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NASA NTRS2004

Verification of Emergent Behaviors in Swarm-based Systems

The emergent properties of swarms make swarm-based missions powerful, but at the same time more difficult to design and to assure that the proper behaviors will emerge. We are currently investigating formal methods and techniques for verification and validation of swarm-based missions. The Autonomous Nano-Technology Swarm (ANTS) mission is being used as an example and case study for swarm-based missions to experiment and test current formal methods with intelligent swarms. Using the ANTS mission, we have evaluated multiple formal methods to determine their effectiveness in modeling and assuring swarm behavior. This paper introduces how intelligent swarm technology is being proposed for NASA missions, and gives the results of a comparison of several formal methods and approaches for specifying intelligent swarm-based systems and their effectiveness for predicting emergent behavior.

Rouff, Christopher↗

NASA NTRS2006

UWB Tracking System Design with TDOA Algorithm

This presentation discusses an ultra-wideband (UWB) tracking system design effort using a tracking algorithm TDOA (Time Difference of Arrival). UWB technology is exploited to implement the tracking system due to its properties, such as high data rate, fine time resolution, and low power spectral density. A system design using commercially available UWB products is proposed. A two-stage weighted least square method is chosen to solve the TDOA non-linear equations. Matlab simulations in both two-dimensional space and three-dimensional space show that the tracking algorithm can achieve fine tracking resolution with low noise TDOA data. The error analysis reveals various ways to improve the tracking resolution. Lab experiments demonstrate the UWBTDOA tracking capability with fine resolution. This research effort is motivated by a prototype development project Mini-AERCam (Autonomous Extra-vehicular Robotic Camera), a free-flying video camera system under development at NASA Johnson Space Center for aid in surveillance around the International Space Station (ISS).

Ni, Jianjun↗

NASA NTRS2006

Anesthesia during and Immediately after Spaceflight

The increasing presence of humans in space and long-duration manned missions to the Moon or Mars pose novel challenges to the delivery of medical care. Even now, cumulative person-days in space exceed 80 years and preparations for a return to the Moon are actively underway. Medical care after an emergent de-orbit or an accident during a non-nominal landing must not only address the specific disease or injuries but also the challenges posed by physiologic adaptations to microgravity. In the highly autonomous situation of a long-term space mission the situation is even more complex, because personnel, equipment, specific training, and clinical experience are by definition limited. To summarize our current knowledge specifically for anesthetic care during and immediately after spaceflight, we will review physiologic adaptations to microgravity with particular emphasis on the resulting anesthetic risks, discuss veterinary experiences with anesthesia in weightlessness or in animals adapted to microgravity, describe current research that pertains to anesthesia and spaceflight and point out unresolved questions for future investigation.

Seubert, Christoph N.↗

NASA NTRSDate not supplied

Datascope to Enable Earth Independent Medical Operations (EIMO)

BACKGROUND: NASA has amassed sixty years of knowledge and experience relevant to maintenance of crew health and performance in low earth orbit. The Apollo Program introduced the importance of ensuring progressively autonomous operational capability. Earth Independent Medical Operations (EIMO) will require a gradual shift in the balance of medical responsibility, management, and authority from terrestrial to space-based assets. Terrestrial assets will continue to be essential for pre-mission screening and planning in addition to maintenance of crew health and performance. However, new capabilities are needed to enable EIMO and the amount of data required to support these systems, and mitigate the impacts of data transmission delays and reduced bandwidth coupled with lack of cloud-like resources and on-board computing capacity that is currently unclear or operationally insufficient. OVERVIEW: The overall goal of EIMO is to develop artificial intelligence (AI)-based solutions to analyze crew health and performance data utilizing a clinical decision support system (CDSS) to provide crew medical officers (CMO) with the equivalent of real-time, on-board medical consults. The EIMO ecosystem is envisioned as a “system of systems” where embedded reference databases and real-time data streams from multiple input vectors continuously and seamlessly assess crew health and performance. EIMO will be designed to make recommendations to the CMO using multi-modal AI-based natural language processing and machine learning methods with interoperability to push/pull data within and between multiple vehicle and habitat architectures. DISCUSSION: Data flows and storage/retrieval capacity are severely constrained during space missions and the challenges will become even greater during exploration missions. Just as each past program from Mercury to the International Space Station (ISS) required rethinking the interaction between ground-based controllers and space-based crew, so too will future missions to the Moon and Mars. While the NASA High-Performance Spaceflight Computing Processor project aims to increase computational capacity by 100 times over current spaceflight computers, the projected deliverable still lags considerably behind what will be needed to enable an AI-driven CDSS. Restrictions in processing speed and data storage capacity, coupled with transmission bottlenecks and delays, necessitate definition and optimization of an integrated data architecture to enable a progressively autonomous medical capability.

Medical operations↗

NASA NTRSDate not supplied

Modeling Deformable Linear Objects for Autonomous Robotic Outfitting of Lunar Surface Systems

This paper presents structural models of deformable linear objects (DLOs). DLOs are a subclass of deformable objects that encompasses common outfitting elements such as cables and ropes. Models are validated through hardware experiments, and integration in a robotic autonomy architecture for space environments is discussed. A persistent human presence on the lunar surface is one of the next major milestones in space exploration. This requires the development of robust extraplanetary construction technologies including structures and materials modeling and robotic systems. Previous robotic construction technology development has primarily focused on structural assembly, with significantly less focus on robotically performed outfitting tasks to instantiate subsystems providing power, data, life support, etc. These tasks involve manipulation of highly flexible elements, which are difficult to model, such as cable harnesses, ropes, and hoses. Robotic manipulation of DLOs, especially cable harnesses, is an active area of research as cable harnesses are essential for providing power and data to space assets. DLO models that can be used for robot manipulator trajectory generation are necessary for autonomous operation of lunar infrastructure. There are many proposed methods for modeling DLOs, and they primarily fall into three types: 1) discrete model-based, 2) continuum model-based, and 3) Neural Network-based. These types each have pros and cons, and the tradeoff between model accuracy and computational speed informs which type should be used. An understanding of this trade-off is imperative for real-time control of autonomous systems. High computational requirements reduce the speed of the model, making real-time control difficult, while accuracy is critical to preventing collisions. Discrete models, such as a mass-spring multibody representation, require relatively few calculations, and accuracy is directly tied to the step size of the discretization. Continuum models, such as a B-spline representation or a Cosserat rod model (a mix of continuous and discrete), are more informed of the structural properties of the cable and are much more accurate than a rigid body mass-spring model, but at significant computational cost. A Neural Network approach can provide an online solution with very few computational steps, but properly generating training data can be difficult and validation for an in-space application is not trivial. This paper explores the trade-off between different modeling approaches and compares accuracy and computational speed/complexity of the three types mentioned above. Model accuracy is evaluated using a cable in a static configuration. True cable shape is obtained using a depth camera for RGB images and point-cloud segmentation. The purpose of this experiment is to evaluate the trade-offs of different approaches to the DLO modeling problem. Understanding the tradeoffs between different cable modeling techniques paves the way for developing robotic control and planning architectures necessary for real-time manipulation of DLOs for lunar infrastructure outfitting. Real-time control is required for robotic systems to be able to actively manipulate a cable in a harsh environment where model and sensor errors compound, and environmental conditions can cause significant disturbances. Cable routing must be performed in areas with high density of objects/obstacles: through truss structures, near solar panels or mirror arrays, next to bundles of electrical equipment. Understanding the best way to plan and manipulate a cable without disrupting the environment or damaging the cable is imperative to robotic outfitting operations on the lunar surface.

Amy M Quartaro↗

NASA NTRS2004

Planning and Execution: The Spirit of Opportunity for Robust Autonomous Systems

One of the most exciting endeavors pursued by human kind is the search for life in the Solar System and the Universe at large. NASA is leading this effort by designing, deploying and operating robotic systems that will reach planets, planet moons, asteroids and comets searching for water, organic building blocks and signs of past or present microbial life. None of these missions will be achievable without substantial advances in.the design, implementation and validation of autonomous control agents. These agents must be capable of robustly controlling a robotic explorer in a hostile environment with very limited or no communication with Earth. The talk focuses on work pursued at the NASA Ames Research center ranging from basic research on algorithm to deployed mission support systems. We will start by discussing how planning and scheduling technology derived from the Remote Agent experiment is being used daily in the operations of the Spirit and Opportunity rovers. Planning and scheduling is also used as the fundamental paradigm at the core of our research in real-time autonomous agents. In particular, we will describe our efforts in the Intelligent Distributed Execution Architecture (IDEA), a multi-agent real-time architecture that exploits artificial intelligence planning as the core reasoning engine of an autonomous agent. We will also describe how the issue of plan robustness at execution can be addressed by novel constraint propagation algorithms capable of giving the tightest exact bounds on resource consumption or all possible executions of a flexible plan.

Muscettola, Nicola↗

NASA NTRS1996

Definition of exobiology experiments for future Mars missions

During the past year we have concentrated on two objectives. The first objective is ongoing and is to define the experimental parameters that are necessary to conduct autonomously a mineralogical analysis of the Martian surface in situ using differential thermal analysis coupled with gas chromatography (DTA/GC). The rationale in support of this objective is that proper interpretation of the mineralogical data from the DTA/GC can be used to better describe the present and past environments of Mars, leading to a better assessment of the probability of life evolving on Mars. To meet these objectives we have analyzed a number of samples collected from nature using the DTA/GC. One of the more significant findings was that in samples of desert varnish we detected magnetite and maghemite that may serve as potential biomarkers applicable to DTA/GC analyses of Martian surface material during landed missions. The second objective follows from the first and is to better understand microbe-environment interactions by determining the response of microbes to changes in their environment, including extreme desiccation and solar UV-radiation. The rationale behind this is to develop hypotheses regarding what may have happened to life that may have arose on Mars, and microbial life that may get to the surface of Mars via spacecraft, or meteors from Earth. To accomplish this objective we have exposed microbes, collected from NaCl and gypsum-halite crystals, to the space environment aboard the ESA-German Biopan facility for 15 days. The most significant finding was that these microbes survived the exposure better than others.

Mancinelli, Rocco L.↗

NASA NTRS1992

Autonomous Frequency-Domain Indentification

Test and data-processing system determines plant models and uncertainties. Integrated system of methods, digital signal-processing, and algorithms identifies parametric model of large, flexible structures. Experiments in development of system conducted on laboratory model intended to represent large space antenna or flexible spacecraft. Also applicable to many terrestrial systems, robust control of dynamic plants and processes, robust control of systems about which knowledge uncertain or incomplete, decentralized control, and knowledge-based control systems.

Mettler, Edward↗

DOE OSTI2025

AI Applications to Physics Experiments at Jefferson Lab

We survey how AI/ML is being deployed across Jefferson Lab's experimental and accelerator programs. In EPSCI, Hydra applies computer vision to automate real-time data-quality monitoring across all four experimental halls, replacing manual inspection of hundreds to thousands of histograms per shift. AIEC (AI Experiment Controls) uses ML to stabilize drift chamber gains and is now part of standard CEBAF production running, while AI Optimized Polarization (AIOP) targets autonomous control of polarized targets and photon beam angular alignment. In CASA, cavity fault classification models identify faulted cavities and trip types from waveform data with ~85% and ~78% agreement to labeled data, respectively, and are deployed in production; a separate effort applies LLMs and hybrid search to make the CEBAF operations logbook AI-ready. QCD-focused work includes transformer- and GAN-based generative models for particle-level event simulation, with distributed GAN training scaling studies on Polaris. Additional efforts span ML-on-FPGA for the EIC and a new Data Science Department coordinating anomaly detection, uncertainty quantification, and HPC-scalable ML lab-wide. Collectively, these projects illustrate AI's growing role in improving efficiency across JLab's nuclear physics mission.

Mei, Xinxin [Thomas Jefferson National Accelerator↗

NASA NTRS1992

An expert system/ion trap mass spectrometry approach for life support systems monitoring

Efforts to develop sensor and control system technology to monitor air quality for life support have resulted in the development and preliminary testing of a concept based on expert systems and ion trap mass spectrometry (ITMS). An ITMS instrument provides the capability to identify and quantitate a large number of suspected contaminants at trace levels through the use of a variety of multidimensional experiments. An expert system provides specialized knowledge for control, analysis, and decision making. The system is intended for real-time, on-line, autonomous monitoring of air quality. The key characteristics of the system, performance data and analytical capabilities of the ITMS instrument, the design and operation of the expert system, and results from preliminary testing of the system for trace contaminant monitoring are described.

Palmer, Peter T.↗

NASA NTRS2019

Innovative Approaches to Using the International Space Station as a Mars Transit Analog

Human research on the International Space Station (ISS) crew has made significant advances in understanding of the effects of physiology on human health in space missions. However, ISS has not been as suitable for research on other hazards of human spaceflight such as isolation and communications delay. NASA recently completed a special assessment of whether modifications could be made to operations or facilities so that ISS could be used more effectively as an analog to simulate long-duration crew missions beyond low earth orbit. A cross-disciplinary team met to identify concept of operations, trade spaces, challenges, and opportunities to making ISS more operationally relevant as a Mars transit mission analog, and the results and implementation plans are summarized in this manuscript. In addition to the use case of 12-month missions (already in planning by the NASA ISS Program to bound expected Mars transit durations), three new use cases where ISS could provide valuable high-fidelity experience were identified. (1) Testing of operations procedures and medical care could be enhanced by demonstrating crew handling a simulated medical event in microgravity, autonomously, and with significant communications delay. (2) Isolation and confinement effects of deep space transit could be studied on ISS to validate current habitable volume requirements for Mars transit as well as provide context for evaluating the results of the extensive ground-based simulations in HERA and NEK. A trade study of possible operational and hardware changes that would make ISS applicable to these use cases was completed. (3) Surface operations after the physiological deconditioning of a long transit could be conducted to validate crew ability to perform critical ground tasks after 6-month Mars transit and aid in conceptual design of Mars surface element architectures. Each of the case studies includes a trade space between operational impacts on nominal ISS activities and degree of fidelity. A phased approach to implementation means that several "quick start" activities can be done in 2019-2020 at the same time as planning continues for more complex exploration analog options beginning as early as 2022. The team determined that many of these quick-start tasks could be done with available assets, entirely independent of other exploration system development timelines (such as Orion, Space Launch System). The consideration of the full suite of human spaceflight capabilities in the lunar vicinity can also be included as each step in human exploration serves as a simulation opportunity for some aspect of subsequent missions. Further discussions of options with the international community are critical for considering the benefits as well as impacts of simulation activities on ISS, as well as to better formulate future mission architectures.

Robinson, Julie A.↗

NASA NTRSDate not supplied

Enabling a Voice Management System for Space Applications, Design and Software Development

Sustainable missions, beyond low Earth orbit, will require autonomous capabilities in order to achieve NASA’s Artemis program objectives. Correspondingly, the crew must have a means to efficiently interact with these autonomous systems; this can be facilitated via voice and speech communications. Voice-based controls enable the user to access autonomous systems hands-free/eyes-free, allowing the user to better focus on critical tasks. The goal of this project was to explore the knowledge and technology needed to successfully design effective voice interfaces for autonomous systems. The main objective was to understand how a crew member, through voice interaction, could most efficiently and intuitively communicate with a notional autonomous vehicle system manager. This project leveraged prior research conducted by the University of Michigan’s Bioastronautics and Life Support System (BLiSS) team as part of a NASA Moon to Mars eXploration Systems and Habitation (M2M X-Hab) 2020 Academic Innovation Challenge. The X-Hab 2020 work from the BliSS Team resulted in an intuitive graphical user interface/user experience that was built on an Internet of Things (IOT) platform. The Voice User Interface (VUI) design for the M2M X-Hab 2021 project leveraged this technology and incorporated a voice-based assistant and NASA’s Platform for Autonomous Systems (NPAS) software. This required technologies to convert voice to text, conduct semantic interpretations, and convert responses from the autonomous system to text and to speech; additionally, the background noise environment of spacecraft was assessed, and a relatable personality for the autonomous system to facilitate human-like conversations was created. This work’s success was largely due to the diverse team that included expertise in Space Systems Engineering, Human Computer Interaction, Aerospace Engineering, Computer Science, Biomedical Engineering, and Applied Physics. The differing perspectives fostered elaborate discussions, resulting in the conception of three main interactions: (1) User-System, (2) NPAS-System, and (3) Environment-System. The system developed, i.e. the VUI, had to be unique, efficient, and intuitive; thus, the team crafted a personality for the system to enable human-like conversation. User surveys sent to students and young professionals were used to help determine these personality traits by capturing perspectives and expectations of the “Artemis Generation Astronauts”. To further simulate human-like conversations, the system had to be able to quickly interpret user speech and be able to integrate with NASA’s NPAS system for quick and reliable information transfer. Results of this research include (1) a working prototype user interface, that is compatible with NASA’s NPAS system; (2) software that demonstrates the ability to interpret user requests and respond appropriately; (3) the capability to implement fully expanded conversations between user and system using intuitive communication in four request categories; and (4) software and hardware recommendations that optimize the system’s ability to operate, i.e. be heard, in a noisy environment. The technologies chosen for this project’s demonstrations included the following: Raspberry Pi, RASA, Mozilla Deep Speech, Coqui, RTX Voice and Adobe XD. This work has laid the foundation for the development of VUI’s used for autonomy, and is intended to provide guidance for future VUI development.

Tara Vega↗

NASA NTRSDate not supplied

Automating Maneuvers: Considerations for Collision Avoidance

As more space operators implement large constellations of spacecraft, automating orbit maintenance maneuvers becomes a key feature of their operations concept to ensure that the workload is manageable. However, the practice of performing a maneuver without sharing the plan with other nearby spacecraft causes a risk that two spacecraft will collide, not only destroying the spacecraft involved, but creating debris that will affect all other spacecraft using that orbit regime. In order to share the maneuver plan, a predicted ephemeris file containing the maneuver must be sent to a central authority to screen against predicted trajectories of all other on-orbit objects to determine where and when close approaches will occur that may need to be mitigated. Currently the screening authority used by US operators is the 19th Space Defense Squadron; screenings are performed once every 8 hours, meaning that spacecraft using automated maneuvering need to allow 16 hours to share their maneuver plan via the screening process in advance of maneuver execution in case one screening is missed and the next needs to be used. In an effort to speed up the screening process to benefit spacecraft using automated maneuvering, a prototype system for performing near-real-time screenings has been developed in support of the NASA Starling mission, a constellation of four cubesats that fly at the same altitude as the SpaceX Starlink constellation. Both of these constellations perform automated maneuvering, so without screening the planned maneuvers before execution, the two constellations would risk a collision. This paper describes the traditional conjunction assessment (CA) process, the prototype real-time CA screening capability, plans for the experiment to test the prototype, and next steps.

conjunction assessment↗

NASA NTRSDate not supplied

Automating Maneuvers: Considerations for Collision Avoidance

conjunction assessment↗

NASA NTRS2016

UAV Research at NASA Langley: Towards Safe, Reliable, and Autonomous Operations

Unmanned Aerial Vehicles (UAV) are fundamental components in several aspects of research at NASA Langley, such as flight dynamics, mission-driven airframe design, airspace integration demonstrations, atmospheric science projects, and more. In particular, NASA Langley Research Center (Langley) is using UAVs to develop and demonstrate innovative capabilities that meet the autonomy and robotics challenges that are anticipated in science, space exploration, and aeronautics. These capabilities will enable new NASA missions such as asteroid rendezvous and retrieval (ARRM), Mars exploration, in-situ resource utilization (ISRU), pollution measurements in historically inaccessible areas, and the integration of UAVs into our everyday lives all missions of increasing complexity, distance, pace, and/or accessibility. Building on decades of NASA experience and success in the design, fabrication, and integration of robust and reliable automated systems for space and aeronautics, Langley Autonomy Incubator seeks to bridge the gap between automation and autonomy by enabling safe autonomous operations via onboard sensing and perception systems in both data-rich and data-deprived environments. The Autonomy Incubator is focused on the challenge of mobility and manipulation in dynamic and unstructured environments by integrating technologies such as computer vision, visual odometry, real-time mapping, path planning, object detection and avoidance, object classification, adaptive control, sensor fusion, machine learning, and natural human-machine teaming. These technologies are implemented in an architectural framework developed in-house for easy integration and interoperability of cutting-edge hardware and software.

Davila, Carlos G.↗

DOE OSTI2026

An agentic artificially intelligent X-ray scientist

Executing experimental tasks in both normal research laboratories and large-scale scientific facilities often requires extensive human supervision and remains a key challenge on the path to fully autonomous, artificial intelligence (AI)-driven science. Here we demonstrate a large language model-driven agent that autonomously performs X-ray sample alignment on a synchrotron beamline by planning actions, executing instrumental commands, interpreting observations and iterating towards experimental goals. Based on existing large language models with structured tool-use via the model context protocol, our AI X-ray scientist was guided and tested using an in-house-built virtual experimental setup that mirrors a six-circle diffractometer at an operational synchrotron beamline. The agentic workflow developed in the virtual environment was directly deployed on a real beamline, where it correctly identified reference reflections and determined the orientation matrix, an essential first step in any type of single-crystal scattering experiment. Our AI X-ray scientist responded effectively to unexpected experimental conditions, demonstrating adaptive problem-solving and readiness for addressing practical experimental situations. Our study provides a step towards autonomous operation across diverse experimental environments at large-scale scattering facilities.

Chen, Zhantao (ORCID:0000000319543868)↗

NASA NTRS2010

A Modular Instrumentation System for NASA's Habitat Demonstration Unit

NASA's human spaceflight program is focused on developing technologies to expand the reaches of human exploration and science activities beyond low earth orbit. A critical aspect of living in space or on planetary surfaces is habitation, which provides a safe and comfortable space in which humans can live and work. NASA is seeking out the best option for habitation by exploring several different concepts through the Habitat Demonstration Unit (HDU) project. The purpose of this HDU is to develop a fully autonomous habitation system that enables human exploration of space. One critical feature of the HDU project that helps to accomplish its mission of autonomy is the instrumentation system that monitors key subsystems operating within a Habitat configuration. The following paper will discuss previous instrumentation systems used in analog habitat concepts and how the current instrumentation system being implemented on the HDU1-PEM, or pressurized excursion module, is building upon the lessons learned of those previous systems. Additionally, this paper will discuss the benefits and the limitations of implementing a wireless sensor network (WSN) as the basis for data transport in the instrumentation system. Finally, this paper will address the experiences and lessons learned with integration, testing prior to deployment, and field testing at the JSC rock yard. NASA is developing the HDU1-PEM as a step towards a fully autonomous habitation system that enables human exploration of space. To accomplish this purpose, the HDU project is focusing on development, integration, testing, and evaluation of habitation systems. The HDU will be used as a technology pull, testbed, and integration environment in which to advance NASA's understanding of alternative mission architectures, requirements, and operations concepts definition and validation. This project is a multi-year effort. In 2010, the HDU1-PEM will be in a pressurized excursion module configuration, and in 2011 the module will be reconfigured for a pressurized core module configuration. Each year the HDU configurations will undergo testing at NASA's Desert Research and Technology Studies (D-RaTS) in Arizona [1]. As part of this project, a modular instrumentation system is developed to meet the monitoring needs of the HDU subsystems and to integrate with the current command and data handling infrastructure that has been developed for the project. The main objective of this study is to provide for the monitoring needs of the HDU. The requirements necessary to meet this objective are developed by working with the subsystem managers of the HDU to understand their monitoring needs. Additionally, the instrumentation system design leverages knowledge and lessons learned from previous studies, such as the inflatable habitat health monitoring system that was deployed in Antarctica [2], the integrated health monitoring system developed for NASA's Microhab [3], and the JSC Lunar Habitat Wireless Testbed to demonstrate a "standardsbased" approach to a wireless instrumentation system [4]. The HDU also requires flexibility in reconfiguration options, and it is necessary to demonstrate and evaluate a modular approach to an instrumentation system. Thus, the instrumentation system is designed in two parts: the primary system employs a standard WSN configuration, and the secondary system employs a wired USB hub. The WSN design provides for reconfiguration or replacement of sensors due to malfunctions or upgrades by using a wireless node that accepts ten instrument inputs and wirelessly transmits the data to the command and data handling system. The USB hub is necessary for those instruments that operate using a wired USB connection, although the design attempts to limit the amount of sensors that need to be wired connections.

Rojdev, Kristina↗

NASA NTRS2017

Sample Processor for Life on Icy Worlds (SPLIce): Design and Test Results

We report the design, development, and testing of the Sample Processor for Life on Icy Worlds (SPLIce) system, a microfluidic sample processor to enable autonomous detection of signatures of life and measurements of habitability parameters in Ocean Worlds. This monolithic fluid processing-and-handling system (Figure 1; mass 0.5 kg) retrieves a 50-L-volume sample and prepares it to supply a suite of detection instruments, each with unique preparation needs. SPLIce has potential applications in orbiter missions that sample ocean plumes, such as found in Saturns icy moon Enceladus, or landed missions on the surface of icy satellites, such as Jupiters moon Europa. Answering the question Are we alone in the universe? is captivating and exceptionally challenging. Even general criteria that define life very broadly include a significant role for water [1,2]. Searches for extinct or extant life therefore prioritize locations of abundant water whether in ancient (Mars), or present (Europa and Enceladus) times. Only two previous planetary missions had onboard fluid processing: the Viking Biology Experiments [3] and Phoenixs Wet Chemistry Laboratory (WCL) [4]. SPLIce differs crucially from those systems, including its capability to process and distribute L-volume samples and the integration autonomous control of a wide range of fluidic functions, including: 1) retrieval of fluid samples from an evacuated sample chamber; 2) onboard multi-year storage of dehydrated reagents; 3) integrated pressure, pH, and conductivity measurement; 4) filtration and retention of insoluble particles for microscopy; 5) dilution or vacuum-driven concentration of samples to accommodate instrument working ranges; 6) removal of gas bubbles from sample aliquots; 7) unidirectional flow (check valves); 8) active flow-path selection (solenoid-actuated valves); 9) metered pumping in 100 nL volume increments. The SPLIce manifold, made of three thermally fused layers of precision-machined cyclo-olefin polymer, supports all fluidic components (Figure 1) and integrated microchannels (125 x 250 m). Fluid is pumped by a stepper-motor-driven pump (Lee Co.). The functionality of the integrated MEMS pressure sensor (Honeywell) and passive check valves (Figure 2) were tested in conjunction with our newly designed integral bubble traps (Figure 3) and hydrophobic membrane-based concentrator (Figure 4). The concentrator (initially tested as a standalone component) demonstrated 5-fold vacuum-evaporative concentration. Polyethylene fused bead beds (PEFBBs; 50 porosity) store drylyophilized buffers, calibrants, and fluorescent dyes, and also promote mixing of sample with calibrant, dye, or H2O. Software-controlled automated tests demonstrated successful 1) fluid delivery to each component 2) valve and pump synchronization 3) sample aliquot delivery to instrument interface ports, and 4) rehydration of vacuum-dried fluorescent dye. In Figure 5, fluorescein on PEFBBs was rehydrated for 15 min using a pump-delivered water aliquot; it is displaced as H2O enters the bottom of the channel and pushes the dye into a check valve. Ultimately, SPLIce will fluorescently label amino acids in the sample for microchip-based electrophoretic (MCE) chiral separation and detection to seek and quantify key organic bio-signatures [5]; it will also deliver sample to a microfluidic version of WCL (mWCL) to measure soluble ions and redox-active species.

Life detection↗