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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Pressure–strain interaction. III. Particle-in-cell simulations of magnetic reconnection

How energy is converted into thermal energy in weakly collisional and collisionless plasma processes, such as magnetic reconnection and plasma turbulence, has recently been the subject of intense scrutiny. The pressure–strain interaction has emerged as an important piece, as it describes the rate of conversion between bulk flow and thermal energy density. In two companion studies, we presented an alternate decomposition of the pressure–strain interaction to isolate the effects of converging/diverging flow and flow shear instead of compressible and incompressible flow, and we derived the pressure–strain interaction in magnetic field-aligned coordinates. Here, we use these results to study pressure–strain interaction during two-dimensional anti-parallel magnetic reconnection. We perform particle-in-cell simulations and plot the decompositions in both Cartesian and magnetic field-aligned coordinates. We identify the mechanisms contributing to positive and negative pressure–strain interaction during reconnection. Furthermore, this study provides a roadmap for interpreting numerical and observational data of the pressure–strain interaction, which should be important for studies of reconnection, turbulence, and collisionless shocks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Sparse Symmetric Format for Tucker Decomposition

Tensor-based methods are receiving renewed attention in recent years due to their prevalence in diverse real-world applications. There is considerable literature on tensor representations and algorithms for tensor decompositions, both for dense and sparse tensors. Many applications in hypergraph analytics, machine learning, psychometry, and signal processing result in tensors that are both sparse and symmetric, making them an important class for further study. Similar to the critical Tensor Times Matrix chain operation (TTM c ) in general sparse tensors, the $\underline{S}$ parse $\underline{S}$ ymmetric $\underline{T}$ ensor $\underline{T}$ imes $\underline{S}$ ame $\underline{M}$ atrix $\underline{c}$ hain (S 3 TTM c ) operation is compute and memory intensive due to high tensor order and the associated factorial explosion in the number of non-zeros. We present the novel Compressed Sparse Symmetric (CSS) format for sparse symmetric tensors, along with an efficient parallel algorithm for the S 3 TTM c operation. We theoretically establish that S 3 TTM c on CSS achieves a better memory versus run-time trade-off compared to state-of-the-art implementations, and visualize the variation of the performance gap over the parameter space. We demonstrate experimental findings that confirm these results and achieve up to 2.72× speedup on synthetic and real datasets. The scaling of the algorithm on different test architectures is also showcased to highlight the effect of machine characteristics on algorithm performance.

42 ENGINEERING↗
DOE OSTI2026

Improvements to In-Canal Assay of High Specific Activity 60Co at the ATR

Improvements to the quality of measurements in the assaying of High Specific Activity (HSA) cobalt 60 produced at the Advanced Test Reactor at the Idaho National Laboratory are presented. Such assays are conducted regularly between cycles at the ATR, and due to the radiological safety concerns, they are performed within the ATR canal. A standard ion chamber detector was placed in a collimated assay tube within the canal. Another tube, parallel to the detector, was used to position various cobalt 60 standards and targets. The collimated port between these tubes allows for the targets to be pulled across via a winch system. Previous measurements were performed at discrete 1.5-inch steps using a hand-cranked winch system. Charge was collected and integrated for 10 seconds at each discrete step during a scan. Two substantial improvements to the assay include an electronically controlled, motor-driven winch system and a software controlled continuous charge collection. Combined, these changes improved the quality of measurements as well as streamline the assay process. Further examination of these charge profiles indicated a reasonable amount of photon scattering, or shine, before a line-of-sight is established. This created inaccuracies in the reported activity of the cobalt targets. A series of MCNP-6.3 calculations were performed in an effort to quantify and correct for this shine effect. The results of the calculations and how they were employed to a create shine correction factor for the in-canal cobalt assay at the ATR are presented. The overall bias showed an overestimation of the HSA cobalt 60 activity by around 7-8%.

07 - ISOTOPES AND RADIATION SOURCES↗
DOE OSTI2020

Molecular-scale origins of wettability at petroleum–brine–carbonate interfaces

Wettability control of carbonates is a central concept for enhanced petroleum recovery, but a mechanistic understanding of the associated molecular-scale chemical processes remains unclear. We directly probe the interface of calcium carbonate (calcite) with natural petroleum oil, synthetic petroleum analogues, and aqueous brines to understand the molecular scale behavior at this interface. The calcite–petroleum interface structure is similar whether or not calcite was previously exposed to an aqueous brine, and is characterized by an adsorbed interfacial layer, significant structural changes within the calcite surface, and increased surface roughness. No evidence for an often-assumed thin-brine wetting layer at the calcite–petroleum interface is observed. These features differ from those observed at the calcite–brine interface, and for parallel measurements using model synthetic petroleum mixtures (consisting of representative components, including dodecane, toluene, and asphaltene). Changes to the interface after petroleum displacement by aqueous brines are also discussed.

02 PETROLEUM↗
DOE OSTI2023

Transforming microseismic clouds into near real-time visualization of the growing hydraulic fracture

SUMMARY Microseismic observations during unconventional reservoir stimulation are typically seen as a proxy for clusters of hydraulic fractures and the extent of the stimulated reservoir. Such straightforward interpretation is often misleading and fails to provide a physically reasonable image of the fracturing process. This paper demonstrates the application of a physics-based machine learning algorithm which enables a rapid and accurate fracture mapping from the microseismic data. Our training and validation data set relies on a history-matched geomechanical modelling workflow implemented in GEOS software for the Hydraulic Fracturing Test Site 1 (HFTS-1) project. For this study we augmented the simulated fracture growth through geostatistical modelling of induced seismicity, so that the synthetic microseismic catalogue matches the main statistical properties of the field observations. We formulated the problem of mapping the actual fracture in the clutter of events to parallel common video segmentation workflows: several past video frames (microseismic density snapshots) are passed through a deep convolutional network to classify whether a given voxel is associated with a fracture or intact rock. We found that for accurate fracture mapping, the network’s input and architecture must be augmented to incorporate the fluid injection parameters (pressure, rate, concentration of proppant, and location of the perforation within the cluster). The error rate for the network reached as little as 10 per cent of the fracture area, while a conventional microseismic interpretation approach yielded ∼300 per cent. Our approach also yields must faster predictions than conventional methods (minutes instead of weeks), and could enable engineers to make rapid decisions regarding engineering parameters (pumping rate, viscosity) in real time during stimulation.

58 GEOSCIENCES↗
DOE OSTI2023

Toward the discovery of matter creation with neutrinoless β β decay

The discovery of neutrinoless ββ decay could soon be within reach. This hypothetical ultrarare nuclear decay offers a privileged portal to physics beyond the standard model of particle physics. Its observation would constitute the discovery of a matter-creating process, corroborating leading theories of why the Universe contains more matter than antimatter, and how forces unify at high energy scales. It would also prove that neutrinos and antineutrinos are not two distinct particles but can transform into each other, with their mass described by a unique mechanism conceived by Majorana. The recognition that neutrinos are not massless necessitates an explanation and has boosted interest in neutrinoless ββ decay. The field stands now at a turning point. Further, a new round of experiments is currently being prepared for the next decade to cover an important region of parameter space. In parallel, advances in nuclear theory are laying the groundwork to connect the nuclear decay with the underlying new physics. Meanwhile, the particle theory landscape continues to find new motivations for neutrinos to be their own antiparticle. This review brings together the experimental, nuclear theory, and particle theory aspects connected to neutrinoless ββ decay to explore the path toward, and beyond, its discovery.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Subspace recursive Fermi-operator expansion strategies for large-scale DFT eigenvalue problems on HPC architectures

Quantum mechanical calculations for material modeling using Kohn–Sham density functional theory (DFT) involve the solution of a nonlinear eigenvalue problem for N smallest eigenvector-eigenvalue pairs, with N proportional to the number of electrons in the material system. Here, these calculations are computationally demanding and have asymptotic cubic scaling complexity with the number of electrons. Large-scale matrix eigenvalue problems arising from the discretization of the Kohn–Sham DFT equations employing a systematically convergent basis traditionally rely on iterative orthogonal projection methods, which are shown to be computationally efficient and scalable on massively parallel computing architectures. However, as the size of the material system increases, these methods are known to incur dominant computational costs through the Rayleigh–Ritz projection step of the discretized Kohn–Sham Hamiltonian matrix and the subsequent subspace diagonalization of the projected matrix. This work explores the potential of polynomial expansion approaches based on recursive Fermi-operator expansion as an alternative to the subspace diagonalization of the projected Hamiltonian matrix to reduce the computational cost. Subsequently, we perform a detailed comparison of various recursive polynomial expansion approaches to the traditional approach of explicit diagonalization on both multi-node central processing unit and graphics processing unit architectures and assess their relative performance in terms of accuracy, computational efficiency, scaling behavior, and energy efficiency.

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

Optimizing High Performance Markov Clustering for Pre-Exascale Architectures

HipMCL is a high-performance distributed memory implementation of the popular Markov Cluster Algorithm (MCL) and can cluster large-scale networks within hours using a few thousand CPU-equipped nodes. It relies on sparse matrix computations and heavily makes use of the sparse matrix-sparse matrix multiplication kernel (SpGEMM). The existing parallel algorithms in HipMCL are not scalable to Exascale architectures, both due to their communication costs dominating the runtime at large concurrencies and also due to their inability to take advantage of accelerators that are increasingly popular. In this work, we systematically remove scalability and performance bottlenecks of HipMCL. We enable GPUs by performing the expensive expansion phase of the MCL algorithm on GPU. Additionally, we propose a CPU-GPU joint distributed SpGEMM algorithm called pipelined Sparse SUMMA and integrate a probabilistic memory requirement estimator that is fast and accurate. Furthermore, we develop a new merging algorithm for the incremental processing of partial results produced by the GPUs, which improves the overlap efficiency and the peak memory usage. We also integrate a recent and faster algorithm for performing SpGEMM on CPUs. We validate our new algorithms and optimizations with extensive evaluations. With the enabling of the GPUs and integration of new algorithms, HipMCL is up to 12.4x faster, being able to cluster a network with 70 million proteins and 68 billion connections just under 15 minutes using 1024 nodes of ORNL's Summit supercomputer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

BAWLD-CH 4 : a comprehensive dataset of methane fluxes from boreal and arctic ecosystems

Methane (CH 4 ) emissions from the boreal and arctic region are globally significant and highly sensitive to climate change. There is currently a wide range in estimates of high-latitude annual CH 4 fluxes, where estimates based on land cover inventories and empirical CH 4 flux data or process models (bottom-up approaches) generally are greater than atmospheric inversions (top-down approaches). A limitation of bottom-up approaches has been the lack of harmonization between inventories of site-level CH 4 flux data and the land cover classes present in high-latitude spatial datasets. Here we present a comprehensive dataset of small-scale, surface CH 4 flux data from 540 terrestrial sites (wetland and non-wetland) and 1247 aquatic sites (lakes and ponds), compiled from 189 studies. The Boreal–Arctic Wetland and Lake Methane Dataset (BAWLD-CH 4 ) was constructed in parallel with a compatible land cover dataset, sharing the same land cover classes to enable refined bottom-up assessments. BAWLD-CH 4 includes information on site-level CH 4 fluxes but also on study design (measurement method, timing, and frequency) and site characteristics (vegetation, climate, hydrology, soil, and sediment types, permafrost conditions, lake size and depth, and our determination of land cover class). The different land cover classes had distinct CH 4 fluxes, resulting from definitions that were either based on or co-varied with key environmental controls. Fluxes of CH 4 from terrestrial ecosystems were primarily influenced by water table position, soil temperature, and vegetation composition, while CH 4 fluxes from aquatic ecosystems were primarily influenced by water temperature, lake size, and lake genesis. Models could explain more of the between-site variability in CH 4 fluxes for terrestrial than aquatic ecosystems, likely due to both less precise assessments of lake CH 4 fluxes and fewer consistently reported lake site characteristics. Analysis of BAWLD-CH 4 identified both land cover classes and regions within the boreal and arctic domain, where future studies should be focused, alongside methodological approaches. Overall, BAWLD-CH 4 provides a comprehensive dataset of CH 4 emissions from high-latitude ecosystems that are useful for identifying research opportunities, for comparison against new field data, and model parameterization or validation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Deterministic Fast Scrambling with Neutral Atom Arrays

Fast scramblers are dynamical quantum systems that produce many-body entanglement on a timescale that grows logarithmically with the system size N. Here, we propose and investigate a family of deterministic, fast scrambling quantum circuits realizable in near-term experiments with arrays of neutral atoms. We show that three experimental tools—nearest-neighbor Rydberg interactions, global single-qubit rotations, and shuffling operations facilitated by an auxiliary tweezer array—are sufficient to generate nonlocal interaction graphs capable of scrambling quantum information using only O(logN) parallel applications of nearest-neighbor gates. These tools enable direct experimental access to fast scrambling dynamics in a highly controlled and programmable way and can be harnessed to produce highly entangled states with varied applications.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Reflection absorption infrared spectroscopy of the surface chemistry of furfural on Pd(111)

The hydrolysis and subsequent acidic dehydration of biomass leads to the production of smaller oxygenates, including furfural, which can undergo subsequent reactions such as hydrogenation to produce value-added products. Palladium has been found to be an active catalyst for this process. As a result, the surface chemistry of furfural is investigated on a Pd(111) single-crystal surface using reflection-absorption infrared spectroscopy as a basis for understanding the catalytic conversion of furfural to value-added products. Following adsorption at 90 K, furfural adopts a flat-lying geometry at low coverages, but converts to a tilted species as the coverage approaches saturation. Heating to ~175 K forms a tilted η 1 (O) species that appears to deprotonate on heating to above 200 K to form an intermediate with a tilted furyl ring and a carbonyl group close to parallel to the surface. Further heating to ~250 K and above caused this species to decarbonylate to form adsorbed carbon monoxide and an infrared invisible furyl intermediate. This can then undergo a ring-opening reaction to produce further CO and form a C 3 H 3 intermediate that can hydrogenate to produce propylene. Finally, this reaction sequence is in good agreement with previous density functional theory calculations and with the products observed in temperature-programmed desorption.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Femtojoule optical nonlinearity for deep learning with incoherent illumination

Optical neural networks (ONNs) are a promising computational alternative for deep learning due to their inherent massive parallelism for linear operations. However, the development of energy-efficient and highly parallel optical nonlinearities, a critical component in ONNs, remains an outstanding challenge. Here, we introduce a nonlinear optical microdevice array (NOMA) compatible with incoherent illumination by integrating the liquid crystal cell with silicon photodiodes at the single-pixel level. We fabricate NOMA with more than half a million pixels, each functioning as an optical analog of the rectified linear unit at ultralow switching energy down to 100 femtojoules per pixel. With NOMA, we demonstrate an optical multilayer neural network. Our work holds promise for large-scale and low-power deep ONNs, computer vision, and real-time optical image processing.

36 MATERIALS SCIENCE↗
DOE OSTI2023

TCF High Efficiency Anaerobic Electroporation (CRADA Final Report)

The Joint BioEnergy Institute (JBEI) researchers were co-inventors of the technology that will be used on this project and have developed a more current version of the chip and controller. JBEI will also assist with the design of the pathways and implementation of pathways on the chip. LanzaTech has developed novel gas fermentation technology that captures and utilizes greenhouse gases for production of fuels and chemicals. In contrast to traditional fermentation that uses sugars as substrate (and releases CO2 as a byproduct), gas fermentation utilizes C1 substrates carbon monoxide (CO) or CO2. This enables a diverse range of feedstock options including waste gases from industrial sources (e.g., steel mills and processing plants) or syngas generated from any biomass resource (e.g., agricultural waste, municipal solid waste, or organic industrial waste). Biomass is then gasified, allowing for maximum yields and complete carbon utilization including the recalcitrant lignocellulosic fraction that cannot be utilized in traditional sugar fermentation. To maximize the value that can be added to the array of gas resources that the LanzaTech process can use as an input, LanzaTech has pioneered genetic modification of acetogens and developed a comprehensive set of genetic tools to perform routine strain modification, including genome editing tools as CRISPR/Cas9 and libraries of validated genetic parts as promoters and terminators. Using this platform, production of over 50 new molecules have been demonstrated directly from gas. For a few selected molecules production rates and yields have been optimized and surpass production of native producers and engineered E. coli or yeast strains, but a higher throughput approach for combinatorial optimization of pathways is required to further advance synthesis of additional products in parallel.

09 BIOMASS FUELS↗
DOE OSTI2020

Integrated hydrogeophysical modelling and data assimilation for geoelectrical leak detection

Time-lapse electrical resistivity tomography (ERT) measurements provide indirect observations of hydrological processes in the Earth's shallow subsurface at high spatial and temporal resolution. ERT has been used in the past decades to detect leaks and monitor the evolution of associated contaminant plumes. Specifically, inverted resistivity images allow visualization of the dynamic changes in the structure of the plume. However, existing methods do not allow the direct estimation of leak parameters (e.g. leak rate, location, etc.) and their uncertainties. We propose an ensemble-based data assimilation framework that evaluates proposed hydrological models against observed time-lapse ERT measurements without directly inverting for the resistivities. Each proposed hydrological model is run through the parallel coupled hydro-geophysical simulation code PFLOTRAN-E4D to obtain simulated ERT measurements. The ensemble of model proposals is then updated using an iterative ensemble smoother. In this paper, we demonstrate the proposed framework on synthetic and field ERT data from controlled tracer injection experiments. Our results show that the approach allows joint identification of contaminant source location, initial release time, and solute loading from the cross-borehole time-lapse ERT data, alongside with an assessment of uncertainties in these estimates. We demonstrate a reduction in site-wide uncertainty by comparing the prior and posterior plume mass discharges at a selected image plane. This framework is particularly attractive to sites that have previously undergone extensive geological investigation (e.g., nuclear sites). It is well suited to complement ERT imaging and we discuss practical issues in its application to field problems.

58 GEOSCIENCES↗
DOE OSTI2024

Reconceptualizing the Ir III Role in Metallaphotoredox Catalysis: From Strong Photooxidant to Potent Energy Donor

Dual Ir III /L n Ni II metallaphotoredox catalyzed C(sp 3 )–C(sp 2 ) cross-coupling reactions are widely assumed to proceed by photoinduced single electron transfer steps due to the highly oxidizing Ir III * excited state (Ir III = [Ir(dF(CF 3 )ppy) 2 (dtbbpy)] + [PF 6 ] – ; dF(CF 3 )ppy = 2-(2,4-difluorophenyl)-5-(trifluoromethyl)pyridine; L n = dtbbpy = 4,4'-di-tert-butyl-2,2'-bipyridine). Using time-resolved absorption and emission spectroscopy, we reveal that energy transfer between Ir III * and various LnNi II precatalysts and intermediates with k q ≥ 10 8 M –1 s –1 also drives catalysis. Specifically, the excited states of L n Ni II dihalide precatalysts/organometallic intermediates accessible by energy transfer appear to drive bond homolysis, halogen radical elimination, and reductive elimination reactions that facilitate formation of cross-coupled products. Energy transfer dynamics consequently circumvent the need for photoinduced electron transfer, thereby extending substrate scopes to coupling partners that cannot be oxidized by Ir III *. Within a cross-electrophile coupling model reaction between 4-bromobenzotrifluoride and bromocyclohexane, energy transfer activates the L n Ni II precatalyst at early reaction times before nucleophilic reductants are present. In the absence of Ir III , direct excitation of L n Ni II (Br) 2 also activates the precatalyst to form a L n Ni II (Br)(Aryl) intermediate. To compare energy transfer and electron transfer kinetics, we determined rate constants for reductive quenching by Br – (k SET = 4.1 × 10 8 M –1 s –1 ) and for the subsequent electron transfer from reduced Ir III•– to L n Ni II (Br) 2 (k SET = 4.1 × 10 7 M –1 s –1 ) using Stern-Volmer analysis and pulse radiolysis, respectively. Energy transfer rate constants are competitive with the electron transfer rate constants and energy transfer is a parallel pathway within metallaphotoredox catalysis. Exploiting the energy transfer mechanism, we demonstrate highly selective cross-electrophile coupling between 4-chlorobenzotrifluoride and bromocyclohexane to form exclusively cross-coupled product. Here, with alkyl-trifluoroborate nucleophiles that do not reductively quench IrIII* emission, transmetalation with L n Ni II (Br/Cl)(Aryl) followed by energy transfer also drives excited state reductive elimination to form C(sp 3 )–C(sp 2 ) cross-coupled product. Similarly, energy transfer rather than Ni II oxidation drives C(sp 2 )–OR reductive elimination, despite the strongly oxidizing ability of Ir III *. In total, these reactions demonstrate energy transfer processes from Ir III * to L n Ni II in metallaphotoredox catalysis that can unlock alternative reactive pathways.

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

Experimental observation and numerical investigation of filamentary structures in magnetized plasmas

Filamentary structures in low-pressure, low-temperature plasmas are produced when strong magnetic fields are applied parallel to the electric field defined by parallel electrodes. Filamentary structures are regions within the plasma that have distinct properties such as optical brightness and extend along the magnetic field lines. In our experiments, an argon, radio frequency discharge is exposed to a strong background magnetic field in the magnetized dusty plasma experiment at Auburn University. Different forms of filamentary structures emerge in the plasma such as columns, target, or spiral-like structures. To investigate the origin and the characteristics of these patterns, we have developed a three-dimensional fluid model that can reproduce the experimental observations which enables us to investigate the underlying mechanisms of the filamentation process.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

BESTEST-GSR (Building Energy Simulation Test - Generation Simulation and Reporting) 2023 [SWR 18-23]

Building Energy Simulation Test (BESTEST) is an NREL-developed method to validate the qualitative performance of different whole building simulations engines relative to each other. https://www.nrel.gov/docs/legosti/old/6231.pdf The purpose of this repository is to generate BESTEST test case models, run simulations, and populate data for ASHRAE Standard 140 reporting spreadsheets for EnergyPlus® based whole building simulation tools. It was originally setup for 2014 version of Standard 140. In May of 2022 it was updated to the 2020 version of Standard 140. This update included updates and additions to existing test suites, the bulk of which was in Section 5.2 (Building Thermal Envelope and Fabric Load Tests). We did not add Section 5.5 Airside HVAC Equipment Performance, but we hope to add that later in 2022. At some point we also hope to add Section 5.2.4 ground modeling, which is currently excluded. Supported Tools The default IDF generation is based on the OpenStudio® CLI, but the workflow supports a 'Bring your own IDF' use case. Additionally, for non-EnergyPlus® based tools the post processing scripts can be used if simulation results are provided as a CSV file.The scripts on this repository should work on Mac, Windows, and Linux. Dependencies Install OpenStudio® 3.4.0 make sure command line can recognize the 'openstudio' command This includes EnergyPlus® 22.1 Install Ruby on your system if it isn't already setup. 2.7 is used for development but other versions may work Since OpenStudio has its own embedded Ruby, which is used for running measures, you don't necessarily have to use a version of Ruby supported by OpenStudio. Install RubyXL Ruby gem This is used to modify Microsoft Excel spreadsheets Install Parallel Ruby gem This allows the CLI to run simulations in parallel

Goldwasser, David↗
DOE OSTI2023

Smart Droplets Stabilized by Designer Surfactants: From Biomimicry to Active Motion to Materials Healing

The science and technologies of emulsion droplets have been a long‐term focus of extensive research endeavors for their practical utility across a breadth of industries, including pharmaceutical products, oil recovery processes, and the food sciences. However, with advances in materials chemistry and characterization tools, new emerging areas are arising with a focus on “smart droplets”. The versatility of emulsion droplets across is based on their ability to partition and create isolated systems with properties defined by the liquid–liquid interface, while preparative routes allow manipulation of droplet size, stability, and encapsulated contents. As described in this article, significant efforts are being devoted to creating new types of droplets by “activating” this interface through the incorporation of reactive structures that trigger droplet response to applied or environmental stimuli (e.g., pH, temperature, salt, or external fields). Moreover, parallels between droplets and live cells inspire efforts to conceive systems that resemble biological motifs or that can produce cellular behaviors that imitate biology (e.g., swarming, communication, or motion). Here, the authors highlight recent advances in smart droplets, with emphasis on organic, polymer, and/or particle surfactants that give rise to inter‐droplet communication (via aggregation, fusion, division, or mass transfer), droplet vehicles for controlled delivery, autonomous droplet motion, and tunable emulsion inversion. Especially emphasized is the macromolecular design to produce reactive and functional surfactants, which are crucial to responsive droplet behavior and their underlying mechanisms. More generally, the exquisite interplay between materials science and biology inspires the review of this research area that provides unique opportunities for insight and inspiration into the capabilities of new droplet designs.

36 MATERIALS SCIENCE↗