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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

High-pressure neutron diffraction at ultra-low temperature

Neutron diffraction is a powerful tool in the study of quantum materials and associated emergent phenomena as it allows for direct detection of magnetic structure even at ultra-low temperatures. As pressure can drive systems across quantum critical points and tune emergent behaviors at the quantum scale, coupling neutron diffraction with extreme conditions of high pressure at (ultra-)low temperatures has been a key research target over decades. This has proven challenging as magnetic neutron diffraction typically requires large sample volumes due to flux limitations, whereas high-pressure studies require small sample volumes due to pressure limitations. Combining these two contradictory requirements poses many difficulties, but also brings opportunities in research and development. Here, we address these shortcomings through the use of a diamond anvil cell equipped with polycrystalline anvils with relatively large sample volumes coupled with the high neutron flux made available by the high-pressure diffractometer of the Spallation Neutron Source. This particular diamond anvil cell configuration has previously proven useful for single-crystal samples and is here coupled with the ultra-low temperatures of a dilution refrigerator for the first time. Our study on a single crystal of Yb 2 ⁢O 3 successfully collected magnetic neutron diffraction data at 5.3 GPa below 200 mK inside a dilution refrigerator. We have performed a detailed analysis of the magnetic diffraction data to investigate the magnetic structure under pressure and observed a subtle shift in the transition temperature. This development will open the door for future studies on magnetic materials with these much-desired coupled extremes of high pressure and ultra-low temperatures.

Wu, Yan [Oak Ridge National Laboratory (ORNL), Oak↗
DOE OSTI2025

Performance of wave function and Green's function methods for non-equilibrium many-body dynamics

Theoretical descriptions of the non-equilibrium dynamics of quantum many-body systems essentially employ either (i) explicit treatments, relying on the truncation of the expansion of the many-body wave function, (ii) compressed representations of the many-body wave function, or (iii) evolution of an effective (downfolded) representation through Green's functions. In this work, we select representative cases of each of the methods and address how these complementary approaches capture the dynamics driven by intense field perturbations to non-equilibrium states. Under strong driving, the systems are characterized by strong entanglement of the single-particle density matrix and natural populations approaching those of a strongly interacting equilibrium system. We generate a representative set of results that are numerically exact and form a basis for a critical comparison of the distinct families of methods. We demonstrate that the compressed formulation based on similarity-transformed Hamiltonians (coupled-cluster approach) is practically exact in weak fields and, hence, weakly or moderately correlated systems. Coupled cluster, however, struggles for strong driving fields, under which the system exhibits strongly correlated behavior, as measured by the von Neumann entropy of the single-particle density matrix. The dynamics predicted by Green's functions in the (widely popular) G W approximation are less accurate, but improve significantly upon the mean-field results in the strongly driven regime. Published by the American Physical Society 2025

Reeves, Cian C. (ORCID:0009000642581845)↗
DOE OSTI2021

A Circular Economy for Lithium-Ion Batteries Used in Mobile and Stationary Energy Storage: Drivers, Barriers, Enablers, and U.S. Policy Considerations

As large-format battery energy storage (BES) capacity increases in the United States, so will the volume of spent lithium-ion batteries (LiBs) (Bade 2019). Estimates based on a 10-year lifetime assumption found that the volume of LiBs that have reached the end of their utility for electric vehicle (EV) applications could total two million units (four million metric tons) annually by 2040 in the United States (Richa et al. 2014; Ai and Borucki 2018). Although there is currently no publicly available decommissioning or end-of-life (EoL) projection for stationary BES systems, the U.S. energy storage market is expected to grow from an annual deployment of 523 megawatts in 2013 to 7.3 gigawatts in 2025 (Wood MacKenzie and ESA 2020; Wesoff 2020). Despite potential secondary market opportunities and the potential benefits associated with the reuse/recovery of LiB material, anecdotal evidence suggests that in the United States most decommissioned LiBs from EVs are landfilled or otherwise disposed of (Steward et al. 2019; Salim et al. 2019; CPUC 2019; DTSC 2019d; NREL 2019b; Jacoby 2019; DOE 2019). The reuse of large-format LiBs is not at commercial scale and to date consists of only a handful of U.S.-led pilot projects. Similarly, less than 5% of LiBs from EVs are sent to recycling facilities in the United States (Steward et al. 2019; Jacoby 2019; America Made 2019; Patel 2017). As awareness of current practices grows, and the demand for critical LiB materials increases, U.S. industry stakeholders, regulators, and policymakers are starting to (1) consider solutions to drive and enable environmentally sustainable materials management decisions and behaviors and (2) identify barriers to a circular economy for LiBs (Figure 1). Circular economy principles (Figure 1) attempt to transition from a “take-make-consume-dispose” linear economic system to a circular system that allows for the long life, high performance, and the reuse/recovery of products and materials (Ellen MacArthur Foundation 2016). We begin this report by summarizing drivers, barriers, and enablers to a circular economy for LiBs used in mobile and stationary BES systems in the United States. We then report on our analysis of federal and state regulatory considerations that may impact the reuse/recovery and disposal of LiBs, and potential civil and criminal liabilities associated with noncompliance. We conclude by highlighting state policies and initiatives in the United States that expressly address reuse/recovery and disposal of large-format LiBs. Our results are based on legal and literature-based research and interviews with mobile and stationary BES industry stakeholders, regulators, and policymakers. While this report addresses stationary BES, as well as mobile BES, much of the information and experience with LiB decommissioning and EoL material management is derived from the increasing management of spent EV LiBs in the United States.

25 ENERGY STORAGE↗
DOE OSTI2021

A Circular Economy for Solar Photovoltaic System Materials: Drivers, Barriers, Enablers, and U.S. Policy Considerations

As PV capacity increases, owners are also decommissioning older system assets. Estimates based on a 30-year lifetime assumption found that cumulative U.S. end-of-life (EoL) PV modules could total one million metric tons (Mt) by 2030 and up to 10 million Mt by 2050 (Weckend, Wade, and Heath 2016). Beyond maintenance replacements, early retirements that are due to efficiency upgrades and extreme weather, as well as PV deployment beyond earlier expectations, would increase these projections. PV system owners must evaluate equipment management options for used modules and system components retired during maintenance activities, refurbishment, repowering and system decommissioning. PV manufacturers must also evaluate material management options from customer returns, defects, and scrap. Management options for early retired and EoL PV system material include reuse, repair for reuse, recycling-based resource recovery, storage, and disposal. Disposal of PV system material increases the burden on landfill capacity, while reuse, repair for reuse, and recycling-based resource recovery (reuse/repair/recovery) options salvage valuable materials and provide secondary market opportunities and ancillary benefits (Weckend, Wade, and Heath 2016; EPA 2019c; SWEEP 2019). PV system owners may also decide store used modules and components as spares, or in the interim before a reuse or EoL management decision is made. Despite potential secondary market opportunities and the potential benefits associated with the repair/reuse/recovery of PV system material, anecdotal evidence suggests that in the United States decommissioned PV modules are stored, landfilled or otherwise disposed of (Salim et al. 2019; CPUC 2019b; DTSC 2019b; NREL 2019a). Some modules are being disposed of in municipal nonhazardous landfills and federally regulated hazardous treatment, storage, and disposal facilities, and others are being stored in warehouses until economically viable repair/reuse/recycling becomes available (CPUC 2019b; DTSC 2019b; NREL 2019a; Libby and Shaw 2018). As awareness of current practices grows, and the demand for critical PV module material increases, U.S. industry stakeholders, regulators, and policymakers are starting to (1) consider solutions to drive and enable environmentally sustainable materials management decisions and behaviors and (2) identify barriers to a circular economy for PV system materials. Circular economy principles attempt to transition from a "take-make-consume-dispose" linear economic system to a circular system that allows for the long life, and the reuse/repair/recovery of products and materials (Ellen MacArthur Foundation 2020). We begin this report by summarizing the drivers, barriers, and enablers to a circular economy for PV system materials in the United States. We then report on our analysis of federal and state regulatory considerations that may impact the repair/reuse/recovery of PV materials, and potential civil and criminal liabilities associated with noncompliance. We then discuss state policies and initiatives in the United States that expressly address PV system decommissioning and repair/reuse/recovery of PV materials. We conclude by providing case studies of U.S. business models for the repair/reuse/recovery of PV system materials. Our results are based on legal and literature-based research and interviews with solar industry stakeholders, regulators, and policymakers.

14 SOLAR ENERGY↗
DOE OSTI2021

Physics-Informed Machine Learning-Aided System Space Discretization

Decision-making is the process of identifying and choosing alternatives based on an agreed-upon set of metrics and preferences established by the decision-maker. There are options to be considered during the decision-making process and each option offers a different trajectory and associated success profile in moving from a given system state to the desired system state. The decision-making process typically involves uncertainties associated with the current component and system states. In this sense, probabilistic risk assessment (PRA) can be an analytical method and tool for accomplishing the probabilistic aspect of the decision-making process. Dynamic PRA is an evolution of conventional PRA methodology in which driving forces on modeled plant elements and the element behaviors are explicitly modeled over time. In the recent past, risk assessment methodologies have evolved to address risk issues in a continuously evolving environment and a novel probabilistic dynamics framework in continuous time and state-space discretization forms has been proposed. While state-space discretization has shown its strength in both consequence and causal reasoning modes, several challenges, including the computational requirement and physically meaningful system state identification, exist. Conventional system space discretization has usually been done by either the equal width discretization method or a data-driven method. Those methods naturally possess challenges coming from the physical understanding of discretized system space (i.e., system state) and the trajectory moving from a given system state to another system state. The purpose of this paper is to present a physics-based and data-driven system state discretization method such that one can justify what the discretized system space implies and understand the state trajectory from the viewpoint of operational actions.

Kim, Junyung↗
DOE OSTI2024

Reversible to irreversible transitions for ac driven skyrmions on periodic substrates

Abstract Using atomistic simulations, we investigate the dynamical behavior of magnetic skyrmions in dimer and trimer molecular crystal arrangements, as well as bipartite lattices at 3/2 and 5/2 fillings, under ac driving over a square array of anisotropy defects. For low ac amplitudes, at all fillings reversible motion appears in which the skyrmions return to their original positions at the end of each ac drive cycle and the diffusion is zero. We also identify two distinct irreversible regimes. The first is a translating regime in which the skyrmions form channels of flow in opposing directions and translate by one substrate lattice constant per ac drive cycle. The translating state appears in the dimer and trimer arrangements, and produces pronounced peaks in the diffusivity in the direction perpendicular to the external drive. For larger ac amplitudes, we find chaotic irreversible motion in which the skyrmions can randomly exchange places with each other over time, producing long-time diffusive behavior both parallel and perpendicular to the ac driving direction.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Decoding Antenna Behavior in Metal—Organic Frameworks

Metal–organic frameworks (MOFs) define a solid-state platform for developing artificial photosystems. Efficient anisotropic exciton migrations in these frameworks entail “antenna behavior” that can power up the distal interior reaction centers (RC), driving charge separation between donor-acceptor pairs. Reminiscent of the natural light-harvesting complex, such processes can achieve high quantum yield by exploiting the vast interior surface of the porous crystallites. It is important to understand the optimum positioning of the RC site relative to the anisotropic exciton migration path within these frameworks. The efficiency of such antenna behavior is probed here through Stern–Volmer (SV) type analysis with a series of node-anchored redox quenchers, ferrocene-carboxylate, ferrocene acetate, and dinitrobenzoate. Decoding various intrinsic processes, this work constructs a revised SV formalism in solid assembly that hosts ultrafast anisotropic exciton migration to account for the intrinsic exciton hopping rate from the extrinsic electron transfer rate, and the dimension of effective quenching. In conclusion, this transformative understanding can be applied to other relevant solid-state assemblies.

Saha, Bapan [Southern Illinois University, Carbond↗
DOE OSTI2021

Recognition Method of Vehicle Cluster Situation Based on Set Pair Logic considering Driver’s Cognition

The recognition of vehicle cluster situations is one of the critical technologies of advanced driving, such as intelligent driving and automated driving. The accurate recognition of vehicle cluster situations is helpful for behavior decision‐making safe and efficient. In order to accurately and objectively identify the vehicle cluster situation, a vehicle cluster situation model is proposed based on the interval number of set pair logic. The proposed model can express the traffic environment’s knowledge considering each vehicle’s characteristics, grouping relationships, and traffic flow characteristics in the target vehicle’s interest region. A recognition method of vehicle cluster situation is designed to infer the traffic environment and driving conditions based on the connection number of set pair logic. In the proposed model, the uncertainty of the driver’s cognition is fully considered. In the recognition method, the relative uncertainty and relative certainty of driver’s cognition, traffic information, and vehicle cluster situation are fully considered. The verification results show that the proposed recognition method of vehicle cluster situations can realize accurate and objective recognition. The proposed anthropomorphic recognition method could provide a basis for vehicle autonomous behavior decision‐making.

Liu, Shijie↗
DOE OSTI2025

KIPM Detector Characterization in QUIET

Kinetic Inductance Phonon‑Mediated (KIPM) detectors are superconducting microwave resonators that sense energy depositions in the substrate through a transient shift in their resonant frequency. In this work, I installed new devices in the QUIET cryogenic facility and used a network analyzer to drive them across a range of power levels. At each setting, I measured the transmitted signal and fit it to a simple notch‑filter model, allowing us to extract key performance metrics. Despite the increased noise at low power, the model consistently captured the resonance behavior. I first measured the resonance parameters as a function of RF drive power, then repeated the measurement across a range of temperatures to test whether the device behaved like an MKID. While the notch-filter fits captured the resonance reliably, the observed temperature dependence did not match the expected MKID signature — indicating that these first in-house fabricated chips are not yet functioning as true MKIDs. Overall, this reframes our work as a study of resonance parameter extraction and identification, pointing towards future iterations of device design and fabrication to get the true MKID response.

Savitala, Akash [U. Washington, Seattle (main); Fe↗
DOE OSTI2020

Drive-pressure optimization in ramp-wave compression experiments through differential evolution

Ramp-wave dynamic-compression experiments are used to examine quasi-isentropic loading paths in materials. The gradual and continuous increase in pressure created by ramp waves make these types of experiments ideal for studying nonequilibrium material behavior, such as solidification kinetics. In ramp-wave compression experiments, the input drive pressure to the experimental setup may be exerted through one of a number of different mechanisms (e.g., magnetic fields, gas-gun-driven impactors, or high-energy lasers) and is generally required for simulating such experiments. Yet, regardless of the specific mechanism, this drive pressure cannot be measured directly (measurements are generally taken at a location near the back of the experimental setup through a transparent window), leading to an inverse problem where one must determine the drive pressure at the front of the experimental setup (i.e., the input) that corresponds to the particle velocity (the output) measured near the back of the experimental setup. Furthermore, we solve this inverse problem using a heuristic optimization algorithm, known as differential evolution, coupled with a multiphysics, hydrodynamics code that simulates the compression of the experimental setup. By running many rounds of forward simulations of the experimental setup, our optimization process iteratively searches for a drive pressure that is optimized to closely reproduce the experimentally measured particle velocity near the back of the experimental setup. While our optimization methodology requires a significant number of hydrodynamics simulations to be conducted, many of these can be performed in parallel, which greatly reduces the time cost of our methodology. One novel aspect of our method for determining the drive pressure is that it does not require physical modeling of the drive mechanism and can thus be broadly applied to many types of ramp-compression experiments, regardless of the drive mechanism.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Operation-Induced BiVO4 Surface Reconstruction Modulates Photoelectrochemical Glycerol Photooxidation Stability and Activity

Abstract Operation-induced surface reconstruction of photoelectrodes is underexplored as a path to control stability and performance. We show how adaptive junctions form via surface reconstruction of BiVO4 during glycerol photooxidation and how these surfaces affect electrolyte-dependent kinetics and durability. Preferential V dissolution in both acidic and alkaline media forms a Bi-rich layer. In situ measurements through a dual-working-electrode platform quantify the changes in photovoltage and charge-transfer resistance derived from adaptive junction formation, while enabling quantitative separation of the driving forces for charge separation and interfacial catalysis. The reconstructed surface in acidic media improves hole-transfer kinetics, functions as a glycerol-oxidation catalyst, and imparts photostability. Surface reconstruction in alkaline media exhibits the opposite behavior, impeding hole injection. This instability is mitigated by trace Ni2+ ions, which drive in situ surface activation without cocatalyst pre-deposition. This study shows the significance of surface reconstruction in the design of durable photoelectrodes for applications targeting organic electro-oxidation.

Yang, Jin Wook↗
DOE OSTI2020

Jamming, fragility and pinning phenomena in superconducting vortex systems

Abstract We examine driven superconducting vortices interacting with quenched disorder under a sequence of perpendicular drive pulses. As a function of disorder strength, we find four types of behavior distinguished by the presence or absence of memory effects. The fragile and jammed states exhibit memory, while the elastic and pinning dominated regimes do not. In the fragile regime, the system organizes into a pinned state during the first pulse, flows during the second perpendicular pulse, and then returns to a pinned state during the third pulse which is parallel to the first pulse. This behavior is the hallmark of the fragility proposed for jamming in particulate matter. For stronger disorder, we observe a robust jamming state with memory where the system reaches a pinned or reduced flow state during the perpendicular drive pulse, similar to the shear jamming of granular systems. We show signatures of the different states in the spatial vortex configurations, and find that memory effects arise from coexisting elastic and pinned components of the vortex assembly. The sequential perpendicular driving protocol we propose for distinguishing fragile, jammed, and pinned phases should be general to the broader class of driven interacting particles in the presence of quenched disorder.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Self-driving laboratories to autonomously navigate the protein fitness landscape

Abstract Protein engineering has nearly limitless applications across chemistry, energy and medicine, but creating new proteins with improved or novel functions remains slow, labor-intensive and inefficient. Here we present the Self-driving Autonomous Machines for Protein Landscape Exploration (SAMPLE) platform for fully autonomous protein engineering. SAMPLE is driven by an intelligent agent that learns protein sequence–function relationships, designs new proteins and sends designs to a fully automated robotic system that experimentally tests the designed proteins and provides feedback to improve the agent’s understanding of the system. We deploy four SAMPLE agents with the goal of engineering glycoside hydrolase enzymes with enhanced thermal tolerance. Despite showing individual differences in their search behavior, all four agents quickly converge on thermostable enzymes. Self-driving laboratories automate and accelerate the scientific discovery process and hold great potential for the fields of protein engineering and synthetic biology.

Rapp, Jacob T. (ORCID:0000000226835204)↗
DOE OSTI2023

How to select distracted driving countermeasures evaluation metrics: A systematic review

While there are numerous performance metrics that have been developed for the evaluation of distracted driving prevention programs, there is little information on how to select them depending on the requirements and/or objectives of the study. Here, this paper describes a systematic literature review that was conducted on the metrics for evaluating distracted driving countermeasures in order to bridge this research gap. A summary of the evaluation metrics used for the existing distracted driving countermeasures was provided. Guidance for choosing an evaluation measure was provided by analyzing the metrics from the perspectives of functionality, spatial-temporal dimension, and equity. Three examples of distracted driving countermeasure evaluation processes were thoroughly reviewed in order to offer insight into metric selection and measurement. This paper contributes to the body of knowledge by discussing the implications for policy on how to enhance the thoroughness and accuracy of the evaluation of distracted driving countermeasures. Analysis from multiple angles, the development of data collection tools and direct behavior indicators, taking into account temporal dimensions, and equity considerations, are proposed.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Ecological stoichiometry as a foundation for omics-enabled biogeochemical models of soil organic matter decomposition

Coupled biogeochemical cycles drive ecosystem ecology by influencing individual-to-community scale behaviors; yet the development of process-based models that accurately capture these dynamics remains elusive. Soil organic matter (SOM) decomposition in particular is influenced by resource stoichiometry that dictates microbial nutrient acquisition (‘ecological stoichiometry’). Despite its basis in biogeochemical modeling, ecological stoichiometry is only implicitly considered in high-resolution microbial investigations and the metabolic models they inform. State-of-science SOM decomposition models in both fields have advanced largely separately, but they agree on a need to move beyond seminal pool-based models. This presents an opportunity and a challenge to maximize the strengths of various models across different scales and environmental contexts. To address this challenge, we contend that ecological stoichiometry provides a framework for merging biogeochemical and microbiological models, as both explicitly consider substrate chemistries that are the basis of ecological stoichiometry as applied to SOM decomposition. We highlight two gaps that limit our understanding of SOM decomposition: (1) understanding how individual microorganisms alter metabolic strategies in response to substrate stoichiometry and (2) translating this knowledge to the scale of biogeochemical models. We suggest iterative information exchange to refine the objectives of high-resolution investigations and to specify limited dynamics for representation in large-scale models, resulting in a new class of omics-enabled biogeochemical models. Assimilating theoretical and modelling frameworks from different scientific domains is the next frontier in SOM decomposition modelling; advancing technologies in the context of stoichiometric theory provides a consistent framework for interpreting molecular data, and further distilling this information into tractable SOM decomposition models.

Carbon cycling↗
DOE OSTI2020

Nonlinear modeling and performance analysis of cracked beam microgyroscopes

Cracks constitute a common structural defect in microelectromechanical systems that may arise during manufacturing, mechanical fatigue, or shock loading. Areas weakened by cracks increase the flexibility of the microstructure. Furthermore, depending on the crack severity, the increased flexibility can cause dramatic changes in the static and dynamic behaviors of electrically actuated MEMS. In this study, a numerical investigation of the depth and location of multiple edge cracks on the performance of beam microgyroscopes is conducted. Applying the Griffith strain energy release theorem for an edge crack, the vibrational characteristics of microgyroscopes with multiple cracks including the static deflection, natural frequencies, and mode shapes are studied analytically. Then, the differential quadrature method is employed to model the nonlinear dynamic behaviors of the cracked gyroscope system. Cracks initiated along the driving or sensing directions of the microgyroscope are found to have differing effects on its nonlinear dynamic response. This numerical study reveals that the onset of severe single cracks or a series of multiple cracks can significantly affect the sensitivity of the microgyroscope to base rotations and therefore leads to a degradation in the performance of the damaged MEMS sensor. This study also shows that a potential design approach for broadband microgyroscope systems manufactured with cracks can be proposed.

42 ENGINEERING↗
DOE OSTI2025

Exploring the Utility-Privacy Trade-Off: Impacts of Semantic and Visit Types Ambiguities on Human Mobility Simulation

Humans are in perpetual movement, constantly traversing buildings, cities, waters, oceans, and countries. Mobility stands out as a major driving force shaping our modern societies. Capturing and explaining human behavior in a world of eight billion distinct mobility agendas is a complex challenge. With the rise of interconnected devices and platforms, such as smartphones, wearables, and point-of-interest data, largescale behavioral data has become more accessible, enabling rich insights into mobility patterns. However, the widespread availability of such data introduces significant ethical challenges. Detailed mobility data can inadvertently reveal sensitive personal information, including individuals' locations, habits, social interactions, and even political or religious affiliations. Beyond privacy breaches, the ethical implications of uncovering and potentially manipulating underlying behavioral patterns demand attention. Striking a balance between the utility of mobility models and the protection of individual privacy is therefore paramount. This paper explores the utility-privacy trade-offs in human mobility modeling, focusing on the impacts of introducing semantic and visit type ambiguities. By systematically examining how these ambiguities affect the fidelity of simulated trajectories and privacy risks, we provide a framework for evaluating ethical and privacy-conscious modeling practices. Our findings emphasize the need for methods that safeguard privacy without undermining the usefulness of mobility models, contributing to the responsible advancement of mobility science in alignment with ethical standards and societal expectations.

Amichi, Licia [ORNL] (ORCID:0000000177631394)↗
DOE OSTI2023

Pattern formation and transport for externally driven active matter on periodic substrates (a)

Abstract We investigate the transport of interacting active run-and-tumble particles moving under an external drift force through a periodic array of obstacles for increasing drive amplitudes. For high activity where the system forms a motility-induced phase-separated state, there are several distinct dynamic phases including a low drive pinned cluster phase, an intermediate uniform fluid, and a higher drive stripe crystal state. The transitions between the phases are correlated with signatures in the transport curves, differential mobility, and power spectra of the velocity fluctuations. In contrast, in the low activity regime the transport curves and power spectra undergo little change as a function of drive. We argue that in the high activity limit, the behavior is similar to that of driven solids on periodic substrates, while in the low activity limit the system behaves like a driven fluid.

36 MATERIALS SCIENCE↗