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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Modern analogs for understanding pollen-vegetation dynamics in a Mediterranean mosaic landscape (Balearic Islands, Western Mediterranean)

This paper presents the study of modern pollen analogs from the Balearic Islands. While similar studies have been largely applied to mainland areas, research focused on modern vegetation dynamics on Mediterranean islands remains very rare. In this research, we combine vegetation surveys, pollen analysis and multivariate statistics to understand landscape composition. The main objectives of are: (1) to examine pollen-vegetation relationships in relation to environmental and land-use variables; (2) to understand modern pollen representation in a mosaic landscape structure; and (3) to propose pollen indicators that characterize the primary vegetation types from the Balearic Islands to better interpret past pollen records in Mediterranean island environments. Pollen results and Redundancy Analysis (RDA) distinguish three major groups: (a) Holm oak and box formations; (b) maquis and garrigues; and (c) anthropogenic and open habitats. Landscape form, mean decadal rainfall, mean decadal temperature, fire activity, trampling, slope percentage, wet/flooded soil, saline soil, distance to agropastoral cells, gHM index, domestic herbivory presence, agropastoral use, and soil type are the major variables explaining modern pollen assemblage variation in our research. Poaceae undiff., Plantago sp., Apiaceae undiff., Cerealia-t, and Cichorieae are highly correlated to human activities but should be interpreted cautiously when occurring in low values. Quercus ilex-t, Hypericum, and Buxus are correlated to humid locations while Pistacia, Pinus, Juniperus-t, and Olea to high mean decadal temperatures. Our study indicates how pollen analysis and multivariate analysis are powerful tools for characterizing the mosaic landscape, with special focus on the main vegetation types of the Balearic Islands.

Geology↗
DOE OSTI2021

Enhancement of Industry Legacy Probabilistic Risk Assessment Methods and Tools

Probabilistic risk assessments (PRAs) are integral to nuclear power plant (NPP) operations, having tremendously benefitted the safety of the U.S. reactor fleet for decades. Insights obtained from the models have provided perspectives on a variety of applications, both at the plant and for the regulator. While these models are very useful, they are now being asked to represent and analyze aspects of the plant that were never envisioned by the initial PRA practitioners. Furthermore, heightened demands on the PRA models have led to increased computing power requirements. Additionally, as the complexity of the PRA models increased, the difficulty experienced by non-PRA experts in trying to understand these models, grasp the insights they provide, and effectively use that information has become problematic. The need for research to address key issues regarding PRA tools and methods has never been greater. Although the nuclear power industry has largely been well-served by these tools and methods, the underlying science is dated, remaining mostly unchanged for over two decades. Three areas were identified as most beneficial to address to maintain and improve the usefulness of the current practice legacy PRA tools: improvement in quantification speed, increased ability to efficiently model multi-hazard models, and improvement in modeling human action dependency in PRA. This report provides the outcomes from the FY2021 research into these three areas, identifying potential technical gaps and solutions, and charting the next steps forward to address current PRA challenges.

42 ENGINEERING↗
DOE OSTI2021

Naturalistic Intensities of Light at Night: A Review of the Potent Effects of Very Dim Light on Circadian Responses and Considerations for Translational Research

In this review, we discuss the remarkable potency and potential applications of a form of light that is often overlooked in a circadian context: naturalistic levels of dim light at night (nLAN), equivalent to intensities produced by the moon and stars. It is often assumed that such low levels of light do not produce circadian responses typically associated with brighter light levels. A solid understanding of the impacts of very low light levels is complicated further by the broad use of the somewhat ambiguous term “dim light,” which has been used to describe light levels ranging seven orders of magnitude. Here, we lay out the argument that nLAN exerts potent circadian effects on numerous mammalian species, and that given conservation of anatomy and function, the efficacy of light in this range in humans warrants further investigation. We also provide recommendations for the field of chronobiological research, including minimum requirements for the measurement and reporting of light, standardization of terminology (specifically as it pertains to “dim” light), and ideas for reconsidering old data and designing new studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Evaluating SWAT + model uncertainties for human and natural outcomes: Application in a Great Lakes agricultural watershed

Nutrient exports from agricultural lands in the Great Lakes Region pose significant threats to water quality and ecological health through eutrophication, hypoxia, and harmful algal blooms. Climate change and agricultural adaptation practices complicate future nutrient loading due to intensified hydrologic cycles and land use decisions. Our research focuses on evaluating the Soil and Water Assessment Tool (SWAT) plus model parametric uncertainties for human and natural outcomes across different scales. These factors are integral to ensuring a balance between productive agricultural practices and maintaining the health of watershed hydrology. However, uncertainties in modeling such complex interactions pose significant challenges, limiting our ability to precisely determine critical factors that influence crop yield and soil moisture. Our analysis employs Sobol global sensitivity analysis to evaluate first-order, second order, and total-order indices for SWAT crop growth parameter, ensuring comprehensive assessment of individual and interactive effects on model outputs. The objective is to identify the parameters that significantly affect model outputs for crop yield and soil moisture and improve our understanding of their interactions at the basin and hydrological response unit (HRU) scale. Our case study, the Portage River Watershed, which drains into Lake Erie, is chosen to better capture finer scale interactions crucial for predicting nutrient loading under future climate scenarios. This foundational work is aimed at setting the stage for the future development of an agent-based model (ABM). The ABM model would incorporate SWAT outputs to dynamically simulate decision-making processes.

Bunyon, Enock↗
DOE OSTI2024

In Silico Human Mobility Data Science: Leveraging Massive Simulated Mobility Data (Vision Paper)

Human mobility data science using trajectories or check-ins of individuals has many applications. Recently, we have seen a plethora of research efforts that tackle these applications. However, research progress in this field is limited by a lack of large and representative datasets. The largest and most commonly used dataset of individual human trajectories captures fewer than 200 individuals, while datasets of individual human check-ins capture fewer than 100 check-ins per city per day. Thus, it is not clear if findings from the human mobility data science community would generalize to large populations. Since obtaining massive, representative, and individual-level human mobility data is hard to come by due to privacy considerations, the vision of this work is to embrace the use of data generated by large-scale socially realistic microsimulations. Informed by both real data and leveraging social and behavioral theories, massive spatially explicit microsimulations may allow us to simulate entire megacities at the person level. The simulated worlds, which do not capture any identifiable personal information, allow us to perform “in silico” experiments using the simulated world as a sandbox in which we have perfect information and perfect control without jeopardizing the privacy of any actual individual. In silico experiments have become commonplace in other scientific domains such as chemistry and biology, permitting experiments that foster the understanding of concepts without any harm to individuals. This work describes challenges and opportunities for leveraging massive and realistic simulated alternate worlds for in silico human mobility data science.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Heavy metal imprints in Antarctic snow from research and tourism

Antarctica, long regarded as one of the last pristine environments on Earth, is increasingly affected by human activity. As tourism surges and scientific operations expand, air pollution from local emissions is raising new environmental concerns. Here, in this study, we analyze surface snow samples collected along a ~2,000 km transect, from the South Shetland Islands (62°S) to the Ellsworth Mountains (79°S), to map the geochemical fingerprints of aerosol deposition. We identify distinct spatial patterns shaped by crustal, marine, biogenic, and anthropogenic sources. Notably, we detect heavy metal imprints in the snow chemistry of the northern Antarctic Peninsula, where major research stations are concentrated and marine tourism traffic is most intense. Our findings shed light on the extent of the impacts from energy-intensive local activities in Antarctica, underscoring the need for enhanced environmental monitoring and sustainable management strategies in this fragile region.

Cordero, Raúl R. [Univ. of Groningen, Leeuwarden (↗
DOE OSTI2025

U-Surf: a global 1 km spatially continuous urban surface property dataset for kilometer-scale urban-resolving Earth system modeling

High-resolution urban climate modeling has faced substantial challenges due to the absence of a globally consistent, spatially continuous, and accurate dataset to represent the spatial heterogeneity of urban surfaces and their biophysical properties. This deficiency has long obstructed the development of urban-resolving Earth system models (ESMs) and ultra-high-resolution urban climate modeling, over large domains. Here, we present U-Surf, a first-of-its-kind 1 km resolution present-day (circa 2020) global continuous urban surface parameter dataset. Using the urban canopy model (UCM) in the Community Earth System Model as a base model for satisfying dataset requirements, U-Surf leverages the latest advances in remote sensing, machine learning, and cloud computing to provide the most relevant urban surface biophysical parameters, including radiative, morphological, and thermal properties, for UCMs at the facet and canopy level. Generated using a systematically unified workflow, U-Surf ensures internal consistency among key parameters, making it the first globally coherent urban canopy surface dataset. U-Surf significantly improves the representation of the urban land heterogeneity both within and across cities globally; provides essential, high-fidelity surface biophysical constraints to urban-resolving ESMs; enables detailed city-to-city comparisons across the globe; and supports next-generation kilometer-resolution Earth system modeling across scales. U-Surf parameters can be easily converted or adapted to various types of UCMs, such as those embedded in weather and regional climate models, as well as air quality models. The fundamental urban surface constraints provided by U-Surf can also be used as features for machine learning models and can have other broad-scale applications for socioeconomic, public health, and urban planning contexts. We expect U-Surf to advance the research frontier of urban system science, climate-sensitive urban design, and coupled human–Earth systems in the future. The dataset is publicly available at https://doi.org/10.5281/zenodo.11247598 (Cheng et al., 2024).

Cheng, Yifan [Univ. of Illinois at Urbana-Champaig↗
DOE OSTI2026

Report of the 2026 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Science

Scientific computing is undergoing rapid transformation as advances in artificial intelligence, heterogeneous computing, automation, and data-intensive research reshape not only computational tools but also the institutions, workforce models, and collaborative practices that support scientific discovery. This report synthesizes insights from the 2026 Workshop on Next-Generation Ecosystems for Scientific Computing, the second in a three-year series focused on strengthening scientific computing ecosystems through socio-technical co-design. Workshop discussions identified four interdependent strategic themes: software ecosystems for AI-enabled scientific discovery; trust, validation, and traceability; human-AI teaming and paradigm shifts; and workforce, pedagogy, and governance. The report translates these themes into eight priorities for community action spanning shared research infrastructure, trust and traceability, user experience, human-AI teaming, workforce development, cross-sector coordination, stewardship and sustainability, and evaluation of scientific value. Together, these priorities outline directions for building scientific computing ecosystems that remain trustworthy, sustainable, innovative, and resilient as AI assumes a growing role in scientific work.

AI↗
DOE OSTI2023

PNNL DataHub NIAID Program Project: Modeling Host Responses to Understand Severe Human Virus Infections, Multi-Omic Viral Dataset Catalog Collection

The National Institute of Allergy and Infectious Diseases (NIAID) "Modeling Host Responses to Understand Severe Human Virus Infections" program project was a highly integrated and comprehensive systems biology research core, funded by the National Institute of Health (U19AI106772) from 2013-06-01 to 2018-05-31, investigating the complex host response to category A, B, and C priority pathogen infections. Resulting project deliverables include an extensive comprehensive collections of linked primary and secondary transformation viral experimental infection data. Here we provide a never before released comprehensive infectious disease collection of primary and secondary transformation multi-Omics data profiling a series of priority pathogen primary experimental studies for enhanced open access to viral Omics lifecycle datasets and project metadata. Using a highly integrated and multidisciplinary approach, linked primary data and metadata supporting secondary normalization datasets, provide critical information necessary for research reproducibility and long-term preservation. Enabling on-demand data access for research community consumption and developer reuse, serves to support new mechanistic insights and discoveries into host-pathogen interactions for aiding future biohazard data preparedness efforts in emergency response to global health crises involving viral infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

2024 International Conference on Microbiome Engineering (ICME)

The 2024 International Conference on Microbiome Engineering (ICME) took place November 12-14 at Tufts University in Medford, MA. ICME connects experts from academia and industry to share the most recent developments in the field of microbiome engineering. This includes genetically engineered organisms that function within microbiomes, control of microbiomes through environmental/nutrient modifications, and inference of engineering principles from analysis of synthetic and natural microbiomes. The conference is unique and distinct from other microbiome conferences in that it specifically highlights the integration of engineering design principles with microbiome research (others are more focused on basic biological principles). The conference thus integrates synthetic biology, systems biology, microbial ecology, and bioinformatics across a range of application spaces from the environment to manufacturing, food, and human health. This project utilized support from the Department of Energy’s (DOE) Office of Biological and Environmental Research (BER) to help trainees and early career faculty attend ICME.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Yes, No, Maybe So: Human Factors Considerations for Fostering Calibrated Trust in Foundation Models Under Uncertainty

High-stakes analytical environments require analysts to evaluate evidence and generate conclusions to inform critical decisions often under conditions of uncertainty. Probabilistic decision-making based on incomplete or inaccurate information can reduce productivity, compromise national interests, and endanger public safety. Researchers are developing expert systems built on foundation models (FMs) to support analysts’ decision-making processes by enabling human-artificial intelligence (AI) teaming, in part through the quantification and expression of uncertainty information. As FMs continue to mature, it is imperative to correspondingly consider analysts’ needs for appropriately interpreting and using uncertainty information. However, prior research indicates that it remains unclear how analysts engage with FM-generated uncertainty information and the extent to which these interactions influence trust in, and reliance on, expert systems. We plan to review the state of the science and conduct an exploratory, qualitative study to (a) understand how properly communicated uncertainty can foster calibrated trust and appropriate reliance and (b) identify approaches for effectively conveying FM-generated uncertainty information during analytical workflows. We will administer semi-structured interviews with analysts from a specific high-stakes analytical environment to collect their current experiences with job-related uncertainty and their impressions when viewing FM-generated uncertainty information. During the interview protocol, participants will be presented with several different FM outputs and invited to discuss their thoughts and beliefs about the uncertainty information displayed. Participants may provide insights into how trust and reliance may be influenced by uncertainty. The results of this study will help us to better understand how analysts currently interpret and use uncertainty information. Our findings may inform human factors recommendations for effectively conveying uncertainty information to foster calibrated trust in, and appropriate reliance on, expert systems. Interaction designers and FM developers can use this knowledge to enhance human-AI teaming and ensure the responsible deployment of FM-based expert systems in analytical workflows.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Sensitive Resources Assessment and Forest Analysis for the Proposed Versatile Test Reactor, Oak Ridge, Tennessee

The US Department of Energy’s (DOE’s) Oak Ridge National Laboratory (ORNL) is a leading institution in advanced materials, supercomputing, neutrons, and nuclear science. As a research laboratory managed by UT-Battelle, LLC for DOE, ORNL has national priorities in energy, security, and scientific discovery that necessitate facility improvements and expansions. DOE is also committed to environmental stewardship. The laboratory is located on the ~32,000-acre (~13,000-ha) Oak Ridge Reservation (ORR), much of which is categorized as a National Environmental Research Park (NERP) and a state Wildlife Management Area. DOE works with the Tennessee Wildlife Resources Agency (TWRA), Tennessee Department of Environment and Conservation (TDEC), US Fish and Wildlife Service (USFWS), US Department of Agriculture, and other agencies to serve as an effective steward of the ORR. Accordingly, project managers must conform to environmental regulations, agreements, and policies at the federal, state, and institutional levels. Per 40 CFR (Code of Federal Regulations) 1508.14, potential effects on research and science education also represent potential effects of federal actions on the NERP, and impacts on, e.g., deer harvest, must be considered on the Oak Ridge Wildlife Management Area when other aspects of the human environment are affected. The United States currently has no fast neutron testing capability to support advanced nuclear research and development. The proposed Versatile Test Reactor (VTR) will take advantage of current investments by the US government and private industry in nuclear reactors to expedite the design and construction process, using proven technology to create a world-class scientific infrastructure. The VTR will take advantage of fast neutrons provided by this proven technology, along with a capability to rapidly insert, conduct, and remove state-of-the-art experiments. An advantage of the VTR is that it can support future innovations in experimental capabilities without modifying the facility. The VTR will support progress in a variety of science and technology areas, including testing and qualification of advanced reactor fuels; testing and qualification of innovative structural materials; testing of innovative components and instruments; validation of advanced modeling and simulation tools; and versatility for future technical missions. Through proven technology, the VTR can take advantage of existing reactor designs and operating experience to reduce the risk, cost, and time for design and construction. The top available resources of DOE laboratories, industry, and universities will be used to expedite reactor design and construction toward developing the scientific infrastructure that affords a strong testing capability that can be sustained over many years. This report summarizes current knowledge of natural and cultural resources primarily within the VTR construction area. At the time of this report, the proposed VTR site design includes a construction area of ~150.4 acres (~69.9 ha), which contains an ~51.3-acre (~20.8-ha) operations area, located within forested natural areas of the ORR. The primary goal of the work presented here was to evaluate potential effects on sensitive resources that might result from development and construction activities associated with VTR. In addition to on-the-ground surveys during spring and summer 2020 by the ORNL Natural Resources Management Program and Aquatic Ecology Group staff, this report makes use of historical (pre-1995) and contemporary (1995 to present) data from additional confirmed sources (e.g., TDEC). Likewise, forest conditions were compiled from a 2011 forest inventory and supplemented with limited ground observations in 2020. The individuals who obtained and compiled the data presented here are familiar with and routinely assess sensitive resources on the ORR. Anyone who references this report must consider that the timing of surveys did not permit a complete delineation of the resources that will be affected. If the VTR project proceeds, additional surveys will be required to account for the seasonal patterns of various threatened and endangered species. Data deficiencies and potential resources that likely went undetected are indicated where possible. Accordingly, this report should facilitate more environmentally sound decisions during planning and 2 development of the VTR site, provide a foundation for further assessment of sensitive and cultural resources, and help project managers better address regulatory guidance and DOE policies on sustainable development in compliance with, for example, the US Endangered Species Act (ESA), Migratory Bird Treaty Act (MBTA), Tennessee Rare Plant Protection and Conservation Act of 1985, Tennessee Nongame and Endangered or Threatened Wildlife Species Conservation Act of 1974, several federal and state regulations regarding aquatic resource protection, and site-specific policies as outlined in various ORR management plans developed by ORNL and TWRA for DOE.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Deciphering the source of primary biological aerosol particles: a pollen case study

Primary biological aerosol particles (PBAPs) are microscopic solids suspended in the atmosphere emitted by biological systems and play critical roles in the atmosphere and at the atmosphere-biosphere interface, impacting human health, climate, and the ecosystem function. Understanding the sources of PBAPs is necessary to decipher the mechanistic interactions between aerosols, climate, and distinct ecosystem components. However, the detection of specific PBAPs in complex ambient aerosol samples is challenging. We performed metabolomics analyses of pollen from three pollinating tree species and ambient samples collected during the peak pollination period of each species. Random Forest and sPLS-DA machine learning methods were employed to evaluate whether metabolic signatures of ambient samples can reveal the source of the main pollen particles present in the atmosphere. Our results suggest that atmospheric eco-metabolomics techniques combined with sophisticated statistical methods can decipher the origin of abundant PBAPs from complex ambient samples. Developing complete libraries containing high-resolution metabolomic fingerprints of the major PBAPs present in the atmosphere would significantly advance future research to accurately understand the role of PBAPs in the atmosphere, ecosystems and human health.

Rivas-Ubach, Albert↗
DOE OSTI2021

A Comprehensive Review of Selected Major Categories of Lithium Isotope Separation Techniques

The ability to generate materials with an enriched isotopic abundance, that is one that differs from natural abundance, is critical in terms of technology. Isotopes are used in a wide range of applications, including radioactive tracers, nondestructive tests, radiotherapy in human medicine, nuclear fuels, and isotope‐substituted compounds for chemistry and biology research, as well as environmental geochemical signature tracers. A commonly discussed research topic is the isotopic separation of various elements—uranium, hydrogen, lithium, and iodine, among many others. Among these isotopes, lithium isotopes are especially important in various applications including strategic areas. These isotopes are light and hence their separation techniques are not very obvious. Herein, all the main categories of Li isotope separation are reviewed in depth with a focus on electrochemical technologies for stable lithium isotope separation.

Murali, Arun↗
DOE OSTI2024

The role of driver head pose dynamics and instantaneous driving in safety critical events: Application of computer vision in naturalistic driving

This paper investigates the role of driver behavior especially head pose dynamics in safety–critical events (SCEs). Using a large dataset collected in a naturalistic driving study, this paper analyzes the head pose dynamics and driving behavior in moments leading up to crashes or near-crashes. The study uses advanced computer vision and mixed logit modeling techniques to identify patterns and relationships between drivers’ head pose dynamics and crash involvement. The results suggest that driver-head pose dynamics, especially poses that indicate distraction and movement volatility, are important factors that can contribute to undesirable safety outcomes. Marginal effects show that angular deviation for head pose dynamics indicated by yaw, pitch and roll increase the likelihood of crash intensity by 4.56%, 4.92% and 8.26% respectively. Furthermore, traffic flow and lane changing also contribute to increase in likelihood of crash intensity. These findings provide new insights into pre-crash factors, especially human factors and safety–critical events. The study highlights the importance of considering human factors in designing driver assistance systems and developing safer vehicles. This research contributes by examining naturalistic driving data at the microscopic level with early detection of behaviors that lead to SCEs and provides a basis for future research on automation.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Perspectives for self-driving labs in synthetic biology

Self-driving labs (SDLs) combine fully automated experiments and data collection with artificial intelligence (AI) and control algorithms that decide not only the set of parameters for the next experiment, but also potentially which scientific hypotheses to test. Taken to their ultimate expression, SDLs could usher a new paradigm of scientific research, where the world is probed, interpreted, and explained by machines for human benefit. Whereas there are functioning SDLs in the fields of chemistry and materials science, we contend that synthetic biology provides a unique opportunity since the genome provides a single, easily accessible, target for affecting the incredibly wide repertoire of biological cell behavior. Since they can provide large amounts of high-quality data, SDLs can be a platform for AI to develop approaches to systematically convert data into scientific knowledge systems. These knowledge systems can be used both to understand the biological world and to design bioengineered systems to fit a desired specification (inverse design). However, the level of investment required for the creation of biological SDLs is only warranted if directed towards solving difficult and enabling biological questions. Here, we discuss challenges and opportunities in creating SDLs for synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Hybrid classical-quantum communication networks

Over the past several decades, the proliferation of global classical communication networks has transformed various facets of human society. Concurrently, quantum networking has emerged as a dynamic field of research, driven by its potential applications in distributed quantum computing, quantum sensor networks, and secure communications. This prompts a fundamental question: rather than constructing quantum networks from scratch, can we harness the widely available classical fiber-optic infrastructure to establish hybrid quantum–classical networks? This paper aims to provide a comprehensive review of ongoing research endeavors aimed at integrating quantum communication protocols, such as quantum key distribution, into existing lightwave networks. This approach offers the substantial advantage of reducing implementation costs by allowing classical and quantum communication protocols to share optical fibers, communication hardware, and other network control resources—arguably the most pragmatic solution in the near term. In the long run, classical communication will also reap the rewards of innovative quantum communication technologies, such as quantum memories and repeaters. Accordingly, our vision for the future of the Internet is that of heterogeneous communication networks thoughtfully designed for the seamless support of both classical and quantum communications.

Fiber-optic communication↗
DOE OSTI2022

Flexible organic integrated electronics for self-powered multiplexed ocular monitoring

Smart contact lens has drawn extensive research interests due to the noninvasive real-time detection of the human body to provide biomedical information for health management. However, it has been difficult to accurately measure the physiological signals in tears, and the use of external power source has also hindered the future applications. Here, we demonstrated an organic electrochemical transistor based multiplexed sensors self-powered by the organic solar cells (OSCs). The integrated device was fabricated via simple process including solution blade-coating and thermal evaporation. OSCs were optimized to provide optimal operation voltage for the sensors that exhibit semilog-linear response to the glucose and calcium ions in tear fluids without any peripheral circuits. The sensing signals can be transmitted to the laptop wirelessly through a near filed communication unit. This integrated self-powered multiplexed sensing device will provide real-time monitoring of the biomarkers in tears, prospected to be installed on the smart contact lens for the early detection and diagnosis of diabetes.

36 MATERIALS SCIENCE↗