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Results for “Stimuli”

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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Combined light- and heat-induced shape memory behavior of anthracene-based epoxy elastomers

Abstract The development of multi-stimuli-responsive shape memory polymers has received increasing attention because of its scientific and technological significance. In this work, epoxy elastomers with reversible crosslinks are synthesized by polymerizing an anthracene-functionalized epoxy monomer, a diepoxy comonomer, and a dicarboxylic acid curing agent. The synthesized elastomers exhibit active responses to both light and heat enabled by the incorporated anthracene groups. When exposed to 365 nm UV light, additional crosslinking points are created by the photo-induced dimerization of pendant anthracene groups. The formation of the crosslinking points increases modulus and glass transition temperature of the elastomers, allowing for the fixation of a temporary shape at room temperature. The temporary shape remains stable until an external heat stimulus is applied to trigger the scission of the dimerized anthracene, which reduces the modulus and glass transition temperature and allows the elastomers to recover their original shapes. The effects of external stimuli on the thermal and dynamic mechanical properties of the elastomers are investigated experimentally and are correlated with molecular dynamics simulations that reveal the changes of structure and dynamics of the anthracene molecules and flexible chains.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Controlled release of entrapped nanoparticles from thermoresponsive hydrogels with tunable network characteristics

Thermoresponsive hydrogels have been studied intensively for creating smart drug carriers and controlled drug delivery. Understanding the drug release kinetics and corresponding transport mechanisms of nanoparticles (NPs) in a thermoresponsive hydrogel network is the key to the successful design of smart drug delivery systems. Here, we construct a mesoscopic model of rigid NPs entrapped in a hydrogel network in an aqueous solution, where the hydrogel network is formed by cross-linked semiflexible polymers of thermoresponsive poly(N-isopropylacrylamide) (PNIPAM). By varying the temperature crossing the lower critical solution temperature of PNIPAM, we can significantly change the hydrogel network characteristics. We systematically investigate how the matrix porosity and the nanoparticle size affect the transport kinetics of NPs at different temperatures. Quantitative results on the mean-squared displacement and the van Hove displacement distributions of NPs show that all NPs entrapped in the smart hydrogels undergo subdiffusion at both low and high temperatures. For a coil state, the transport of NPs in the hydrogels can be enhanced by decreasing the matrix porosity of the polymer network and NPs' size. However, when the solution temperature is increased above the critical temperature, the hydrogel network collapses following the coil-to-globule transition, with the NPs tightly trapped in some local regions inside the hydrogels. Consequently, the NP diffusion coefficient can be reduced by two orders of magnitude, or the diffusion processes can even be completely stopped. These findings provide new insights for designing controlled drug release from stimuli-responsive hydrogels, including autonomously switch on/off drug release in response to physical and chemical stimuli.

42 ENGINEERING↗
DOE OSTI2022

Effect of chemical substitution and external strain on phase stability and ferroelectricity in two dimensional M 2 CT 2 MXenes

Two dimensional ferroelectric materials are gaining increasing attention for use in ultrathin electronic devices owing to the presence of a spontaneous polarization down to one or two monolayers. However, such materials are difficult to identify, especially those with out-of-plane electric polarizations. Previous work predicted that a metastable ferroelectric phase exists in the 2D MXene Sc 2 CO 2 , while further studies have predicted that this phase exists in other MXene chemistries. However, questions remain about the origin of ferroelectricity, the stability of this phase relative to other competing phases, and the effect of external stimuli in these materials. In this work, we use density functional theory calculations to investigate 12 M 2 CT 2 MXenes (M = transition metal, T = surface terminating group) and determine which have the ferroelectric phase as their ground state. We compute these materials’ polarizations, densities of states, phonon band structures, Bader charges, and Born effective charges in the ferroelectric phase to elucidate the reasons for its stabilization. We demonstrate that this ferroelectric phase can be preferentially stabilized in non-ferroelectric MXenes through full chemical substitution of Sc or O, alloying of the Sc sites, or application of epitaxial strain. Finally, we show that these materials have excellent piezoelectric properties as well. This work provides a detailed understanding of ferroelectric MXenes and show how the number of 2D ferroelectric materials can be increased through chemical substitution or application of external stimuli.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Correlating structural changes in thermoresponsive hydrogels to the optical response of embedded plasmonic nanoparticles

Stimuli-responsive microgels, composed of small beads with soft, deformable polymer networks swollen through a combination of synthetic control over the polymer and its interaction with water, form a versatile platform for development of multifunctional and biocompatible sensors. The interfacial structural variation of such materials at a nanometer length scale is essential to their function, but not yet fully comprehended. Here, we take advantage of the plasmonic response of a gold nanorod embedded in a thermoresponsive microgel (AuNR@PNIPMAm) to monitor structural changes in the hydrogel directly near the nanorod surface. By direct comparison of the plasmon response against measurements of the hydrogel structure from dynamic light scattering and nuclear magnetic resonance, we find that the microgel shell of batch-polymerized AuNR@PNIPMAm exhibits a heterogeneous volume phase transition reflected by different onset temperatures for changes in the hydrodyanmic radius (R H ) and plasmon resonance, respectively. The new approach of contrasting plasmonic response (a measure of local surface hydrogel structure) with R H and relaxation times paves a new path to gain valuable insight for the design of plasmonic sensors based on stimuli-responsive hydrogels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Regulating hydrogel mechanical properties with an electric field

Stimuli-responsive polymeric materials have attracted significant attention due to their ability to change properties in response to various external stimuli. Using an electric field as the stimulus is of particular interest as it possesses the potential for seamless integration of materials with electronic systems. While many materials with electric field responsive actuation have an associated mechanical property change, it is beneficial to develop materials that exhibit mechanical property changes without accompanying significant shape deformation. To address this challenge, here we designed a semi-interpenetrating polymer network (semi-IPN) hydrogel system containing both polyelectrolytes and salt ions, which enables electric field induced changes in mechanical properties while minimizing actuation. We first successfully verified the viability of our design by removing salt ions through a diffusion-only method where we witnessed the stiffness increased to 4.5 times the initial value while still being highly deformable. After this, we applied an electric field to transport the salt ions out of the hydrogel, as shown by both Raman spectroscopy and scanning electron microscopy. We were able to show a time-dependent stiffness increase, the maximum of which was 5 times the original stiffness. We quantified ion transport and water-splitting in the hydrogel by both experiments and simulations. Following this, we showed functional system reversibility by reversing the direction of the current to reinject salt ions into the semi-IPN hydrogel and reducing its stiffness to below the initial value. It's worth noting that our simulations enable us to understand the governing mechanisms behind ion generation and salt transport that leads to mechanical property changes. Finally, we were able to fabricate a spatially variable stiffness haptic interface with our hydrogel, with demonstrated reversibility and cyclability. This research can possibly find applications in soft robotics and haptics and also inspire the development of bio-compatible electronics related devices.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Predicting the effects of thermally-induced density gradients on the hydrodynamic behavior of PBX 9502

High explosives are often exposed to thermal and mechanical stimuli within normal and abnormal environments. These stimuli can introduce density gradients in the explosive charge but the effect of such gradients is not well-understood. The goal of this work is to develop a comprehensive methodology to model the evolution of density gradients under various thermal conditions and then to predict shock initiation and detonation behavior of the gradated sample. PBX 9502 was chosen for these scoping studies because it has a large coefficient of thermal expansion and because the available shock initiation data indicates that initial temperature strongly affects the shock-to-detonation transition (SDT). The multiphysics code COMSOL was first used to model induced density gradients in a slab of PBX 9502 with asymmetric heating. Then, the gradated sample was constructed in the Pagosa hydrocode to simulate steel flyer impact scenarios, with SDT and detonation propagation following a calibrated Scaled Uniform Reactive Front (SURF) burn model. Furthermore, the gradated material exhibited very different initiation and corner turning behavior compared to homogeneous materials, and the orientation of the gradation was also found to have some effect. The methodology used here can estimate thermomechanical response of the material for non-uniform thermal environments and compute the resulting detonation properties of the PBX.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

A hybrid optoelectronic Mott insulator

The coupling of electronic degrees of freedom in materials to create “hybridized functionalities” is a holy grail of modern condensed matter physics that may produce versatile mechanisms of control. Correlated electron systems often exhibit coupled degrees of freedom with a high degree of tunability which sometimes lead to hybridized functionalities based on external stimuli. However, the mechanisms of tunability and the sensitivity to external stimuli are determined by intrinsic material properties which are not always controllable. A Mott metal-insulator transition (MIT) is technologically attractive due to the large changes in resistance, tunable by doping, strain, electric fields, and orbital occupancy but not, in and of itself, controllable with light. Here, an alternate approach is presented to produce optical functionalities using a properly engineered photoconductor/strongly correlated hybrid heterostructure. This approach combines a photoconductor, which does not exhibit an MIT, with a strongly correlated oxide, which is not photoconducting. Due to the intimate proximity between the two materials, the heterostructure exhibits giant volatile and nonvolatile, photoinduced resistivity changes with substantial shifts in the MIT transition temperatures. This approach can be extended to other judicious combinations of strongly correlated materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Improving nanoparticle superlattice stability with deformable polymer gels

The self-assembly of colloidal nanoparticles into ordered superlattices typically uses dynamic interactions to govern particle crystallization, as these non-permanent bonds prevent the formation of kinetically trapped, disordered aggregates. However, while the use of reversible bonding is critical in the formation of highly ordered particle arrangements, dynamic interactions also inherently make the structures more prone to disassembly or disruption when subjected to different environmental stimuli. Thus, there is typically a trade-off between the ability to initially form an ordered colloidal material and the ability of that material to retain its order under different conditions. Here, we present a method for embedding colloidal nanoparticle superlattices into a polymer gel matrix. This encapsulation strategy physically prevents the nanoparticles from dissociating upon heating, drying, or the introduction of chemicals that would normally disrupt the lattice. However, the use of a gel as the embedding medium still permits further modification of the colloidal nanoparticle lattice by introducing stimuli that deform the gel network (as this deformation in turn alters the nanoparticle lattice structure in a predictable manner). Moreover, encapsulation of the lattice within a gel permits further stabilization into fully solid materials by removing the solvent from the gel or by replacing the solvent with a liquid monomer that can be photopolymerized. This embedding method therefore makes it possible to incorporate ordered colloidal arrays into a polymer matrix as either dynamic or static structures, expanding their potential for use in responsive materials.

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

Neuromorphic learning with Mott insulator NiO

Habituation and sensitization (nonassociative learning) are among the most fundamental forms of learning and memory behavior present in organisms that enable adaptation and learning in dynamic environments. Emulating such features of intelligence found in nature in the solid state can serve as inspiration for algorithmic simulations in artificial neural networks and potential use in neuromorphic computing. In this work, we demonstrate nonassociative learning with a prototypical Mott insulator, nickel oxide (NiO), under a variety of external stimuli at and above room temperature. Similar to biological species such as Aplysia, habituation and sensitization of NiO possess time-dependent plasticity relying on both strength and time interval between stimuli. A combination of experimental approaches and first-principles calculations reveals that such learning behavior of NiO results from dynamic modulation of its defect and electronic structure. An artificial neural network model inspired by such nonassociative learning is simulated to show advantages for an unsupervised clustering task in accuracy and reducing catastrophic interference, which could help mitigate the stability–plasticity dilemma. Mott insulators can therefore serve as building blocks to examine learning behavior noted in biology and inspire new learning algorithms for artificial intelligence.

42 ENGINEERING↗
DOE OSTI2025

Tunable shear thickening, aging, and rejuvenation in suspensions of shape-memory-endowed liquid crystalline particles

The morphological features of particles, notably shape anisotropy, critically influence the rheological properties of dense suspensions, spanning both natural and engineered systems. This work explores the potential of using shape memory particles to dynamically regulate suspension fluid flow through controllable shape transformations. First, we synthesize shape-memory particles with programmable anisotropy from liquid crystal elastomers, such that the stiffness and shapes of the particles can be tuned by manipulating temperature. Our findings reveal that suspensions from such particles exhibit significant tunability in shear thickening behavior, transitioning from discontinuous shear thickening to a Newtonian-like response within a narrow temperature range of 60 ° C. This capability to modulate rheological responses in situ presents an approach for addressing processing challenges in many applications where control over flow behavior is paramount. Furthermore, we also show that suspensions composed of these anisotropic particles can undergo physical aging, and evolve into a glassy state. This state can be escaped upon activation of the shape memory effect. This reversibility underscores the potential for using such materials to engineer systems that can enter or come out of kinetic arrest by leveraging internal mechanical responses to external stimuli. The insights gained here not only broaden our understanding of the interplay between particle geometry and suspension dynamics but also pave the way for leveraging ensembles of stimuli-responsive objects to precisely control collective behaviors in many-body systems.

Science & Technology - Other Topics↗
DOE OSTI2024

Stress-regulated Arabidopsis GAT2 is a low affinity γ-aminobutyric acid transporter

Abstract The four-carbon non-proteinogenic amino acid γ-aminobutyric acid (GABA) accumulates to high levels in plants in response to various abiotic and biotic stress stimuli, and plays a role in C:N balance, signaling, and as a transport regulator. Expression in Xenopus oocytes and voltage-clamping allowed the characterization of Arabidopsis GAT2 (At5g41800) as a low affinity GABA transporter with a K0.5GABA ~8 mM. l-Alanine and butylamine represented additional substrates. GABA-induced currents were strongly dependent on the membrane potential, reaching the highest affinity and highest transport rates at strongly negative membrane potentials. Mutation of Ser17, previously reported to be phosphorylated in planta, did not result in altered affinity. In a short-term stress experiment, AtGAT2 mRNA levels were up-regulated at low water potential and under osmotic stress (polyethylene glycol and mannitol). Furthermore, AtGAT2 promoter activity was detected in vascular tissues, maturating pollen, and the phloem unloading region of young seeds. Even though this suggested a role for AtGAT2 in long-distance transport and loading of sink organs, under the conditions tested neither AtGAT2-overexpressing plants, atgat2 or atgat1 T-DNA insertion lines, nor atgat1 atgat2 doubleknockout mutants differed from wild-type plants in growth on GABA, amino acid levels, or resistance to salt and osmotic stress.

Plant Sciences↗
DOE OSTI2022

Gene-by-environment interactions in plants: Molecular mechanisms, environmental drivers, and adaptive plasticity

Abstract Plants demonstrate a broad range of responses to environmental shifts. One of the most remarkable responses is plasticity, which is the ability of a single plant genotype to produce different phenotypes in response to environmental stimuli. As with all traits, the ability of plasticity to evolve depends on the presence of underlying genetic diversity within a population. A common approach for evaluating the role of genetic variation in driving differences in plasticity has been to study genotype-by-environment interactions (G × E). G × E occurs when genotypes produce different phenotypic trait values in response to different environments. In this review, we highlight progress and promising methods for identifying the key environmental and genetic drivers of G × E. Specifically, methodological advances in using algorithmic and multivariate approaches to understand key environmental drivers combined with new genomic innovations can greatly increase our understanding about molecular responses to environmental stimuli. These developing approaches can be applied to proliferating common garden networks that capture broad natural environmental gradients to unravel the underlying mechanisms of G × E. An increased understanding of G × E can be used to enhance the resilience and productivity of agronomic systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

A glimpse into the fungal metabolomic abyss: Novel network analysis reveals relationships between exogenous compounds and their outputs

Fungal specialized metabolites are a major source of beneficial compounds that are routinely isolated, characterized, and manufactured as pharmaceuticals, agrochemical agents, and industrial chemicals. The production of these metabolites is encoded by biosynthetic gene clusters that are often silent under standard growth conditions. There are limited resources for characterizing the direct link between abiotic stimuli and metabolite production. Herein, we introduce a network analysis-based, data-driven algorithm comprising two routes to characterize the production of specialized fungal metabolites triggered by different exogenous compounds: the direct route and the auxiliary route. Both routes elucidate the influence of treatments on the production of specialized metabolites from experimental data. The direct route determines known and putative metabolites induced by treatments and provides additional insight over traditional comparison methods. The auxiliary route is specific for discovering unknown analytes, and further identification can be curated through online bioinformatic resources. We validated our algorithm by applying chitooligosaccharides and lipids at two different temperatures to the fungal pathogen Aspergillus fumigatus. After liquid chromatography–mass spectrometry quantification of significantly produced analytes, we used network centrality measures to rank the treatments’ ability to elucidate these analytes and confirmed their identity through fragmentation patterns or in silico spiking with commercially available standards. Later, we examined the transcriptional regulation of these metabolites through real-time quantitative polymerase chain reaction. Our data-driven techniques can complement existing metabolomic network analysis by providing an approach to track the influence of any exogenous stimuli on metabolite production. Our experimental-based algorithm can overcome the bottlenecks in elucidating novel fungal compounds used in drug discovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A multisensory approach to understanding bat responses to wind energy developments

Abstract Millions of bats are killed at wind energy facilities worldwide, yet the behavioural mechanisms underlying why bats are vulnerable to wind turbines remain unclear. Anthropogenic stimuli that alter perceptions of the environment, known as sensory pollution, could create ecological traps and cause bat mortality at wind farms. We review the sensory abilities of bats to evaluate potential stimuli associated with wind farms and examine the role of spatial scale on the perceptual mechanisms of sensory pollutants associated with wind energy facilities. Audition, vision, somatosensation and olfaction are sensory modalities that bats use to perceive their environment, including wind farms and turbine structures, but they will not all be useful at the same spatial scales. Bats most likely use vision to perceive wind farms on the landscape, and obstruction lighting may be the first sensory cue to attract bats to wind farms from kilometres away. Research that assesses the risks posed by specific sensory pollutants, when conducted at the appropriate scale, can help identify solutions to reduce bat mortality, such as determining the attractiveness of obstruction lighting to bats at a landscape scale.

Jonasson, Kristin A.↗
DOE OSTI2022

Discrimination of xylene isomers in a stacked coordination polymer

The separation and purification of xylene isomers is an industrially important but challenging process. Developing highly efficient adsorbents is crucial for the implementation of simulated moving bed technology for industrial separation of these isomers. Herein, we report a stacked one-dimensional coordination polymer {[Mn(dhbq)(H 2 O) 2 ], H 2 dhbq = 2,5-dihydroxy-1,4-benzoquinone} that exhibits an ideal molecular recognition and sieving of xylene isomers. Its distinct temperature-adsorbate–dependent adsorption behavior enables full separation of p -, m -, and o -xylene isomers in both vapor and liquid phases. The delicate stimuli-responsive swelling of the structure imparts this porous material with exceptionally high flexibility and stability, well-balanced adsorption capacity, high selectivity, and fast kinetics at conditions mimicking industrial settings. This study may offer an alternative approach for energy-efficient and adsorption-based industrial xylene separation and purification processes.

Science & Technology - Other Topics↗
DOE OSTI2020

Skeletal tissue regulation by catalase overexpression in mitochondria

Accumulation of oxidative damage from excess reactive oxygen species (ROS) may contribute to skeletal aging and mediate adverse responses to physiological challenges. Wild-type (WT) mice and transgenic mice (male, 16 wk of age) with human catalase targeted to the mitochondria (mCAT) were analyzed for skeletal responses to the remodeling stimuli of combined hind-limb unloading and exposure to ionizing radiation ( 137 Cs, 2 Gy). Treatment for 2 wk caused lipid peroxidation in the bones WT but not mCAT mice, showing that transgene expression mitigated oxidative stress. Ex vivo osteoblast colony growth rate was 95% greater in mCAT than WT mice and correlated with catalase activity levels ( P < 0.005, r = 0.67), although terminal osteoblast and osteoclast differentiation were unaffected. mCAT mice had lower cancellous bone volume and cortical size than WT mice. Ambulatory control mCAT animals also displayed reduced cancellous and cortical structural properties compared with control WT mice. In mCAT but not WT mice, treatment caused an unexpectedly rapid radial expansion (+8% cortical area, +22% moment of inertia), reminiscent of compensatory bone growth during advancing age. In contrast, treatment caused similar structural deficits in cancellous tissue of mCAT and WT mice. In sum, mitochondrial ROS signaling via H 2 O 2 was important for the acquisition of adult bone structure and catalase overexpression failed to protect cancellous tissue from treatment. In contrast, catabolic stimuli caused radial expansion in mCAT not WT mice, suggesting that mitochondrial ROS in skeletal cells act to suppress tissue turnover in response to remodeling challenges.

Cell Biology↗
DOE OSTI2022

Maximum likelihood estimation of difference scaling functions for suprathreshold judgments

Maximum likelihood estimation (MLE) has been used to produce perceptual scales from binary judgments of triads and quadruples. This method relies on Thurstone’s theory of a stochastic perceptual process where the perceived difference of two stimuli is the difference in their perceived strengths. It is possible that the perception of a suprathreshold difference is overestimated when adding smaller differences, a phenomenon referred to as diminishing returns. The current approach to construct a perceptual scale using MLE does not account for this phenomenon. We present a way to model the perception of differences using MLE and Thurstone’s theory, adapted to allow the possibility of diminishing returns. This method is validated using Monte Carlo simulated responses to experimental triads and can correctly model diminishing returns, the absence of diminishing returns, and the opposite of diminishing returns both in the cases when a perceptual scale is known and when the true perceived strengths of the stimuli are unknown. Additionally, this method was applied to empirical data sets to determine its feasibility in investigations of perception. Ultimately, it was found that this analysis allows for more accurate modeling of suprathreshold difference judgments, a more complete understanding of the perceptual processes underlying comparisons, and the evaluation of Thurstone’s theory of difference judgments.

97 MATHEMATICS AND COMPUTING↗