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NASA NTRS2000

Fluid Physics and Macromolecular Crystal Growth in Microgravity

The first protein crystallization experiment in microgravity was launched in April, 1981 and used Germany's Technologische Experimente unter Schwerelosigkeit (TEXUS 3) sounding rocket. The protein P-galactosidase (molecular weight 465Kda) was chosen as the sample with a liquid-liquid diffusion growth method. A sliding device brought the protein, buffer and salt solution into contact when microgravity was reached. The sounding rocket gave six minutes of microgravity time with a cine camera and schlieren optics used to monitor the experiment, a single growth cell. In microgravity a strictly laminar diffusion process was observed in contrast to the turbulent convection seen on the ground. Several single crystals, approx 100micron in length, were formed in the flight which were of inferior but of comparable visual quality to those grown on the ground over several days. A second experiment using the same protocol but with solutions cooled to -8C (kept liquid with glycerol antifreeze) again showed laminar diffusion. The science of macromolecular structural crystallography involves crystallization of the macromolecule followed by use of the crystal for X-ray diffraction experiments to determine the three dimensional structure of the macromolecule. Neutron protein crystallography is employed for elucidation of H/D exchange and for improved definition of the bound solvent (D20). The structural information enables an understanding of how the molecule functions with important potential for rational drug design, improved efficiency of industrial enzymes and agricultural chemical development. The removal of turbulent convection and sedimentation in microgravity, and the assumption that higher quality crystals will be produced, has given rise to the growing number of crystallization experiments now flown. Many experiments can be flown in a small volume with simple, largely automated, equipment - an ideal combination for a microgravity experiment. The term "protein crystal growth" is often historically used to describe these microgravity experiments. This is somewhat inaccurate as the field involves the study of many varied biological molecules including viruses, proteins, DNA, RNA and complexes of those structures. For this reason we use the term macromolecular crystal growth. In this chapter we review a series of diagnostic microgravity crystal growth experiments carried out principally using the European Space Agency (ESA) Advanced Protein Crystallization Facility (APCF). We also review related research, both experimental and theoretical, on the aspects of microgravity fluid physics that affect microgravity protein crystal growth. Our experiments have revealed some surprises that were not initially expected. We discuss them here in the context of practical lessons learnt and how to maximize the limited microgravity opportunities available.

Helliwell, John R.↗

NASA NTRS2009

Wireless Avionics Packet to Support Fault Tolerance for Flight Applications

In this protocol and packet format, data traffic is monitored by all network interfaces to determine the health of transmitter and subsystems. When failures are detected, the network inter face applies its recover y policies to provide continued service despite the presence of faults. The protocol, packet format, and inter face are independent of the data link technology used. The current demonstration system supports both commercial off-the-shelf wireless connections and wired Ethernet connections. Other technologies such as 1553 or serial data links can be used for the network backbone. The Wireless Avionics packet is divided into three parts: a header, a data payload, and a checksum. The header has the following components: magic number, version, quality of service, time to live, sending transceiver, function code, payload length, source Application Data Interface (ADI) address, destination ADI address, sending node address, target node address, and a sequence number. The magic number is used to identify WAV packets, and allows the packet format to be updated in the future. The quality of service field allows routing decisions to be made based on this value and can be used to route critical management data over a dedicated channel. The time to live value is used to discard misrouted packets while the source transceiver is updated at each hop. This information is used to monitor the health of each transceiver in the network. To identify the packet type, the function code is used. Besides having a regular data packet, the system supports diagnostic packets for fault detection and isolation. The payload length specifies the number of data bytes in the payload, and this supports variable-length packets in the network. The source ADI is the address of the originating interface. This can be used by the destination application to identify the originating source of the packet where the address consists of a subnet, subsystem class within the subnet, a subsystem unit, and the local ADI number. The destination ADI is used to route the packet to its ultimate destination. At each hop, the sending interface uses the destination address to determine the next node for the data. The sending node is the node address of the interface that is broadcasting the packet. This field is used to determine the health of the subsystem that is sending the packet. In the case of a packet that traverses several intermediate nodes, it may be the node address of the intermediate node. The target node is the node address of the next hop for the packet. It may be an intermediate node, or the final destination for the packet. The sequence number is used to identify duplicate packets. Because each interface has multiple transceivers, the same packet will appear at both receivers. The sequence number allows the interface to correlate the reception and forward a single, unique packet for additional processing. The subnet field allows data traffic to be partitioned into segregated local networks to support large networks while keeping each subnet at a manageable size. This also keeps the routing table small enough so routing can be done by a simple table lookup in an FPGA device. The subsystem class identifies members of a set of redundant subsystems, and, in a hot standby configuration, all members of the subsystem class will receive the data packets. Only the active subsystem will generate data traffic. Specific units in a class of redundant units can be identified and, if the hot standby configuration is not used, packets will be directed to a specific subsystem unit.

Block, Gary L.↗

DOE OSTI2025

Development of a robust damage analysis scheme at the National Ignition Facility

The onset of laser-induced damage in optical materials is a limiting factor in the design and operation of most high-energy laser systems. As such, significant effort has been dedicated to developing laser damage testing protocols and procedures to inform laser system design and operating limits. These tests typically rely on multiple laser exposures for statistical validation. Historically, small beam single fluence (N / 1) or ramped fluence (R / 1) tests have been used to quantify the “laser-induced damage threshold” of a material. However, due to various distributions in damage precursor populations, the laser fluence at which damage occurs for a given sample varies with beam size and is therefore better described as the onset of observed damage for that testing geometry. In conclusion, we document the development of irradiation, measurement, and analysis methods for damage testing resulting in damage initiation density as a function of incident fluence or ρ(ϕ) which is suitable for both small and large beam area testing and more conducive to extrapolating from one to the other.

Beam diameter↗

NASA NTRS2025

Limitations and Feasibility of Mini X-Ray Devices in Space Environments

LIMITATIONS AND FEASIBILITY OF MINI X-RAY DEVICES IN SPACE ENVIRONMENTS As space exploration advances toward long-duration missions, reliable medical diagnostic tools become increasingly critical. The miniature x-ray (XR) technology demonstrations by the Exploration Medical Capability (ExMC) and the Exploration Medical Integrated Product Team (XMIPT) aim to assess the feasibility and utility of miniature XR devices in spaceflight. This abstract explores the limitations of current miniature XR systems, the challenges of training crew members, the potential role of clinical decision support systems (CDSS), and the feasibility of ground-based image interpretation. We also propose the integration of miniature XR into other ExMC efforts aimed at identifying the capabilities and resources needed for future exploration class missions. One of the primary challenges with miniature XR devices is the ability to achieve specific anatomical views, particularly in the confined and weightless conditions of a spacecraft. Operators may struggle to acquire diagnostic-quality images when space is limited for proper patient positioning and the volume of the imaging device. Since space radiation and detector limitations may further impact image quality, the flexibility of the operating procedures of these devices will be critical for their success in space applications. CHALLENGES IN TRAINING CREW TO OPERATE IMAGING DEVICES Training in the skills necessary to acquire diagnostic-quality scans may be a barrier for non-clinician crewmembers. The curriculum developed for crew medical officers (CMOs) will require simplification and adaptation to fit into the highly truncated pre-flight training period. Therefore, hands-on familiarization and simulation, both pre-flight and just-in-time training during missions, will be crucial to ensuring the crew can operate the devices in real-life situations. The ability to adjust acquisition parameters must be simplified or made automatic through exam selections on equipment user interfaces, and subject and operator positioning should be assisted with laser guidance and pictorial guides. POTENTIAL FOR CDSS OR ARTIFICIAL INTELLIGENCE (AI)-ASSISTED CDSS CDSS and AI-assisted CDSS offer significant promise in assisting crew members with limited medical training. These systems could provide real-time feedback on image quality and interpretation, helping to mitigate the risks of human error during space missions. Integrating procedural guidance tools, such as virtual and augmented reality, will support crewmembers in accurately positioning patients and obtaining high-quality images. However, the success of such systems will depend on the development of robust training datasets, integration with spaceflight-rated hardware, and the medical decision-making capabilities of operators. FEASIBILITY OF GROUND INTERPRETATION AND DATA TRANSMISSION Reliance on ground-based interpretation may prove difficult for acute care during exploration class-missions due to delays in transmission with increasing distance from Earth or complete communication blackout periods. In such instances where immediate interpretation for clinical intervention is required, crew must be able to interpret the images independently or utilize AI-based assistance to do so. File sizes for XR exams can also be large if numerous images are acquired and bandwidth constraints may limit data transmissions for both radiography and ultrasound exams. FUTURE WORK AND INTEGRATION INTO THE EVIDENCE LIBRARY Future work proposes integrating miniature XR devices into NASA’s Evidence Library to address medical conditions identified as significant contributors to crew morbidity and mortality. The possibility of combining miniature XR with other imaging modalities, such as ultrasound devices, is also under investigation. In conclusion, while miniature XR technology holds potential for extraterrestrial medical systems, there are significant challenges to overcome. Training, integration of AI tools, dedicated exam protocols for microgravity, and improved data transmission systems will be key to realizing the full benefits of miniature XR technology in space.

A M Nelson↗

NASA NTRSDate not supplied

Rational Design of Nanoplasmonic Array Geometries for Biosensing

Background: Molecular diagnostics provide early and accurate diagnosis, which is essential for the prevention and treatment of infectious as well as chronic diseases. These tests are designed to detect disease-specific bioanalytes such as nucleic acid (DNA or RNA) or protein (antigens, antibodies) biomarkers. In the context of infectious disease diagnosis, nucleic acid-based detection methods are known to provide more specific and sensitive results. Here, the presence of a unique sequence belonging to the pathogenic genomic material is targeted to identify species, organism, genera and/or antimicrobial resistant gene markers. The majority of the common nucleic acid based diagnostic techniques require amplification (polymerase chain reaction, isothermal amplification etc.) of the pathogenic genetic material prior to detection impacting diagnostic speed, complexity, and cost thereby limiting ease of use. Thus, the development of simplified nucleic acid-based diagnostics that can be even used in resource-poor settings may hugely benefit patients across the globe. Nanopath is a molecular diagnostics company utilizing a solid-state nanosensor to enable sequence-specific detection of target nucleic acids without the need of amplification. These nanostructures enable ultra-sensitive biomarker detection using geometric, feature-dependent properties highly dependent on the local dielectric environment, allowing them to be sensitive to low concentration binding events. This paper describes an application of this approach to provide highly relevant clinical information within a single doctor’s office visit. Intro: The Nanopath team is in collaboration with NASA (National Aeronautics and Space Administration) and NIST (National Institute of Standards and Technology) to push the bounds of the fundamental physics associated with their biosensing platform. The ability of metals to support electromagnetic surface waves gives rise to surface plasmons when optically illuminated. This property, and its strong sensitivity to changes in the local refractive index, allows for the use of metal nanoparticles as ultra-sensitive transducers. In prior work by members of this team, ensembles of randomly oriented nanoparticles (i.e., colloidal nanorods dispersed on chip) were employed for sequence-specific nucleic acid sensing (1-3). While these particle sensors have the advantage of rapid fabrication, they suffer from low sensitivity and quality factor due to the random particle dispersity. In contrast, in this study we employ ordered array nanoparticle ensembles which can be used to improve sensor sensitivity and figure-of-merit. Study Methods Overview: In this talk, we detail the results of sensing experiments and computational simulations to outline a rational design of the structure of these plasmonic nanoparticle arrays for biomolecular sensing. Through simulation and experiment, we iteratively tailor nanostructure dimension to provide high quality signal and large resonance shifts upon modeled nucleic acid binding. In particular, full-wave electromagnetic simulations were conducted using Lumerical photonic simulation software in which periodic boundary conditions were applied in the x- and y- dimensions for each of the nanoplasmonic sensor geometries. To simulate the resonance response to changes in the bulk solution in contact with the sensor surface, the refractive index of the surrounding media was changed appropriately. Nucleic acid hybridization events were modeled using either using spherical structures approximating the relevant radius of genomic material as estimated by polymer models, or as conformal layers with the known refractive indices for nucleic acids. On the basis of initial simulations, nanosensors were fabricated using traditional electron-beam lithography protocols at NIST. To evaluate consensus between simulations and experiments, bulk sensing experiments were carried out in which the resonance peaks were obtained by submerging the sensors in refractive index standards. Key nanosensor characteristics including resonance peak locations, resonance peak shifts as a function of refractive index, and figure of merit (FOM) of extinction curves were examined between the experimental and simulation results prior to proceeding with simulations on additional geometries and more complex solution conditions, and further device fabrication. This iterative process is repeated toward a rational design of nanoplasmonic array geometries for biosensing optimizing response for targeted disease detection. In summary, this study puts forth a methodology for rational design and characterization of regularly spaced nanoparticle arrays for optics-based biosensing. The results of this study will allow for more informed design of nanostructure geometries towards sequence-specific nucleic acid detection. These improved designs have the potential to improve clinical sensitivity and limit-of-detection across disease indication.

sensor↗

DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗