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At least 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Enhanced Boundary Layer Height Detection Using Ceilometer, Surface Meteorology, and Radiation Products With a Random Forest Ensemble Method

This study develops and evaluates a Random Forest (RF) model for estimating planetary boundary layer height (PBLH) using 9 years of data from the Atmospheric Radiation Measurement Southern Great Plains (ARM SGP) user facility, with potential application in the NOAA Surface Radiation (SURFRAD) Network. The model integrates ceilometer, surface meteorology, and radiation measurements, and is trained using thermodynamic PBLH estimates derived from radiosondes. This approach aims to bridge gaps between aerosol-based and thermodynamic-based PBLH estimates. The RF model outperformed traditional methods during daytime and better captured transition periods, demonstrating improved accuracy and robustness. At ARM SGP, it showed a substantial reduction in both bias and RMSE, with a bias near zero (−4.9 m) compared with traditional Haar Wavelet (HW) (70.9 m) and Vaisala BL-View software (124.1 m), and an RMSE of 303.2 m, lower than both BL-View (566.9 m) and HW (404.6 m). During daytime hours, RF consistently outperformed both alternatives, maintaining lower bias and RMSE across all periods. At a second evaluation site, RF achieved the lowest overall RMSE (323.7 m), similar to HW (326.4 m) and significantly better than BL-View (738.3 m). However, all models showed reduced accuracy under stable nighttime conditions, limiting the reliability of PBLH estimates. Key predictors for the model included the lifting condensation level height (LCLH), aerosol gradients, and month for seasonal variability. The study underscores the potential of integrating machine learning with multiple data sets such as surface energy and thermodynamic data to advance PBLH estimation.

boundary layer height↗
DOE OSTI2025

Maximizing quantum enhancement in axion dark matter experiments

We provide a comprehensive comparison of linear amplifiers and microwave photon counters in axion dark matter experiments. The study is done assuming a range of realistic operating conditions and detector parameters, over the frequency range between 1 and 30 GHz. As expected, photon counters are found to be advantageous under low background, at high frequencies (𝜈 >5 GHz), if they can be implemented with robust wide-frequency tuning or a very low dark count rate. Additional noteworthy observations emerging from this study include: (1) an expanded applicability of off-resonance photon background reduction, including the single-quadrature state squeezing, for scan rate enhancements; (2) a much broader appeal for operating the haloscope resonators in the overcoupling regime, up to 𝛽 ∼10; (3) the need for a detailed investigation into the cryogenic and electromagnetic conditions inside haloscope cavities to lower the photon temperature for future experiments; (4) the necessity to develop a distributed network of coupling ports in high-volume axion haloscopes to utilize these potential gains in the scan rate.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Rare Earth Elements Alter Redox Balance in Methylomicrobium alcaliphilum 20Z R

Background: Rare Earth Elements (REEs) control methanol utilization in both methane- and methanol-utilizing microbes. It has been established that the addition of REEs leads to the transcriptional repression of MxaFI-MeDH (a two-subunit methanol dehydrogenase, calcium-dependent) and the activation of XoxF-MeDH (a one-subunit methanol dehydrogenase, lanthanumdependent). Both enzymes are pyrroquinoline quinone-dependent alcohol dehydrogenases and show significant homology; however, they display different kinetic properties and substrate specificities. This study investigates the impact of the MxaFI to XoxF switch on the behavior of metabolic networks at a global scale. Results: In this study we investigated the steady-state growth of Methylomicrobium alcaliphilum 20Z R in media containing calcium (Ca) or lanthanum (La, a REE element). We found that cells supplemented with La show a higher growth rate compared to Ca-cultures; however, the efficiency of carbon conversion, estimated as biomass yield, is higher in cells grown with Ca. Three complementary global-omics approaches—RNA-seq transcriptomics, proteomics, and metabolomics—were applied to investigate the mechanisms of improved growth vs carbon conversion. Cells grown with La showed the transcriptional activation of the xoxF gene, a homologue of the formaldehyde-activating enzyme (fae2), a putative transporter, genes for hemin-transport proteins, and nitrate reductase. In contrast, genes for mxaFI and associated cytochrome (mxaG) expression were downregulated. Proteomic profiling suggested additional adjustments of the metabolic network at the protein level, including carbon assimilation pathways, electron transport systems, and the tricarboxylic acid (TCA) cycle. Discord between gene expression and protein abundance changes points toward the possibility of post-transcriptional control of the related systems including key enzymes of the TCA cycle and a set of electron-transport carriers. Metabolomic data followed proteomics and showed the reduction of the ribulosemonophosphate (RuMP) pathway intermediates and the increase of the TCA cycle metabolites. Conclusions: Cells exposed to REEs display higher rates of growth but have lower carbon conversion efficiency compared to cells supplemented with Ca. The most plausible explanation for these physiological changes is an increased conversion of methanol into formate by XoxF-MeDH, which further stimulates methane oxidation but limits both the supply of reducing power and flux of formaldehyde into the RuMP pathway.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1991

The behavior of forecast error covariances for a Kalman filter in two dimensions

The behavior of forecast error covariances in a fairly realistic setting is demonstrated via a Kalman filter algorithm. It is used to assimilate simulated data from the existing radiosonde network, from the demonstration network of 31 Doppler wind profilers in the central U.S., and from hypothetical radiometers located at five of the profiler sites. Some theoretical justification of the hypothesis advanced by Phillips (1982), and the hypothesis is used to formulate the model error covariance matrix required by the Kalman filter. The results show that assimilating the profiler wind data leads to a large reduction of forecast/analysis error in heights as well as in winds, over the profiler region and also downstream, when compared with the results of assimilating the radiosonde data alone. The forecast error covariance matrices that the Kalman filter calculates to obtain this error reduction differ considerably from those prescribed by the optimal interpolation schemes that are employed for data assimilation at operational centers.

Cohn, Stephen E.↗
NASA NTRS2022

Climate Change-Induced Peatland Drying in Southeast Asia

When organic peat soils are sufficiently dry, they become flammable. In Southeast Asian peatlands, widespread deforestation and associated drainage create dry conditions that, when coupled with El Niño-driven drought, result in catastrophic fire events that release large amounts of carbon and deadly smoke to the atmosphere. While the effects of anthropogenic degradation on peat moisture and fire risk have been extensively demonstrated, climate change impacts to peat flammability are poorly understood. These impacts are likely to be mediated primarily through changes in soil moisture. Here, we used neural networks (trained on data from the NASA Soil Moisture Active Passive satellite) to model soil moisture as a function of climate, degradation, and location. The neural networks were forced with regional climate model projections for 1985–2005 and 2040–2060 climate under RCP8.5 forcing to predict changes in soil moisture. We find that reduced precipitation and increased evaporative demand will lead to median soil moisture decreases about half as strong as those observed during recent El Niño droughts in 2015 and 2019. Based on previous studies, such reductions may be expected to accelerate peat carbon emissions. Our results also suggest that soil moisture in degraded areas with less tree cover may be more sensitive to climate change than in other land use types, motivating urgent peatland restoration. Climate change may play an important role in future soil moisture regimes and by extension, future peat fire in Southeast Asian peatlands.

VIIRS↗
DOE OSTI2024

Control and Optimization of Energy Storage System in Power Distribution System

The widespread adoption of electric vehicles (EVs) and transportation electrification is encumbered by two chief barriers: i) the limited driving range of EVs in the market today and ii) inadequate fast-charging infrastructure for long-distance trips. Extreme fast charging (XFC) technology can recharge EVs in less than 10 minutes for 200 miles range. Firstly, a novel robust optimization-based mixed integer linear programming model is proposed to size a battery energy storage system (BESS) and PV system in an XFCS. In this part, it is assumed that the sizing and location of the XFCS are known. Secondly, the aforesaid assumption is relaxed, and a strategic multi-period coordinated planning model is proposed to optimally site and size BESS-assisted charging stations in a highway transportation network and PV systems in a power distribution network by considering the coupling between both networks. Optimal operation and control of BESS-assisted EV charging stations are vital to alleviate the adverse impact of extreme fast charging of EVs on the host power network. A joint solution is proposed to mitigate the steady state and transient impact of extremefast charging of EVs and ensure grid-friendly integration of XFCSs with the host grid. Lastly, to make the operation of the XFCS cost-effective, a multi-layered energy management framework is proposed for the XFCS by considering forecast uncertainties, monthly demand charges reduction, and BESS degradation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2000

Deconditioning and Reconditioning: Humans in Stressful Environments

Deconditioning is an integrated physiological response of the body to a reduction in metabolic rate; that is, to a reduction in energy use or in exercise level. While it may involve assumption of a horizontal body position, it certainly perturbs bodily homeostasis - at least temporarily. The reduction in physical activity that causes deconditioning is often associated with an increase in the time spent, for whatever reason, in a sitting or horizontal position. As a result, orthostatic factors may also contribute to the deconditioning mechanism. The word decondition may be defined as "1: to cause extinction of (a conditioned response) 2: to cause to lose physical fitness". This definition implies that psychological/emotional factors may accompany physical deconditioning, and it is this interpretation of the word that is used throughout this volume. It is apparent that deconditioning plays a major role in the mechanism of the general adaptive (homeostatic) response that is initiated by exposure to prolonged bed rest (BR). And the total homeostatic response to BR involves more than deconditioning per se. For example, it has been shown that the restoration of plasma volume and maximal work capacity after 4 weeks of BR deconditioning left other bodily functions (submaximal exercise oxygen uptake and cardiac output, leg proprioception and posterior leg muscle thickness and volume, head-up tilt tolerance, and sleep quality) functioning at decreased levels. The precise effect of deconditioning on BR homeostasis is difficult to determine, because the fundamental interactive neuro-endocrine-immune control networks that facilitate conditioning and deconditioning also act to maintain basic wholebody homeostasis. For example, is the mechanism of BR-induced deconditioning independent of the mechanism that provokes concomitant orthostatic intolerance; that is, fainting? Assumption of the recumbent body position for prolonged periods of time, results in a new adaptive-homeostatic state. This state occurs in response to the mutually interactive effects of the change in bodily position (hydrostatic pressure), to the virtual elimination of longitudinal pressure on the bones, to the increased confinement with possible reduction in total daily energy (exercise) expenditure, to the reorientation of stimuli within the vestibular organs, and (often) to altered socio-psychological conditions. The exercise-training (reconditioning) syndrome affects total body homeostasis by facilitating increases in work capacity and endurance, whereas deconditioning decreases physical performance. There are many interrelated factors that influence the control parameters that seek to maintain the adaptive conditioning-deconditioning syndrome. These control parameters can be better elucidated by subjecting otherwise healthy ambulatory people to various stresses, such as exercise training and prolonged spaceflight, bed rest, water immersion, hyperbaria, and isolation and confinement. Changes in control parameters will be manifested in muscle function, orthostatic tolerance, cardiorespiratory responses, musculo-skeletal systems, free-radical processes, and body thermoregulation with overarching effects on the subjects' psycho-sociological states. A discussion of these factors and the control parameters constitutes the substance of this volume. Special emphasis is placed on delineating practical applications of the findings that will be of special interest to physicians, nurses, and other health-care workers.

Greenleaf, John E.↗
DOE OSTI2015

Model reduction for stochastic chemical systems with abundant species

Biochemical processes typically involve many chemical species, some in abundance and some in low molecule numbers. We first identify the rate constant limits under which the concentrations of a given set of species will tend to infinity (the abundant species) while the concentrations of all other species remains constant (the non-abundant species). Subsequently, we prove that, in this limit, the fluctuations in the molecule numbers of non-abundant species are accurately described by a hybrid stochastic description consisting of a chemical master equation coupled to deterministic rate equations. This is a reduced description when compared to the conventional chemical master equation which describes the fluctuations in both abundant and non-abundant species. We show that the reduced master equation can be solved exactly for a number of biochemical networks involving gene expression and enzyme catalysis, whose conventional chemical master equation description is analytically impenetrable. We use the linear noise approximation to obtain approximate expressions for the difference between the variance of fluctuations in the non-abundant species as predicted by the hybrid approach and by the conventional chemical master equation. Furthermore, we show that surprisingly, irrespective of any separation in the mean molecule numbers of various species, the conventional and hybrid master equations exactly agree for a class of chemical systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Predicting the quantifiable impacts of ISO 50001 on climate change mitigation

The ISO 50001-Energy management standard provides a continual improvement framework for organizations to reduce their energy consumption, which in the industrial and commercial (service) sectors, accounts for nearly 40% of global greenhouse gas emissions. Reducing this energy consumption will be critical for countries to achieve their national greenhouse gas reduction commitments. Several national policies already support ISO 50001; however, there is no transparent, consistent process to estimate the potential impacts of its implementation. This paper presents the ISO 50001 Impacts Methodology, an internationally-developed methodology to calculate these impacts at a national, regional, or global scale suitable for use by policymakers. The recently-formed ISO 50001 Global Impacts Research Network provides a forum for policymakers to refine and encourage use of the methodology. Using this methodology, a scenario with 50% of projected global industrial and service sector energy consumption under ISO 50001 management by 2030 would generate cumulative primary energy savings of approximately 105 EJ, cost savings of nearly US $700 billion (discounted to 2016 net present value), and 6500 million metric tons (Mt) of avoided CO 2 emissions. The avoided annual CO 2 emissions in 2030 alone are equivalent to removing 210 million passenger vehicles from the road.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2014

Micromechanisms of grain refinement during extrusion of Mg–0.3 at.% Al at low homologous temperature

Coarse grained Mg–0.3 at.% Al (0.33 in wt.%) alloy was processed by direct extrusion with a reduction ratio of 25:1 at a temperature of ∼ 433 K. The extrusion remainder was removed from the die and analysed in three distinct zones: the cast billet, the conical zone of extrusion die, and the as-extruded rod. The zones were characterized by electron backscatter diffraction (EBSD) and light microscopy techniques to identify the processes responsible for grain refinement. Complex networks of (10–12) twins in practically all grains produced a noticeable microstructural fragmentation even before the material reached the conical zone of the die. Deformation twinning extended up to the entrance zone of the conical die where it was followed by a continuous dynamic recrystallization (CDRX) that gradually changed low angle boundaries to high angle boundaries. It is apparent that geometrically necessary dislocations play a crucial role in the formation of new grain boundaries. CDRX results in a bimodal structure with grain diameters ∼ 3 and ∼ 30 μm. As a material flows through the conical zone, the ratio of large to small grains is progressively decreased by CDRX in favour of fine grains. The as-extruded microstructure (a rod 8 mm in diameter), with an average grain diameter of ∼ 2.1 μm, shows a strong texture where the vast majority of grains (99.99%) have the c-axis oriented at least 30° from the extrusion direction. - Highlights: • Coarse grained Mg–0.3 at.% Al alloy was extruded at temperature of ∼ 433 K. • Processes responsible for grain refinement were analysed in extrusion remainder. • In the first stage, complex (10–12) twinning produced a noticeable fragmentation. • Deformation twinning was followed by continuous dynamic recrystallization. • 99.99% of grains in extruded rod have c-axis oriented > 30° from extrusion direction.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Electronic, structural, and substrate effect properties of single-layer covalent organic frameworks

Recently synthesized two-dimensional covalent organic frameworks (COFs) exhibit high surface area, large pore size, and unique structural architectures, making them promising materials for various energy applications. Here, a total of nine COFs structures, including two deposited on a hexagonal boron nitride substrate, are investigated using density functional theory, quasi-particle many-body theory within the GW approximation, and an image charge model. The structures considered belong to two major families (thiophene-based COF-n (T-COF-n) and tetrakis (4-aminophenyl) porphyrin-x (TAPP-x)) differing from the presence of B—O or C=N linkers. While T-COF-n structures are shown to constitute planar networks, TAPP-x systems can display non-negligible corrugation due to the out-of-plane rotation of phenyl rings. We find that the electronic properties do not differ significantly when altering the chain molecules within each family. Many-body effects are shown to lead to large band-gap increase while the presence of the substrate yields appreciable reductions of the gaps, due to substrate polarization effects.

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

Latent Twins

Over the past decade, scientific machine learning has transformed the development of mathematical and computational frameworks for analyzing, modeling, and predicting complex systems. From inverse problems to numerical partial differential equations (PDEs), dynamical systems, and model reduction, these advances have pushed the boundaries of what can be simulated. Yet they have often progressed in parallel, with representation learning and algorithmic solution methods evolving largely as separate pipelines. With Latent Twins, we propose a unifying mathematical framework that creates a hidden surrogate in latent space for the underlying equations. Whereas digital twins mirror physical systems in the digital world, Latent Twins mirror mathematical systems in a learned latent space governed by operators. Through this lens, classical modeling, inversion, model reduction, and operator approximation all emerge as special cases of a single principle. We establish the fundamental approximation properties of Latent Twins for both ordinary differential equations (ODEs) and PDEs and demonstrate the framework across three representative settings: (i) canonical ODEs, capturing diverse dynamical regimes; (ii) a PDE benchmark using the shallow-water equations, contrasting Latent Twin simulations with deep operator network and forecasts with a four-dimensional variational method baseline; and (iii) a challenging real-data geopotential reanalysis dataset, reconstructing and forecasting from sparse, noisy observations. Latent Twins provide a compact, interpretable surrogate for solution operators that evaluate across arbitrary time gaps in a single-shot, while remaining compatible with scientific pipelines such as assimilation, control, and uncertainty quantification. Looking forward, this framework offers scalable, theory-grounded surrogates that bridge data-driven representation learning and classical scientific modeling across disciplines.

Latent Twins↗
DOE OSTI2013

Building Scalable PGAS Communication Subsystem on Blue Gene/Q

This paper presents a design of scalable Partitioned Global Address Space (PGAS) communication subsystems on recently proposed Blue Gene/Q architecture. The proposed design provides an in-depth modeling of communication infrastructure using Parallel Active Messaging Interface (PAMI). The communication infrastructure is used to design time-space efficient communication protocols for frequently used data-types (contiguous, uniformly non-contiguous) using Remote Direct Memory Access (RDMA) get/put primitives. The proposed design accelerates load balance counters by using asynchronous threads, which are required due to the missing network hardware support for Atomic Memory Operations (AMOs). Under the proposed design, the synchronization traffic is reduced by tracking conflicting memory accesses in distributed space with slightly increment in space complexity. An evaluation with simple communication benchmarks show a adjacent node get latency of 2.89$\mu$s and peak bandwidth of 1775 MB/s resulting in $\approx$ 99\% communication efficiency.The evaluation shows a reduction in the execution time by up to 30\% for NWChem self consistent field calculation on 4096 processes using the proposed asynchronous thread based design.

Vishnu, Abhinav↗
DOE OSTI2025

PCOR partnership initiative to accelerate CCCUS deployment

The Plains CO 2 Reduction (PCOR) Partnership Initiative, led by the Energy & Environmental Research Center (EERC), was a 5-year collaborative effort under the U.S. Department of Energy’s Regional Initiative to Accelerate CCUS (carbon capture, utilization, and storage). With support from the University of Wyoming School of Energy Resources (UW SER), the University of Alaska Fairbanks Institute of Northern Engineering (UAF INE), and a broad network of public and private stakeholders, the program focused on overcoming regional challenges to CCUS across ten U.S. states and four Canadian provinces. This report summarizes the notable findings of the EERC and its collaborators through the 5-year PCOR Partnership Initiative phase. The EERC developed and demonstrated a risk-based area of review (AOR) workflow for U.S. Environmental Protection Agency Class VI carbon dioxide (CO 2 ) storage permitting.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS2009

Solar Thermal Vacuum Test of Deployable Astromesh Reflector

On September 10, 2008, a 36-hour Solar Thermal Vacuum Test of a 5m deployable mesh reflector was completed in JPL's 25' Space Simulator by the Advanced Deployable Structures Group at JPL. The testing was performed under NASA's Innovative Partnership Program (IPP) as a risk reduction effort for two JPL Decadal Survey Missions: DESDynI and SMAP. The 5.0 m aperture Astromesh reflector was provided by Northrop Grumman Aerospace Systems (NGAS) Astro Aerospace, our IPP industry partner. The testing utilized a state-of-the-art photogrammetry system to measure deformation of the reflector under LN2 cold soak, 0.25 Earth sun, 0.5 sun and 1.0 sun. An intricate network of thermocouples (approximately 200 in total) was used to determine the localized temperature across the mesh as well as on the perimeter truss of the reflector. Half of the reflector was in a fixed shadow to maximize thermal gradients. A mobility system was built for remotely actuating the cryo-vacuum capable photogrammetry camera around the circumference of the Solar Simulator. Photogrammetric resolution of 0.025 mm RMS (0.001") was achieved over the entire 5 meter aperture for each test case. The data will be used for thermo-elastic model correlation and validation, which will benefit the planned Earth Science Missions.

Photogrammetry↗
DOE OSTI2022

Deep Convolutional Neural Networks Exploit High-Spatial- and -Temporal-Resolution Aerial Imagery to Phenotype Key Traits in Miscanthus

Miscanthus is one of the most promising perennial crops for bioenergy production, with high yield potential and a low environmental footprint. The increasing interest in this crop requires accelerated selection and the development of new screening techniques. New analytical methods that are more accurate and less labor-intensive are needed to better characterize the effects of genetics and the environment on key traits under field conditions. We used persistent multispectral and photogrammetric UAV time-series imagery collected 10 times over the season, together with ground-truth data for thousands of Miscanthus genotypes, to determine the flowering time, culm length, and biomass yield traits. We compared the performance of convolutional neural network (CNN) architectures that used image data from single dates (2D-spatial) versus the integration of multiple dates by 3D-spatiotemporal architectures. The ability of UAV-based remote sensing to rapidly and non-destructively assess large-scale genetic variation in flowering time, height, and biomass production was improved through the use of 3D-spatiotemporal CNN architectures versus 2D-spatial CNN architectures. The performance gains of the best 3D-spatiotemporal analyses compared to the best 2D-spatial architectures manifested in up to 23% improvements in R2, 17% reductions in RMSE, and 20% reductions in MAE. The integration of photogrammetric and spectral features with 3D architectures was crucial to the improved assessment of all traits. In conclusion, our findings demonstrate that the integration of high-spatiotemporal-resolution UAV imagery with 3D-CNNs enables more accurate monitoring of the dynamics of key phenological and yield-related crop traits. This is especially valuable in highly productive, perennial grass crops such as Miscanthus, where in-field phenotyping is especially challenging and traditionally limits the rate of crop improvement through breeding.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Reduction of detection limit and quantification uncertainty due to interferent by neural classification with abstention

Many measurements in the physical sciences can be cast as counting experiments, where the number of occurrences of a physical phenomenon informs the prevalence of the phenomenon's source. Often, detection of the physical phenomenon (termed signal) is difficult to distinguish from naturally occurring phenomena (termed background). In this case, the discrimination of signal events from background can be performed using classifiers, and they may range from simple, threshold-based classifiers to sophisticated neural networks. These classifiers are often trained and validated to obtain optimal accuracy, however we show that the optimal accuracy classifier does not generally coincide with a classifier that provides the lowest detection limit, nor the lowest quantification uncertainty. Here, we present a derivation of the detection limit and quantification uncertainty in the classifier-based counting experiment case. We also present a novel abstention mechanism to minimize the detection limit or quantification uncertainty a posteriori. We illustrate the method on two data sets from the physical sciences, discriminating Ar-37 and Ar-39 radioactive decay from non-radioactive events in a gas proportional counter, and discriminating neutrons from gammas in an inorganic scintillator and report results therefrom.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Oxygen reduction reaction induced pH-responsive chemo-mechanical hydrogel actuators

We describe and characterize elementary designs for electrochemical micro- and macro-scale chemomechanical hydrogel actuators. The actuation of a pH-sensitive cross-linked polyacrylic acid (PAA) hydrogel is driven in the model devices through the oxygen reduction reaction (ORR) occurring at the electrodes of an embedded Au mesh micro-electrochemical array. Proton consumption by the ORR at the cathode of the embedded electrochemical cell leads to the formation of a localized pH gradient that in turn drives the strain response in the composite actuators. The dynamics result from the ionization of the carboxylic acid moieties of the PAA network in the high pH region, yielding an osmotic pressure that drives a volumetric expansion due to water imbibition. This system actuates both stably and reversibly; when the electrochemically-induced ORR is halted, the localized pH gradient dissipates due to diffusive mixing, which in turn relaxes the induced strains. Two approaches to the fabrication of hydrogel actuators were examined in this work. The first method adopted a design based on small flagella (~0.2 mm × 1.5 mm × 60 μm, width × length × height) in which the actuating PAA structures are molded atop a set of fixed electrodes mounted on a supporting substrate. These hydrogel actuators show fast, large-amplitude, and largely reversible responses in the ORR mediated chemomechanical dynamics. We also investigated larger hydrogel actuators (~4.5 mm × 11 mm × 1 mm, width × length × height), based on an autonomous design that embeds an open mesh stretchable micro-electrode array within the hydrogel. Furthermore, the significant and design-dependent impacts of mass transfer on the chemomechanical dynamics are evidenced in each case, a feature examined to elucidate more efficient mesoscopic design rules for actuators of this form.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗