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DOE OSTI2023

An finite element analysis surrogate model with boundary oriented graph embedding approach for rapid design

Abstract In this work, we present a boundary oriented graph embedding (BOGE) approach for the graph neural network to assist in rapid design and digital prototyping. The cantilever beam problem has been solved as an example to validate its potential of providing physical field results and optimized designs using only 10 ms. Providing shortcuts for both boundary elements and local neighbor elements, the BOGE approach can embed unstructured mesh elements into the graph and performs an efficient regression on large-scale triangular-mesh-based finite element analysis (FEA) results, which cannot be realized by other machine-learning-based surrogate methods. It has the potential to serve as a surrogate model for other boundary value problems. Focusing on the cantilever beam problem, the BOGE approach with 3-layer DeepGCN model achieves the regression with mean square error (MSE) of 0.011 706 (2.41% mean absolute percentage error) for stress field prediction and 0.002 735 MSE (with 1.58% elements having error larger than 0.01) for topological optimization. The overall concept of the BOGE approach paves the way for a general and efficient deep-learning-based FEA simulator that will benefit both industry and Computer Aided Design (CAD) design-related areas.

42 ENGINEERING↗

DOE OSTI2018

Environmental limitation mapping of potential biomass resources across the conterminous U nited S tates

Abstract Several crops have recently been identified as potential dedicated bioenergy feedstocks for the production of power, fuels, and bioproducts. Despite being identified as early as the 1980s, no systematic work has been undertaken to characterize the spatial distribution of their long‐term production potentials in the United states. Such information is a starting point for planners and economic modelers, and there is a need for this spatial information to be developed in a consistent manner for a variety of crops, so that their production potentials can be intercompared to support crop selection decisions. As part of the Sun Grant Regional Feedstock Partnership (RFP), an approach to mapping these potential biomass resources was developed to take advantage of the informational synergy realized when bringing together coordinated field trials, close interaction with expert agronomists, and spatial modeling into a single, collaborative effort. A modeling and mapping system called PRISM‐ELM was designed to answer a basic question: How do climate and soil characteristics affect the spatial distribution and long‐term production patterns of a given crop? This empirical/mechanistic/biogeographical hybrid model employs a limiting factor approach, where productivity is determined by the most limiting of the factors addressed in submodels that simulate water balance, winter low‐temperature response, summer high‐temperature response, and soil pH , salinity, and drainage. Yield maps are developed through linear regressions relating soil and climate attributes to reported yield data. The model was parameterized and validated using grain yield data for winter wheat and maize, which served as benchmarks for parameterizing the model for upland and lowland switchgrass, CRP grasses, Miscanthus, biomass sorghum, energycane, willow, and poplar. The resulting maps served as potential production inputs to analyses comparing the viability of biomass crops under various economic scenarios. The modeling and parameterization framework can be expanded to include other biomass crops.

09 BIOMASS FUELS↗

DOE OSTI2018

Use of an ocular wound chamber for the prevention of exposure keratopathy in a guinea pig model

Abstract Current therapies available to treat and heal ocular surface injuries and periocular burns are frequently inadequate, costly, and labor intensive. To address these limitations, we have employed a flexible, semitransparent ocular wound chamber (OWC) to provide protection as well as a watertight seal to allow for the constant delivery of therapeutics to the ocular surface and surrounding periocular tissue. This study demonstrates the safety and utilization of the OWC on uninjured eyes and in our exposure keratopathy model. For initial safety studies ( N = 3 per group), the eyelids remained intact and the eye uninjured. A blepharotomy ( N = 6 per group) was performed to remove the upper and lower eyelids surrounding the left (OS) eye to create our exposure keratopathy model. Right (OD) eyes served as uninjured controls in all studies. Following OWC placement, 0.5 mL HPMC gel or balanced saline solution (BSS) was injected into the chamber. Animals were monitored daily and fully assessed via white light, fluorescein, and OCT imaging at least through 72 hours post OWC placement. In studies that included a blepharotomy, skin samples were analyzed by multiplex cytokine analysis. Results of safety experiments revealed no significant differences between treatment groups in corneal thickness, fluorescein staining, OCT imaging, or histological eye or skin sections when compared to control eyes. In our exposure keratopathy model, OWC treated eyes showed significantly less fluorescein uptake and also were found to have significantly lower levels of cytokines IL‐13 and IL‐5 in skin samples. These results demonstrate for the first time that treatment using the OWC device is not only safe, but significantly protects against blepharotomy‐induced exposure keratopathy. As a whole, this study advances our overall efforts to develop a feasible solution to treat ocular surface injuries, infections, and periocular burns.

Holt, Andrew W.↗

DOE OSTI2016

Coherent states, quantum gravity, and the Born- Oppenheimer approximation. II. Compact Lie groups

In this article, the second of three, we discuss and develop the basis of a Weyl quantisation for compact Lie groups aiming at loop quantum gravity-type models. This Weyl quantisation may serve as the main mathematical tool to implement the program of space adiabatic perturbation theory in such models. As we already argued in our first article, space adiabatic perturbation theory offers an ideal framework to overcome the obstacles that hinder the direct implementation of the conventional Born-Oppenheimer approach in the canonical formulation of loop quantum gravity. Additionally, we conjecture the existence of a new form of the Segal-Bargmann-Hall “coherent state” transform for compact Lie groups G, which we prove for G = U(1){sup n} and support by numerical evidence for G = SU(2). The reason for conjoining this conjecture with the main topic of this article originates in the observation that the coherent state transform can be used as a basic building block of a coherent state quantisation (Berezin quantisation) for compact Lie groups G. But, as Weyl and Berezin quantisation for ℝ{sup 2d} are intimately related by heat kernel evolution, it is natural to ask whether a similar connection exists for compact Lie groups as well. Moreover, since the formulation of space adiabatic perturbation theory requires a (deformation) quantisation as minimal input, we analyse the question to what extent the coherent state quantisation, defined by the Segal-Bargmann-Hall transform, can serve as basis of the former.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Prototype energy models for data centers

Data centers in the United States consume about two percent of the nation’s electricity. Because heat gains from IT equipment drive cooling demand, data centers offer unique opportunities for energy savings. However, no prototype energy model for data centers is available in the suite of existing U.S. Department of Energy’s Commercial Prototype Building Models. Here we present the development of two new data center prototype models and their implementation in OpenStudio and EnergyPlus. The small-size data center model represents a computer room in a building served by computer room air conditioners (CRACs); while the large-sized model represents stand-alone data centers served by computer room air handlers (CRAHs) with a central chiller plant. For each data center model, two levels of IT equipment (ITE) load density were considered, to cover the wide range of IT power density of data centers: 40 and 100 W/ft 2 (430 and 1076 W/m 2 ) for the computer room, and 100 and 500 W/ft 2 (1076 and 5382 W/m 2 ) for the stand-alone data center. All other assumptions, such as building envelope, lighting, HVAC efficiencies and schedules, were based on the minimal requirements of ASHRAE Standard 90.1 at various vintages. We introduced a novel concept of supply and return air approach temperatures to capture the essential effects of non-uniform airflow and temperature distribution in data centers. The approach temperatures were pre-computed by computational fluid dynamics (CFD) simulations for various configurations of ITE loads and airflow containment management in data centers. A new feature was developed in EnergyPlus to implement the approach temperature method. A case study was conducted to demonstrate the use of the data center models. The two data center models cover all U.S. climate zones and can be used to evaluate energy saving measures for data centers, as well as to support development of data center energy efficiency codes and standards.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Observability Analysis of a Power System Stochastic Dynamic Model Using a Derivative-Free Approach

Serving as a prerequisite to power system dynamic state estimation, the observability analysis of a power system dynamic model has recently attracted the attention of many power engineers. However, because this model is typically nonlinear and large-scale, the analysis of its observability is a challenge to the traditional derivative-based methods. Indeed, the linear-approximation-based approach may provide unreliable results while the nonlinear-technique-based approach inevitably faces extremely complicated derivations. Furthermore, because power systems are intrinsically stochastic, the traditional deterministic approaches may lead to inaccurate observability analyses. In this work, facing these challenges, we propose a novel polynomial-chaos-based derivative-free observability analysis approach that not only is free of any linear approximations, but also accounts for the stochasticity of the dynamic model while bringing a low implementation complexity. Furthermore, this approach enables us to quantify the degree of observability of a stochastic model, what conventional deterministic methods cannot do. The excellent performance of the proposed method has been demonstrated by performing extensive simulations using a synchronous generator model with IEEE-DC1A exciter and the TGOV1 turbine governor.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

32 examples of LLM applications in materials science and chemistry: towards automation, assistants, agents, and accelerated scientific discovery

Abstract Large language models (LLMs) are reshaping many aspects of materials science and chemistry research, enabling advances in molecular property prediction, materials design, scientific automation, knowledge extraction, and more. Recent developments demonstrate that the latest class of models are able to integrate structured and unstructured data, assist in hypothesis generation, and streamline research workflows. To explore the frontier of LLM capabilities across the research lifecycle, we review applications of LLMs through 32 total projects developed during the second annual LLM hackathon for applications in materials science and chemistry, a global hybrid event. These projects spanned seven key research areas: (1) molecular and material property prediction, (2) molecular and material design, (3) automation and novel interfaces, (4) scientific communication and education, (5) research data management and automation, (6) hypothesis generation and evaluation, and (7) knowledge extraction and reasoning from the scientific literature. Collectively, these applications illustrate how LLMs serve as versatile predictive models, platforms for rapid prototyping of domain-specific tools, and much more. In particular, improvements in both open source and proprietary LLM performance through the addition of reasoning, additional training data, and new techniques have expanded effectiveness, particularly in low-data environments and interdisciplinary research. As LLMs continue to improve, their integration into scientific workflows presents both new opportunities and new challenges, requiring ongoing exploration, continued refinement, and further research to address reliability, interpretability, and reproducibility.

Computer Science↗

DOE OSTI2014

WE-E-18A-09: Application of a Channelized Hotelling Observer Model to Evaluate Angiographic Imaging Equipment

Purpose: To develop and apply an observer model to objectively evaluate and compare the performance of different angiographic imaging equipment and acquisition variables. Methods: Image Acquisition— Iodine-based phantoms were created with target diameters: 0.5, 1, 2, and 4 mm. The phantoms were imaged using both planes of a bi-plane angiography system with detector pixel dimensions 0.1542 mm{sup 2} and 0.1842 mm{sup 2}, respectively. All four phantoms were imaged with magnification factors 1.5, 1.25 and 1 and with the large and small focal spots. Phantom position and the dose per frame (0.12– 0.24 μ Gy/frame) were varied for a single phantom size, magnification and focal spot. Observer Model— For each experimental condition, 1200 signal-present and signal-absent images were acquired and a detectability index (d') was calculated with a Gabor-channelized Hotelling observer (CHO) model. Detectability indices were evaluated as a function of dose, phantom size, and magnification. The model was then applied to compare d' of the two imaging planes and focal spots. Uncertainty in d' was estimated by bootstrapping the data and by examining the shift-variance of systems. Results: Detectability indices varied linearly with magnification and the square root of dose. For the 2 and 4 mm phantoms, d' varied linearly with diameter. For the 0.5 and 1 mm phantoms, d' expectedly deviated from this linear relationship due to substantial detector and focal spot blurring of the phantoms. The small focal spot yielded up to 50% greater d' values than the large focal spot. For the two detectors, differences in d' did not exceed the estimated ∼7% error. Conclusions: The detectability indices predictably scaled with dose, diameter, magnification, and focal spot size and serve to validate the model. Results demonstrate statistically similar target detectability for both investigated detectors, despite differences in pixel dimensions. This CHO model provides a framework to evaluate angiographic system performance.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Survey of Advanced Generation IV Reactor Parameters for Integrated Energy System Modeling Capabilities

This paper is to categorize and characterize advanced Generation IV nuclear reactors that are not water based according to the key parameters for the Integrated Energy Systems (IES) project[1]. A key goal of the IES project is to assess the economic viability of including an advanced nuclear reactor into an IES. The landscape of advanced reactors is heterogeneous: several unique designs with different heat profiles are currently being studied and designed. This report provides a high-level perspective of advanced reactor concepts, including primary loop nuclear output temperatures and operation schemes that could affect secondary side power production or storage. For example, this report addresses the type of thermodynamic system (Brayton, supercritical CO 2 [S-CO 2 ], etc.) and the various pressures and temperatures on the secondary side that are expected to be provided by the various primary side reactor types. Based on these characteristics, it may be possible to determine which type of nuclear power plant could be the most economical for analysis in the IES framework for power production coupled with energy storage and waste heat utilization. The results of this effort will serve as input for model development of various secondary side components, concentrating on off-the-shelf capabilities for current and near future secondary side power generation and heat rejection as simulated in TRANSFORM. Generic models can be created which are agnostic of the nuclear energy supply without violating intellectual property rights of the developer. These models can be used to make informed decisions on the economics of integrating various energy system components with nuclear plant designs. Once complete, conclusions may be drawn regarding (1) the economics, efficiency, and reliability of certain nuclear reactors, (2) certain industry processes and energy storage systems, and (3) prioritization of certain reactor types with the studied industry types.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Phase-field modeling of radiation-induced composition redistribution: An application to additively manufactured austenitic Fe–Cr–Ni

Multicomponent alloys undergoing irradiation damage develop radiation-induced composition redistribution at point defect sinks such as grain boundaries (GBs) and dislocations. Such redistribution results in undesired changes to their mechanical behavior and corrosion resistance. Additively manufactured alloys proposed for future nuclear applications are expected to demonstrate a distinct response to irradiation owing to their unique microstructure with as-solidified dislocation density and chemical microsegregation. To capture the composition redistribution in such systems, we develop a mesoscale model with coupled evolution of atomic and point defect components in the presence of dislocation density, dislocation heterogeneity, and thermodynamic interactions at the GB. The model is parameterized for an FCC Fe–Cr–Ni alloy as a representative system for austenitic stainless steels, and simulations are performed in 1D and 2D as a function of irradiation temperature, dose, dislocation density, and grain size. Radiation-induced segregation (RIS) characterized by Cr depletion and Ni enrichment is predicted at both the GB and the dislocation cell wall, with RIS being lower in magnitude but wider at the cell wall. Strongly biased absorption of self-interstitials by dislocations is found to suppress Ni enrichment but slightly enhance Cr depletion under certain conditions. Thermodynamic segregation at the GB is predicted to be narrower and opposite in sign to RIS for both Cr and Ni. Importantly, non-monotonic segregation is found to occur when both thermodynamic and RIS mechanisms are considered, providing a novel physical interpretation of experimental observations. The model is expected to serve as a key tool in accelerated qualification of irradiated materials.

additively manufactured microstructure↗

DOE OSTI2013

The cyanobacterial neurotoxin beta-N-methylamino-L-alanine (BMAA) induces neuronal and behavioral changes in honeybees

The cyanobacterially produced neurotoxin beta-N-methylamino-L-alanine (BMAA) is thought to induce amyotrophic lateral sclerosis/Parkinsonism dementia complex (ALS/PDC)-like symptoms. However, its mechanism of action and its pathway of intoxication are yet unknown. In vivo animal models suitable for investigating the neurotoxic effect of BMAA with applicability to the human are scarce. Hence, we used the honeybee (Apis mellifera) since its nervous system is relatively simple, yet having cognitive capabilities. Bees fed with BMAA-spiked sugar water had an increased mortality rate and a reduced ability to learn odors in a classical conditioning paradigm. Using {sup 14}C-BMAA we demonstrated that BMAA is biologically available to the bee, and is found in the head, thorax and abdomen with little to no excretion. BMAA is also transferred from one bee to the next via trophallaxis resulting in an exposure of the whole beehive. BMAA bath application directly onto the brain leads to an altered Ca{sup 2+} homeostasis and to generation of reactive oxygen species. These behavioral and physiological observations suggest that BMAA may have effects on bee brains similar to those assumed to occur in humans. Therefore the bee could serve as a surrogate model system for investigating the neurological effects of BMAA. - Highlights: • Investigating of neurotoxic effects of BMAA in honeybees • BMAA impairs ALS markers (ROS, Ca{sup 2+}, learning, memory, odor) in bees. • A method for the observation of ROS development in living bees brain was established. • Honeybees are a suitable model to explore neurodegenerative processes. • Neurotoxic BMAA can be spread in bee populations by trophallaxis.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2011

Resolution of Disulfide Heterogeneity in Nogo Receptor 1 Fusion Proteins by Molecular Engineering

NgRI (Nogo-66 receptor) is part of a signalling complex that inhibits axon regeneration in the central nervous system. Truncated soluble versions of NgRI have been used successfully to promote axon regeneration in animal models of spinal-cord injury, raising interest in this protein as a potential therapeutic target. The LRR (leucine-rich repeat) regions in NgRI are flanked by N- and C-terminal disulfide-containing 'cap' domains (LRRNT and LRRCT respectively). In the present work we show that, although functionally active, the NgRI(310)-Fc fusion protein contains mislinked and heterogeneous disulfide patterns in the LRRCT domain, and we report the generation of a series of variant molecules specifically designed to prevent this heterogeneity. Using these variants we explored the effects of modifying the NgRI truncation site or the spacing between the NgRI and Fc domains, or replacing cysteines within the NgRI or IgG hinge regions. One variant, which incorporates replacements of Cys{sup 266} and Cys{sup 309} with alanine residues, completely eliminated disulfide scrambling while maintaining functional in vitro and in vivo efficacy. This modified NgRI-Fc molecule represents a significantly improved candidate for further pharmaceutical development, and may serve as a useful model for the optimization of other IgG fusion proteins made from LRR proteins.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Observations of high-time-resolution and size-resolved aerosol chemical composition and microphysics in the central Arctic: implications for climate-relevant particle properties

Abstract. Aerosols play a critical role in the Arctic's radiative balance, influencing solar radiation and cloud formation. Limited observations in the central Arctic leave gaps in understanding aerosol dynamics year-round, affecting model predictions of climate-relevant aerosol properties. Here, we present the first annual high-time-resolution observations of submicron aerosol chemical composition in the central Arctic during the Arctic Ocean 2018 (AO2018) and the 2019–2020 Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expeditions. Seasonal variations in the aerosol mass concentrations and chemical composition in the central Arctic were found to be driven by typical Arctic seasonal regimes and resemble those of pan-Arctic land-based stations. Organic aerosols dominated the pristine summer, while anthropogenic sulfate prevailed in autumn and spring under haze conditions. Ammonium, which impacts aerosol acidity, was consistently less abundant, relative to sulfate, in the central Arctic compared to lower latitudes of the Arctic. Cyclonic (storm) activity was found to have a significant influence on aerosol variability by enhancing emissions from local sources and the transport of remote aerosol. Local wind-generated particles contributed up to 80 % (20 %) of the cloud condensation nuclei population in autumn (spring). While the analysis presented herein provides the current central Arctic aerosol baseline, which will serve to improve climate model predictions in the region, it also underscores the importance of integrating short-timescale processes, such as seasonal wind-driven aerosol sources from blowing snow and open leads/ocean in model simulations. This is particularly important, given the decline in mid-latitude anthropogenic emissions and the increase in local ones.

Heutte, Benjamin (ORCID:0000000173727460)↗

DOE OSTI2014

An Aeroelastic Reference Model for the SWIFT Turbines

This report serves as documentation of the information and considerations involved in creation of the latest version of the SWIFT turbines aeroelastic model. Information used to create the model came from a variety of sources including original Vestas drawings and hardware characterization during construction of turbines at the site. Much of the original Vestas drawings remain proprietary and are not available to the public, though they have been referenced and included in the bibliography. The tower and blades of the turbine model were first created using available design information and then were calibrated to match experimental characterizations performed during construction. Some model inputs, such as airfoil polar data and estimated blade material properties, were computed. A basic controller is created to represent the basic operation of the modified SWiFT turbines.

17 WIND ENERGY↗

DOE OSTI2020

Global biogeography of fungal and bacterial biomass carbon in topsoil

Bacteria and fungi, representing two major soil microorganism groups, play an important role in global nutrient biogeochemistry. Biogeographic patterns of bacterial and fungal biomass are of fundamental importance for mechanistically understanding nutrient cycling. We synthesized 1323 data points of phospholipid fatty acid-derived fungal biomass C (FBC), bacterial biomass C (BBC), and fungi:bacteria (F:B) ratio in topsoil, spanning 11 major biomes. The FBC, BBC, and F:B ratio display clear biogeographic patterns along latitude and environmental gradients including mean annual temperature, mean annual precipitation, net primary productivity, root C density, soil temperature, soil moisture, and edaphic factors. At the biome level, tundra has the highest FBC and BBC densities at 3684 (95% confidence interval: 1678–8084) mg kg -1 and 428 (237–774) mg kg -1 , respectively; desert has the lowest FBC and BBC densities at 16.92 (14.4–19.89) mg kg -1 and 6.83 (6.1–7.65) mg kg -1 , respectively. The F:B ratio varies dramatically, ranging from 1.8 (1.6–2.1) in savanna to 8.6 (6.7–11.0) in tundra. An empirical model was developed for the F:B ratio and it is combined with a global dataset of soil microbial biomass C to produce global maps for FBC and BBC in 0–30 cm topsoil. Across the globe, the highest FBC is found in boreal forest and tundra while the highest BBC is in boreal forest and tropical/subtropical forest, the lowest FBC and BBC are in shrub and desert. Global stocks of living microbial biomass C were estimated to be 12.6 (6.6–16.4) Pg C for FBC and 4.3 (0.5–10.3) Pg C for BBC in topsoil. These findings advance our understanding of the global distribution of fungal and bacterial biomass, which facilitates the incorporation of fungi and bacteria into Earth system models. The global maps of bacterial and fungal biomass serve as a benchmark for validating microbial models in simulating the global C cycle under a changing climate.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Smelly-Odor Webtool (Smelly) v1

Smelly is an interactive webtool displaying odor dispersion from various potential waste-to-energy sites across California. It currently displays data for dry anaerobic digestion technology with organic waste intake of 90,000 tons per year. The model addresses meteorological and geographical differences in offsite odor impacts (Jin et al. 2019). In addition to interactive display of odor dispersions, the embedded emission calculator provides two additional functionalities: (1) determine the impact distance for given onsite odor emission rates; and (2) determine allowable odor emission rates at given separation distance between the facility and its downwind communities. Please note that data and model is preliminary at this point and serve as a Proof of Concept. Additional data collection, modeling and research is needed for final application.

Jin, Ling↗

DOE OSTI2013

THERMAL AND DYNAMICAL PROPERTIES OF GAS ACCRETING ONTO A SUPERMASSIVE BLACK HOLE IN AN ACTIVE GALACTIC NUCLEUS

We study stability of gas accretion in active galactic nuclei (AGNs). Our grid-based simulations cover a radial range from 0.1 to 200 pc, which may enable linking the galactic/cosmological simulations with small-scale black hole (BH) accretion models within a few hundreds of Schwarzschild radii. Here, as in previous studies by our group, we include gas radiative cooling as well as heating by a sub-Eddington X-ray source near the central supermassive BH of 10{sup 8} M{sub Sun }. Our theoretical estimates and simulations show that for the X-ray luminosity, L{sub X} {approx} 0.008 L{sub Edd}, the gas is thermally and convectively unstable within the computational domain. In the simulations, we observe that very tiny fluctuations in an initially smooth, spherically symmetric, accretion flow, grow first linearly and then nonlinearly. Consequently, an initially one-phase flow relatively quickly transitions into a two-phase/cold-hot accretion flow. For L{sub X} = 0.015 L{sub Edd} or higher, the cold clouds continue to accrete but in some regions of the hot phase, the gas starts to move outward. For L{sub X} < 0.015 L{sub Edd}, the cold phase contribution to the total mass accretion rate only moderately dominates over the hot phase contribution. This result might have some consequences for cosmological simulations of the so-called AGN feedback problem. Our simulations confirm the previous results of Barai et al. who used smoothed particle hydrodynamic (SPH) simulations to tackle the same problem. Here, however, because we use a grid-based code to solve equations in one dimension and two dimensions, we are able to follow the gas dynamics at much higher spacial resolution and for longer time compared with the three-dimensional SPH simulations. One of the new features revealed by our simulations is that the cold condensations in the accretion flow initially form long filaments, but at the later times, those filaments may break into smaller clouds advected outward within the hot outflow. Therefore, these simulations may serve as an attractive model for the so-called narrow-line region in AGNs.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Dynamic Oscillation and Motion of Oil‐in‐Water Emulsion Droplets

Abstract The interplay of interfacial tensions on droplets results in a range of self‐powered motions that mimic those of living systems and serve as a tunable model to understand their complex non‐equilibrium behavior. Spontaneous shape deformations and oscillations are crucial features observed in nature but difficult to incorporate in synthetic artificial systems. Here, we report sessile oil‐in‐water emulsions that exhibit rapid oscillating behavior. The oscillations depend on the nature and concentration of the surfactant, the chemical composition of the oil, and the wettability of the solid substrate. The rapid changes in the contact angle per oscillation are observed using side‐view optical microscopy. We propose that the changes in the interfacial tension of the oil droplets is due to the partitioning of the surfactant into the oil phase and the movement of self‐emulsified oil out of the parent droplets giving rise to the rhythmic variation in droplet contact‐line. The ability to control and understand droplet oscillation can help model similar oscillations in out‐of‐equilibrium systems in nature and reproduce biomimetic behavior in artificial systems for various applications, such as microfluidic lab‐on‐a‐chip and adaptive materials.

Krishna Mani, Sanjana↗