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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Grain boundary widening controls siderite (FeCO3) replacement of limestone (CaCO3)

Abstract The microstructure of minerals and rocks can significantly alter reaction rates. This study focuses on identifying transport paths in low porosity rocks based on the hypothesis that grain boundary widening accelerates reactions in which one mineral is replaced by another (replacement reaction). We conducted a time series of replacement experiments of three limestones (CaCO 3 ) of different microstructures and solid impurity contents using FeCl 2 . Reacted solids were analyzed using chemical imaging, small angle X-ray and neutron scattering and Raman spectroscopy. In high porosity limestones replacement is reaction controlled and complete replacement was observed within 2 days. In low porosity limestones that contain 1–2% dolomite impurities and are dominated by grain boundaries, a reaction rim was observed whose width did not change with reaction time. Siderite (FeCO 3 ) nucleation was observed in all parts of the rock cores indicating the percolation of the solution throughout the complete core. Dolomite impurities were identified to act as nucleation sites leading to growth of crystals that exert force on the CaCO 3 grains. Widening of grain boundaries beyond what is expected based on dissolution and thermal grain expansion was observed in the low porosity marble containing dolomite impurities. This leads to a self-perpetuating cycle of grain boundary widening and reaction acceleration instead of reaction front propagation.

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

Observing neutron alignment at high angular momenta in heavy deformed actinides

An outstanding puzzle in the structure of very heavy nuclei lies in the rotation response of deformed transuranic isotopes. While the rotation alignment of pairs of 𝑖 13/2 protons is ubiquitous and well understood, observing the analogous alignment of the 𝑗 15/2 neutrons has been elusive. In this work we present a new quantitative analysis approach: from their moments of inertia as a function of frequency, we compare the alignments of rotational bands with both “low” and high-𝑗 intrinsic structures in the 𝑁 = 151 isotones of Pu, Cm, Cf, and No, thereby distinguishing between the alignments of neutron versus proton pairs through “blocking” effects. In this way, the alignment of 𝑗 15/2 neutrons can be clearly identified for the first time. The protons and neutrons begin aligning at a very similar frequency. The contribution of 𝑗 15/2 neutrons to the total alignment is found to grow with increasing 𝑍 compared to 𝑖 13/2 protons. To explain these observations, it is necessary to adopt a self-consistent set of single-particle energies corresponding to the nuclear shape that minimizes the mass. The shape description needs to include high-order deformations up to at least 𝛽 6 .

A ≥ 220↗
DOE OSTI2020

Determining population densities in bimodal micellar solutions using contrast-variation small angle neutron scattering

Self-assembly of amphiphilic polymers in water is of fundamental and practical importance. Significant amounts of free unimers and associated micellar aggregates often coexist over a wide range of phase regions. The thermodynamic and kinetic properties of the microphase separation are closely related to the relative population density of unimers and micelles. Although the scattering technique has been employed to identify the structure of micellar aggregates as well as their time-evolution, the determination of the population ratio of micelles to unimers remains a challenging problem due to their difference in scattering power. In this work, using small-angle neutron scattering (SANS), we present a comprehensive structural study of amphiphilic n-dodecyl-PNIPAm polymers, which shows a bimodal size distribution in water. By adjusting the deuterium/hydrogen ratio of water, the intra-micellar polymer and water distributions are obtained from the SANS spectra. The micellar size and number density are further determined, and the population densities of micelles and unimers are calculated to quantitatively address the degree of micellization at different temperatures. Our method can be used to provide an in-depth insight into the solution properties of microphase separation, which are present in many amphiphilic systems.

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

Affinity of Nicotinoids to a Model Nicotinic Acetylcholine Receptor (nAChR) Binding Pocket in the Human Brain

The binding affinity of nicotinoids to the binding residues of the a4ß2 variant of the nicotinic acetylcholine receptor (nAChR) was identified as a strong predictor of the nicotinoid’s addictive character. Using ab-iniito calculations for model binding pockets of increasing size comprising of 3, 6, and 14 amino acids (3AA, 6AA, and 14AA) that are derived from the crystal structure, the differences in binding affinity of 6 nicotinoids, namely nicotine (NIC), nornicotine (NOR), anabasine (ANB), anatabine (ANT), myosmine (MYO), and cotinine (COT) were correlated to their previously reported doses required for increases in intracranial self-stimulation (ICSS) thresholds, a metric for their addictive function. By employing the many body decomposition, the differences in the binding affinities of the various nicotinoids could be attributed mainly to the proton exchange energy between the Pyridine and non-Pyridine rings of the nicotinoids and the interactions between them and a handful of proximal amino acids, namely Trp156, Trpß57, Tyr100, and Tyr204. Interactions between the guest nicotinoid and the amino acids of the binding pocket were found to be mainly classical in nature, except for those between the nicotinoid and Trp156. The larger pockets were found to model binding structures more accurately and predicted the addictive character of all nicotinoids while smaller models, which are more computationally feasible, would only predict the addictive character of nicotinoids that are similar to nicotine. Here, the present study identifies the binding affinity of the guest nicotinoid to the host binding pocket as a strong descriptor of the nicotinoid’s addiction potential and as such it can be employed as a fast screening technique for the potential addiction of nicotine analogs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Robust silane self-assembled monolayer coatings on plasma-engineered copper surfaces promoting dropwise condensation

Dropwise condensation is well known to result in better heat transfer performance owing to efficient condensate/droplet removal, which can be harnessed in various industrial heat/mass transfer applications such as power generation and conversion, water harvesting/desalination, and electronics thermal management. The key to enhancing condensation via the dropwise mode is thin low surface energy coatings (<100 nm) with low contact angle hysteresis. Ultrathin (<5 nm) silane self-assembled monolayers (or SAMs) have been widely studied to promote dropwise condensation due to their minimal thermal resistance and scalable integration processes. Such thin coatings typically degrade within an hour during condensation of water vapor. After coating failure, water vapor condensation transitions to the inefficient filmwise mode with poor heat transfer performance. We enhance silane SAM quality and durability during water vapor condensation on copper compared to state-of-the-art silane coatings on metal surfaces. We achieve this via (i) surface polishing to sub-10 nm levels, (ii) pure oxygen plasma surface treatment, and (iii) silane coating integration with the copper substrate in an anhydrous/moisture-free environment. The resulting silane SAM has low contact angle hysteresis (≈20°) and promotes efficient dropwise condensation of water for >360 hours without any visible sign of coating failure/degradation in the absence of non-condensable gases. We further demonstrate enhanced heat transfer performance (≈5-7× increase over filmwise condensation) over an extended period of time. Surface characterization data post-condensation leads us to propose that in the absence of non-condensable gases in the vapor environment, the silane SAM degrades due to reduction and subsequent dissolution of copper oxide at the oligomer-substrate interface. The experiments also indicate that the magnitude of surface subcooling (or condensation rate) affects the rate of coating degradation. Finally, this work identifies a pathway to durable dropwise promoter coatings that will enable efficient heat transfer in industrial applications.

42 ENGINEERING↗
DOE OSTI2021

Characterizing Long COVID: Deep Phenotype of a Complex Condition

Background: Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or "long COVID"), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the natural history of COVID-19, but integration is hampered because they often use different terms to describe the same symptom or condition. This significant disparity in patient versus clinical characterization motivated the proposed ontological approach to specifying manifestations, which will improve capture and integration of future long COVID studies. Methods: The Human Phenotype Ontology (HPO) is a widely used standard for exchange and analysis of phenotypic abnormalities in human disease but has not yet been applied to the analysis of COVID-19. Funding: We identified 303 articles published before April 29, 2021, curated 59 relevant manuscripts that described clinical manifestations in 81 cohorts three weeks or more following acute COVID-19, and mapped 287 unique clinical findings to HPO terms. We present layperson synonyms and definitions that can be used to link patient self-report questionnaires to standard medical terminology. Long COVID clinical manifestations are not assessed consistently across studies, and most manifestations have been reported with a wide range of synonyms by different authors. Across at least 10 cohorts, authors reported 31 unique clinical features corresponding to HPO terms; the most commonly reported feature was Fatigue (median 45.1%) and the least commonly reported was Nausea (median 3.9%), but the reported percentages varied widely between studies. Interpretation: Translating long COVID manifestations into computable HPO terms will improve analysis, data capture, and classification of long COVID patients. If researchers, clinicians, and patients share a common language, then studies can be compared/pooled more effectively. Furthermore, mapping lay terminology to HPO will help patients assist clinicians and researchers in creating phenotypic characterizations that are computationally accessible, thereby improving the stratification, diagnosis, and treatment of long COVID.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

4D-STEM Mapping of Nanocrystal Reaction Dynamics and Heterogeneity in a Graphene Liquid Cell

Chemical reaction kinetics at the nanoscale are intertwined with heterogeneity in structure and composition. However, mapping such heterogeneity in a liquid environment is extremely challenging. Here, in this work, we integrate graphene liquid cell (GLC) transmission electron microscopy and four-dimensional scanning transmission electron microscopy to image the etching dynamics of gold nanorods in the reaction media. Critical to our experiment is the small liquid thickness in a GLC that allows the collection of high-quality electron diffraction patterns at low dose conditions. Machine learning-based data-mining of the diffraction patterns maps the three-dimensional nanocrystal orientation, groups spatial domains of various species in the GLC, and identifies newly generated nanocrystallites during reaction, offering a comprehensive understanding on the reaction mechanism inside a nanoenvironment. This work opens opportunities in probing the interplay of structural properties such as phase and strain with solution-phase reaction dynamics, which is important for applications in catalysis, energy storage, and self-assembly.

four-dimensional scanning transmission electron mi↗
DOE OSTI2020

Disappearance of Superconductivity Due to Vanishing Coupling in the Overdoped Bi 2 Sr 2 CaCu 2 O 8+δ

In cuprate superconductors, superconductivity is accompanied by a ‘plethora of orders’, and phenomena that complicate our understanding of superconductivity in these materials. Prominent in the underdoped regime, these orders weaken or vanish with overdoping. Here, we approach the superconducting phase from the more conventional overdoped side. We present angle-resolve photoemission spectroscopy studies of Bi 2 Sr 2 CaCu 2 O 8+δ , cleaved and annealed in ozone to increase the doping all the way to the non-superconducting phase. In this work, we show that the mass renormalizationin the antinodal region of the Fermi surface, associated with the structure in the quasiparticle self-energy, that possibly reflects the pairing, weakens with doping and completely disappears precisely where superconductivity disappears the evidence that in the overdoped regime, superconductivity is determined by the coupling strength. A doping dependence and an abrupt disappearance above the transition temperature eliminate phononic mechanism of the observed renormalization and identify the onset of spin-fluctuations as its likely origin.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Measurements of the Growth and Saturation of Electron Weibel Instability in Optical-Field Ionized Plasmas

The temporal evolution of the magnetic field associated with electron thermal Weibel instability in optical-field ionized plasmas is measured using ultrashort (1.8 ps), relativistic (45 MeV) electron bunches from a linear accelerator. The self-generated magnetic fields are found to self-organize into a quasistatic structure consistent with a helicoid topology within a few picoseconds and such a structure lasts for tens of picoseconds in underdense plasmas. Here, the measured growth rate agrees well with that predicted by the kinetic theory of plasmas taking into account collisions. Magnetic trapping is identified as the dominant saturation mechanism.

Electric & magnetic plasma measurements↗
DOE OSTI2021

Displacement Analysis of Geothermal Field Based on PSInSAR And SOM Clustering Algorithms A Case Study of Brady Field, Nevada—USA

The availability of free and high temporal resolution satellite data and advanced SAR techniques allows us to analyze ground displacement cost-effectively. Our aim was to properly define subsidence and uplift areas to delineate a geothermal field and perform time-series analysis to identify temporal trends. A Persistent Scatterer Interferometry (PSI) algorithm was used to estimate vertical displacement in the Brady geothermal field located in Nevada by analyzing 70 Sentinel-1A Synthetic-Aperture Radar (SAR) images, between January 2017 and December 2019. To classify zones affected by displacement, an unsupervised Self-Organizing Map (SOM) algorithm was applied to classify points based on their behavior in time, and those clusters were used to determine subsidence, uplift, and stable regions automatically. Finally, time-series analysis was applied to the clustered data to understand the inflection dates. The maximum subsidence is –19 mm/yr with an average value of –6 mm/yr within the geothermal field. The maximum uplift is 14 mm/yr with an average value of 4 mm/yr within the geothermal field. The uplift occurred on the NE of the field, where the injection wells are located. On the other hand, subsidence is concentrated on the SW of the field where the production wells are located. The coupling of the PSInSAR and the SOM algorithms was shown to be effective in analyzing the direction and pattern of the displacements observed in the field.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Self Configuring Digital Twin for Optimizing E-Waste Recycling

Electronic waste recycling industry needs a decision support tool for optimizing their processes to become cost competitive. We developed a software called CMAT, Comprehensive Manufacturing Assessment Tool. The aim of CMAT is to provide the e-waste recycling companies with a fully customizable decision support framework that analyzes the optimal supply chain configurations. The software optimizes the logistics operations, helps to identify the best recycling process configuration, and generates valuable insights regarding the economic performance of different categories of e-waste. The ultimate purpose of the tool is to assist the users developing a digital twin of their processes and to provide insights on questions pertinent to the e-waste recycling industry including how to increase efficiency and reduce costs, energy consumption, and greenhouse gas emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Quantitative Evaluation of Reliability Improvement: Case Study on a Self-healing Distribution System

In this work, we develop a methodology and tool to quantitatively evaluate the reliability of a self-healing system that considers practical distribution system features such as the distributed energy resources, microgrids, and service restoration strategies. Also, this paper addresses various practical issues when being applied to an actual Duke Energy distribution system, including the design of feasible and practical service restoration strategies that are used to identify the customer interruptions after a fault, and the incorporation of the utility’s historical reliability indices that are used to calibrate the failure rate and repair time of distribution system components such as overhead lines and underground cables. This case study demonstrates the effectiveness of the proposed method.

Dong, Jiaojiao↗
DOE OSTI2022

Sampling-based Sublinear Low-rank Matrix Arithmetic Framework for Dequantizing Quantum Machine Learning

We present an algorithmic framework for quantum-inspired classical algorithms on close-to-low-rank matrices, generalizing the series of results started by Tang’s breakthrough quantum-inspired algorithm for recommendation systems [STOC’19]. Motivated by quantum linear algebra algorithms and the quantum singular value transformation (SVT) framework of Gilyén et al. [STOC’19], we develop classical algorithms for SVT that run in time independent of input dimension, under suitable quantum-inspired sampling assumptions. Our results give compelling evidence that in the corresponding QRAM data structure input model, quantum SVT does not yield exponential quantum speedups. Since the quantum SVT framework generalizes essentially all known techniques for quantum linear algebra, our results, combined with sampling lemmas from previous work, suffice to generalize all prior results about dequantizing quantum machine learning algorithms. In particular, our classical SVT framework recovers and often improves the dequantization results on recommendation systems, principal component analysis, supervised clustering, support vector machines, low-rank regression, and semidefinite program solving. We also give additional dequantization results on low-rank Hamiltonian simulation and discriminant analysis. Our improvements come from identifying the key feature of the quantum-inspired input model that is at the core of all prior quantum-inspired results: ℓ 2 -norm sampling can approximate matrix products in time independent of their dimension. We reduce all our main results to this fact, making our exposition concise, self-contained, and intuitive.

Computer Science↗
DOE OSTI2020

Challenges for and Pathways Toward Solid-State Batteries

Solid-state batteries utilizing lithium metal anodes have the potential to enable batteries with a specific energy of >500 Wh/kg and an energy density of >1,500 Wh/L for thousands of cycles. When optimized they will improve the energy efficiency, operating temperature range, sustainability, and safety at a lower cost compared to projections for advanced Li-ion batteries. This improved performance is critical for the widespread adoption of electric vehicles and may enable future applications such as electric aviation. Expectations for solid-state batteries are high, there are significant materials and processing challenges that need to be overcome. Some of these challenges are well known; others are more subtle and are just becoming known. The challenges and their solutions must be clearly identified to realize high-energy solid-state Li metal batteries. In the United States, the U.S. Department of Energy (DOE) funds the majority of energy storage research and development, including solid state battery research. Web of Science publication analysis shows that worldwide DOE is second largest funder. Work on solid state batteries is distributed across different arms of DOE and is coordinated at headquarters to ensure a broad national portfolio for advanced batteries, including lithium batteries and solid-state battery devices. We note that university and national laboratory researchers in the US with a long-standing interest in solid state batteries is a small, integrated community with recognized impact for publications, patents and startup companies. The opportunity for this group to engage for research with international colleagues is growing, fostered by periodic bilateral meetings supported by DOE and by the recent joint US German research program for lithium battery interface studies. These are valuable opportunities to speed solid-state battery development. The ORNL led virtual workshop, overviewed here, confirms the community’s shared vision of the exciting advances, opportunities, and challenges. Further, we are seeing that this workshop has spawned several new informal collaborations and draft proposals. This encourages us to propose future discussion. On May 11, 2020, Oak Ridge National Laboratory (ORNL) hosted a 6-hour, on-line national workshop to discuss recent advances and most the prominent obstacles to realizing solid-state Li metal batteries. The workshop included more than 30+ experts from national laboratories, universities, and companies, all of whom have worked on solid-state batteries for multiple years. The participants shared recent advances, many not yet in print, illustrating that the community has gained significant new insights for solid-state Li battery materials over the last 5 years. In this report, the major outcomes of the workshop are organized to identify the gaps in our scientific knowledge for four core materials science areas: (1) Li metal anodes, (2) the solid electrolyte in contact with Li metal, (3) active cathode materials and solid-state composite cathodes, and (4) solid electrolytes. Illustrative examples and discussions are reported with the more comprehensive issues in the report. Discussion of additional challenges related to processing of solid-state battery materials and to the designs and architectures for mechanically robust, long-lived batteries received less attention due to time constraints. These are good themes for deeper discussion at a follow-on workshop, where a complete list of critical research topics can be identified.

25 ENERGY STORAGE↗
DOE OSTI2023

Gravitational Wave Eigenfrequencies from Neutrino-driven Core-collapse Supernovae

Abstract Core-collapse supernovae (CCSNe) are predicted to produce gravitational waves (GWs) that may be detectable by Advanced LIGO/Virgo. These GW signals carry information from the heart of these cataclysmic events, where matter reaches nuclear densities. Recent studies have shown that it may be possible to infer the properties of the proto-neutron star (PNS) via GWs generated by hydrodynamic perturbations of the PNS. However, we lack a comprehensive understanding of how these relationships may change with the properties of CCSNe. In this work, we build a self-consistent suite of over 1000 exploding CCSNe from a grid of progenitor masses and metallicities combined with six different nuclear equations of state (EOS). Performing a linear perturbation analysis on each model, we compute the resonant GW frequencies of the PNS, and we motivate a time-agnostic method for identifying characteristic frequencies of the dominant GW emission. From this, we identify two characteristic frequencies, of the early- and late-time signal, that measure the surface gravity of the cold remnant neutron star, and simultaneously constrain the hot nuclear EOS. However, we find that the details of the CCSN model, such as the treatment of gravity or the neutrino transport, and whether it explodes, noticeably change the magnitude and evolution of the PNS eigenfrequencies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Quantitative Evaluation of Reliability Improvement: Case Study on a Self-healing Distribution System

In this work, we develop a methodology and tool to quantitatively evaluate the reliability of a self-healing system that considers practical distribution system features such as the distributed energy resources, microgrids, and service restoration strategies. Also, this paper addresses various practical issues when being applied to an actual Duke Energy distribution system, including the design of feasible and practical service restoration strategies that are used to identify the customer interruptions after a fault, and the incorporation of the utility's historical reliability indices that are used to calibrate the failure rate and repair time of distribution system components such as overhead lines and underground cables. This case study demonstrates the effectiveness of the proposed method.

Dong, Jiaojiao↗
DOE OSTI2023

Reservoir Thermal Energy Storage Benchmarking (Rev. 3)

A benchmarking analysis of RTES research funded by GTO through the Beyond Batteries projects was conducted against the ESGC to see where they fit within the identified ESGC Use Cases. The projects were found to advance knowledge in multiple ESGC use cases, either directly or in some cases, indirectly as enabling technologies. This analysis is helpful to understand where RTES and associated research fits into the larger discussion around energy storage technologies. Also, a retrospective analysis of the Beyond Batteries projects was conducted to evaluate what the projects learned and how the results can be applied to advance the value of RTES. Major results of each of the studies are summarized in Table 2. Additionally, a comparative metrics analysis for RTES was completed to understand where RTES lies within the energy storage industry. Metrics for evaluation of RTES and its comparison to other storage technologies were selected and ranges of their values compiled. The selected metrics – LCOE (levelized cost of energy), capital costs, roundtrip efficiency, energy storage capacity, and storage time – were chosen based on data availability and have a particularly strong influence on the potential deployment of a storage technology. Charts which compare the metrics are presented in section 4.3 and show ranges for each of the 10 selected technologies. However, due to a lack of domestic operational facilities, values for RTES and for portions of the remaining technologies are based on theoretical modeling and studies of best-case scenarios. LCOE estimates for RTES fall within the lower reaches of Figure 15, but nevertheless amount to 2 – 5 times the ESGC Roadmap goal for LCOE, for example in the Facilitating and Evolving Grid Use Case. Capital costs for RTES sit on the higher end (Figure 16) but are expected to decrease as new projects are developed and the technology is refined. The theoretical roundtrip efficiency reported for RTES varies from mid to high percentages (Figure 17) with efficiencies upwards of 93% in modeled scenarios in the Portland Basin (Bershaw et al.,2020). RTES is also expected to have the largest energy storage capacities and longest storage times, likely matched only by lower efficiency hydrogen storage. To better assess the role that RTES could play in energy storage we examined it’s potential in the U.S. The potential depends on many factors. Recently, many researchers have started looking at deep sedimentary basins, depleted oil and gas fields, and basalt formations as potential targets for RTES development. The United States Geological Survey (USGS) has analyzed various cities and shown substantial RTES potential in the cooling sector (Pepin et al., 2021). By modeling RTES in low-quality groundwater (e.g., brackish), it is shown to be favorable across the U.S. with particular suitability in the Illinois Basin, Coastal Plains, and Basin and Range regions. Seasonal RTES operations have also been modeled in the Portland Basin by those at the USGS and Portland State University to simulate an RTES system supplying heating loads needed for the Oregon Health and Science University. Simulations suggest that high conductive heat loss in the initial years exists but tends to decrease with increasing time and development of the resource due to self-insulating nature of the basalts (Burns et al., 2020). Other national laboratory efforts are taking a close look at many of the technical issues involved with RTES (McLing et al., 2019, McLing et al., 2022). These include difficulties in understanding geochemical, hydrogeological, mechanical, and microbiological changes at such elevated temperatures and operational scenarios. Major gaps in research are identified and suggested for future work. With this increased focus to understand how to make RTES successful in the U.S., this technology could be a potential solution to many of the nation’s energy storage problems. For the energy independence of this country, the DOE should prioritize de-risking this technology by making future investments in pilot-scale demonstrations to attract potential investors.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Nanocarrier-loaded block copolymer dual domain organogels

Loaded polymer gels are prevalent materials in the controlled release community and, fairly recently, have been formulated to include nanocarrier domains such as micelles and vesicles. One mechanism used to establish the solid-like characteristic of gels is block copolymer self-assembly, which can result in a system-spanning, physically-crosslinked network. Additionally, the combination of nanocarrier and crosslink domain presence offers gels with a rich nanoscale phase space capable of intricate macroscopic property tuning. The current manuscript provides an overview of nanocarrier-loaded block copolymer organogels wherein nanocarriers are reverse micelles formed by sodium dioctyl sulfosuccinate (AOT), the block copolymer is a styrenic ABA triblock copolymer, and the gel solvent is aliphatic mineral oil. This introductory overview starts by identifying the envelope in ternary phase space wherein nanocarrier-loaded block copolymer organogels form (2-49 wt% triblock copolymer and 8x10 -3 -1 wt% AOT). Next, a detailed nanostructural description of gels varying in AOT and triblock copolymer concentration is presented. The manuscript concludes with demonstration of AOT reverse micelle release and gel uniaxial tensile response for gels containing 0-1 wt% AOT and 5-40 wt% styrenic triblock copolymer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗