncertain variables with different dynamic patterns and included 100 realizations of the considered uncertainty in the evaluation to better catch the probability distribution of the control performance. The evaluation results suggest that deterministic load scheduling can reduce the operating energy cost by 18% but its performance can be affected by uncertainty. Stochastic load scheduling can further decrease the operating energy cost under uncertainty compared to deterministic load scheduling. We also found that the effectiveness of stochastic load scheduling in handling uncertainty is not directly associated with the number of uncertainty scenarios that are considered in its formulation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Benchmarking highly entangled states on a 60-atom analogue quantum simulator

Abstract Quantum systems have entered a competitive regime in which classical computers must make approximations to represent highly entangled quantum states 1,2 . However, in this beyond-classically-exact regime, fidelity comparisons between quantum and classical systems have so far been limited to digital quantum devices 2–5 , and it remains unsolved how to estimate the actual entanglement content of experiments 6 . Here, we perform fidelity benchmarking and mixed-state entanglement estimation with a 60-atom analogue Rydberg quantum simulator, reaching a high-entanglement entropy regime in which exact classical simulation becomes impractical. Our benchmarking protocol involves extrapolation from comparisons against an approximate classical algorithm, introduced here, with varying entanglement limits. We then develop and demonstrate an estimator of the experimental mixed-state entanglement 6 , finding our experiment is competitive with state-of-the-art digital quantum devices performing random circuit evolution 2–5 . Finally, we compare the experimental fidelity against that achieved by various approximate classical algorithms, and find that only the algorithm we introduce is able to keep pace with the experiment on the classical hardware we use. Our results enable a new model for evaluating the ability of both analogue and digital quantum devices to generate entanglement in the beyond-classically-exact regime, and highlight the evolving divide between quantum and classical systems.

Science & Technology - Other Topics↗
DOE OSTI2022

Trotter Errors from Dynamical Structural Instabilities of Floquet Maps in Quantum Simulation

We study the behavior of errors in the quantum simulation of spin systems with long-range multibody interactions resulting from the Trotter-Suzuki decomposition of the time-evolution operator. We identify a regime where the Floquet operator underlying the Trotter decomposition undergoes sharp changes even for small variations in the simulation step size. This results in a time evolution operator that is very different from the dynamics generated by the targeted Hamiltonian, which leads to a proliferation of errors in the quantum simulation. These regions of sharp change in the Floquet operator, referred to as structural instability regions, appear typically at intermediate Trotter step sizes and in the weakly interacting regime, and are thus complementary to recently revealed quantum chaotic regimes of the Trotterized evolution [L. M. Sieberer et al. npj Quantum Inf. 5, 78 (2019); M. Heyl, P. Hauke, and P. Zoller, Sci. Adv. 5, eaau8342 (2019)]. We characterize these structural instability regimes in p-spin models, transverse-field Ising models with all-to-all p-body interactions, and analytically predict their occurrence based on unitary perturbation theory. We further show that the effective Hamiltonian associated with the Trotter decomposition of the unitary time-evolution operator, when the Trotter step size is chosen to be in the structural instability region, is very different from the target Hamiltonian, which explains the large errors that can occur in the simulation in the regions of instability. These results have implications for the reliability of near-term gate-based quantum simulators, and reveal an important interplay between errors and the physical properties of the system being simulated.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Atomistic simulation of PDADMAC/PSS oligoelectrolyte multilayers: overall comparison of tri- and tetra-layer systems

By employing large-scale molecular dynamics simulations of atomistically resolved oligoelectrolytes in aqueous solutions, we study in detail the first four layer-by-layer deposition cycles of an oligoelectrolyte multilayer made of poly(diallyl dimethyl ammonium chloride)/poly(styrene sulfonate sodium salt) (PDADMAC/PSS). The multilayers are grown on a silica substrate in 0.1 M NaCl electrolyte solutions and the swollen structures are then subsequently exposed to varying added salt concentration. We investigated the microscopic properties of the films, analyzing in detail the differences between three- and four-layer systems. Our simulations provide insights into the early stages of growth of a multilayer, which are particularly challenging for experimental observations. Here, we found rather strong complexation of the oligoelectrolytes, with fuzzy layering of the film structure. The main charge compensation mechanism is for all cases intrinsic, whereas extrinsic compensation is relatively enhanced for the layer of the last deposition cycle. In addition, we quantified other fundamental observables of these systems, such as the film thickness, water uptake, and overcharge fractions for each deposition layer.

74 ATOMIC AND MOLECULAR PHYSICS↗