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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Low Carbon Inducible2/Fatty Acid Desaturase4 locus in C. reinhardtii directs plastid peroxidase location and trans fatty acid production

Light capture and photosynthetic energy conversion depend on photosynthetic complexes that are embedded within lipid membranes. Components of these complexes are vulnerable to damage by reactive oxygen species, byproducts of photosynthesis that accumulate under environmental stress. Here we explore the basis for a lipid-based sensing mechanism allowing plants or algae to assess and respond to damage to the photosynthetic membranes. In Chlamydomonas reinhardtii, Low Carbon Inducible2 (LCI2) and Fatty Acid Desaturase4 (FAD4) are two proteins derived from the same locus by a differential splicing event, sharing an N-terminus encoded by the first two exons. FAD4 produces a 16-carbon, trans double bond-containing fatty acid found exclusively in phosphatidylglycerol of chloroplast membranes, while LCI2 recruits peroxidase activity to the membrane. The unique organization and transcriptional regulation of the LCI2/FAD4 locus represents a regulatory interface that allows cells to initiate the biosynthesis of a fatty acid unique to the photosynthetic membranes while also linking it to the production of an enzyme involved in the mitigation of reactive oxygen species.

Nicodemus, Timothy J [Michigan State University, E↗
DOE OSTI2020

Developing Flexible, Networked Lighting Control Systems That Reliably Save Energy in California Buildings

An important strategy to meet California's ambitious energy efficiency goals is to use innovative wireless communications, embedded sensors, data analytics and controls to significantly reduce lighting energy use in commercial buildings. This project developed a suite of networked lighting solutions to further this goal. The technologies include a platform for low-cost sensing, distributed intelligence and communications, the “PermaMote,” which is a self-powered sensor and controller for lighting applications. The project team also developed a task ambient daylighting system that integrates sensors with data-driven daylighting control using an open communication interface, called the “Readings-At-Desk” (RAD) system. To address the problem of building occupants being confused about how to operate traditional lighting control systems, the research team created content that could be the basis for a user interface standard for lighting controls. Finally, to address the difficulty of ensuring that advanced lighting control systems actually deliver their promised energy savings, the project team developed a new method for evaluating and specifying lighting systems’ performance. The research team validated these technologies in the laboratory, showing significant lighting energy savings, up to 73% for the PermaMote sensor system from occupancy control and daylight dimming features, compared to the same light source (LED replacement lamps) operated via simple on/off scheduling. The project team also developed a proposed standard lighting data model and user interface elements, which were contributed to the ANSI Lighting Systems Committee (C137) for standardization. Existing data models are incomplete and inconsistent, whereas the lighting-specific data model developed here is clear and comprehensive, to serve as a starting point for creating common, universally agreed upon semantic definitions of key lighting parameters, to promote interoperability. For the task on verifiable performance of lighting systems, the project team developed a more effective metric for capturing the actual energy impact of a lighting system over time — the energy usage intensity (kWh/ft2/year). Three commercial lighting systems were tested in FLEXLAB® using this new metric, and the tests show a wide range in the accuracy of the self-reported energy-use metric, from 0.5% to 28% error compared to direct measurement of lighting energy using dedicated submeters. Overall, the project team estimates that these advanced technologies can reduce California office lighting energy use by 20% (above and beyond normal advanced lighting controls mandated by Title 24), resulting in about 1,600 GWh/year in savings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

First-Principles Predictions of Out-of-Plane Group IV and V Dimers as High-Symmetry, High-Spin Defects in Hexagonal Boron Nitride

Hexagonal boron nitride (h-BN) has been recently found to host a variety of quantum point defects, which are promising candidates as single-photon sources for solid-state quantum nanophotonic applications. Most recently, optically addressable spin qubits in h-BN have been the focus of intensive research due to their unique potential in quantum computation, communication, and sensing. However, the number of high-symmetry, high-spin defects that are desirable for developing spin qubits in h-BN is highly limited. Here, we combine density functional theory (DFT) and quantum embedding theories to show that out-of-plane X N Y i dimer defects (X, Y = C, N, P, and Si) form a new class of stable C 3v spin-triplet defects in h-BN. We find that the dimer defects have a robust 3 A 2 ground state and 3 E excited state, both of which are isolated from the h-BN bulk states. We show that 1 E and 1 A shelving states exist and they are positioned between the 3 E and 3 A 2 states for all the dimer defects considered in this study. To support future experimental identification of the X N Y i dimer defects, we provide extensive characterization of the defects in terms of their spin and optical properties. We predict that the zero-phonon line of the spin-triplet X N Y i defects lies in the visible range (800 nm to 500 nm). We compute the zero-field splitting of the dimers’ spin to range from 1.79 GHz (Si N P i o ) to 29.5 GHz (C N N i o ). Furthermore, our results broaden the scope of high-spin defect candidates that would be useful for the development of spin-based solid-state quantum technologies in two-dimensional hexagonal boron nitride.

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

Carbon-Based Quantum Information Science with Symmetry Protected Topological States (Final Report, DOE-BES award DE-SC0023105)

This research program established the scientific foundation for the rational, bottom-up design, synthesis, isolation, and investigation of symmetry-protected topological (SPT) electron spin qubits embedded in graphene nanoribbons (GNRs). The work focused on integrating atomically precise low-dimensional carbon nanostructures with emerging quantum logic architectures, providing a pathway toward scalable quantum materials for next-generation computing and sensing technologies. A central component of the program was the elucidation of fundamental relationships between real-space molecular architecture, local spin density distributions, electronic band dispersion, and energy level alignment in atomically precise GNR systems. These correlations define key operational parameters of SPT qubits and were systematically investigated to establish quantitative benchmarks against established molecular and solid-state spin qubit platforms. Attention was given to properties critical for quantum device performance, e.g. decoherence times, spectral sharpness of energy transitions, and tunable exchange interactions between spin states. The research demonstrated that these parameters can be engineered with atomic precision through scalable bottom-up synthetic strategies. Theory-guided design played a central role in identifying candidate structures hosting topologically protected spin states. Experimental validation was performed using both ensemble measurements and single-molecule characterization. In addition to advances in quantum materials synthesis, the program developed and applied spin-sensitive scanning probe microscopy techniques capable of directly probing quantum states and dynamic processes with atomic-scale spatial resolution. These capabilities enabled direct observation and characterization of quantum structures at the single-atom level. While the research activities were primarily hypothesis-driven fundamental investigations, the program adopted a comprehensive materials-by-design framework aimed at translating scientific discoveries into technological concepts compatible with scalable and intelligent manufacturing approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Distributed Optical Fiber Sensor Systems: Application to Natural Gas Pipeline Monitoring

Distributed fiber optic sensing is a cutting-edge technology that has found extensive applications in the monitoring of pipelines. Considering the low backscattering level of standard single-mode fiber as fiber under test, a Rayleigh enhanced optical fiber embedded within the tight-buffered cable is demonstrated in field testing. We analyzed the increased backscattering fiber cable's vibration performance to the conventional single-mode telecom fiber using a custom-built Φ-OTDR interrogator system. Thereafter, using a 4-inch steel pipeline with a flow rate of 5, 10, 15, and 20 ft/s and a fixed pressure level of 1000 psi, we field-tested the sensor system for monitoring natural gas pipeline acoustic vibrations. We also field tested Brillouin optical time domain analysis (BOTDA) system for pipeline hoop strain monitoring under various pressure conditions. The pilot-scale testing results presented in this study suggested that pipeline operators can accurately perform flow monitoring, leak detection, and pressure monitoring for pipeline integrity monitoring.

Lalam, Nageswara↗
DOE OSTI2023

Middleware for a Heterogeneous CAV Fleet

This paper introduces CAN to ROS, a model-based code generation tool used in development, testing, and deployment of a heterogeneous fleet of vehicles with robotic sensing in ROS. Code generation supports two main features: (1) self-configuration for deployment in a heterogeneous vehicle fleet, and (2) quick iteration for testing and development of reading vehicle sensors and robotic control. This tool features the ability to detect the vehicle it is in and regenerate and rebuild itself at runtime to provide the proper two-way bridge between ROS and the sensed on-board vehicle sensor network. Code generation relies on a per-model defined JSON to map a CAN database (DBC) to the desired ROS topic names and message types. The live ROS publishing of CAN messages allows for instant feedback, and the code regeneration allows for adjustments in DBC or vehicle JSON to iteratively hone in on new vehicle signals. Generated ROS nodes are written in C++ for runtime use in lightweight embedded computers. This has been tested in vehicles from three different Original Equipment Manufacturers (OEMs), and can be extended to support a wide array of vehicles. By using a unifying ROS specification, a heterogeneous set of vehicles can be unified into a fleet with abstracted model-specific details; this opens the door for developing cross-model software applications for vehicle control, connected vehicle applications, or fleet monitoring systems.

42 ENGINEERING↗
DOE OSTI2025

REFRACTORY COMPACT HEAT EXCHANGERS WITH EMBEDDED SENSORS ENABLED BY HYBRID ADVANCED SINTERING AND ADDITIVE APPROACH

Structural health monitoring (SHM) of compact heat exchangers (CHXs) operating in extreme environments is essential for ensuring system reliability, safety, and longevity. This study presents the development of high-temperature sensors fabricated via aerosol jet printing (AJP) using platinum ink, selected for its exceptional thermal stability, oxidation resistance, and electrical conductivity. AJP enables precise deposition of fine-feature sensor patterns onto complex geometries, making it well-suited for integration within CHX architectures. To enhance sensor durability, an alumina-based ceramic protective layer was printed over the platinum sensing elements. The sensors demonstrated stable, repeatable performance up to 900?°C during extended thermal cycling. A custom test setup was developed to evaluate sensor accuracy and robustness under steady-state and transient conditions. Substrate screening identified HG-1 ceramic-coated stainless steel as the most effective platform, offering strong adhesion and low resistance. Furthermore, electric field-assisted sintering (EFAS) was employed to embed the sensors into stainless steel 316L matrices without degrading their functionality. Post-embedding electrical tests confirmed sensor integrity, and initial characterization suggests strong potential for in-situ monitoring. This work provides a scalable strategy for integrating high-performance temperature sensors directly into refractory components, advancing embedded SHM technologies for harsh operating environments.

36 - MATERIALS SCIENCE↗
DOE OSTI2020

AFM Microcantilever With a Collocated AlN Sensor-Actuator Pair: Enabling Efficient Q-Control for Dynamic Imaging

This manuscript presents a novel microcantilever with an embedded piezoelectric sensor-actuator pair for dynamic atomic force microscopy (AFM). The transducer pair is constructed from a two-layered AlN stack. Stacking the piezoelectric transducers in this manner leads to a minimal feedthrough from actuation to sense electrode, granting a high dynamic range frequency response for dynamic mode AFM. The cantilever's design allows for dual mode operation at 1 st and 2 nd resonance modes. High resolution tapping mode imaging results are reported, while the cantilever is operated at these modes. A feedback control loop is used to modify quality factor of the 1 st mode of the cantilever, using a positive position feedback (PPF) controller. Here, a faster response time is achieved by reducing the Q-factor, enabling the cantilever to track the topography at a higher scan rate. Results of bimodal AFM imaging are reported, using amplitude changes of the 1 st mode for surface topography, while material properties are encoded in phase changes of the 2 nd mode.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Technical Characterization and Benefit Evaluation of 5G-Enabled Grid Data Transport and Applications

This report summarizes the Year 1 work of Pacific Northwest National Laboratory’s (PNNL’s) 5G Fabricated Resource and Asset Management Encompassment for energy infrastructure (Energy FRAME) project funded by the Department of Energy Office of Science’s Advanced Scientific Computing Research Program. 5G is a breakthrough technology that enables a fully mobile and connected society, and a 5G-enabled digital continuum will be one of the critical foundations for a clean energy economy and grid modernization. In collaboration with PNNL’s Advanced Wireless Communication team and Center for Advanced Technology Evaluation team, the project team has been evaluating the system performance of 5G testbeds in the PNNL 5G Innovation Studio, and has formulated a co-simulation test case of power system transmission, distribution, and communication (T&D&C) networks considering 5G technology and high penetration of distributed energy resources. The methodology developed in the 5G Energy FRAME project can be customized to fit different future grid scenarios to evaluate multiple (dynamic) configurations (computing, sensing, communication, environment) for different stakeholders. In summary, our main technical highlights in project Year 1 are as follows: 1) Technical characterization of 5G standalone architectures, 2) Formulation of co-simulation test case of T&D&C networks embedded with 5G, 3) Initial benefit evaluation of 5G communication platform for grid use cases, and 4) Additional extended discussions on edge computing, artificial intelligence and machine learning, and high-performance computing and cloud computing adoptions. In addition, a collection of system performance data is shared through the publicly available weblink, https://www.pnnl.gov/projects/5g-energy-frame/publications

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Towards Geospatial Knowledge Graph Infused Neuro-Symbolic AI for Remote Sensing Scene Understanding

Deep learning has proven its effectiveness in numerous tasks for remote sensing scene understanding. However there is an increasing interest to explore fusion of domain-specific background information to the deep neural network to further improve its performance. Remote sensing researchers are also working towards developing models that generalize and adapt to multiple applications. Generalization challenges coupled with the scarcity of large corpora of high-quality noise-free labelled data, have together fueled an interest for leveraging background information. Knowledge graphs serve as excellent choice to represent domain-specific information in a structured, standardized and extensible manner. Integrating symbolic knowledge representations in the form of Knowledge Graph Embedding (KGE) to perform neuro-symbolic reasoning is an emerging research direction promising significant impacts. This vision paper seeks to position ideas and provoke early thoughts toward advancing neuro-symbolic artificial intelligence in the context of geospatial challenges. Specifically, it conceptualizes and elaborates on an architecture for infusing geospatial knowledge from knowledge graph in a deep neural network pipeline. As guiding case studies - land-use land-cover classification, object detection and instance segmentation can benefit from infusing spatio-contextual information with remote sensing imagery. The discussion further reflects on and articulates the challenges and explainable AI opportunities anticipated when scaling and maintaining large-scale geospatial knowledge graphs.

Potnis, Abhishek↗
DOE OSTI2025

Quantum sensing of paramagnetic analytes by nanodiamonds in levitated microdroplets and aqueous solutions

Nanodiamonds (ND) hosting negatively charged nitrogen-vacancy (NV-) color centers have received attention for applications in magnetic field, electric field, chemical, and bio-sensing. The versatility of these probes is their excellent room-temperature optical and spin properties, along with their small size, functionalized surfaces and resistance to bleaching, making them ideal as nanoscopic sensors in picoliter volumes (e.g. single cells, but also microcompartments and aerosols). For quantitative ND-NV- sensing of paramagnetic analytes in such contexts, however, there remains an incomplete understanding of how factors related to the aqueous phase environment control detection efficiency. To address this, optically detected magnetic resonance (ODMR) is measured in bulk macroscale solutions and single levitated microdroplets as a function of Gd+3 concentration (340 nM to 1.5 mM), nanodiamond size, pH, competitor ions, and ligands. The ODMR response to [Gd+3] is found to be nonlinear, and pH, ND and sample volume dependent; indicating the detection of Gd+3 requires efficient adsorption of the analyte to the diamond surface. Langmuir adsorption isotherms embedded in a quantitative photophysical model links the ODMR response to adsorption thermodynamics of Gd+3. The equilibrium constant for Gd+3 adsorption to a carboxylated ND surface is determined to be (1 ± 0.5) x 105 M-1 corresponding to a free energy of adsorption of (-28 ± 1) kJ mol-1. These results provide general insight into how complex aqueous and microscale environments impact nanodiamond based quantum sensing modalities, and portend their application as quantitative chemical sensors in microenvironments.

Brown, Emily K↗
DOE OSTI2020

Integrated Harsh Environment Gas / Temperature Wireless Microwave Acoustic Sensor System for Fossil Energy Applications

There is a significant need for sensors capable of detecting gases, such as H 2 , O 2 , NO x , SO x within harsh environments encountered in power plants, industrial manufacturing, oil and gas exploration, and aerospace applications. This project successfully demonstrated the use of wireless microwave acoustic sensor technology for the detection of gases (H 2 or O 2 ) from ambient temperatures up to 650°C. The work focused on langasite (LGS) based surface acoustic wave resonator (SAWR) sensors as the harsh-environment sensor platform and explored multiple combinations of high-temperature thin films and device structures which were used to increase the sensor platform stability and detection capability at temperatures in the operational range of 150°C to 700°C. Specific material configurations that were investigated include: yttria-stabilized-zirconia (YSZ) decorated with Pt nanoparticles, atomic layer deposited (ALD) Al 2 O 3 , palladium, and Pt/Al 2 O 3 co-deposited electrode alloys. Through the deposition of YSZ at temperatures as high as 850°C and the use of graded alloy concentrations of Pt in the fabrication of the Pt/Al 2 O 3 electrode structures, film stress problems were mitigated, and sensor operation and stability achieved. To test and evaluate SAWR sensor performance for the detection of H 2 and O 2 under the influence of temperature variations, a comprehensive gas sensor control system and test apparatus was created to operate within a laboratory box furnace-controlled environment. In addition to the advancement in thin film materials through the deposition and fabrication techniques mentioned above, the work characterized the performance of sensors containing these films in the presence of oxidizing and reducing gases between 25°C and 700°C. In particular, the work revealed that the exposure of the SAWR sensor surfaces to oxidizing environments significantly improve the sensor response to H 2 , whereas the exposure of the sensor to reducing environments at high temperatures (≈ 500°C) renders the sensor irresponsive to H 2 , requiring sensor surface treatment at high temperatures (above 500°C) to recover the responsiveness to H 2 . The SAWR sensors have been also tested for wireless operation and array operation using multiple orientations to resolve the detection of gases under temperature variations. The work developed at the University of Maine was aided by a collaboration with the NETL Research and Innovation Center, Pittsburgh, PA, where thin film materials and device structures fabricated at UMaine were tested and characterized using NETL gas reactors and surface analysis techniques. SAWR sensors fabricated at UMaine were exposed multiple times to temperatures up to 700°C and H 2 concentrations up to 100% in the NETL facilities to measure the sensor performance. Environetix Technologies Corporation, a UMaine harsh-environment sensor spin-off company, also provided support and assistance in sensor system testing and implementation. The sensor small size and configuration allows flexible sensor placement and embedding of multiple sensor arrays into a variety of components within power systems and other aerospace or industrial settings that need to be interrogated wirelessly. The SAW platform is an attractive option for high-temperature harsh-environment gas sensing applications due to its inherent features, namely small size, capability of battery-free and wireless operation, and cost effective scale production using well-established production techniques from the semiconductor industry. The research findings achieved in this work, particularly advances regarding the fabrication and performance of the SAWR gas sensor platform, can be adapted and transferred to industrial power plants and other harsh environments.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Field Results from New Tensor Borehole Optical Fiber Strainmeter Installations in Oklahoma and Utah

The time evolving strain field contains a wealth of information that can be used to interpret subsurface behavior. For example, injecting or removing fluids from reservoirs or aquifers causes deformation that can be used as a diagnostic signal in some cases, while it can interfere with geodetic interpretations in other cases. We've previously demonstrated the feasibility of measuring the strain tensor at a depth of 30m caused by injection into a reservoir at 530m. The observed strain signals were interpreted using four independent analytic and numerical methods that resulted in estimates of the poroelastic properties and geometry of the reservoir that was consistent with data from well logs. However, studies like these are only possible if these deformations can be reliably measured. Years of lab and field work has culminated in the development of a novel borehole strainmeter capable of resolving multiple components of strain using embedded optical fibers configured as Michelson interferometers. It features four horizontal gauges separated by 45° to resolve the horizontal strain tensor as well as a vertical strain gauge and a sixth null component for state-of-health monitoring. The downhole sensing package also includes an open pipe through its center for grout circulation during single-trip deployments and a fully welded stainless steel exterior for robustness and longevity. These instruments have a resolution of 2x10-13 strain that can easily measure the solid earth tides. Preliminary data are available from four strainmeters in shale at our Oklahoma site and four in compacted sand and gravel in Utah. These are deployed from 40-60m, except one of the strainmeters in Oklahoma is deployed at 500m. The data include strains from the initial grout curing, comparisons to predicted earth tide models and in-situ calibration results, barometric pressure admittances and spectral analyses as well as signals from underground injections and surface waves from teleseismic events. Preliminary analyses indicate behavior consistent with other strainmeter deployments, and comparison to data from a Gladwin strainmeter at the Oklahoma site validate the performance of the new design. Analyses from a suite of six well tests at the Oklahoma site show for the first time how the strain tensor field varies with location during well testing.

DeWolf, Scott↗
DOE OSTI2022

Metal-embedded optical fibers for monitoring pressure or corrosion at high temperatures

A fiber optic sensor and a related method of manufacture are provided. The fiber optic sensor includes an embedded optical fiber contained within a metal diaphragm assembly, where the terminal end of the optical fiber is positioned opposite a diaphragm. The method includes forming a metal-embedded optical fiber by ultrasonic additive manufacturing and securing the metal-embedded optical fiber to a housing having a diaphragm that is opposite of the terminal end of the optical fiber. The sensor can provide extremely accurate pressure measurement at high temperatures and in highly corrosive media. An optical fiber-based pressure sensing system is also provided.

Petrie, Christian M.↗
DOE OSTI2020

Mixed Material Scintillator Systems for Neutron Detection

Scintillators are a fundamental technology that enables radiation detection. Their use has historically enabled the detection of incoming gamma radiation, with recent advances in plastic scintillator development enabling detection and discrimination of neutron and gamma radiation through pulse shape discrimination. However, scintillators have so far consisted of a single material, typically one primary dye and one secondary dye embedded in a plastic matrix. Based on the simulation studies described previously, mixed material scintillator systems with multiple secondary dyes arranged in alternating, periodic micro-sized regions opens the door for scintillators with a wide variety of different capability, such as directional sensing, positional reconstruction, particle identification, and pulse shape discrimination. However, fabrication of a mixed material scintillator system by conventional manufacturing methods is difficult to manufacture and scale, creating a barrier to their wide spread implementation. On the other hand, additive manufacturing additive manufacturing presents itself as the optimal method for fabricating mixed material scintillator systems based on its flexibility, ability to fabricate fine features, and potential for multimaterial fabrication.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

A Self-Sustained CPS Design for Reliable Wildfire Monitoring

Continuous monitoring of areas nearby the electric grid is critical for preventing and early detection of devastating wildfires. Existing wildfire monitoring systems are intermittent and oblivious to local ambient risk factors, resulting in poor wildfire awareness. Ambient sensor suites deployed near the gridlines can increase the monitoring granularity and detection accuracy. However, these sensors must address two challenging and competing objectives at the same time. First, they must remain powered for years without manual maintenance due to their remote locations. Second, they must provide and transmit reliable information if and when a wildfire starts. The first objective requires aggressive energy savings and ambient energy harvesting, while the second requires continuous operation of a range of sensors. To the best of our knowledge, this paper presents the first self-sustained cyber-physical system that dynamically co-optimizes the wildfire detection accuracy and active time of sensors. The proposed approach employs reinforcement learning to train a policy that controls the sensor operations as a function of the environment (i.e., current sensor readings), harvested energy, and battery level. Here, the proposed cyber-physical system is evaluated extensively using real-life temperature, wind, and solar energy harvesting datasets and an open-source wildfire simulator. In long-term (5 years) evaluations, the proposed framework achieves 89% uptime, which is 46% higher than a carefully tuned heuristic approach. At the same time, it averages a 2-minute initial response time, which is at least 2.5× faster than the same heuristic approach. Furthermore, the policy network consumes 0.6 mJ per day on the TI CC2652R microcontroller using TensorFlow Lite for Micro, which is negligible compared to the daily sensor suite energy consumption.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Mixed-phase clouds and precipitation in Southern Ocean cyclones and cloud systems observed poleward of 64°S by ship-based cloud radar and lidar

Mixed-phase clouds (MPCs), composed of both liquid and ice, are prevalent in Southern Ocean cyclones. A characterisation of these clouds on fine vertical scales is required in order to understand the microphysical processes within these clouds, and for model and satellite evaluations over this region. We investigated three examples of cloud systems collected by ship-mounted remote sensing instruments adjacent to East Antarctica at latitudes between 64°S and 69°S. These cases allow us to examine the properties of mid-level MPCs, with cloud tops between 2 and 6 km. Mid-level MPCs contain multiple layers of supercooled liquid water (SLW) embedded within ice during the passage of cyclones. SLW layers are capped by strong temperature inversions and are observed at temperatures as low as - 31°C. Convective generating cells (GCs) are present inside supercooled liquid-topped mid-level MPCs. The horizontal extent, vertical extent and maximum upward Doppler velocity of these GCs were 0.6 – 3.6 km, 0.7 – 1.0 km and 0.5 – 1.0 m s -1 , respectively, and are consistent with observations from previous lower-latitude studies. Ice precipitation is nearly ubiquitous, except in the thinnest clouds at the trailing end of the observed systems. Seeding of lower SLW layers from above leads to periods with either larger ice particles or greater ice precipitation rates. Additionally, periods of supercooled drizzle lasting up to two hours were observed toward the end of two of the three cyclone systems. This supercooled drizzle turns into predominantly ice precipitation as the result of seeding by ice clouds located above the precipitating SLW layer.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Engineered Living Materials For Sustainability

Recent advances in synthetic biology and materials science have given rise to a new form of materials, namely engineered living materials (ELMs), which are composed of living matter or cell communities embedded in self-regenerating matrices of their own or artificial scaffolds. Like natural materials such as bone, wood, and skin, ELMs, which possess the functional capabilities of living organisms, can grow, self-organize, and self-repair when needed. They also spontaneously perform programmed biological functions upon sensing external cues. Currently, ELMs show promise for green energy production, bioremediation, disease treatment, and fabricating advanced smart materials. This review first introduces the dynamic features of natural living systems and their potential for developing novel materials. We then summarize the recent research progress on living materials and emerging design strategies from both synthetic biology and materials science perspectives. Lastly, we discuss the positive impacts of living materials on promoting sustainability and key future research directions.

36 MATERIALS SCIENCE↗