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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Chapter 6: Thermoelectric Energy Harvesters and Applications

With recent progress in the field of wearable and bio-integrated devices, which are widely used for various applications, such as real-time health monitoring, point-of-care diagnostics, and biological actuators, the need for a continuous and reliable power source is increasing. As solid-state devices with no moving parts, thermoelectric energy generators provide a reliable solution for harnessing body heat and converting it into electricity on demand. However, traditional thermoelectric generators, comprising inorganic materials, are rigid and bulky, limiting their wide deployment. Nonconventional thermoelectric generators, composed of organic and hybrid thermoelectric materials, are flexible and lightweight. In this chapter, we will discuss the working principle of thermoelectric energy harvesting, including materials, devices, and applications. While we briefly touch upon the inorganic materials, we will focus primarily on the organic and hybrid materials, which are nontoxic, flexible, easy to manufacture, easy to scale, and readily available at low cost, providing a promising solution for lightweight and conformal thermoelectric power generation.

body heat harvesting↗
DOE OSTI2020

Flexible Electronics: Flexible Electrochemical Bioelectronics: The Rise of In Situ Bioanalysis (Adv. Mater. 15/2020)

Flexible electrochemical bioelectronics enables in situ quantification of a variety of chemical constituents present in the human body. It holds great promise for personalized health monitoring owing to its inherent wearability, high performance, and low cost. In article number 1902083, Wei Gao, Ali Javey, and co-authors summarize recent key innovations in flexible electrochemical bioelectronics from electrochemical sensing modalities, materials, systems, fabrication, to applications and discuss the challenges and opportunities in this field moving forward toward future preventive and personalized medicine devices.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A prototype cooling blanket for mitigating occupant overheating risk in a hot indoor environment: Modeling and assessments

Conventional ways of cooling a room or an entire house for occupant thermal comfort during summer consume a significant amount of energy and are vulnerable to overheating risk during power outages that lead to loss of cooling system operations. This study investigates a low-power cooling blanket, as a Personal Cooling System (PCS), that covers the upper human body for direct cooling during a five-day heat wave in a single-family house. A modeling framework is developed for evaluating the thermal and energy performance of the cooling blanket, which builds upon the co-simulation of three models: a house energy model, a personal thermal comfort model, and a cooling blanket model. Simulation results show that under the power outage scenario, the cooling blanket can greatly reduce the occupant heat stress with a reduction of daily hours of exceedance (discomfort hours defined as TSV>2) by up to 17.2 h (a 95.3 % improvement from the baseline power outage without the blanket). The cooling blanket, equipped with an innovative electrocaloric heat pump (COP as high as 10.1) consumes 6.31 W and can be operated by a portable battery for several days. The cooling blanket consumes only 0.28 % of the electricity of a central air-conditioning system running to provide cooling for the whole house during the five-day heatwave period. The findings justify further research of electrocaloric wearable PCS as low-power effective cooling to ensure thermal survivability of occupants during extreme indoor environments.

Electrocaloric heat pump↗
DOE OSTI2026

Correlation of Surface Acoustic Wave (SAW) force myography sensor output with elbow joint torque

Accurate assessment of skeletal muscle forces and net joint torque is essential for preventing fatigue-related injuries, optimizing physical training, and monitoring disease progression in neuromuscular conditions. However, existing joint torque evaluation techniques are hindered by limited portability and high operational costs, confining their use to controlled laboratory or clinical settings. Despite substantial advances in wearable joint torque estimation systems, ongoing challenges such as power constraints, bulky wired setups, and susceptibility to environmental or motion artifacts underscore the urgent need for truly batteryless, wireless solutions deployable in real-world settings. This paper proposes a novel surface acoustic wave (SAW)-based force myography (FMG) system for noninvasive measurement of joint torque, validated against a gold-standard electromechanical dynamometer. The approach uses a single SAW sensor embedded in an armband to detect volumetric biceps brachii changes, with a second-order polynomial mapping sensor output and elbow angle to torque. Seven participants were tested in both isometric (15°–90°) and isokinetic (10°/s and 20°/s) supinated elbow flexion tasks. Under isometric conditions, subject-specific calibration achieved a normalized root-mean-square error (NRMSE) of 13.6% ± 6.0% and R 2 = 0.834 ± 0.180, while a group-level model yielded 14.4% ± 6.8% and 0.808 ± 0.208, respectively. For isokinetic trials, the group model produced an NRMSE of 24.1% ± 6.6% at 10°/s and 24.9% ± 08.9% at 20°/s, highlighting the feasibility of using a single-sensor SAW-FMG setup across different speeds. Because SAW devices support wireless, battery-free operation, the proposed system offers a pathway to portable, real-time monitoring for sports medicine, rehabilitation, and clinical diagnostics.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Guest Editorial: Special Issue on InterPACK 2019 - Part 1

This is a collection of papers drawn from the 2019 ASME InterPACK Conference. The content spans the areas of heterogeneous integration, servers, flexible and wearable electronics, photonics, power electronics, energy storage, and autonomous and electric vehicles.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

2010-2012 California Household Travel Survey

The 2010-2012 California Household Travel Survey (CHTS) was administered by the California Department of Transportation, which collected demographic and travel behavior characteristics for residents across the entire state. At the time, it was the largest such regional or statewide survey ever conducted in the United States. Detailed travel behavior information was obtained from more than 42,500 households via multiple data-collection methods, including computer-assisted telephone interviewing, online and mail surveys, wearable (7,574 participants) and in-vehicle (2,910 vehicles) global positioning system devices, and on-board diagnostic sensors that gathered data directly from a vehicle's engine. Details of personal travel behavior were gathered within the region of residence, inter-regionally within the state, and in adjoining states and Mexico. The survey sampling plan was designed to ensure an accurate representation of the entire population of the state. The CHTS included additional features, such as vehicle-acquisition decisions, parking choices, work schedules and flexibility, use of toll lanes/priced facilities, and walk and bicycle trips, to support advanced model development.

1Hz data↗
DOE OSTI2026

2007 Chicago Regional Household Travel Inventory

To provide data for developing and refining travel demand forecast models, the 2007 Regional Household Travel Inventory studied the demographic and travel behavior characteristics of residents in the greater Chicago area. It included households in eight counties in Illinois and three in Indiana. The Chicago Metropolitan Agency for Planning conducted the study in coordination with the Illinois Department of Transportation, the Northwestern Indiana Regional Planning Commission, and the Indiana Department of Transportation. Travel and activity information for all household members (regardless of age) was collected during a randomly assigned 24- or 48-hour period. It relied on the willingness of households to provide detailed information about their members and vehicles, and to record all travel and associated activity during the collection period. This study also featured a subsample of households collecting data via in-vehicle and wearable global positioning system devices.

1Hz data↗
DOE OSTI2026

2012-2013 Delaware Valley Household Travel Survey

The 2012-2013 Delaware Valley Household Travel Survey collected data for multiple planning purposes such as the calibration of a new activity-based travel demand model. It features data from households across nine counties in the region, including southern New Jersey and southeastern Pennsylvania. The Delaware Valley Regional Planning Commission (DVRPC) sponsored the survey, which was administered by Abt Srbi Inc. A sampling strategy was designed to recruit households for survey participation that would best represent overall regional travel trends. Households were selected randomly, but with special consideration given to under-represented geographies and transit propensity. On their assigned travel day, households were asked to record all trips made within a 24-hour period. Additionally, select households were chosen to participate in a wearable global positioning system (GPS) technology-based component of the study. A total of 811 participants wore the GPS system.

1Hz data↗
DOE OSTI2026

2010-2012 Minneapolis - St. Paul Travel Behavior Inventory

The 2010-2012 Travel Behavior Inventory (TBI) provided Minnesota policymakers and researchers with data about travel in the Minneapolis - St. Paul region. It also updated the region's travel demand forecasting, including transit ridership for major transportation projects. The Metropolitan Council in the Minneapolis-St. Paul area conducted the survey. The TBI consists of a paper-based survey and a wearable global positioning system survey. The data collection process for these two surveys was independent, and the results are not intended to function together.

1Hz data↗
DOE OSTI2026

2013 New Mexico Mid-Region Travel Survey

The 2013 New Mexico Mid-Region Travel Survey assessed travel behavior patterns to update a travel demand model for the Albuquerque Metropolitan Planning Area, which consists of Bernalillo County, Valencia County, and southern Sandoval County. It includes the cities of Albuquerque, Rio Rancho, Los Lunas, and Belen as well as some tribal lands. The Mid-Region Council of Governments contracted with Westat to conduct the survey, which included the collection of socio-demographic data and a one-day (24-hour) period of household travel behavior collected during weekdays (Monday through Friday). The survey also included a random selection of a 20% subsample of households (1,023 participants) to take part in a wearable global positioning system, technology-based component of the study, which was used to assess the level of trip under-reporting from the self-reported component of the survey.

1Hz data↗
DOE OSTI2026

2014 Southern Nevada Household Travel Survey

The 2014 Southern Nevada Household Travel Survey collected information from residents in the Las Vegas area to update the regional travel demand model and assess travel behavior. The Regional Transportation Commission of Southern Nevada contracted with Westat to conduct the survey. The survey was conducted in two phases—from March to May 2014 and from August to October 2014. Participants provided demographic and travel data (via a travel log). A 10% subsample (1,694 participants) was randomly selected to take part in a wearable global positioning system (GPS) technology-based component of the study, the purpose of which was to assess the level of trip under-reporting in the self-reported travel logs. Participants in the GPS portion of the study were instructed to record trips in their travel logs on the first day only, while passively recording their travel for three full days.

1Hz data↗
DOE OSTI2024

Fueling the Future: The Emergence of Self-Powered Enzymatic Biofuel Cell Biosensors

Self-powered biosensors are innovative devices that can detect and analyze biological or chemical substances without the need for an external power source. These biosensors can convert energy from the surrounding environment or the analyte itself into electrical signals for sensing and data transmission. The self-powered nature of these biosensors offers several advantages, such as portability, autonomy, and reduced waste generation from disposable batteries. They find applications in various fields, including healthcare, environmental monitoring, food safety, and wearable devices. While self-powered biosensors are a promising technology, there are still challenges to address, such as improving energy efficiency, sensitivity, and stability to make them more practical and widely adopted. This review article focuses on exploring the evolving trends in self-powered biosensor design, outlining potential advantages and limitations. With a focal point on enzymatic biofuel cell power generation, this article describes various sensing mechanisms that employ the analyte as substrate or fuel for the biocatalyst’s ability to generate current. Technical aspects of biofuel cells are also examined. Research and development in the field of self-powered biosensors is ongoing, and this review describes promising areas for further exploration within the field, identifying underexplored areas that could benefit from further investigation.

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

Improving Medication Regimen Recommendation for Parkinson’s Disease Using Sensor Technology

Parkinson’s disease medication treatment planning is generally based on subjective data obtained through clinical, physician-patient interactions. The Personal KinetiGraph™ (PKG) and similar wearable sensors have shown promise in enabling objective, continuous remote health monitoring for Parkinson’s patients. In this proof-of-concept study, we propose to use objective sensor data from the PKG and apply machine learning to cluster patients based on levodopa regimens and response. The resulting clusters are then used to enhance treatment planning by providing improved initial treatment estimates to supplement a physician’s initial assessment. We apply k-means clustering to a dataset of within-subject Parkinson’s medication changes—clinically assessed by the MDS-Unified Parkinson’s Disease Rating Scale-III (MDS-UPDRS-III) and the PKG sensor for movement staging. A random forest classification model was then used to predict patients’ cluster allocation based on their respective demographic information, MDS-UPDRS-III scores, and PKG time-series data. Clinically relevant clusters were partitioned by levodopa dose, medication administration frequency, and total levodopa equivalent daily dose—with the PKG providing similar symptomatic assessments to physician MDS-UPDRS-III scores. A random forest classifier trained on demographic information, MDS-UPDRS-III scores, and PKG time-series data was able to accurately classify subjects of the two most demographically similar clusters with an accuracy of 86.9%, an F1 score of 90.7%, and an AUC of 0.871. A model that relied solely on demographic information and PKG time-series data provided the next best performance with an accuracy of 83.8%, an F1 score of 88.5%, and an AUC of 0.831, hence further enabling fully remote assessments. These computational methods demonstrate the feasibility of using sensor-based data to cluster patients based on their medication responses with further potential to assist with medication recommendations.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2020

An Ultra-long Life, High-performance, Flexible Li-CO2Battery Based on Multifunctional Carbon Electrocatalysts

Integrating CO2 utilization and renewable energy delivery/storage, the rechargeable Li–CO2 battery has been considered as a promising candidate for next-generation secondary batteries. However, high-performance catalyst(s) for efficient formation and decomposition of the discharge product, Li2CO3, are an imperative part of a Li–CO2 battery. The development of flexible Li–CO2 batteries extends their applications into compliant and wearable devices/systems, but at the same time imposes a big challenge for battery fabrication and lifetime enhancement. In this study, a rechargeable quasi-solidus flexible Li–CO2 battery was designed and fabricated using highly active N,S-doped carbon nanotubes (N,S-doped CNTs) as the cathode catalyst, and a smart polymer gel as the flexible electrolyte. This newly-developed flexible Li–CO2 battery exhibited a capacity as high as 23560 mAh g−1 based on the catalyst mass and an ultra-long lifetime of up to 538 cycles with excellent mechanical flexibility. This work provides a platform for the design and development of high-performance flexible Li–CO2 batteries from low-cost, earth-abundant, carbon-based multifunctional cathode catalysts.

Superior stability↗
NASA NTRS2024

A Perspective on Multi-Source Energy Harvesting Technology Using Piezoelectric and Thermoelectric Materials

Energy harvesting using various locally available energy sources such as vibration energy, heat, sound, or magnetic field have become attractive topics for supplying power to modular electronic devices making them run independently in extreme environments. In this paper, we will be discussing the perspectives on thermoelectric (TE) and piezoelectric materials and devices, and then the concept of multi-source energy harvester using piezoelectric and thermoelectric devices and integration of them into a reliable and independent power source. TE materials having low thermal conductivity and high figure-of-merit ( zT ) are developed to convert even a small temperature gradient efficiently into electrical energy with the state-of-the-art conversion efficiency of ~15% and output power of ~56 W from single device. The piezoelectric device architecture is configured using high performance piezoelectric ceramics (Cu-Mn-PIN-PMN-PT). These ceramics exhibit high piezoelectric coefficient with high mechanical quality factor and low dielectric loss factor. Using these piezoelectric materials, power density as high a 2 mW/cm 2 is demonstrated in 1-1.5 g vibration environments. The piezoelectric device is attached on the surface of TE module to capture both the vibration and thermal energy sources to realize dual mode energy harvester. The multi-energy transfer strategy opens opportunities for a future generation of wireless and modular electronic devices. These devices would be useful in powering wearable electronic devices, micro sensor chargers, etc. in extreme environmental conditions using body heat/thermal sources and induced motion/vibrations.

Piezoelectric↗
DOE OSTI2025

Improving Surface Quality of Titanium Electrodeposition from a Deep Eutectic Solvent with Organic and Inorganic Additives

Titanium electroreduction is desired for a variety of medical, electronic, and bonding applications but has not been possible until recently. Titanium electrodeposition with leveler and brightener additives in the deep eutectic solvent ethaline has been studied for effects on spectroscopic reflectance. Polymeric leveling agents and several small‐molecule brighteners produce level/bright films (respectively) with high values for both specular and diffuse reflectance. The application of these leveling and brightening agents can produce films with appearances and surface roughnesses that may be suitable for application in medical implants such as stents, corrosion protection of electronics for wearable technology, and as interlayers between dissimilar metals.

deep eutectic solvents↗
DOE OSTI2023

Stretchable and Self‐Healable Semiconductive Composites Based on Hydrogen Bonding Cross‐linked Elastomeric Matrix

Abstract Semiconductors with both high stretchability and self‐healing capability are highly desirable for various wearable devices. Much progress has been achieved in designing highly stretchable semiconductive polymers or composites. The demonstration of self‐healable semiconductive composite is still rare. Here, an extremely soft, highly stretchable, and self‐healable hydrogen bonding cross‐linked elastomer, amide functionalized‐polyisobutylene (PIB‐amide) is developed, to enable a self‐healable semiconductive composite through compounding with a high‐performance conjugated diketopyrrolopyrrole (DPP‐T) polymer. The composite, consisting of 20% DPP‐T and 80% PIB‐amide, shows record high crack‐onset strain (COS ≈1500%), extremely low elastic modulus (E≈1.6 MPa), and unique ability to spontaneously self‐heal atroom temperature within 5 min. Unlike previous works, these unique composite materials also show strain‐independent charge mobility. An in‐depth morphological study based on multi‐model techniques indicate that all composites show blending ratio‐ and stretching‐independent fibril‐like aggregation due to the strong hydrogen bond in elastomer to enable the unique stable charge mobility. This study provides a new direction to develop highly healable and electronically stable semiconductive composite and will enable new applications of stretchable electronics.

Chemistry↗
DOE OSTI2023

Mechanical, Morphological, and Charge Transport Properties of NDI Polymers with Variable Built‐in Π‐Conjugation Lengths Probed by Simulation and Experiment

Abstract Mechanically deformable polymeric semiconductors are a key material for fabricating flexible organic thin‐film transistors (FOTFTs)—the building block of electronic circuits and wearable electronic devices. However, for many π‐conjugated polymers achieving mechanical deformability and efficient charge transport remains challenging. Here the effects of polymer backbone bending stiffness and film microstructure on mechanical flexibility and charge transport are investigated via experimental and computational methods for a series of electron‐transporting naphthalene diimide (NDI) polymers having differing extents of π‐conjugation. The results show that replacing increasing amounts of the π‐conjugated comonomer dithienylvinylene (TVT) with the π‐nonconjugated comonomer dithienylethane (TET) in the backbone of the fully π‐conjugated polymeric semiconductor, PNDI‐TVT 100 (yielding polymeric series PNDI‐TVT x , 100 ≥x≥ 0), lowers backbone rigidity, degree of texturing, and π–π stacking interactions between NDI moieties. Importantly, this comonomer substitution increases the mechanical robustness of PNDI‐TVT x while retaining efficient charge transport. Thus, reducing the TVT content of PNDI‐TVT x suppresses film crack formation and dramatically stabilizes the field‐effect electron mobility upon bending (e.g., 2 mm over 2000 bending cycles). This work provides a route to tune π–π stacking in π‐conjugated polymers while simultaneously promoting mechanical flexibility and retaining good carrier mobility in FOTFTs.

Chemistry↗