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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

From Protein Design to the Energy Landscape of a Cold Unfolding Protein

Understanding protein folding is crucial for protein sciences. The conformational spaces and energy landscapes of cold (unfolded) protein states, as well as the associated transitions, are hardly explored. Furthermore, it is not known how structure relates to the cooperativity of cold transitions, if cold and heat unfolded states are thermodynamically similar, and if cold states play important roles for protein function. We created the cold unfolding 4-helix bundle DCUB1 with a de novo designed bipartite hydrophilic/hydrophobic core featuring a hydrogen bond network which extends across the bundle in order to study the relative importance of hydrophobic versus hydrophilic protein–water interactions for cold unfolding. Structural and thermodynamic characterization resulted in the discovery of a complex energy landscape for cold transitions, while the heat unfolded state is a random coil. Below ~0 °C, the core of DCUB1 disintegrates in a largely cooperative manner, while a near-native helical content is retained. The resulting cold core-unfolded state is compact and features extensive internal dynamics. Below -5 °C, two additional cold transitions are seen, that is, (i) the formation of a water-mediated, compact, and highly dynamic dimer, and (ii) the onset of cold helix unfolding decoupled from cold core unfolding. Our results suggest that cold unfolding is initiated by the intrusion of water into the hydrophilic core network and that cooperativity can be tuned by varying the number of core hydrogen bond networks. Protein design has proven to be invaluable to explore the energy landscapes of cold states and to robustly test related theories.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Combined Force-Frequency Sampling for Simulation of Systems Having Rugged Free Energy Landscapes.

An adaptive, machine learning-based sampling method is presented for simulation of systems having rugged, multidimensional free energy landscapes. The method's main strength resides in its ability to learn both from the frequency of visits to distinct states and the generalized force estimates that arise in a system as it evolves in phase space. This is accomplished by introducing a self-integrating artificial neural network, which generates an estimate of the free energy directly from its derivatives. The usefulness of the proposed combined approach is examined in the context of two concrete examples, namely, an alanine dipeptide molecule in water and a polymer diffusing through a narrow pore. This new method is found to be robust, faster, and more accurate than approaches that rely only on frequency-based or generalized force-based estimations. After combining the proposed approach with overfill protection and support for sparse data storage and training, the method is shown to be more effective than comparable, previously available techniques and capable of scaling efficiently to larger numbers of collective variables.

Sevgen, Emre↗
NASA NTRS1996

Approximate scaling properties of RNA free energy landscapes

RNA free energy landscapes are analysed by means of "time-series" that are obtained from random walks restricted to excursion sets. The power spectra, the scaling of the jump size distribution, and the scaling of the curve length measured with different yard stick lengths are used to describe the structure of these "time series". Although they are stationary by construction, we find that their local behavior is consistent with both AR(1) and self-affine processes. Random walks confined to excursion sets (i.e., with the restriction that the fitness value exceeds a certain threshold at each step) exhibit essentially the same statistics as free random walks. We find that an AR(1) time series is in general approximately self-affine on timescales up to approximately the correlation length. We present an empirical relation between the correlation parameter rho of the AR(1) model and the exponents characterizing self-affinity.

Signal Processing, Computer-Assisted↗
DOE OSTI2023

Renewable Energy Landscapes: Southwest and Pacific Northwest Workshops

To connect landscape architects and the energy sector, the University of Arizona and the University of Oregon hosted two virtual workshops with support from Pacific Northwest National Laboratory in January 2023. These workshops were intended to co-create new principles and perspectives for designing renewable energy landscapes for the Southwest and Pacific Northwest, respectively, balancing place-based perspectives and at-scale deployment. Working across six design pathways through three phases, participants in the Southwest Workshop established and prioritized design opportunities by identifying relevant actions that are high impact, low effort; high impact, high effort; low impact, high effort; low impact, low effort. In contrast, participants in the Pacific Northwest Workshop produced a series of design options for the three sites to support broader efforts to visualize energy infrastructure deployment. The workshop outcomes reflect the current state of innovation in designing renewable energy landscapes. Collective understanding is largely focused on the practical—what is feasible in this moment—rather than pushing the boundaries on what might be possible. Achieving that next step requires that we first catch up to existing innovation in implementation and design since it is not yet commonplace. These workshops served as the first step in reimagining the potential of energy infrastructure across landscapes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Spatially varying colloidal phase behavior on multi-dimensional energy landscapes

A method is reported to determine equilibrium concentration profiles and local phase behavior for colloids on multi-dimensional energy landscapes. A general expression is derived based on local particle concentration and osmotic pressure differences that are balanced by forces on colloids due to energy landscape gradients. This analysis is applied to colloidal particles in high frequency AC electric fields within octupolar electrodes, where the energy landscape can be shaped in two dimensions. These results are also directly applicable to any particles having induced dipoles in spatially non-uniform electromagnetic fields. Predictions based on modelling colloids with an effective hard disk equation of state indicate inhomogeneous solid and fluid states coexisting on different shaped energy landscapes including multiple minima. Model predictions show excellent agreement with time-averaged Brownian Dynamic simulations at equilibrium. Findings demonstrate a general approach to understand colloidal phase behavior on energy landscapes due to external fields, which could enable control of colloidal microstructure on morphing energy landscapes and the inverse design of fields to assemble hierarchically structured colloidal materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Entropic control of the free-energy landscape of an archetypal biomolecular machine

Biomolecular machines are complex macromolecular assemblies that utilize thermal and chemical energy to perform essential, multistep, cellular processes. Despite possessing different architectures and functions, an essential feature of the mechanisms of action of all such machines is that they require dynamic rearrangements of structural components. Surprisingly, biomolecular machines generally possess only a limited set of such motions, suggesting that these dynamics must be repurposed to drive different mechanistic steps. Although ligands that interact with these machines are known to drive such repurposing, the physical and structural mechanisms through which ligands achieve this remain unknown. Using temperature-dependent, single-molecule measurements analyzed with a time-resolution-enhancing algorithm, here, we dissect the free-energy landscape of an archetypal biomolecular machine, the bacterial ribosome, to reveal how its dynamics are repurposed to drive distinct steps during ribosome-catalyzed protein synthesis. Specifically, we show that the free-energy landscape of the ribosome encompasses a network of allosterically coupled structural elements that coordinates the motions of these elements. Moreover, we reveal that ribosomal ligands which participate in disparate steps of the protein synthesis pathway repurpose this network by differentially modulating the structural flexibility of the ribosomal complex (i.e., the entropic component of the free-energy landscape). Here, we propose that such ligand-dependent entropic control of free-energy landscapes has evolved as a general strategy through which ligands may regulate the functions of all biomolecular machines. Such entropic control is therefore an important driver in the evolution of naturally occurring biomolecular machines and a critical consideration for the design of synthetic molecular machines.

Science & Technology - Other Topics↗
DOE OSTI2020

Controlling colloidal crystals via morphing energy landscapes and reinforcement learning

We report a feedback control method to remove grain boundaries and produce circular shaped colloidal crystals using morphing energy landscapes and reinforcement learning–based policies. We demonstrate this approach in optical microscopy and computer simulation experiments for colloidal particles in ac electric fields. First, we discover how tunable energy landscape shapes and orientations enhance grain boundary motion and crystal morphology relaxation. Next, reinforcement learning is used to develop an optimized control policy to actuate morphing energy landscapes to produce defect-free crystals orders of magnitude faster than natural relaxation times. Morphing energy landscapes mechanistically enable rapid crystal repair via anisotropic stresses to control defect and shape relaxation without melting. This method is scalable for up to at least N = 10 3 particles with mean process times scaling as N 0.5 . Further scalability is possible by controlling parallel local energy landscapes (e.g., periodic landscapes) to generate large-scale global defect-free hierarchical structures.

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

The hierarchical energy landscape of screw dislocation motion in refractory high-entropy alloys

High-entropy alloys (HEAs) with concentrated solid solutions are conceived to possess a rugged atomic and energy landscape in which dislocation motion necessarily proceeds to accommodate mechanical deformation. Fundamental questions remain as to how rough the energy landscape is and to what extent it can be influenced by the local ordering of their constituent elements. Here, we construct and report the potential energy landscape (PEL) governing screw dislocation motion in refractory HEAs that reveals a hierarchical and multilevel structure with a collection of small basins nested in large metabasin. This striking feature pertaining to HEAs exerts a trapping force and back stress on saddle point activations, retarding dislocation movement. Further, by introducing chemical short-range order, the energy landscape is smoothed but skewed to different degrees that shifts the rate-liming process from kink-glide to kink-pair nucleation. The chemical disorder-roughened PEL in HEAs, analogous to structural disorder induced in metallic glasses, signifies the role of various barrier-hopping processes underlying the extraordinary mechanical behaviors of the two distinct groups of materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Land-use intensity of electricity production and tomorrow’s energy landscape

The global energy system has a relatively small land footprint at present, comprising just 0.4% of ice-free land. This pales in comparison to agricultural land use– 30–38% of ice-free land–yet future low-carbon energy systems that shift to more extensive technologies could dramatically alter landscapes around the globe. The challenge is more acute given the projected doubling of global energy consumption by 2050 and widespread electrification of transportation and industry. Yet unlike greenhouse gas emissions, land use intensity of energy has been rarely studied in a rigorous way. Here we calculate land-use intensity of energy (LUIE) for real-world sites across all major sources of electricity, integrating data from published literature, databases, and original data collection. We find a range of LUIE that span four orders of magnitude, from nuclear with 7.1 ha/TWh/y to dedicated biomass at 58,000 ha/TWh/y. By applying these LUIE results to the future electricity portfolios of ten energy scenarios, we conclude that land use could become a significant constraint on deep decarbonization of the power system, yet low-carbon, land-efficient options are available.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Renewable Energy Landscapes: Designing Place-Based Infrastructure for Scale

This paper offers a pathway for developing community-centered renewable energy at scale, outlining how renewable energy landscapes can be envisioned alongside the high environmental and social equity standard that is at the heart of the future clean energy system. We call this “place-based at scale” and “renewable energy landscapes” because the ultimate aim is to adapt technology and infrastructure coherently and collectively toward community objectives, and to organize it to allow replicability and scaled approaches across the country. Realizing this type of development in practice will require reconciling the challenges and tensions that currently existing between top-down and bottom-up approaches. It will also require reckoning with greenhouse gas emission goals, large investments in infrastructure, and community self-determination as the driving priority in those investments. We believe a window of opportunity is presenting itself to shape and envision the future of renewable energy installations and move into action to create them. Six pathways that draw upon new cooperation between disciplines for designing renewable energy landscapes at scale are presented and historical perspectives are explored.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Energy landscapes from cryo-EM snapshots: a benchmarking study

Abstract Biomolecules undergo continuous conformational motions, a subset of which are functionally relevant. Understanding, and ultimately controlling biomolecular function are predicated on the ability to map continuous conformational motions, and identify the functionally relevant conformational trajectories. For equilibrium and near-equilibrium processes, function proceeds along minimum-energy pathways on one or more energy landscapes, because higher-energy conformations are only weakly occupied. With the growing interest in identifying functional trajectories, the need for reliable mapping of energy landscapes has become paramount. In response, various data-analytical tools for determining structural variability are emerging. A key question concerns the veracity with which each data-analytical tool can extract functionally relevant conformational trajectories from a collection of single-particle cryo-EM snapshots. Using synthetic data as an independently known ground truth, we benchmark the ability of four leading algorithms to determine biomolecular energy landscapes and identify the functionally relevant conformational paths on these landscapes. Such benchmarking is essential for systematic progress toward atomic-level movies of continuous biomolecular function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Tunable energy landscape of screw dislocation cores by compositional fluctuations in bcc high-entropy alloys from first-principles calculations

The energy landscape of screw dislocation cores plays a central role in dislocation-mediated deformation mechanisms in body-centered cubic (bcc) metals. In bcc high-entropy alloys (HEAs), this energy landscape is modulated by local compositional fluctuations, which has important implications for deformation processes in these materials. Through first-principles calculations, this study investigates high-symmetry screw dislocation core structures in NbTaMoW and NbTaTiHf bcc HEAs. The results show that alloying group IV transition metals lead to large local lattice distortions at dislocation cores, which is demonstrated to be an important factor governing fluctuations in core configurations along a dislocation line. Importantly, group IV elements near the core induce features in the energy landscape that are exclusive for HEAs, specifically lowering the energy of core configurations that are unstable in elemental bcc metals. A combined influence of these chemical effects with crystallographic details enables the activation of glide planes, a feature that has been linked to ductility improvements in bcc HEAs. These findings provide new insights into the atomic-scale mechanisms underlying dislocation mobility in bcc HEAs, offering a pathway for designing materials with tailored mechanical properties.

Borges, Pedro P P O↗
DOE OSTI2022

Extraction of the spin-glass free-energy landscape from $1/f$ noise measurements

The 1/f resistance noise has been measured in thin CuMn (13.5 at.%) spin-glass films. The temperature and frequency dependence have been analyzed in terms of the landscape of free-energy barriers. Here this analysis provides the full barrier distribution for various thin film thicknesses between 10 nm and 80 nm. The free-energy barrier height distribution's width and energy position have been determined. Contrary to previous models with fixed shape and energy, the free-energy landscape is described by a distribution of barriers that both shifts and changes shape as the temperature is reduced. The dependence of this distribution is in contrast with recent predictions. Using the fluctuation dissipation theorem, the 1/f measurements connect with χ", displaying agreement with other direct measurements of the latter.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Adsorbate Free Energies from DFT-Derived Translational Energy Landscapes

Adsorption free energies are fundamental to surface chemistry and catalysis. Standard models combine some assumed analytical form of the translational potential energy surface, often parameterized against density functional theory (DFT) calculations, with an analytical expression for the resultant translational densities of states (DOS), free energy, and entropy. Here we compare the performance of such models against numerical evaluations of the DOS and thermodynamic functions derived from solutions to the translational Schrodinger equation. We compare results for a translational potential energy surface (PES) derived from nudged eleastic band calculations with those obtained from adsorbate rastering across a series of monatomic (O, S, C, N, H) and polyatomic (NH x ) adsorbates on (100) Pt and Au facets. We find that analytical models as commonly parameterized have mixed performance for describing the translational PES and that the consequences for computed free energies are modest but potentially significant in microkinetic models. Here, numerical solutions are possible for modest to no additional computational cost over analytical models and thus should be considered when reliable free energy estimates are needed or translational potential energy surfaces are available.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2022

Resolving the fine structure in the energy landscapes of repeat proteins

Ankyrin (ANK) repeat proteins are coded by tandem occurrences of patterns with around 33 amino acids. They often mediate protein–protein interactions in a diversity of biological systems. These proteins have an elongated non-globular shape and often display complex folding mechanisms. This work investigates the energy landscape of representative proteins of this class made up of 3, 4 and 6 ANK repeats using the energy-landscape visualisation method (ELViM). By combining biased and unbiased coarse-grained molecular dynamics AWSEM simulations that sample conformations along the folding trajectories with the ELViM structure-based phase space, one finds a three-dimensional representation of the globally funnelled energy surface. In this representation, it is possible to delineate distinct folding pathways. We show that ELViMs can project, in a natural way, the intricacies of the highly dimensional energy landscapes encoded by the highly symmetric ankyrin repeat proteins into useful low-dimensional representations. These projections can discriminate between multiplicities of specific parallel folding mechanisms that otherwise can be hidden in oversimplified depictions.

Murilo N. Sanches↗
DOE OSTI2020

Universal free-energy landscape produces efficient and reversible electron bifurcation

For decades, it was unknown how electron-bifurcating systems in nature prevented energy-wasting short-circuiting reactions that have large driving forces, so synthetic electron-bifurcating molecular machines could not be designed and built. The underpinning free-energy landscapes for electron bifurcation were also enigmatic. We predict that a simple and universal free-energy landscape enables electron bifurcation, and we show that it enables high-efficiency bifurcation with limited short-circuiting (the EB scheme). The landscape relies on steep free-energy slopes in the two redox branches to insulate against short-circuiting using an electron occupancy blockade effect, without relying on nuanced changes in the microscopic rate constants for the short-circuiting reactions. The EB scheme thus unifies a body of observations on biological catalysis and energy conversion, and the scheme provides a blueprint to guide future campaigns to establish synthetic electron bifurcation machines.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Structural dynamics of first-order phase transition in giant magnetocaloric La(Fe,Si) 13 : The free energy landscape

Maximizing the performance of magnetic refrigerators and thermomagnetic energy harvesters is imperative for their successful implementation and can be done by maximizing their operation frequency. One of the features delimiting the frequency and efficiency of such devices is the phase transition kinetics of their magnetocaloric/thermomagnetic active material. While previous studies have described the magnetic component governing the kinetics of the magnetovolume phase transition in La(Fe,Si) 13 giant magnetocaloric materials, a comprehensive description of its structural component has yet to be explored. In this study, in situ synchrotron X-ray diffraction is employed to describe the structural changes upon magnetic field application/removal. Long magnetic field dependent relaxation times up to a few hundred seconds are observed after the driving field is paused. The phase transition is found to be highly asymmetric upon magnetic field cycling due to the different Gibbs energy landscapes and the absence of an energy barrier upon field removal. An exponential relationship is found between the energy barriers and the relaxation times, suggesting the process is governed by a non-thermal activation over an energy barrier process. Such fundamental knowledge on first-order phase transition kinetics suggests pathways for materials optimization and smarter design of magnetic field cycling in real-life devices.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Tuning martensitic transformations via coherent second phases in nanolaminates using free energy landscape engineering

In this work we explore the possibilities and limitations of using a coherent second phase to engineer the thermo-mechanical properties of a martensitic alloy by modifying the underlying free energy landscape that controls the transformation. We use molecular dynamics simulations of a model atomistic system where the properties of a coherent, nanoscale second phase can be varied systematically. With a base martensitic material that undergoes a temperature-induced transformation from a cubic austenite to a monoclinic martensite, simulations show significant ability to engineer the transformation temperatures, from a ~50% reduction to a ~200% increase, with 50 at.% of the cubic second phase. We establish correlations between the properties of the second phase, the transformation characteristics, and the microstructure via the free energy landscape of the twophase systems. Coherency stresses have a strong influence on the martensitic variants observed and can even cause the non-martensitic second phase to undergo a transformation. Reducing the stiffness of the second phase increases the transformation strain and modifies the martensitic microstructure, increasing the volume fraction of the transformed material. This increase in transformation strain is accompanied by a significant increase in Af and thermal hysteresis, while Ms remains unaltered. Our findings on the tunability of martensitic transformations can be used for informed searches of second phases to achieve desired material properties, such as achieving room temperature, lightweight shape memory alloys.

36 MATERIALS SCIENCE↗