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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Time-on-task decrements in "steer clear" performance of patients with sleep apnea and narcolepsy

Loss of attention with time-on-task reflects the increasing instability of the waking state during performance in experimentally induced sleepiness. To determine whether patients with disorders of excessive sleepiness also displayed time-on-task decrements indicative of wake state instability, visual sustained attention performance on "Steer Clear," a computerized simple RT driving simulation task, was compared among 31 patients with untreated sleep apnea, 16 patients with narcolepsy, and 14 healthy control subjects. Vigilance decrement functions were generated by analyzing the number of collisions in each of six four-minute periods of Steer Clear task performance in a mixed-model analysis of variance and linear regression equations. As expected, patients had more Steer Clear collisions than control subjects (p=0.006). However, the inter-subject variability in errors among the narcoleptic patients was four-fold that of the apnea patients, and 100-fold that of the controls volunteers; the variance in errors among untreated apnea patients was 27-times that of controls. The results of transformed collision data revealed main effects for group (p=0.006), time-on-task (p=0.001), and a significant interaction (p=0.022). Control subjects showed no clear evidence of increasing collision errors with time-on-task (adjusted R2=0.22), while apnea patients showed a trend toward vigilance decrement (adjusted R2=0.42, p=0.097), and narcolepsy patients evidenced a robust linear vigilance decrement (adjusted R2=0.87, p=0.004). The association of disorders of excessive somnolence with escalating time-on-task decrements makes it imperative that when assessment of neurobehavioral performance is conducted in patients, it involves task durations and analyses that will evaluate the underlying vulnerability of potentially sleepy patients to decrements over time in tasks that require sustained attention and timely responses, both of which are key components in safe driving performance.

NASA Discipline Space Human Factors↗
NASA NTRS2010

Analysis of Skeletal Muscle Metrics as Predictors of Functional Task Performance

PURPOSE: The ability to predict task performance using physiological performance metrics is vital to ensure that astronauts can execute their jobs safely and effectively. This investigation used a weighted suit to evaluate task performance at various ratios of strength, power, and endurance to body weight. METHODS: Twenty subjects completed muscle performance tests and functional tasks representative of those that would be required of astronauts during planetary exploration (see table for specific tests/tasks). Subjects performed functional tasks while wearing a weighted suit with additional loads ranging from 0-120% of initial body weight. Performance metrics were time to completion for all tasks except hatch opening, which consisted of total work. Task performance metrics were plotted against muscle metrics normalized to "body weight" (subject weight + external load; BW) for each trial. Fractional polynomial regression was used to model the relationship between muscle and task performance. CONCLUSION: LPMIF/BW is the best predictor of performance for predominantly lower-body tasks that are ambulatory and of short duration. LPMIF/BW is a very practical predictor of occupational task performance as it is quick and relatively safe to perform. Accordingly, bench press work best predicts hatch-opening work performance.

Ryder, Jeffrey W.↗
NASA NTRS2015

Visual Attention Allocation Between Robotic Arm and Environmental Process Control: Validating the STOM Task Switching Model

Fifty six participants time shared a spacecraft environmental control system task with a realistic space robotic arm control task in either a manual or highly automated version. The former could suffer minor failures, whose diagnosis and repair were supported by a decision aid. At the end of the experiment this decision aid unexpectedly failed. We measured visual attention allocation and switching between the two tasks, in each of the eight conditions formed by manual-automated arm X expected-unexpected failure X monitoring- failure management. We also used our multi-attribute task switching model, based on task attributes of priority interest, difficulty and salience that were self-rated by participants, to predict allocation. An un-weighted model based on attributes of difficulty, interest and salience accounted for 96 percent of the task allocation variance across the 8 different conditions. Task difficulty served as an attractor, with more difficult tasks increasing the tendency to stay on task.

STOM attention allocation model validation↗
NASA NTRSDate not supplied

Human Thermal Assessment of Traverse and Geology Task Iterations During Simulated Lunar Extravehicular Activity

Spacewalks or extravehicular activities (EVA) in microgravity are mentally and physically demanding. Current microgravity EVAs are predominantly focused on upper body tasks on engineered surfaces; however, the introduction of gravity means that crew members during future lunar EVAs will be required to perform tasks that generate full body workloads such as navigating natural lunar terrain while conducting geological sampling. To date, only 12 people have walked on the surface of the Moon resulting in limited knowledge of suited thermal regulation under lunar-relevant physical workloads. To address this gap, a study is underway to focus on spacesuit operations with simulated lunar EVA workloads. This study presents methodology for collecting standard thermal measures during suit testing. In this pilot study, two suited subjects underwent simulated lunar EVAs using the NASA Active Response Gravity Offload System (ARGOS) to simulate the effects of partial gravity. Each lunar EVA, lasting three to five hours, included various metabolically demanding EVA tasks. Subjects donned the NASA Mark III (MK III) space suit and were offloaded to 1/6th G (lunar gravity). A subset task circuit from one of these simulations replicated an EVA traverse to a lunar crater, taking a geological sample, and returning to base. The suited subject walked one 1500 m (0% grade) and three 500 m traverses at three different grades (10, 20, 30%). Between each traverse, subjects performed geology sampling tasks (0 and 10% grade). Thermal measurements included core and skin temperature, liquid cooling garment (LCG) inlet and outlet temperature, and spacesuit gas inlet and outlet temperature and humidity. Compared to baseline core temperature (S1 = 37.07±0.32 °C, S2 = 37.27±0.01 °C) and mean skin temperature (S1 = 32.38±0.34 °C, S2 = 33.62±0.03 °C), after a 1500 m traverse, each suited subject showed an increased core temperature (S1 = 37.23±0.12 °C, S2 = 37.41±0.11°C) and decreased mean skin temperature (S1 = 32.16±0.17 °C, S2 = 31.53±1.15 °C) at a delta LCG temperature (S1 = 1.86±0.24 °C, S2 = 2.20±0.76 °C) and delta suit humidity (S1 = 9.66±1.49 %, S2 = 11.50±1.58 %). Core temperature continued to increase from compounding traverse and geology tasks (S1 = 38.04±0.03 °C, S2 = 38.1±0.02 °C) accompanied by an increase in delta LCG temperature (S1 = 2.24±0.13 °C, S2 = 2.67±0.12 °C) and delta suit humidity (S1 = 28±2.42 %, S2 = 31±2.13 %). Conversely, as the circuit progressed, mean skin temperature continued to decrease due to sustained LCG heat rejection (S1 = 30.08±0.15 °C, S2 = 30.28±0.07 °C). During the simulated EVA circuit core temperature increased to elevated values and remained elevated as heat was retained while mean skin temperature decreased due to peripheral heat offloaded to the LCG. The thermal measures collected during this study provided critical heat loading dynamics during lunar EVA tasks. Including core and skin temperatures along with suited thermal measures provides a standard data collection scheme for human thermal metrics during EVA task management. Data collected in this configuration can be used to build future lunar EVA task circuits and human thermal predictions.

Bradley Hoffmann↗
NASA NTRSDate not supplied

Validation of Fitness for Duty Standards Using Pre- and Post-Flight Capsule Egress and Suited Functional Performance Tasks in Simulated Reduced Gravity

The transition between gravity environments will involve one of the most complex, high-risk phases of any mission. For example, the reduced functional capacity caused by physiological deconditioning adaptations in microgravity coupled with the stressors of re-entry into partial gravity environments will increase risks to crew, even with rigorous adherence to inflight countermeasures. Quantification of the astronauts’ post-landing functional performance is necessary to design ConOps for exploration missions. Specifically, these two high-risk scenarios may be required to be performed soon after gravity transitions: • Nominal and/or emergency unassisted capsule egress task after return to Earth • Planetary extravehicular activity (EVA) soon after landing on Mars or the Moon This study is broken down into two phases. Phase 1: A feasibility study that will assess the overall feasibility and demonstrate the capability to do these tasks shortly after landing. Phase 2: the full Egress Fitness study, which is part of the CIPHER complement. This study uses a task-based approach to characterize functional performance of these high-risk scenarios in long-duration ISS crewmembers before flight and shortly after return to Earth. Prior to any testing, each astronaut subject completes a suit fit check to ensure adequate sizing and a mobility assessment to confirm completion of the EVA tasks. Pilot Egress Fitness pre-flight and post-flight testing includes an Earth-based emergency egress out of a functional capsule mockup and a short Mars gravity EVA simulation including suit donning, hatch egress, ladder descent, task board cable operations, baggage transfer over sand/rocky regolith, alignment with a rear entry port, and suit egress. Pre-flight testing will occur at any time point prior to flight. Post-flight assessment is much more critical with the capsule egress test that will occur 1–4 hours after landing and the planetary EVA approximately 18–36 hours after landing. The CIPHER study will incorporate additional pre-flight sessions, longer EVA tasks that include traverse and geology sampling, and post-flight sessions on R+1, 4, and 8 to characterize the timeframe of recovery. Data collected for both tasks include task completion time, photo, and video. The EVA portion also includes collection of metabolic and heart rate. Pilot Egress Fitness study has completed both baseline and post-flight testing on four astronaut subjects, with all four able to complete post-flight EVA testing and three able to complete postflight capsule egress testing. Preliminary results observe individual physiological variations, which were to be expected but also suggest the need to carefully track the timeline from undock to landing to testing. Furthermore, some task performance instructions and equipment may need to be adjusted to ensure results are primarily physiological. These and other lessons learned will be addressed with minor protocol changes in the full CIPHER Egress Fitness study.

J R Norcross↗
DOE OSTI2019

Temperature-aware task scheduling and proactive power management

Systems, apparatuses, and methods for performing temperature-aware task scheduling and proactive power management. A SoC includes a plurality of processing units and a task queue storing pending tasks. The SoC calculates a thermal metric for each pending task to predict an amount of heat the pending task will generate. The SoC also determines a thermal gradient for each processing unit to predict a rate at which the processing unit's temperature will change when executing a task. The SoC also monitors a thermal margin of how far each processing unit is from reaching its thermal limit. The SoC minimizes non-uniform heat generation on the SoC by scheduling pending tasks from the task queue to the processing units based on the thermal metrics for the pending tasks, the thermal gradients of each processing unit, and the thermal margin available on each processing unit.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Fault-tolerant dynamic task graph scheduling

In this paper, we present an approach to fault tolerant execution of dynamic task graphs scheduled using work stealing. In particular, we focus on selective and localized recovery of tasks in the presence of soft faults. We elicit from the user the basic task graph structure in terms of successor and predecessor relationships. The work stealing-based algorithm to schedule such a task graph is augmented to enable recovery when the data and meta-data associated with a task get corrupted. We use this redundancy, and the knowledge of the task graph structure, to selectively recover from faults with low space and time overheads. We show that the fault tolerant design retains the essential properties of the underlying work stealing-based task scheduling algorithm, and that the fault tolerant execution is asymptotically optimal when task re-execution is taken into account. Experimental evaluation demonstrates the low cost of recovery under various fault scenarios.

fault tolerance↗
NASA NTRS1996

Effects of adaptive task allocation on monitoring of automated systems

The effects of adaptive task allocation on monitoring for automation failure during multitask flight simulation were examined. Participants monitored an automated engine status task while simultaneously performing tracking and fuel management tasks over three 30-min sessions. Two methods of adaptive task allocation, both involving temporary return of the automated engine status task to the human operator ("human control"), were examined as a possible countermeasure to monitoring inefficiency. For the model-based adaptive group, the engine status task was allocated to all participants in the middle of the second session for 10 min, following which it was again returned to automation control. The same occurred for the performance-based adaptive group, but only if an individual participant's monitoring performance up to that point did not meet a specified criterion. For the nonadaptive control groups, the engine status task remained automated throughout the experiment. All groups had low probabilities of detection of automation failures for the first 40 min spent with automation. However, following the 10-min intervening period of human control, both adaptive groups detected significantly more automation failures during the subsequent blocks under automation control. The results show that adaptive task allocation can enhance monitoring of automated systems. Both model-based and performance-based allocation improved monitoring of automation. Implications for the design of automated systems are discussed.

Task Performance and Analysis↗
DOE OSTI2016

TH-CD-207B-09: Task-Driven Fluence Field Modulation Design for Model-Based Iterative Reconstruction in CT

Purpose: There has been increasing interest in integrating fluence field modulation (FFM) devices with diagnostic CT scanners for dose reduction purposes. Conventional FFM strategies, however, are often either based on heuristics or the analysis of filtered-backprojection (FBP) performance. This work investigates a prospective task-driven optimization of FFM for model-based iterative reconstruction (MBIR) in order to improve imaging performance at the same total dose as conventional strategies. Methods: The task-driven optimization framework utilizes an ultra-low dose 3D scout as a patient-specific anatomical model and a mathematical formation of the imaging task. The MBIR method investigated is quadratically penalized-likelihood reconstruction. The FFM objective function uses detectability index, d’, computed as a function of the predicted spatial resolution and noise in the image. To optimize performance throughout the object, a maxi-min objective was adopted where the minimum d’ over multiple locations is maximized. To reduce the dimensionality of the problem, FFM is parameterized as a linear combination of 2D Gaussian basis functions over horizontal detector pixels and projection angles. The coefficients of these bases are found using the covariance matrix adaptation evolution strategy (CMA-ES) algorithm. The task-driven design was compared with three other strategies proposed for FBP reconstruction for a calcification cluster discrimination task in an abdomen phantom. Results: The task-driven optimization yielded FFM that was significantly different from those designed for FBP. Comparing all four strategies, the task-based design achieved the highest minimum d’ with an 8–48% improvement, consistent with the maxi-min objective. In addition, d’ was improved to a greater extent over a larger area within the entire phantom. Conclusion: Results from this investigation suggests the need to re-evaluate conventional FFM strategies for MBIR. The task-based optimization framework provides a promising approach that maximizes imaging performance under the same total dose constraint.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Exploiting Vector and Multicore Parallelsim for Recursive, Data- and Task-Parallel Programs

Modern hardware contains parallel execution resources that are well-suited for data-parallelism-vector units-and task parallelism-multicores. However, most work on parallel scheduling focuses on one type of hardware or the other. In this work, we present a scheduling framework that allows for a unified treatment of task- and data-parallelism. Our key insight is an abstraction, task blocks, that uniformly handles data-parallel iterations and task-parallel tasks, allowing them to be scheduled on vector units or executed independently as multicores. Our framework allows us to define schedulers that can dynamically select between executing task- blocks on vector units or multicores. We show that these schedulers are asymptotically optimal, and deliver the maximum amount of parallelism available in computation trees. To evaluate our schedulers, we develop program transformations that can convert mixed data- and task-parallel pro- grams into task block-based programs. Using a prototype instantiation of our scheduling framework, we show that, on an 8-core system, we can simultaneously exploit vector and multicore parallelism to achieve 14×-108× speedup over sequential baselines.

Ren, Bin↗
DOE OSTI2017

Synthetic Proxy Infrastructure for Task Evaluation

The Synthetic Proxy Infrastructure for Task Evaluation is a proxy application designed to support application developers in gauging the performance of various task granularities when determining how best to utilize task based programming models.The infrastructure is designed to provide examples of common communication patterns with a synthetic workload intended to provide performance data to evaluate programming model and platform overheads for the purpose of determining task granularity for task decomposition purposes. This is presented as a reference implementation of a proxy application with run-time configurable input and output task dependencies ranging from an embarrassingly parallel scenario to patterns with stencil-like dependencies upon their nearest neighbors. Once all, if any, inputs are satisfied each task will execute a synthetic workload (a simple DGEMM of in this case) of varying size and output all, if any, outputs to the next tasks.The intent is for this reference implementation to be implemented as a proxy app in different programming models so as to provide the same infrastructure and to allow for application developers to simulate their own communication needs to assist in task decomposition under various models on a given platform.

Junghans, Christoph↗
DOE OSTI2023

Iterative multi-task learning and inference from seismic images

Seismic interpretation aims to extract quantitative and interpretable attributes from a seismic image produced using some migration method to inform characteristics of a subsurface reservoir or target of interest. Current paradigms for computing seismic attributes mostly rely on single-task algorithms. We develop an iterative, multi-task machine learning method to learn and infer multiple attributes from a seismic image. This method is composed of two stages: a multi-task inference stage and a multi-modal, multi-task refinement stage. The basic mechanism of this method is that we train a multi-task inference neural network (NN) to estimate a set of attributes, including a relative geological time (RGT), a denoised higher-resolution (DHR) seismic image, and multiple fault attributes (including probability, dip, and strike), from a low-resolution, noisy seismic image; then we input the inferred attributes to a multi-task refinement NN to enhance the raw inference results iteratively. The two multi-task NNs are trained separately based on synthetic seismic images and associated attributes generated by a geological modeling algorithm. The software we intend to release is a PyTorch implementation of this multi-task learning method for both 2D and 3D cases along with scripts to run the training/validation. The algorithm and software can be a useful tool for automatic seismic interpretation.

Gao, Kai↗
DOE OSTI2022

Occupational Experience Effects on Physiological and Perceptual Responses of Common Soldiering Tasks

Abstract Cohen BS, Redmond JE, Haven CC, Foulis SA, Canino MC, Frykman PN, Sharp MA. Occupational Experience Effects on Physiological and Perceptual Responses of Common Soldiering Tasks. J Strength Cond Res 37(4): 894–901, 2023—This study measured the impact of occupational experience (i.e., time spent deployed, in military service, and in job and task performance frequency in training, deployment, and study practice) on the physiological (heart rate [HR] and oxygen consumption [VO 2 ]) and perceptual (rate of perceived exertion [RPE]) responses to performance of critical physically demanding tasks (CPDTs). Five CPDTs (road march, build a fighting position, move under fire, evacuate a casualty, and drag a casualty to safety), common to all soldiers, were performed by 237 active duty soldiers. Linear regression models examined the association between measures of experience and physiological and perceptual performance responses to task demands. The level of significance was adjusted for multiple comparisons and set at ρ ≤ 0.0125 for this study. Significant and notable effect sizes included the impact of time spent deployed on the physiological measures of the road march (PostHR F = 24.84, p < 0.0001, β=-9.65), sandbag fill (PostHR F = 8.26, p = 0.005, β = −2.83), and sandbag carry (MeanHR F = 7.51, p = 0.007, β = −1.12; PostHR F = 7.35, p = 0.007, β = −0.87). For the road march task, there was a nearly 10 bpm decrease in postperformance HR for every year spent deployed. Road march, sandbag fill, and sandbag carry tasks PostHRs were also notably negatively associated with the experience measures of time in their MOS (job and time in military service but not for other physiological and perceptual responses, including VO 2 and RPE. Frequency of task performance in training, deployment, and study practice was not meaningfully associated with experience. The results suggest that increasing task familiarization through on-the-job occupational operational experience may result in greater proficiency and reduced physiological effort.

Sport Sciences↗
DOE OSTI2016

Status Report on Activities of the Systems Assessment Task Force, OECD-NEA Expert Group on Accident Tolerant Fuels for LWRs

The Organization for Economic Cooperation and Development /Nuclear Energy Agency (OECD/NEA) Nuclear Science Committee approved the formation of an Expert Group on Accident Tolerant Fuel (ATF) for LWRs (EGATFL) in 2014. Chaired by Kemal Pasamehmetoglu, INL Associate Laboratory Director for Nuclear Science and Technology, the mandate for the EGATFL defines work under three task forces: (1) Systems Assessment, (2) Cladding and Core Materials, and (3) Fuel Concepts. Scope for the Systems Assessment task force (TF1) includes definition of evaluation metrics for ATF, technology readiness level definition, definition of illustrative scenarios for ATF evaluation, and identification of fuel performance and system codes applicable to ATF evaluation. The Cladding and Core Materials (TF2) and Fuel Concepts (TF3) task forces will identify gaps and needs for modeling and experimental demonstration; define key properties of interest; identify the data necessary to perform concept evaluation under normal conditions and illustrative scenarios; identify available infrastructure (internationally) to support experimental needs; and make recommendations on priorities. Where possible, considering proprietary and other export restrictions (e.g., International Traffic in Arms Regulations), the Expert Group will facilitate the sharing of data and lessons learned across the international group membership. The Systems Assessment task force is chaired by Shannon Bragg-Sitton (Idaho National Laboratory [INL], U.S.), the Cladding Task Force is chaired by Marie Moatti (Electricite de France [EdF], France), and the Fuels Task Force is chaired by a Masaki Kurata (Japan Atomic Energy Agency [JAEA], Japan). The original Expert Group mandate was established for June 2014 to June 2016. In April 2016 the Expert Group voted to extend the mandate one additional year to June 2017 in order to complete the task force deliverables; this request was subsequently approved by the Nuclear Science Committee. This report provides an update on the status Systems Assessment Task Force activities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Hierarchical Task-Data Parallelism using Kokkos and Qthreads

This report describes a new capability for hierarchical task-data parallelism using Sandia's Kokkos and Qthreads, and evaluation of this capability with sparse matrix Cholesky factorization and social network triangle enumeration mini-applications. Hierarchical task-data parallelism consists of a collection of tasks with executes-after dependences where each task contains data parallel operations performed on a team of hardware threads. The collection of tasks and dependences form a directed acyclic graph of tasks - a task DAG. Major challenges of this research and development effort include: portability and performance across multicore CPU; manycore Intel Xeon Phi, and NVIDIA GPU architectures; scalability with respect to hardware concurrency and size of the task DAG; and usability of the application programmer interface (API).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

DECOVALEX-2023: Task F2 Salt Final Report

The subject of Task F of DECOVALEX-2023 concerns performance assessment modelling of radioactive waste disposal in deep mined repositories. The primary objectives of Task F are to build confidence in the models, methods, and software used for performance assessment (PA) of deep geologic nuclear waste repositories, and/or to bring to the fore additional research and development needed to improve PA methodologies. In Task F2- (salt), these objectives have been accomplished through staged development and comparison of the models and methods used by participating teams in their PA frameworks. Coupled-process submodels and deterministic simulations of the entire PA model for a reference scenario for waste disposal in domal salt have been conducted. The task specification has been updated continuously since the initiation of the project to reflect the staged development of the conceptual repository model and performance metrics. Thermal, hydrological, mechanical, and chemical properties of individual components of the engineered and natural system were chosen for relevance by participating teams. The salt reference case system was characterized using data and measurements collected at relevant underground research laboratories (URLs), field sites, and simulation results from teams with specialized modelling capability. Participating teams made a wide range of model assumptions from compartmentalized networks to full 3D models of the salt formation. No single contributed model includes full-fidelity representation of all the features, events, and processes (FEPs) detailed in the task specification, but almost all features and processes are represented in at least one model. Despite differences in the modelling strategies developed by participating teams, all models indicate that salt compaction and radionuclide diffusion are key processes in the repository, and for the FEPs and model scenario considered, little of the disposed radionuclides will migrate beyond the repository seal over the 100,000 year simulations. In general, the model output quantities have the largest differences over the short term and near the waste. The models tend to be more similar further from waste and at later time. Disparities between the models are believed to be due to differing simplifications from the task specification, some of which are chosen simplifications to reduce complexity, and some are restrictions imposed by the modelling tools. A second round of this task has been accepted for DECOVALEX-2027 in conjunction with Task F1 on crystalline PA modelling. The future round includes waste package heating, improved modelling of salt creep closure, additional comparisons of coupled-process sub-models, and the impact of repository engineering design on radionuclide migration in the repository. Participants will also propose and finalize a set of uncertain inputs for the reference case simulations, propagate these uncertainties in a set of realizations, and conduct sensitivity analyses on the simulation results.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Molecular To Mesoscale Targeting of Oxoanions with Multi-Tasking Hosts

Achieving a better understanding of anion interactions both in solution and crystalline state was the overarching goal of this project. Anions are everywhere throughout Nature and play important roles in biological and environmental processes. They can be beneficial or deleterious or both in different situations and concentrations. For either reason it is important to have molecules that can bind anions for key needs that benefit society. However, recognition of specific anions is challenging due to the diffuse nature of their negative charge(s) as well as their various shapes and sizes. Understanding the basic properties of anions and how they interact with other molecules and ions in surrounding environments is key to selective recognition. In this project multi-tasking molecules for selective binding of targeted anions were designed to achieve cooperativity and synergism in one rather than multiple host molecules, including (1) cation:anion pair hosts for anions with charges of -2 or greater; (2) pH and redox activated hosts for on-off binding and release; and (3) multiple anion capture in extended host networks. Our design strategy was to combine the use of simple inexpensive building blocks and high yield synthetic pathways to provide economically feasible scale-up for applications. Oxoanions representing multiple shapes and charges were chosen based on having the potential for significant impact on DOE separations needs. Amide/amine-based macrocycles and urea/amine-based chelates and macrocycles with multiple hydrogen bonding sites provided the basic anion-binding frameworks. Successful multi-tasking outcomes were forthcoming in all three tasks. In Task 1, successful ion pair binding for anions with multiple charges was achieved. Furthermore, the ion pair molecules were capable of extended interactions through supramolecular intertwining, like fishing nets for capturing pools of fish (also fitting with Task 3). In Task 2, molecules were synthesized possessing on-off switches. These included a pH sensitive sensor for on-off binding of anions in general, as well as an electrochemical sensor selective for sulfate capture. Three new classes of extended anion host networks capable of binding multiple ions was a major outcome of Task 3. These systems included: anion sensitive, fluorescent organogels; channel-forming macrocycles for studying anion-water including larger macrocyclic cluster sandwiches; and, the offshoot of Task 1, fishing net ion-pair networks for higher valent anions. These strategies can be expanded in the future to other ions and molecules for a better understanding of intermolecular and interionic interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1973

Life sciences payload definition and integration study, task C and D. Volume 2: Payload definition, integration, and planning studies

The Life Sciences Payload Definition and Integration Study was composed of four major tasks. Tasks A and B, the laboratory definition phase, were the subject of prior NASA study. The laboratory definition phase included the establishment of research functions, equipment definitions, and conceptual baseline laboratory designs. These baseline laboratories were designated as Maxi-Nom, Mini-30, and Mini-7. The outputs of Tasks A and B were used by the NASA Life Sciences Payload Integration Team to establish guidelines for Tasks C and D, the laboratory integration phase of the study. A brief review of Tasks A and B is presented provide background continuity. The tasks C and D effort is the subject of this report. The Task C effort stressed the integration of the NASA selected laboratory designs with the shuttle sortie module. The Task D effort updated and developed costs that could be used by NASA for preliminary program planning.

Source record↗