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At least 361 records · Page 20

Portable Load Measurement Device for Use During ARED Exercise on ISS

The Advanced Resistive Exercise Device (ARED) (Fig.1) is unique countermeasure hardware available to crewmembers aboard the International Space Station (ISS) used for resistance exercise training to protect against bone and muscle loss during long duration space missions. ARED instrumentation system was designed to measure and record exercise load data, but: - Reliably accurate data has not been available due to a defective force platform. - No ARED data has been recorded since mid-2011 due to failures in the instrumentation power system. ARED load data supports on-going HRP funded research, and is available to extramural researchers through LSDA-Repository. Astronaut Strength, Conditioning, and Rehabilitation specialists (ASCRs) use ARED data to track training progress and advance exercise prescriptions. ARED load data is necessary to fulfill medical requirements. HRP directed task intends to reduce to program risk (HRP IRMA Risk 1735), and evaluate the XSENS ForceShoeTM as a means of obtaining ARED load data during exercise sessions. The XSENS ForceShoes"TM" will fly as a hardware demonstration to ISS in May 2014 (39S). Additional portable load monitoring devices (PLMDs) are under evaluation in the ExPC Lab. PLMDs are favored over platform redesign as they support future exploration needs.

Hanson, A.↗

Real-Time Health Monitoring for Gas Turbine Components Using Online Learning and High-Dimensional Data

Capital-intensive turbomachinery, such as gas turbines and combined cycle plants, are constantly being monitored for performance anomalies, faults, and physical degradation. Although these power-generating assets are equipped with hundreds of sensors, existing monitoring tools can only handle moderate-sized data. As a result, only a handful of aggregate metrics are used to monitor machine health. At the same time, developing advanced tools suitable for large datasets have been restricted by the lack of appropriate data. The objective of this proposal was to demonstrate a Big Data analytics framework for fault detection and diagnosis in gas turbine applications. We develop a predictive analytics framework methodology guided by these experimental data, industrial data from our collaborators, and physics-based models with engineering domain knowledge. Our analytics framework consists of four key components (1) a data curation process that addresses data storage, data quality assessments, and integrity checks, (2) a feature engineering component that utilizes statistical methods and transformation algorithms guided by physics-based models to extract high-fidelity fault features that can be leveraged for fault detection and classifying fault severities, (3) a Machine Learning-based fault detection and diagnostics algorithms for detecting operational and hardware faults in the combustion and the turbines section. We utilize two industry-class gas turbine component test rigs to generate first of its kind data for critical gas turbine faults with varying severity levels. Advanced gas turbine test facilities will be interrogated using state-of-the-art instrumentation techniques to build fault signatures and data trends for key combustor and turbine faults. Data generated from a combustor test rig (Georgia Tech) and a turbine test rig (Penn State) during both normal operation and with seeded faults serve as the basis for the Big Data sets. The test conditions in the two test facilities include common, critical events that occur in the operation. Utilizing the combustor test rig, we examine two common combustor faults: lean blowout and centerbody degradation. For the turbine section we develop analytic models for monitoring cooling faults in the gas turbine

03 NATURAL GAS↗

Real-Time Health Monitoring for Gas Turbine Components Using Online Learning and High-Dimensional Data (Final Report)

Capital-intensive turbomachinery, such as gas turbines and combined cycle plants, are constantly being monitored for performance anomalies, faults, and physical degradation. Although these power-generating assets are equipped with hundreds of sensors, existing monitoring tools can only handle moderate-sized data. As a result, only a handful of aggregate metrics are used to monitor machine health. At the same time, developing advanced tools suitable for large datasets have been restricted by the lack of appropriate data. The objective of this proposal was to demonstrate a Big Data analytics framework for fault detection and diagnosis in gas turbine applications. We develop a predictive analytics framework methodology guided by these experimental data, industrial data from our collaborators, and physics-based models with engineering domain knowledge. Our analytics framework consists of four key components: (1) a data curation process that addresses data storage, data quality assessments, and integrity checks, (2) a feature engineering component that utilizes statistical methods and transformation algorithms guided by physics-based models to extract high-fidelity fault features that can be leveraged for fault detection and classifying fault severities, (3) a Machine Learning-based fault detection and diagnostics algorithms for detecting operational and hardware faults in the combustion and the turbines section. We utilize two industry-class gas turbine component test rigs to generate first of its kind data for critical gas turbine faults with varying severity levels. Advanced gas turbine test facilities will be interrogated using state-of-the-art instrumentation techniques to build fault signatures and data trends for key combustor and turbine faults. Data generated from a combustor test rig (Georgia Tech) and a turbine test rig (Penn State) during both normal operation and with seeded faults serve as the basis for the Big Data sets. The test conditions in the two test facilities include common, critical events that occur in the operation. Utilizing the combustor test rig, we examine two common combustor faults: lean blowout and centerbody degradation. For the turbine section we develop analytic models for monitoring cooling faults in the gas turbine.

20 FOSSIL-FUELED POWER PLANTS↗

Robotics for HVAC applications: A critical review and future perspectives

Recent advances in artificial intelligence (AI), enhanced computational capabilities, and innovations in sensors and hardware have driven the increasing development and application of robots in heating, ventilation, and air conditioning (HVAC) systems. We selected and reviewed 101 studies published between 2005 and 2025, sourced from IEEE Xplore, Scopus, Web of Science, and the ACM Digital Library. To analyze these works, we developed a five-dimensional analytical framework (morphology, sensing, navigation, task execution, and system integration), inspired by the Springer Handbook of Robotics and tailored specifically for robotic applications in HVAC. Based on the reviewed studies, six distinct tasks spanning the entire HVAC lifecycle have been identified. Among the six tasks, inspection and maintenance dominate (59 %), followed by indoor monitoring and auditing (21 %), whereas leakage detection, comfort support, and installation/retrofit remain less explored. To address the identified gaps, this review proposes future research directions including investigating robot-aware HVAC design principles, developing multimodal HVAC sensing and data fusion techniques, enhancing robot training and hardware capabilities, and expanding robotic applications beyond Maintenance and Operations (M&O). The findings from this review inform future robotics research for HVAC applications and ultimately enhance system affordability, energy efficiency, resilience or reliability, and occupant environmental comfort. Moreover, it seeks to inspire researchers to explore the intersections of robotics, computer science, building science, and HVAC engineering fostering advancements in this multidisciplinary field.

AI↗

Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation

The author has identified the following significant results. A comprehensive review of ERTS-1 MSS color composite imagery, obtained during the autumnal and vernal phases over the Great Plains Corridor test sites, shows that temporal changes in rangeland vegetation can be manually interpreted. The degree to which manual interpretations can be made from the MSS color composites appears to be limited primarily by variations in image reproduction quality. The vernal advancement and other phenophase related phenomena are observable from cycle to cycle and within a single frame for rangeland vegetation. Vegetation changes due to environmental conditions among the test sites and among grazing treatments within test sites are readily observable. An investigation has been initiated which will evaluate band-to-band ratios as an index of rangeland vegetation condition. Data currently available from August 1972 through April 1973 for the five southern test sites are being used to characterize band-to-band ratios as a function of quantity and quality of rangeland vegetation at each of the test sites.

Rouse, J. W., Jr.↗

Embedding thermocouples in SS316 with laser powder bed fusion

Recent advances in manufacturing technologies have enabled the fabrication of complex geometries for a wide range of applications, including the energy, aerospace, and civil sectors. The ability to integrate sensors at critical locations within these complex components during the manufacturing process could benefit process monitoring and control by reducing reliance on models to relate surface measurements to internal phenomena. This study investigated embedding thermocouples in a SS316 matrix using laser powder bed fusion. Under optimal processing conditions, embedded thermocouples were characterized post-building, finding good bonding to the matrix with no melt pool penetration to the sensing elements. Futher, the embedded thermocouple performed similarly to an identical non-embedded thermocouple during thermal testing to 500 °C with only a slight difference in response time, which was attributed to the differences in mass and the associated thermal time constants.

image analysis↗

Optimizing infrasound observations for sample return capsule re-entry: Insights from OSIRIS-REx and Hayabusa2

The atmospheric entry of meteoroids presents a rare and unpredictable phenomenon, posing challenges for systematic observation and detailed characterization. Such events are nonetheless critical for advancing understanding of acoustic wave propagation, atmospheric structure, and entry dynamics. In contrast, sample return capsules (SRCs) from space missions follow well constrained re-entry trajectories, enabling planned observations of shock wave generation and propagation under controlled conditions. This study compares two SRC atmospheric entries, Hayabusa2 in 2020 and OSIRIS-REx in 2023, to assess how different infrasound array configurations influence shock wave detection and trajectory validation. Hayabusa2’s re-entry was monitored using a distributed network of 28 portable infrasound sensors across seven arrays in Woomera, Australia, permitting three-dimensional reconstruction of the trajectory and analysis of wave characteristics. For OSIRIS-REx, a compact four-sensor array deployed near Eureka Airport provided trajectory confirmation through arrival-time differences and back-azimuth estimates. Spectral and waveform analyses revealed differences in signal properties associated with variations in entry angle and velocity. The results illustrate both the strengths and the limitations of the deployed array configurations. The dense and distributed arrays during Hayabusa2’s re-entry enabled detailed trajectory reconstruction, whereas the compact array at Eureka primarily provided confirmation of signal coherence and back-azimuth consistency. These case studies highlight that even relatively small arrays, if located close to the predicted ground track, can still capture useful information on arrival direction and timing. Such insights provide practical guidance for planning future observational campaigns of SRC returns and other controlled atmospheric entries, and may also inform approaches to opportunistic observations of meteoroid events and other atmospheric acoustic phenomena.

celestial mechanics: orbit determination↗

Detection techniques for tenuous planetary atmospheres

The application of detectors developed for analysis of planetary atmospheres under partial vacuum conditions, and data obtained during dust charging studies to various industrial problems is summarized. A specialized apparatus for dust measurements on a planetary lander was designed with the capability of measuring ambient dust density as a function of particle size, as well as for observing the charge of the collected dust. the optical system operates on an intermittent basis and requires only low power. No radioactive source or delicate detection equipment is required. Advances in monitoring catalyst operation by means of exoelection emission are also reported.

Hoenig, S. A.↗

Assessing Options for Particulate Measurement Tools to Advance Wood Heaters (CRADA Final Report)

For approximately 40 years, particulate matter (PM) from residential wood heaters has been certified in North America using an EPA dilution tunnel with a filter-based gravimetric measurement. While reasonably repeatable, this approach reports only a single value for the entire burn sequence and does not provide information on PM at different points within the sequence, which would support improved wood heater designs. PM monitors that report with high time resolution offer a potential solution, but their performance for various types of heaters and across heater operating conditions has not been extensively evaluated. In this 18-month collaborative project, the Hearth, Patio & Barbecue Association (HPBA) and Lawrence Berkeley National Laboratory (LBNL) tested five continuous PM instruments spanning three measurement principles—light-scattering, inertial mass (TEOM), and triboelectric—against gravimetric and size-resolved references on three residential heater types (cordwood, catalytic cordwood, and pellet) across startup, high-burn, and low-burn operating phases.

42 ENGINEERING↗

Red and near-infrared sensor response to off-nadir viewing

It has first been intended to employ the Advanced Very High Resolution Radiometer (AVHRR) as a meteorological instrument to aid in detecting clouds and atmospheric temperature stratifications over large areas. However, more recently the satellite data have been used for monitoring large areas of vegetation with emphasis on the visible (VIS) and near-infrared (NIR) bands. The present investigation is concerned with the objective to model ranges in AVHRR VIS and NIR radiances and normalized differences expected under typical AVHRR viewing and illumination conditions. Atmospheric data sets reported by Dave (1978) and Dave and Braslau (1975) were used. It is shown that sensor response to atmospheric path length can be substantial for the AVHRR VIS and NIR channels and normalized difference (ND) values. However, errors can be minimized by high sun and clear atmosphere viewing.

Holben, B.↗

Preliminary flight results from the second U.S. Microgravity Payload (USMP-2)

The second U.S. Microgravity Payload (USMP-2) was flown on the Space Shuttle in March 1994. It carried four major microgravity experiments plus a sophisticated accelerometer system to record the microgravity environment during USMP-2 operations. The USMP program is designed to accommodate experiments requiring extensive resources short of a full Spacelab mission, and the experiments are remotely operated and monitored. Results are reviewed from the four experiments: the Advanced Automated Directional Solidification Facility (AADSF), the Isothermal Dendrite Growth Experiment (IDGE), the Materiel por Etude des Phenomenes Interessant la Soldification sur Terre et en Orbite (MEPHISTO), and the Critical Fluid Light Scattering Experiment (Zeno). AASDF grew what is expected to be the largest steady-state sample ever of HgCdTe during 240 hours of operation. IDGE provided 60 growth cycles over a wide range of supercooling conditions studying the dendritic solidification of succinonitrile. MEPHISTO achieved 55 melt-solidify cycles and grew over 1 m of Bi/Sn alloy. Zeno located the critical point temperature for liquid Xe to 0.00001 K. IDGE and Zeno also provided the most extensive demonstrations to date of telescience.

Curreri, Peter↗

Space Radiation Technologies for Human Missions beyond Low-Earth-Orbit

Ionizing radiation exposure is a pervasive occupational risk to astronauts and remains a major health risk associated with human exploration beyond low-Earth-orbit. Sustained lunar and Mars exploration crew will be at increased risk of radiogenic cancers and cardiovascular disease, as well as, the potential for in-mission performance decrements, immune system decrements, and late neurodegenerative conditions impacting crew health. Optimizing astronaut space radiation protection will incorporate both physical and biological radiological aspects and will implement protection strategies that span pre-mission, in-flight, and post mission timelines. Major facets of physical risk mitigation include accuracy in predicting the space radiation solar environment, monitoring environmental and human exposures, and minimizing exposure through vehicle shielding and design. Biological mitigation facets include understanding and predicting biological response to the space environment, developing advanced medical countermeasures, and identifying appropriate surveillance strategies to preserve long-term health. Coordinated investments in these major capability areas will support development of an integrated radiation protection solution to minimize astronaut risk for moon to Mars exploration missions.

Lisa C Simonsen↗

Potential Application of Airborne Passive Microwave Observations for Monitoring Inland Flooding Caused by Tropical Cyclones

Inland flooding from tropical cyclones can be a significant factor in storm-related deaths in the United States and other countries. Information collected during NASA tropical cyclone field studies suggest surface water and flooding induced by tropical cyclone precipitation can be detected and therefore monitored using passive microwave airborne radiometers. In particular, the 10.7 GHz frequency of the NASA Advanced Microwave Precipitation Radiometer (AMPR) flown on the NASA ER-2 has demonstrated high resolution detection of anomalous surface water and flooding in numerous situations. This presentation will highlight the analysis of three cases utilizing primarily satellite and airborne radiometer data. Radiometer data from the 1998 Third Convection and Moisture Experiment (CAMEX-3) are utilized to detect surface water during landfalling Hurricane Georges in both the Dominican Republic and Louisiana. A third case is landfalling Tropical Storm Gert in Eastern Mexico during the Tropical Cloud Systems and Processes (TCSP) experiment in 2005. AMPR data are compared to topographic data and vegetation indices to evaluate the significance of the surface water signature visible in the 10.7 GHz information. The results of this study suggest the benefit of an aircraft 10 GHz radiometer to provide real-time observations of surface water conditions as part of a multi-sensor flood monitoring network.

Hood, Robbie E.↗

Airspace Performance Observations of Scalable Autonomous Operations in a High Density Vertiplex Simulation

The National Aeronautics and Space Administration’s (NASA’s) High Density Vertiplex (HDV) subproject aims to develop and demonstrate progressive automation technologies that contribute to the Advanced Air Mobility (AAM) concept. Using Human-and-Hardware-In-TheLoop (HHITL) techniques, HDV demonstrates initial vertiport automation services at vertiports with increased air traffic volume in both simulated and live test environments. In 2023, the Scalable Autonomous Operations (SAO) simulation was conducted in which prototype vertiport, airspace, and ground control station technologies were assessed on technical performance. During the SAO simulation, an observational study captured an initial impression of the HDV airspace performance, potential disruptions to the airspace, and highlighted some capability and procedural gaps. Observations took place in two parts. In the first part, five scenario use cases (Nominal, Missed Approach, Speed Change, Divert, and MultiAircraft Divert) were conducted with three human operator roles (Vertiport Manager, Fleet Manager, and Ground Control Station Operator). Researchers collected metrics on throughput, closest point of approach, and airborne delay. In the second part of the study, the Missed Approach scenario was observed under three traffic density levels (20, 40, and 60 operations per hour) to challenge the automation to correctly identify slots in the vertiport arrival schedule. The results showed that the automation successfully found a slot for the Missed Approach vehicle in the 20 operations per hour condition, after some delay it found one in the 40 condition, and it did not find one in the 60 condition. The observations of technical and human performance throughout the five scenario use cases and the Missed Approach case study indicated that for HDV to increase traffic density and maintain or increase throughput, airspace monitoring services should be able to detect and resolve conflicts between aircraft. Furthermore, the roles and responsibilities of human operators need additional definition when it comes to responding to vehicle conflicts.

Advanced Air Mobility↗

Coupled Aerodynamic and Hydrodynamic Hybrid Simulation of Floating Offshore Wind Turbines

The development and innovation of floating offshore wind energy in the U.S. requires detailed high-fidelity observations and measurements of turbine and platform loading due to wind, waves, and currents. However, full-scale and quasi-full-scale experiments require significant financial and temporal investments for construction, experimental testing, and long-term field campaigns. To support the commercial advancement of the offshore wind energy industry, specialized wind tunnel and wave basin experimental facilities are critical to be able to test FOWT designs at small scale under controlled conditions prior to full-scale deployment. Oregon State University (OSU) is internationally known as a leader in water and energy research, development, and testing. The O.H. Hinsdale Wave Research Laboratory (HWRL) and the Wallace Energy Systems and Renewables Facility (WESRF) at OSU have extensive experience building, modeling, monitoring, controlling, and actuating scaled systems. Experiments on wave-structure interaction have been performed at the HWRL since its establishment in 1972. Studies have included the interaction of waves with coastal structures (breakwaters, seawalls, buildings, cylinders, bridges, fixed foundations of offshore wind turbines, etc.) and with floating structures (e.g., wave energy converters, maneuvering of vessels, etc.). Hinsdale is actively used by marine energy technology developers, both for private testing and OSU-collaborative research projects. However, despite the availability of several large-scale facilities for hydrodynamic testing (at OSU and elsewhere in the U.S.), existing experimental laboratories are generally limited in their ability to accurately generate combined wind and wave conditions. The simulation of both wind and waves in experimental testing is complicated due to a number of constraints, including: [i] incompatible similitude laws governing the wind and waves for scaled experiments, [ii] producing accurate wind over a large enough control volume via fans, and [iii] generating wind that reasonably represents the atmospheric boundary layer in existing wave basins/flumes. Hence, physical test data providing insight into the simultaneous wave- and wind-structure response of floating offshore wind components can be difficult to generate. Given the aforementioned challenges in classic hydrodynamic experiments, the motivation of this project is to establish a real-time hybrid simulation (RTHS) approach that can apply aero- and hydro-dynamic loading by augmenting wave-only experimental facilities with virtual aerodynamic forces through numerical models representing the remaining dynamic forces. RTHS is a physical-numerical approach that partitions a prototype system into physical and numerical sub-assemblies that interact with each other through actuators and sensors in real time. In coupling physical and numerical models, the hybrid simulation approach applied herein is ideal for problems with: (1) structures subjected to different scaling laws, such as floating offshore wind turbines subjected to combined aero/hydro-dynamic loading, (2) structures that are too large or complex to be tested entirely in a laboratory setting, such as deep-water mooring applications, and (3) component testing, where the behavior of a portion of the assembly is uncertain but still interacts with other portions of the structure, such as testing the fatigue life of turbine blades. Few U.S. experimental facilities are able to test simultaneous aero- and hydro-dynamic loading and none can accurately produce aero/hydro-dynamic response on scaled FOWT models due to conflicting similitude laws between the wind (commonly Reynolds) and the waves (commonly Froude). To aid in accelerating the development of the U.S. floating offshore industry, there is a significant need to develop a flexible, modular framework that can expand the capacities of existing wave-only laboratories. The project goal is to demonstrate a hydrodynamic real-time hybrid simulation (hydro-RTHS) framework that couples numerical wind and physical waves acting on a FOWT, thus representing simultaneous aero/hydro-dynamic loading. The FOWT is partitioned into a full-scale numerical sub-assembly associated with the aerodynamics and a model-scale physical sub-assembly associated with the hydrodynamics. The numerical-physical partition associated with hydro-RTHS mitigates scaling constraints by supplying different scaling laws to the physical and numerical sub-assemblies. Herein, length, force, and time are scaled and exchanged between the sub-assemblies using Froude scaling to represent the open-channel flow in the physical sub-assembly. Other similitude laws could also be utilized depending on the problem definition. It is envisioned that the ability to model FOWTs under waves and wind, with mitigation of similitude distortions, would result in reduced development costs (currently, FOWT concept development is performed with full-size pro- totypes at enormous expense and risk) and increase the reliability of the FOWT industry (since extreme wave and wind conditions and contingency events can be tested safely in a controlled environment).

16 TIDAL AND WAVE POWER↗

Flexible control techniques for a lunar base

The fundamental elements found in every terrestrial control system can be employed in all lunar applications. These elements include sensors which measure physical properties, controllers which acquire sensor data and calculate a control response, and actuators which apply the control output to the process. The unique characteristics of the lunar environment will certainly require the development of new control system technology. However, weightlessness, harsh atmospheric conditions, temperature extremes, and radiation hazards will most significantly impact the design of sensors and actuators. The controller and associated control algorithms, which are the most complex element of any control system, can be derived in their entirety from existing technology. Lunar process control applications -- ranging from small-scale research projects to full-scale processing plants -- will benefit greatly from the controller advances being developed today. In particular, new software technology aimed at commercial process monitoring and control applications will almost completely eliminate the need for custom programs and the lengthy development and testing cycle they require. The applicability of existing industrial software to lunar applications has other significant advantages in addition to cost and quality. This software is designed to run on standard hardware platforms and takes advantage of existing LAN and telecommunications technology. Further, in order to exploit the existing commercial market, the software is being designed to be implemented by users of all skill levels -- typically users who are familiar with their process, but not necessarily with software or control theory. This means that specialized technical support personnel will not need to be on-hand, and the associated costs are eliminated. Finally, the latest industrial software designed for the commercial market is extremely flexible, in order to fit the requirements of many types of processing applications with little or no customization. This means that lunar process control projects will not be delayed by unforeseen problems or last minute process modifications. The software will include all of the tools needed to adapt to virtually any changes. In contrast to other space programs which required the development of tremendous amounts of custom software, lunar-based processing facilities will benefit from the use of existing software technology which is being proven in commercial applications on Earth.

Kraus, Thomas W.↗

The Impact of Atmospheric InfraRed Sounder (AIRS) Profiles on Short-term Weather Forecasts

The Atmospheric Infrared Sounder (AIRS), together with the Advanced Microwave Sounding Unit (AMSU), represents one of the most advanced spacebased atmospheric sounding systems. The combined AlRS/AMSU system provides radiance measurements used to retrieve temperature profiles with an accuracy of 1 K over 1 km layers under both clear and partly cloudy conditions, while the accuracy of the derived humidity profiles is 15% in 2 km layers. Critical to the successful use of AIRS profiles for weather and climate studies is the use of profile quality indicators and error estimates provided with each profile Aside form monitoring changes in Earth's climate, one of the objectives of AIRS is to provide sounding information of sufficient accuracy such that the assimilation of the new observations, especially in data sparse region, will lead to an improvement in weather forecasts. The purpose of this paper is to describe a procedure to optimally assimilate highresolution AIRS profile data in a regional analysis/forecast model. The paper will focus on the impact of AIRS profiles on a rapidly developing east coast storm and will also discuss preliminary results for a 30-day forecast period, simulating a quasi-operation environment. Temperature and moisture profiles were obtained from the prototype version 5.0 EOS science team retrieval algorithm which includes explicit error information for each profile. The error profile information was used to select the highest quality temperature and moisture data for every profile location and pressure level for assimilation into the ARPS Data Analysis System (ADAS). The AIRS-enhanced analyses were used as initial fields for the Weather Research and Forecast (WRF) system used by the SPORT project for regional weather forecast studies. The ADASWRF system will be run on CONUS domain with an emphasis on the east coast. The preliminary assessment of the impact of the AIRS profiles will focus on quality control issues associated with AIRS, intelligent use of the quality indicators, and forecast verification.

Chou, Shih-Hung↗

High precision monitoring of outgassing species in model EUV photoresists with a cavity ring-down spectrometer

Extreme ultraviolet (EUV) photoresists play a pivotal role in advancing nanopatterning technologies by balancing image quality and sensitivity. The outgassing behavior of photoresist thin films under EUV and deep ultraviolet (DUV) exposure reveals chemical details relevant to their performance. This study focuses on utilizing an analytical technique not previously used in photolithography, the tabletop cavity ring-down spectrometer, to investigate outgassing dynamics in EUV photoresists, enabling precise chemical identification and deeper insights into resist processing. The spectrometer’s enhanced laser path length (~20 km) and broadband absorption capabilities in the CH overtone region allow for sensitive and temporally resolved detection of outgassed species. Using a model resist comprising a polymer matrix with a photoacid generator and quencher, we analyzed the influence of time delays between exposure and Post-Exposure Bake (PEB) as well as storage under varying environmental conditions. Suppression of isobutylene outgassing and thickness loss was observed with extended delays between exposure and PEB, potentially linked to water absorption and acid deactivation. The technique proved highly effective in distinguishing subtle chemical differences between processing stages. Delay times and their environmental conditions, particularly humidity, reduce outgassing and thickness loss of photoresists during PEB, suggesting decreased acid-driven deprotection. This can potentially impact sensitivity, defectivity, and roughness of resist patterns, necessitating precise monitoring and control.

Lüttgenau, Bernhard↗