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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The Second Skin: A Wearable Sensor Suite that Enables Real-Time Human Biomechanics Tracking Through Deep Learning

Objective: Real-time determination of human kinematics and kinetics could advance biomechanics research and enable valuable applications of biofeedback and generalizable exoskeleton control. Here, this work aims to investigate a taskindependent, user-independent method for obtaining precise realtime joint state estimation across lower-body joints during a wide variety of tasks. Methods: We developed a generalizable sensing approach using a suit comprised of inertial measurement units (IMUs) and pressure insoles. With the suit, we collected a dataset of 33 tasks commonly performed during construction and hazardous waste cleanup (N = 10). We then trained deep learning user-independent, task-agnostic models to estimate joint lowerbody kinematics and dynamics using only worn sensor data. We likewise computed joint kinematics and dynamics analytically from sensor data to serve as a comparison tool for model results. Results: Our models achieved overall angle estimation root-meansquared-errors (RMSE) of 6.56±.92°, 8.60±1.01°, 7.58±.89°, and 6.00±.73° compared to 13.9±.1.3°, 15.31±1.0°, 10.76±.70°, and 7.56±.48° via analytical methods at the lower back, hip, knee, and ankle, respectively. Likewise, our models achieved overall normalized moment estimation RMSEs of .207±.069 Nm/kg, .242±.044 Nm/kg, .202±.038 Nm/kg, and .193±.034 Nm/kg compared to .306±.036 Nm/kg, .407±.021 Nm/kg, 1.18 ±.022 Nm/kg, and 1.73±.071 Nm/kg via analytical methods at the lower back, hip, knee, and ankle, respectively. Conclusion: These results are comparable to other state-of-the-art wearable sensing systems, establishing deep learning as a viable sensing approach that generalizes to new users and tasks. Significance: This work shows promise for enabling accurate real-world biomechanical data collection and enhancement of biofeedback systems and wearable robot control.

Casey, Ryan T. F. [Georgia Institute of Technology↗
DOE OSTI2024

Data Visualization: Augmented Reality

In recent years, there has been an increasing interest in developing new technologies for automated characterization and visualization of condition monitoring data. Augmented Reality (AR) is a technology that is being developed to improve such data visualization. Augmented reality has been defined as a technology that merges virtual and physical components in real-time, and in three dimensions. Wearable, commercially-available AR devices allow onsite engineers and technicians to perform inspection tasks with significantly more available information such as comparisons of past and present sensor and imager data, onsite data analysis and result displays, and various forms of metadata including technical drawings, previous inspection reports and maintenance histories, operation manuals, codes and standards, and holograms representing data analysis results superimposed onto the in situ monitored system.

42 ENGINEERING↗
DOE OSTI2021

Integrating Emerging Polymer Chemistries for the Advancement of Recyclable, Biodegradable, and Biocompatible Electronics

Abstract Through advances in molecular design, understanding of processing parameters, and development of non‐traditional device fabrication techniques, the field of wearable and implantable skin‐inspired devices is rapidly growing interest in the consumer market. Like previous technological advances, economic growth and efficiency is anticipated, as these devices will enable an augmented level of interaction between humans and the environment. However, the parallel growing electronic waste that is yet to be addressed has already left an adverse impact on the environment and human health. Looking forward, it is imperative to develop both human‐ and environmentally‐friendly electronics, which are contingent on emerging recyclable, biodegradable, and biocompatible polymer technologies. This review provides definitions for recyclable, biodegradable, and biocompatible polymers based on reported literature, an overview of the analytical techniques used to characterize mechanical and chemical property changes, and standard policies for real‐life applications. Then, various strategies in designing the next‐generation of polymers to be recyclable, biodegradable, or biocompatible with enhanced functionalities relative to traditional or commercial polymers are discussed. Finally, electronics that exhibit an element of recyclability, biodegradability, or biocompatibility with new molecular design are highlighted with the anticipation of integrating emerging polymer chemistries into future electronic devices.

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

Machine Learning-Enabled Wearable Piezoelectric Acoustic Sensor for Real-Time Breast Abnormality Detection

In contemporary society, breast health has become a significant public health concern, particularly among women. According to statistics from the World Health Organization, both the incidence and mortality rates of breast tumors have steadily increased in recent years. Therefore, effective early-stage screening and postoperative monitoring are essential for maintaining breast health. However, conventional clinical diagnostic modalities are typically bulky, operationally complex, and unsuitable for continuous real-time monitoring, which limits their use in portable and everyday health management applications. To address these limitations, this study proposes a machine learning-integrated wearable piezoelectric sensing platform as an auxiliary tool for breast health assessment. The device consists of a PDMS matching layer embedded with flexible silver nanowires, a P(VDF-TrFE) piezoelectric layer, and a multi-channel low-noise signal acquisition circuit. It is capable of acquiring acoustic echo signals from tissue-mimicking environments and automatically evaluating signal validity using a convolutional neural network (CNN). By integrating piezoelectric sensing with deep learning-based signal analysis, the proposed system achieves a signal-to-noise ratio exceeding 70 dB and a real-time classification accuracy above 96% under controlled conditions. These results demonstrate that the platform provides a compact, portable, and intelligent approach for wearable sensing of mechanical heterogeneity and highlight its potential for future development in continuous biomedical monitoring technologies.

He, Shuaitong↗
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↗
DOE OSTI2020

Flexible metal–gas batteries: a potential option for next-generation power accessories for wearable electronics

Flexible metal–gas batteries have become increasingly attractive for use in wearable electronics in the recent years due to their large theoretical energy density and superior adaptability to irregular geometric surfaces, such as the human body. With continuous improvements in design strategies and assembly technologies, the fabrication of various advanced flexible metal–gas batteries has been attempted. In spite of these efforts, the synchronous integration of high flexibility, safety, comfort, and high performance into flexible metal–gas batteries with specifically functionalized configurations still remains a formidable challenge. To resolve these dilemmas, the redesign of cathode catalysts, gel polymer electrolyte, and battery configurations/components has been investigated. In this paper, we review the recent technical advances together with the major dilemmas facing currently available flexible metal–gas batteries, highlighting how flexible cathodes and gel polymer electrolytes with various structures and components can affect the electrochemical performance and functionality of flexible metal–gas batteries. Flexible Zn–air, Li–O 2 /air, and Li–CO 2 batteries are mainly exemplified to elucidate their promising potential. Finally, based on our considerations, unresolved technical hurdles and future research perspectives involving flexible metal–gas batteries for wearable electronics are proposed.

25 ENERGY STORAGE↗
DOE OSTI2024

Wireless Frequency‐Multiplexed Acoustic Array‐Based Acoustofluidics

Abstract Acoustofluidics has shown great potential in enabling on‐chip technologies for driving liquid flows and manipulating particles and cells for engineering, chemical, and biomedical applications. To introduce on‐demand liquid sample processing and micro/nano‐object manipulation functions to wearable and embeddable electronics, wireless acoustofluidic chips are highly desired. This paper presents wireless acoustofluidic chips to generate acoustic waves carrying sufficient energy and achieve key acoustofluidic functions, including arranging particles and cells, generating fluid streaming, and enriching in‐droplet particles. To enable these functions, the wireless acoustofluidic chips leverage mechanisms, including inductive coupling‐based wireless power transfer (WPT), frequency multiplexing‐based control of multiple acoustic waves, and the resultant acoustic radiation and drag forces. For validation, the wirelessly generated acoustic waves are measured using laser vibrometry when different materials (e.g., bone, tissue, and hand) are inserted between the WPT transmitter and receiver. Moreover, the wireless acoustofluidic chips successfully arrange nanoparticles into different patterns, align cells into parallel pearl chains, generate streaming, and enrich in‐droplet microparticles. This research is anticipated to facilitate the development of embeddable wireless on‐chip flow generators, wearable sensors with liquid sample processing functions, and implantable devices with flow generation and acoustic stimulation abilities for engineering, veterinary, and biomedical applications.

Li, Jiali↗
DOE OSTI2023

Electrochemical aptamer-based sensors: leveraging the sensing platform for minimally-invasive microneedle measurements and fundamental exploration of sensor biofouling dynamics

The ability to track the concentrations of specific molecules in the body in real time would significantly improve our ability to study, monitor, and respond to diseases. To achieve this, we require sensors that can withstand the complex environment inside the body. Electrochemical aptamer-based sensors are particularly promising for in vivo sensing, as they are among the only generalizable sensing technologies that can achieve real-time molecular monitoring directly in blood and the living body. In this project, we first focused on extending the application space of aptamer sensors to support minimally-invasive wearable measurements. To achieve this, we developed individually-addressable sensors with commercial off-the-shelf microneedles. We demonstrated sensor function in buffer, blood, and porcine skin (a common proxy for human skin). In addition to the applied sensing project, we also worked to improve fundamental understanding of the aptamer sensing platform and how it responds to biomolecular interferents. Specifically, we explored the interfacial dynamics of biofouling – a process impacting sensors placed in complex fluids, such as blood.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Dielectric Engineering of ZnO@ZIF‐8 for High‐Performance Triboelectric Nanogenerators and Self‐Powered Humidity Sensors

Porous metal oxide–metal-organic framework (MO x @MOF) hybrids offer synergistic effects that enhance surface charge density, electronic structure, and textural properties, making them ideal for self-powered sensing applications. Here, uniform, and pinhole-free ternary porous ZnO–PTFE@ZIF-8 hybrid films are developed on room-temperature co-sputtered ZnO–polytetrafluoroethylene (PTFE) composite films, where ZnO serves as a self-sacrificial precursor to precisely regulate ZIF-8 (Zn-MeIm 2 ) growth through solvothermal methods. The resulting TENG achieves a high output power density of 0.67 mW cm −2 , attributed to the synergistic effects of fluorine-rich PTFE and methyl-functionalized ZIF-8, which enhance surface charge density and dielectric response. By tuning PTFE content in the ZnO–PTFE composite, the dielectric constant and triboelectric output is optimized. The ZP60@ZIF-8-based device also demonstrates excellent humidity sensing performance, with a wide detection range (20–99% RH) and ultrahigh sensitivity (R V % of 19 900%, R I % of 19 325% at 99% RH). These results position ZP@ZIF-8-based TENGs as promising platforms for next-generation self-powered sensors and smart wearable electronics.

42 ENGINEERING↗
DOE OSTI2025

Characterization of Peripheral Neurophotonic Systems for High-Performance Human-Computer Interfaces (CRADA Final Report)

As part of the Cyclotron Road program, Morphosis Inc. sought to investigate a non-invasive neuromuscular sensing approach for use as an intuitive and secure human–computer interface. These highly miniaturized, wearable neural interfaces were completely non-invasive and maintained stable, high-bandwidth, long-term access to a user’s actions, intent, and identity, while offering an exceptionally high signal-to-noise ratio compared to contemporary neural recording technologies. The widespread adoption of neural interfaces had the potential to reshape how people interact with technology, with profound societal impacts. Millions worldwide suffered from movement and/or speech disabilities, and these tools had the potential to democratize access to technology to enhance autonomy and quality of life. More broadly, interfaces capable of accurately conveying intentions and safeguarding identities could serve as a cornerstone for privacy, trust, and personal authenticity in digital environments. The use of thought-driven control of digitally enabled devices and governance of digital identities had the potential to revolutionize relationships with technology, transforming how people learn, communicate, and interact with the world.

42 ENGINEERING↗
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 OSTI2021

High-specific-power flexible transition metal dichalcogenide solar cells

Abstract Semiconducting transition metal dichalcogenides (TMDs) are promising for flexible high-specific-power photovoltaics due to their ultrahigh optical absorption coefficients, desirable band gaps and self-passivated surfaces. However, challenges such as Fermi-level pinning at the metal contact–TMD interface and the inapplicability of traditional doping schemes have prevented most TMD solar cells from exceeding 2% power conversion efficiency (PCE). In addition, fabrication on flexible substrates tends to contaminate or damage TMD interfaces, further reducing performance. Here, we address these fundamental issues by employing: (1) transparent graphene contacts to mitigate Fermi-level pinning, (2) MoO x capping for doping, passivation and anti-reflection, and (3) a clean, non-damaging direct transfer method to realize devices on lightweight flexible polyimide substrates. These lead to record PCE of 5.1% and record specific power of 4.4 W g −1 for flexible TMD (WSe 2 ) solar cells, the latter on par with prevailing thin-film solar technologies cadmium telluride, copper indium gallium selenide, amorphous silicon and III-Vs. We further project that TMD solar cells could achieve specific power up to 46 W g −1 , creating unprecedented opportunities in a broad range of industries from aerospace to wearable and implantable electronics.

42 ENGINEERING↗
DOE OSTI2022

Efficient and mechanically-robust organic solar cells based on vertical stratification modulation through sequential blade-coating

Mechanically durable organic solar cells (OSCs) with high efficiency are deemed as the ideal candidate for the power source of the next generation wearable electronic devices. However, the brittle nature of small molecules in most high-efficiency OSCs consisting of polymer and small molecule encourages easy formation of cracks in the photoactive film under deformation. Here, the vertical composition distribution of the active layer has been well optimized through sequential blade coating to realize highly deformable while efficient OSC. The optimized morphology exhibits distinct donor-rich and homogenous region distributed along the vertical direction in the bulk. The donor-rich region provides sufficient chain entanglements and strong interfaces beneficial for mechanical robustness of film, while homogeneously mixed region offers continuous interpenetrating network to maintain high device through-put, resulting in superior efficiency of 14.4% with high crack-onset strain (COS) of 30.5%. This efficiency versus COS combination is much higher than the best combination reported in all polymer systems (COS of 15.9% and efficiency of 11.1%). To the best of our knowledge, it is the highest COS value achieved in polymer-small molecule systems. As a result, the rational control over vertical stratification demonstrated here would guide researchers in the development of innovative wearable electronics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Highly Deformable Rigid Glassy Conjugated Polymeric Thin Films

Wearable devices benefit from the use of stretchable conjugated polymers (CPs). Traditionally, the design of stretchable CPs is based on the assumption that a low elastic modulus (E) is crucial for achieving high stretchability. However, this research, which analyzes the mechanical properties of 65 CP thin films, challenges this notion. It is discovered that softness alone does not determine stretchability; rather, it is the degree of entanglement that is critical. This means that rigid CPs can also exhibit high stretchability, contradicting conventional wisdom. To inverstigate further, the mechanical behavior, electrical properties, and deformation mechanism of two model CPs: a glassy poly(3-butylthiophene-2,5-diyl) (P3BT) with an E of 2.2 GPa and a viscoelastic poly(3-octylthiophene-2,5-diyl) (P3OT) with an E of 86 MPa, are studied. Ex situ transmission X-ray scattering and polarized UV–vis spectroscopy revealed that only the initial strain (i.e., <20%) exhibits different chain alignment mechanisms between two polymers, while both rigid and soft P3ATs showed similarly behavior at larger strains. In conclusion, by challenging the conventional design metric of low E for high stretchability and highlighting the importance of entanglement, it is hoped to broaden the range of CPs available for use in wearable devices.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Recent Trends and Innovation in Additive Manufacturing of Soft Functional Materials

The growing demand for wearable devices, soft robotics, and tissue engineering in recent years has led to an increased effort in the field of soft materials. With the advent of personalized devices, the one-shape-fits-all manufacturing methods may soon no longer be the standard for the rapidly increasing market of soft devices. Recent findings have pushed technology and materials in the area of additive manufacturing (AM) as an alternative fabrication method for soft functional devices, taking geometrical designs and functionality to greater heights. For this reason, this review aims to highlights recent development and advances in AM processable soft materials with self-healing, shape memory, electronic, chromic or any combination of these functional properties. Furthermore, the influence of AM on the mechanical and physical properties on the functionality of these materials is expanded upon. Additionally, advances in soft devices in the fields of soft robotics, biomaterials, sensors, energy harvesters, and optoelectronics are discussed. Lastly, current challenges in AM for soft functional materials and future trends are discussed.

36 MATERIALS SCIENCE↗