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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Nanodomain Formation and Temperature-Dependent Diffusion in Deep Eutectic Solvents Revealed by Single-Molecule Tracking

Deep eutectic solvents (DESs) are typically regarded as homogeneous liquids; however, recent work shows that many exhibit nanoscale structural heterogeneity. Most studies attribute these nanoscale features to short-range chemical interactions. It is still unclear whether a long-range physical mechanism also plays a role. Here, in this study, we examined the nanoscale structure in two hydrophobic DESs, 1:3 tetrabutylammonium bromide: l-menthol (DES-butyl) and 1:3 tetraoctylammonium bromide: l-menthol (DES-octyl). The notation 1:3 represents the molar ratio of the hydrogen bond acceptors to hydrogen bond donors used in the synthesis of the DESs. Single-molecule tracking (SMT) coupled with maximum entropy method (MEM) analysis was used to measure the number of diffusion populations of a dilute concentration of an added fluorescent probe. The presence of more than one population of diffusion coefficients indicates the existence of multiple local environments for the fluorescent probe (i.e., nanoscale structures in the DES). DES-butyl showed a relatively narrow diffusion coefficient distribution centered at 0.55 μm 2 /s, whereas DES-octyl displayed two distinct diffusing populations at 20 °C, with diffusion coefficients of 0.12 μm 2 /s and 0.53 μm 2 /s for the slow and fast populations, respectively. As DES-octyl was heated, the slow-diffusing population steadily diminished and disappeared above ∼30 °C, indicating that the nanodomains present at lower temperatures collapse as the liquid becomes more thermodynamically mixed. This temperature-dependent homogenization is consistent with a physical mechanism of nanostructure formation, for example, liquid–liquid phase separation (LLPS), wherein the structure is not driven solely by specific chemical interactions. The SMT-MEM results suggest that a long-range physical mechanism is the most plausible origin of the measured nanoscale structure in DES-octyl.

Opare-Addo, Jemima [Ames Laboratory (AMES), Ames, ↗
DOE OSTI2020

Polyelectrolyte Surface Diffusion in a Nanoslit Geometry

The surface diffusion of poly-l-lysine (PLL) in a planar nanoslit was studied using convex lens-induced confinement (CLiC) single-molecule tracking microscopy. Here, three surface chemistries were employed to understand the interplay of electrostatic and short-range interactions: an amine-functionalized silica surface, an oligo(ethylene oxide) (OEG)-modified surface, and a 1:1 mixture of the two ligands. Effective surface diffusion coefficients increased rapidly with slit height until saturating for slit heights <30 nm. While diffusion at a semi-infinite interface was significantly faster for OEG surfaces, the diffusion coefficient increased most rapidly with slit height for amine-functionalized surfaces, resulting in surface diffusion within very thin slits being nearly independent of surface chemistry. Intermittent random walks were simulated within a planar slit geometry, using experimentally measured parameters obtained from diffusion at a single interface to account for the characteristic short-range interactions between PLL and each surface chemistry, and were in good agreement with experimental measurements.

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

Relating Geometric Nanoconfinement and Local Molecular Environment to Diffusion in Ionic Polymer Membranes

Understanding structure-diffusion relationships in ionic polymer membranes not only illuminates fundamental mechanisms for membrane transport, but also informs further membrane development. In this study, we employ NMR diffusometry and molecular dynamics (MD) simulations to investigate diffusion coefficients and activation energies of diffusion (Ea) for both a lithium-form perfluorosulfonic acid membrane and aqueous solutions of lithium triflate. NMR shows that, at high water/ion molar ratio (?), Ea for water diffusion is slightly lower in the membrane than in solution. Conversely, membrane transport exhibits much higher Ea at low hydration as compared to solutions. MD simulations of a model system consisting of carbon nanotubes with varying diameter reveal that Ea of diffusion clearly relates to both the geometric nanoconfinement of the hydrophilic pathways in the membrane as well as the local molecular environment. These results demonstrate that Ea of diffusion can serve as a revelatory tool for the study of molecular transport processes and the coupling of morphology with transport at the nanoscale. This study thus provides new insights and new experimental and computational models for understanding transport in a wide range of polymer membranes, such as those used in molecular separations applications.

Zhang, Rui↗
DOE OSTI2020

Unifying Advective and Diffusive Descriptions of Bedform Pumping in the Benthic Biolayer of Streams

Abstract Many water quality and ecosystem functions performed by streams occur in the benthic biolayer, the biologically active upper (~5 cm) layer of the streambed. Solute transport through the benthic biolayer is facilitated by bedform pumping, a physical process in which dynamic and static pressure variations over the surface of stationary bedforms (e.g., ripples and dunes) drive flow across the sediment‐water interface. In this paper we derive two predictive modeling frameworks, one advective and the other diffusive, for solute transport through the benthic biolayer by bedform pumping. Both frameworks closely reproduce patterns and rates of bedform pumping previously measured in the laboratory, provided that the diffusion model's dispersion coefficient declines exponentially with depth. They are also functionally equivalent, such that parameter sets inferred from the 2D advective model can be applied to the 1D diffusive model, and vice versa. The functional equivalence and complementary strengths of these two models expand the range of questions that can be answered, for example, by adopting the 2D advective model to study the effects of geomorphic processes (such as bedform adjustments to land use change) on flow‐dependent processes and the 1D diffusive model to study problems where multiple transport mechanisms combine (such as bedform pumping and turbulent diffusion). By unifying 2D advective and 1D diffusive descriptions of bedform pumping, our analytical results provide a straightforward and computationally efficient approach for predicting, and better understanding, solute transport in the benthic biolayer of streams and coastal sediments.

Grant, Stanley B.↗
DOE OSTI2022

Uncovering the hydride ion diffusion pathway in barium hydride via neutron spectroscopy

Solid state materials possessing the ability for fast ionic diffusion of hydrogen have immense appeal for a wide range of energy-related applications. Ionic hydrogen transport research is dominated by proton conductors, but recently a few examples of hydride ion conductors have been observed as well. Barium hydride, BaH 2 , undergoes a structural phase transition around 775 K that leads to an order of magnitude increase in the ionic conductivity. This material provides a prototypical system to understand hydride ion diffusion and how the altered structure produced by the phase transition can have an enormous impact on the diffusion. We employ quasielastic and inelastic neutron scattering to probe the atomic scale diffusion mechanism and vibrational dynamics of hydride ions in both the low- and high-temperature phases. Jump lengths, residence times, diffusion coefficients, and activation energies are extracted and compared to the crystal structure to uncover the diffusion pathways. We find that the hydrogen jump distances, residence times, and energy barriers become reduced following the phase transition, allowing for the efficient conduction of hydride ions through a series of hydrogen jumps of length L = 3.1 Å.

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

The nanocaterpillar's random walk: diffusion with ligand–receptor contacts

Particles with ligand–receptor contacts bind and unbind fluctuating “legs” to surfaces, whose fluctuations cause the particle to diffuse. Quantifying the diffusion of such “nanoscale caterpillars” is a challenge, since binding events often occur on very short time and length scales. Here, in this work, we derive an analytical formula, validated by simulations, for the long time translational diffusion coefficient of an overdamped nanocaterpillar, under a range of modeling assumptions. We demonstrate that the effective diffusion coefficient, which depends on the microscopic parameters governing the legs, can be orders of magnitude smaller than the background diffusion coefficient. Furthermore it varies rapidly with temperature, and reproduces the striking variations seen in existing data and our own measurements of the diffusion of DNA-coated colloids. Our model gives insight into the mechanism of motion, and allows us to ask: when does a nanocaterpillar prefer to move by sliding, where one leg is always linked to the surface, and when does it prefer to move by hopping, which requires all legs to unbind simultaneously? We compare a range of systems (viruses, molecular motors, white blood cells, protein cargos in the nuclear pore complex, bacteria such as Escherichia coli, and DNA-coated colloids) and present guidelines to control the mode of motion for materials design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Abell 1430: A merging cluster with exceptional diffuse radio emission

Diffuse radio emission has been found in many galaxy clusters, predominantly in massive systems which are in the state of merging. The radio emission can usually be classified as relic or halo emission, which are believed to be related to merger shocks or volume-filling turbulence, respectively. Recent observations have revealed radio bridges for some pairs of very close galaxy clusters. The mechanisms that may allow one to explain the high specific density of relativistic electrons, which are necessary to explain the radio luminosity of these bridge regions, have been poorly explored until now. When inspecting the first data release of the LOFAR Two-Metre Sky Survey (LoTSS), we discovered diffuse radio emission in the galaxy cluster Abell 1430. Here, for this work, we aim to determine the dynamical state of the cluster and characterise the diffuse radio emission. We analysed the LoTSS data in detail and complemented them with recent Karl G. Jansky Very Large Array observations in the L-band. To study the dynamical state of the cluster, we analysed XMM-Newton data, Chandra data, and Sloan Digital Sky Survey data. Moreover, we compared our results to clusters extracted from THE THREE HUNDRED PROJECT cosmological simulation. We find that Abell 1430 consists of two components, namely A1430-A and A1430-B, with a mass ratio of about 2:1. The massive component shows diffuse radio emission which can be classified as radio halo which shows a low radio power at 1.4 GHz with respect to the mass of the cluster. Most interestingly, there is extended diffuse radio emission in the following dubbed as the ‘Pillow’ according to its morphology, which is apparently related to A1430-B and which is neither typical halo nor typical relic emission. The origin of this emission is puzzling. We speculate that the two components of Abell 1430 undergo an off-axis merger. In this scenario, A1430-B is moving towards the main cluster component and may have compressed and stirred the medium in the filament between the two cluster components. We have discovered evidence for diffuse radio emission related to the low-density intracluster or intergalactic medium in Abell 1430. To date, only a few examples of emission originating from such regions are known. These discoveries are crucial to constrain possible acceleration mechanisms which may allow us to explain the presence of relativistic electrons in these regions. In particular, our results indicate a spectral index of α 144 MHz 1.5 GHz = -1.4±0.5 for the Pillow. If upcoming observations confirm a slope as flat as -1.4 or even flatter, this would pose a challenge for the electron acceleration scenarios.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Effects of surface diffusion in electrocatalytic CO 2 reduction on Cu revealed by kinetic Monte Carlo simulations

We report Kinetic Monte Carlo (KMC) methods are frequently used for mechanistic studies of thermally driven heterogeneous catalysis systems but are underused for electrocatalysis. Here, we develop a lattice KMC approach for electrocatalytic CO 2 reduction. The work is motivated by a prior experimental report that performed electroreduction of a mixed feed of 12 CO 2 and 13 CO on Cu; differences in the 13 C content of C2 products ethylene and ethanol (Δ 13 C) were interpreted as evidence of site selectivity. The lattice KMC model considers the effect of surface diffusion on this system. In the limit of infinitely fast diffusion (mean-field approximation), the key intermediates 12 CO* and 13 CO* would be well mixed on the surface and no evidence of site selectivity could have been observed. Using a simple two-site model and adapting a previously reported microkinetic model, we assess the effects of diffusion on the relative isotope fractions in the products using the estimated surface diffusion rate of CO* from literature reports. We find that the size of the active sites and the total surface adsorbate coverage can have a large influence on the values of Δ 13 C that can be observed. Δ 13 C is less sensitive to the CO* diffusion rate as long as it is within the estimated range. We further offer possible methods to estimate surface distribution of intermediates and to predict intrinsic selectivity of active sites based on experimental observations. This work illustrates the importance of considering surface diffusion in the study of electrochemical CO 2 reduction to multi-carbon products. Our approach is entirely based on a freely available open-source code, so will be readily adaptable to other electrocatalytic systems.

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

Simulation study of the effects of polymer network dynamics and mesh confinement on the diffusion and structural relaxation of penetrants

The diffusion of small molecular penetrants through polymeric materials represents an important fundamental problem, relevant to the design of materials for applications such as coatings and membranes. Polymer networks hold promise in these applications because dramatic differences in molecular diffusion can result from subtle changes in the network structure. In this paper, we use molecular simulation to understand the role that cross-linked network polymers have in governing the molecular motion of penetrants. By considering the local, activated alpha relaxation time of the penetrant and its long-time diffusive dynamics, we can determine the relative importance of activated glassy dynamics on penetrants at the segmental scale vs entropic mesh confinement on penetrant diffusion. We vary several parameters, such as the cross-linking density, temperature, and penetrant size, to show that cross-links primarily affect molecular diffusion through the modification of the matrix glass transition, with local penetrant hopping at least partially coupled to the segmental relaxation of the polymer network. This coupling is very sensitive to the local activated segmental dynamics of the surrounding matrix, and we also show that penetrant transport is affected by dynamic heterogeneity at low temperatures. To contrast, only at high temperatures and for large penetrants or when the dynamic heterogeneity effect is weak, does the effect of mesh confinement become significant, even though penetrant diffusion more broadly empirically follows similar trends as established models of mesh confinement-based transport.

Chemistry↗
DOE OSTI2025

Translational diffusion in supercooled water at and near the glass transition temperature—136 K

The properties of amorphous solid water at and near the calorimetric glass transition temperature, T g , of 136 K have been debated for years. One hypothesis is that water turns into a “true” liquid at T g (i.e., it becomes ergodic) and exhibits all the characteristics of an ergodic liquid, including translational diffusion. A competing hypothesis is that only rotational motion becomes active at T g , while the “real” glass transition in water is at a considerably higher temperature. To address this dispute, we have investigated the diffusive mixing in nanoscale water films, with thicknesses up to ∼100 nm, using infrared (IR) spectroscopy. The experiments used films that were composed of at least 90% H 2 O with D 2 O making up the balance and were conducted under conditions where H/D exchange was essentially eliminated. Because the IR spectra of multilayer D 2 O films (e.g., thicknesses of ∼3–6 nm) embedded within thick H 2 O films are distinct from the spectrum of isolated D 2 O molecules within H 2 O, the diffusive mixing of (initially) isotopically layered water films could be followed as a function of annealing time and temperature. The results show that water films with total thicknesses ranging from ∼20 to 100 nm diffusively mixed prior to crystallization for temperatures between 120 and 144 K. The translational diffusion had an Arrhenius temperature dependence with an activation energy of 40.8 ± 3.5 kJ/mol, which indicates that water at and near T g is a strong liquid. The measured diffusion coefficient at 136 K is 6.25 ± 1.4 × 10 −21 m 2 /s.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Molecular dynamics based study on the effects of cation size on the local structure and diffusion in polymerized ionic liquids

We have used coarse-grained molecular dynamics simulations to understand the effect of cation size on ion diffusion in polymerized ionic liquids at temperatures well above the glass transition temperature of the polymers. We investigated dependencies of the diffusion constant on the cation radius and static dielectric constant and interpreted these results in terms of underlying structural changes, and decoupling phenomenon. We have found non-monotonic effects of the cation radius on the diffusion constant, with a maximum at an intermediate radius resulting from two different size dependent effects. Changes in the radial distribution functions characterizing spatial distribution of cations with respect to anions result in a monotonic increase in the coordination number. This yields an increase in the effective interaction energy as a function of cation radius, which can explain the decrease in the diffusion constant. This increase is counteracted at small cation radii by a corresponding increase in decoupling of cation and anion dynamics. In addition, the diffusion constant is found to increase on increasing the static dielectric constant for all radii of the cations. These results highlight the significant role of decoupling in designing polymerized ionic liquids with an enhanced diffusion constant of cations.

Gillespie, Colin [ORNL] (ORCID:0000000320287080)↗
DOE OSTI2024

Simulating hindered grain boundary diffusion using the smoothed boundary method

Abstract Grain boundaries can greatly affect the transport properties of polycrystalline materials, particularly when the grain size approaches the nanoscale. While grain boundaries often enhance diffusion by providing a fast pathway for chemical transport, some material systems, such as those of solid oxide fuel cells and battery cathode particles, exhibit the opposite behavior, where grain boundaries act to hinder diffusion. To facilitate the study of systems with hindered grain boundary diffusion, we propose a model that utilizes the smoothed boundary method to simulate the dynamic concentration evolution in polycrystalline systems. The model employs domain parameters with diffuse interfaces to describe the grains, thereby enabling solutions with explicit consideration of their complex geometries. The intrinsic error arising from the diffuse interface approach employed in our proposed model is explored by comparing the results against a sharp interface model for a variety of parameter sets. Finally, two case studies are considered to demonstrate potential applications of the model. First, a nanocrystalline yttria-stabilized zirconia solid oxide fuel cell system is investigated, and the effective diffusivities are extracted from the simulation results and are compared to the values obtained through mean-field approximations. Second, the concentration evolution during lithiation of a polycrystalline battery cathode particle is simulated to demonstrate the method’s capability.

Materials Science↗
DOE OSTI2022

Eddy diffusivity operator in homogeneous isotropic turbulence

Here, we use the recently developed macroscopic forcing method to compute the scale-dependent eddy diffusivity characterizing ensemble-averaged scalar and momentum transport in incompressible homogeneous isotropic turbulence. For scales larger than the energy containing eddies, eddy diffusivity is found to be constant and consistent with the Boussinesq approximation. However, for small scales eddy diffusivity is found to vanish inversely proportional to the wave number. Behavior at all scales is reasonably captured by a nonlocal eddy diffusivity operator modeled as D/$\sqrt{I - l^2∇^2}$, where D is the eddy diffusivity in the Boussinesq limit, and l is a constant on the order of the large-eddy length. These results present a direct measurement of eddy diffusivity in turbulence with implications in turbulence modeling.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

In situ counter-diffusion crystallization and long-term crystal preservation in microfluidic fixed targets for serial crystallography

Compared with batch and vapor diffusion methods, counter diffusion can generate larger and higher-quality protein crystals yielding improved diffraction data and higher-resolution structures. Typically, counter-diffusion experiments are conducted in elongated chambers, such as glass capillaries, and the crystals are either directly measured in the capillary or extracted and mounted at the X-ray beamline. Despite the advantages of counter-diffusion protein crystallization, there are few fixed-target devices that utilize counter diffusion for crystallization. In this article, different designs of user-friendly counter-diffusion chambers are presented which can be used to grow large protein crystals in a 2D polymer microfluidic fixed-target chip. Methods for rapid chip fabrication using commercially available thin-film materials such as Mylar, propylene and Kapton are also detailed. Rules of thumb are provided to tune the nucleation and crystal growth to meet users' needs while minimizing sample consumption. These designs provide a reliable approach to forming large crystals and maintaining their hydration for weeks and even months. This allows ample time to grow, select and preserve the best crystal batches before X-ray beam time. Importantly, the fixed-target microfluidic chip has a low background scatter and can be directly used at beamlines without any crystal handling, enabling crystal quality to be preserved. The approach is demonstrated with serial diffraction of photoactive yellow protein, yielding 1.32 Å resolution at room temperature. Fabrication of this standard microfluidic chip with commercially available thin films greatly simplifies fabrication and provides enhanced stability under vacuum. These advances will further broaden microfluidic fixed-target utilization by crystallographers.

Liu, Zhongrui↗
DOE OSTI2024

Constrained Local Approximate Ideal Restriction for Advection-Diffusion Problems

Herein this paper focuses on developing a reduction-based algebraic multigrid (AMG) method that is suitable for solving general (non)symmetric linear systems and is naturally robust from pure advection to pure diffusion. Initial motivation comes from a new reduction-based AMG approach, $\ell \text{AIR}$ (local approximate ideal restriction), that was developed for solving advection-dominated problems. Though this new solver is very effective in the advection-dominated regime, its performance degrades in cases where diffusion becomes dominant. This is consistent with the fact that in general, reduction-based AMG methods tend to suffer from growth in complexity and/or convergence rates as the problem size is increased, especially for diffusion-dominated problems in two or three dimensions. Motivated by the success of $\ell \text{AIR}$ in the advective regime, our aim in this paper is to generalize the AIR framework with the goal of improving the performance of the solver in diffusion-dominated regimes. To do so, we propose a novel way to combine mode constraints as used commonly in energy-minimization AMG methods with the local approximation of ideal operators used in $\ell \text{AIR}$. The resulting constrained $\ell \text{AIR}$ algorithm is able to achieve fast scalable convergence on advective and diffusive problems. In addition, it is able to achieve standard low complexity hierarchies in the diffusive regime through aggressive coarsening, something that was previously difficult for reduction-based methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Calibration of the Diffusivity Predictions of Centipede Using Approximate Bayesian Computation and Applications in Nyx (Engineering Scale) and Xolotl-MARMOT (Meso-Scale) Simulations

Fission gas evolution and release in UO 2 nuclear fuel are important fuel performance metrics and occur in several distinct stages: 1) nucleation, growth and resolution of intra-granular bubbles, 2) diffusion to grain boundaries and 3) nucleation and growth of bubbles at grain boundaries, which eventually form a connected network (percolation) enabling release of gas from grain boundaries through connections to triple junctions, grain edges or free surfaces. The NE-SciDAC project is developing several computational tools to model this problem, which are connected in a hierarchical multi-scale framework. The information transfer in the multi-scale framework is a critical step that, in addition to best-estimates, should include uncertainty quantification. Despite taking a first-principles multi-scale approach, there is a need to perform parameter calibration to ensure consistency with available experimental data. In the present study, uncertainty quantification (UQ) and parameter calibration is demonstrated for one of the lower length scale codes in the multi-scale framework (Centipede) and then the results, including instances of the propagated uncertainties, are used in other codes within the framework, specifically Nyx and Xolotl-MARMOT. We calibrated the model parameters in Centipede, a computer code used to predict diffusivities of uranium (U) and xenon (Xe) in the context of the simulation of fission gas in uranium oxide (UO 2 ) nuclear fuel. The Centipede code depends on 183 parameters, all of which are subject to uncertainty. The three data sets used in our calibration effort are taken from the literature. This data is available as a set of measurements, including measurement errors. Our goal is to calibrate a statistical model that predicts both the value of the measurement and the uncertainty associated with the measurement. We perform a Bayesian calibration of the model parameters using a dedicated approximate Bayesian computation (ABC) likelihood function. To avoid excessive computational costs, we replace the expensive Centipede simulation code by a higher-order surrogate model, constructed using only the 9 most important parameters. These important parameters are identified by a preliminary global sensitivity analysis (GSA) study. Among the important parameters are T0 (the temperature at which UO 2 is perfectly stoichiometric) and Hf_pO2 (the temperature dependence of the oxygen (O) partial pressure) that should be considered as operating conditions to be estimated along with the other parameters. We consider two different cases: one where we define one set of these operating conditions for all data sets, and one where we define distinct operating condition parameters for each data set. The Xe diffusivities predicted by the latter case show distinct features that could not be observed in the former. Next, we use the diffusivity predictions by Centipede as input to Nyx, a reduced order fuel performance code focused on gas behavior alone, in order to estimate quantities associated with inter-granular bubble formation at conditions specified by the experiments. Finally, the diffusivities obtained from the calibrated Centipede runs were used in coupled Xolotl-MARMOT simulations of intra- and inter-granular gas evolution. The results are compared to simulations using the baseline diffusivities from Turnbull et al.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Molecular dynamics simulations of fission gas xenon (Xe) diffusion at UO 2 grain-boundaries (Rev.1)

The diffusivity of fission gas xenon (Xe) at UO 2 grain-boundaries is one of the most important parameters in mechanistic modeling of fission gas diffusion in UO 2 based nuclear fuels. In this report, we use molecular dynamics simulations to investigate the Xe diffusivity in UO 2 grain-boundaries, employing the many-body potential developed by Cooper, Rushton and Grimes for UO 2 . Three different types of grain-boundaries are investigated, twist Σ5, tilt Σ5, and a random grain-boundary. Diffusion activation energies in the range of 0.39 – 1.46 eV are obtained for the Xe diffusivity. Comparison to results for the uranium vacancy diffusivity from MD simulations employing the same methodology suggests a weak to moderate attractive Xe-uranium vacancy binding energy depending on the grain-boundary type.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Solar-Tracker Diffuse-Response Algorithm for Balancing Energy Gain and Mechanical Wear in Photovoltaic Systems

Single-axis solar tracking maximizes photovoltaic energy production under clear-sky conditions; however, its effectiveness decreases under cloudy and overcast skies, where diffuse irradiance dominates and the optimal module orientation changes. Conventional tracking algorithms either neglect sky conditions or rely on simplified diffuse-response strategies that may trigger frequent tracker repositioning under variable cloud cover, leading to increased mechanical wear with marginal energy gains. This work proposes an enhanced diffuse-response tracking algorithm that explicitly accounts for both the intensity and temporal persistence of cloudiness. By requiring overcast conditions to persist for a minimum duration before reorienting the tracker to a diffuse-stow position, the proposed approach reduces unnecessary movements while preserving the benefits of diffuse-response operation. The algorithm is evaluated through numerical simulations based on historical meteorological data and validated using field measurements on monofacial and bifacial photovoltaic strings. The results show that the proposed strategy reduces excess tracker movement from 114% to 0.16% while maintaining nearly the same energy yield. Compared to a conventional diffuse-response algorithm, the associated energy reduction is minimal (≈0.17%) relative to the ≈0.37% yield gain observed at the studied location. These findings demonstrate that incorporating cloudiness duration enables a practical compromise between energy performance and tracker durability, particularly for monofacial photovoltaic systems.

14 SOLAR ENERGY↗