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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,783 records · Page 99
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Three Dimensional Dynamics and Fluctuations of DNA-Nanogold Dimers by Individual-Particle Electron Tomography

Over time, organic-inorganic hybridized nanocrystals have been proven as an important additional tool for addressing many emerging challenges biological and material sciences. Nanogold and quantum dot conjugates have been used extensively as biomolecular markers, while DNA base pairing has directed the self-assembly of discrete groupings and arrays of organic and inorganic nanocrystals in formation of a network solid for electronic devices and memory components. The control of DNA-mediated assembly depends crucially upon the ability to exposure three-dimensional (3D) structure of DNA-nanocrystals hybridized building blocks. Current techniques limit in structure determination of flexible and heterogeneous sample. Here, we employed the electron tomography and negative-staining techniques to investigate the 3D structure of DNA-nanogold dimers that were self-assembled from a mixture of an 84-base-pair double-stranded DNA (dsDNA) conjugated with two 5-nm nanogold particles. We reconstructed a total of 14 electron density maps at a resolution of ~2 nm from each individual dsDNA-nanogold particle using the individual-particle electron tomography (IPET) reconstruction method. Using these 3D density maps as constrain, we projected a standard flexible DNA model onto the observed EM density maps and derived 14 conformations of dsDNA by molecular dynamics simulations. By aligning these structures from one distal end nanogold, the distribution showed the DNA fluctuation and flexibility between nanogolds, which providing a blueprint research for studying of DNA-mediated assembly of complex inorganic nanostructures.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

Solubility-limited depolymerization kinetics in the glycolysis of carbonyl-containing polymers

Chemical recycling of condensation polymers is often rationalized on the basis of the intrinsic reactivity of ester and carbonate functional groups. However, under heterogeneous conditions relevant to plastic waste processing and environmental degradation, bulk depolymerization rates often diverge from trends predicted by homogeneous chemistry. Here, we investigate how polymer–solvent compatibility, catalyst strength, and phase behavior govern the heterogeneous glycolysis of carbonyl-containing polymers. Using poly(ethylene terephthalate) (PET), glycol-modified PET (PETG), and bisphenol-A polycarbonate (PC) as model systems, we examine depolymerization kinetics at 180 °C with ethylene glycol and bisphenol A as diols under both amphoteric organosalt (TBD : MSA) and strong base (TBD) catalysis. Despite substantial differences in crystallinity and glycol uptake, PET and PETG depolymerize at comparable rates under organosalt catalysis, while PC depolymerizes significantly more slowly under identical conditions. Time-resolved molecular weight analysis and thermal characterization demonstrate that these rate differences do not arise from crystallinity, swelling, or inherent carbonyl reactivity, but instead reflect solubility-limited kinetics that constrain the transition from heterogeneous to homogeneous reaction regimes. When polymer solubility is low, depolymerization remains heterogeneous and slow; when solubility is enhanced—either through increased polymer–diol compatibility or stronger base catalysis—rapid homogeneous depolymerization is observed, reversing apparent reactivity trends. These results establish solubility and phase behavior as primary determinants of depolymerization kinetics in heterogeneous polymer recycling systems. By demonstrating how catalyst selection and solvent compatibility can expose or overcome solubility limitations, this work provides mechanistic insight to design more energy-efficient and selective chemical recycling processes. More broadly, these findings suggest that polymers with limited solvent or water compatibility may resist chemical degradation in the environment, favoring fragmentation and persistence as micro- and nanoplastics. Understanding solubility-controlled depolymerization offers a pathway toward more sustainable polymer design and end-of-life chemical recovery.

Watson-Sanders, Shelby [Department of Chemistry, U↗
DOE OSTI2014

Graphene nanopore field effect transistors

Graphene holds great promise for replacing conventional Si material in field effect transistors (FETs) due to its high carrier mobility. Previously proposed graphene FETs either suffer from low ON-state current resulting from constrained channel width or require complex fabrication processes for edge-defecting or doping. Here, we propose an alternative graphene FET structure created on intrinsic metallic armchair-edged graphene nanoribbons with uniform width, where the channel region is made semiconducting by drilling a pore in the interior, and the two ends of the nanoribbon act naturally as connecting electrodes. The proposed GNP-FETs have high ON-state currents due to seamless atomic interface between the channel and electrodes and are able to be created with arbitrarily wide ribbons. In addition, the performance of GNP-FETs can be tuned by varying pore size and ribbon width. As a result, their performance and fabrication process are more predictable and controllable in comparison to schemes based on edge-defects and doping. Using first-principle transport calculations, we show that GNP-FETs can achieve competitive leakage current of ∼70 pA, subthreshold swing of ∼60 mV/decade, and significantly improved On/Off current ratios on the order of 10{sup 5} as compared with other forms of graphene FETs.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
NASA NTRS2012

Joint Chance-Constrained Dynamic Programming

This paper presents a novel dynamic programming algorithm with a joint chance constraint, which explicitly bounds the risk of failure in order to maintain the state within a specified feasible region. A joint chance constraint cannot be handled by existing constrained dynamic programming approaches since their application is limited to constraints in the same form as the cost function, that is, an expectation over a sum of one-stage costs. We overcome this challenge by reformulating the joint chance constraint into a constraint on an expectation over a sum of indicator functions, which can be incorporated into the cost function by dualizing the optimization problem. As a result, the primal variables can be optimized by a standard dynamic programming, while the dual variable is optimized by a root-finding algorithm that converges exponentially. Error bounds on the primal and dual objective values are rigorously derived. We demonstrate the algorithm on a path planning problem, as well as an optimal control problem for Mars entry, descent and landing. The simulations are conducted using a real terrain data of Mars, with four million discrete states at each time step.

Ono, Masahiro↗
DOE OSTI2018

DeStager: feature guided in-situ data management in distributed deep memory hierarchies

In-situ analytics have been increasingly adopted by leadership scientific applications to gain fast insights into massive output data of simulations. With the current practice, systems buffer the output data in DRAM for analytics processing, constraining it to DRAM capacity un-used by the simulation. The rapid growth of data size requires alternative approaches to accommodating data-rich analytics, such as using solid-state disks to increase effective memory capacity. For this purpose, this paper explores software solutions for exploring the deep memory hierarchies expected on future high-end machines. Leveraging the fact that many analytics are sensitive to data features (regions-of-interest) hidden in the data being processed, the approach incorporates the knowledge of the data features into in-situ data management. It uses adaptive index creation/refinement to reduce the overhead of index management. In addition, it uses data features to predict data skew and improve load balance through controlling data distribution and placement on distributed staging servers. The experimental results show that such feature-guided optimizations achieve substantial improvements over state-of-the-art approaches for managing output data in-situ.

Computer Science↗
DOE OSTI2012

STRONG TIDAL DISSIPATION IN SATURN AND CONSTRAINTS ON ENCELADUS' THERMAL STATE FROM ASTROMETRY

Tidal interactions between Saturn and its satellites play a crucial role in both the orbital migration of the satellites and the heating of their interiors. Therefore, constraining the tidal dissipation of Saturn (here the ratio k{sub 2}/Q) opens the door to the past evolution of the whole system. If Saturn's tidal ratio can be determined at different frequencies, it may also be possible to constrain the giant planet's interior structure, which is still uncertain. Here, we try to determine Saturn's tidal ratio through its current effect on the orbits of the main moons, using astrometric data spanning more than a century. We find an intense tidal dissipation (k{sub 2}/Q = (2.3 {+-} 0.7) Multiplication-Sign 10{sup -4}), which is about 10 times higher than the usual value estimated from theoretical arguments. As a consequence, eccentricity equilibrium for Enceladus can now account for the huge heat emitted from Enceladus' south pole. Moreover, the measured k{sub 2}/Q is found to be poorly sensitive to the tidal frequency, on the short frequency interval considered. This suggests that Saturn's dissipation may not be controlled by turbulent friction in the fluid envelope as commonly believed. If correct, the large tidal expansion of the moon orbits due to this strong Saturnian dissipation would be inconsistent with the moon formations 4.5 Byr ago above the synchronous orbit in the Saturnian subnebulae. But it would be compatible with a new model of satellite formation in which the Saturnian satellites formed possibly over a longer timescale at the outer edge of the main rings. In an attempt to take into account possible significant torques exerted by the rings on Mimas, we fitted a constant rate da/dt on Mimas' semi-major axis as well. We obtained an unexpected large acceleration related to a negative value of da/dt = -(15.7 {+-} 4.4) Multiplication-Sign 10{sup -15} AU day{sup -1}. Such acceleration is about an order of magnitude larger than the tidal deceleration rates observed for the other moons. If not coming from an astrometric artifact associated with the proximity of Saturn's halo, such orbital decay may have significant implications on the Saturn's rings.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2012

New Approaches to Quantifying Transport Model Error in Atmospheric CO2 Simulations

In recent years, much progress has been made in observing CO2 distributions from space. However, the use of these observations to infer source/sink distributions in inversion studies continues to be complicated by difficulty in quantifying atmospheric transport model errors. We will present results from several different experiments designed to quantify different aspects of transport error using the Goddard Earth Observing System, Version 5 (GEOS-5) Atmospheric General Circulation Model (AGCM). In the first set of experiments, an ensemble of simulations is constructed using perturbations to parameters in the model s moist physics and turbulence parameterizations that control sub-grid scale transport of trace gases. Analysis of the ensemble spread and scales of temporal and spatial variability among the simulations allows insight into how parameterized, small-scale transport processes influence simulated CO2 distributions. In the second set of experiments, atmospheric tracers representing model error are constructed using observation minus analysis statistics from NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA). The goal of these simulations is to understand how errors in large scale dynamics are distributed, and how they propagate in space and time, affecting trace gas distributions. These simulations will also be compared to results from NASA's Carbon Monitoring System Flux Pilot Project that quantified the impact of uncertainty in satellite constrained CO2 flux estimates on atmospheric mixing ratios to assess the major factors governing uncertainty in global and regional trace gas distributions.

Ott, L.↗
NASA NTRS2014

The Interior and Orbital Evolution of Charon as Preserved in Its Geologic Record

Pluto and its largest satellite, Charon, currently orbit in a mutually synchronous state; both bodies continuously show the same face to one another. This orbital configuration is a natural end-state for bodies that have undergone tidal dissipation. In order to achieve this state, both bodies would have experienced tidal heating and stress, with the extent of tidal activity controlled by the orbital evolution of Pluto and Charon and by the interior structure and rheology of each body. As the secondary, Charon would have experienced a larger tidal response than Pluto, which may have manifested as observable tectonism. Unfortunately, there are few constraints on the interiors of Pluto and Charon. In addition, the pathway by which Charon came to occupy its present orbital state is uncertain. If Charon's orbit experienced a high-eccentricity phase, as suggested by some orbital evolution models, tidal effects would have likely been more significant. Therefore, we determine the conditions under which Charon could have experienced tidally-driven geologic activity and the extent to which upcoming New Horizons spacecraft observations could be used to constrain Charon's internal structure and orbital evolution. Using plausible interior structure models that include an ocean layer, we find that tidally-driven tensile fractures would likely have formed on Charon if its eccentricity were on the order of 0.01, especially if Charon were orbiting closer to Pluto than at present. Such fractures could display a variety of azimuths near the equator and near the poles, with the range of azimuths in a given region dependent on longitude; east-west-trending fractures should dominate at mid-latitudes. The fracture patterns we predict indicate that Charon's surface geology could provide constraints on the thickness and viscosity of Charon's ice shell at the time of fracture formation.

Tectonics↗
DOE OSTI2025

Multivariate environmental and trait-based controls of transpiration in the Central Amazon Rainforest

Tropical forest tree mortality is increasing due to more severe droughts, yet our understanding of how tree traits and life strategies are linked to drought stress has been limited by measurement scarcity. The BIONTE (BIOmass and NuTrient Experiment) near Manaus, Brazil hosts one of the world’s largest sap flow installations, with sensors in 90 canopy trees across a wood density gradient monitored since June 2022. The 2023 El Niño drought provided a unique opportunity to evaluate how water availability impacts tree transpiration. An interpretable machine learning framework was used to study the complex interactions between transpiration and multiple environmental variables such as soil water availability and vapor pressure deficit (VPD), and how these interactions vary with wood density and individual trees. We found varying responses of transpiration from different trees during the El Niño drought. Transpiration generally increased with temperature, with stronger effects in wetter areas and in trees with low to medium wood density. However, this response was modulated by stomatal sensitivity to VPD, which constrained transpiration under high atmospheric demand, particularly in intermediate-moisture area. The inflection in transpiration rate at high temperatures (>32°C) underscores the role of stomatal and hydraulic regulation in limiting water loss and protecting trees from excessive evaporative demand. Analysis of soil water contribution to transpiration revealed unimodal patterns in wetter area, with peak contributions near 0.45 cm 3 cm -3 of surface soil water and declining or flat responses beyond that threshold, suggesting a shift from water- to energy-limited transpiration. In contrast, drier areas exhibited limited transpiration sensitivity to soil water conditions and minimal trait-based variation in VPD responses, indicating supply-limited conditions. Despite higher wood density trees being generally more resilient, this study shows diverse tree drought resilience, prompting further investigation into the specific traits and dynamics between environmental variables in regulating transpiration and other physiological processes in trees.

Drought↗
DOE OSTI2014

Model Evaluation Report for Corrective Action Unit 98: Frenchman Flat, Nevada National Security Site, Nye County, Nevada, Revision 1

Model evaluation focused solely on the PIN STRIPE and MILK SHAKE underground nuclear tests’ contaminant boundaries (CBs) because they had the largest extent, uncertainty, and potential consequences. The CAMBRIC radionuclide migration experiment also had a relatively large CB, but because it was constrained by transport data (notably Well UE-5n), there was little uncertainty, and radioactive decay reduced concentrations before much migration could occur. Each evaluation target and the associated data-collection activity were assessed in turn to determine whether the new data support, or demonstrate conservatism of, the CB forecasts. The modeling team—in this case, the same team that developed the Frenchman Flat geologic, source term, and groundwater flow and transport models—analyzed the new data and presented the results to a PER committee. Existing site understanding and its representation in numerical groundwater flow and transport models was evaluated in light of the new data and the ability to proceed to the CR stage of long-term monitoring and institutional control.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A high-throughput approach for statistical process optimization in Laser Powder Bed Fusion

Process variability is inherent in metal additive manufacturing (AM). However, it is often overlooked in process optimization frameworks, constraining the understanding of process uncertainties and their influence on parameter selection. To address this, we present an integrated framework that combines high-throughput single-track experiments, GAN-based melt pool geometry extraction, robust statistical and machine learning modeling, and uncertainty-quantified process mapping. Process variability is characterized through single-track melt pool behaviors, and its influence on defect formation is systematically quantified to enable statistically guided process parameter optimization. This approach is demonstrated on Laser Powder Bed Fusion (L-PBF) of stainless steel 316L, effectively capturing the interplay between process parameters, melt pool variability, and defect probability. By integrating uncertainty quantification into process optimization, this study provides a structured methodology for addressing variability challenges in AM quality control, ultimately contributing to enhanced manufacturing reliability.

Laser Powder Bed Fusion↗
DOE OSTI2022

Poly(cyclosilane) Connectivity Tunes Optical Absorbance

We report herein the influence of skeletal connectivity on the conformation-dependent optical properties of cyclosilane homo- and copolymers. 1,3-Linked cyclosilanes were bathochromically shifted by 20 nm in solution relative to 1,4-linked cyclosilanes, an effect reproduced by quantum chemical calculations on oligomeric model systems. Polysilane optical properties are conformation-dependent, and 1,3-linked cyclosilanes were hypothesized to adopt a favorable conformation unavailable to 1,4-linked cyclosilanes constrained to an endocyclic gauche conformation. Copolymerization of the isomeric cyclosilanes 1,3Si 6 and 1,4Si 6 afforded linear statistical copolymers, as characterized by 1 H and 29 Si NMR spectroscopies. The distinct connectivity of each comonomer was found to give rise to tunable absorption spectra, where the position of the absorption band systematically increased with the increased corporation of 1,3Si 6 . Computational studies pointed to conformation-dependent changes in orbital symmetry in shifting the most intense transition from the low-energy highest occupied molecular orbital (HOMO) → lowest unoccupied molecular orbital (LUMO) transition to a higher-energy HOMO → LUMO + n transition. Here, the results of these studies demonstrate for the first time the role of silicon skeletal connectivity in controlling conformation and optoelectronic properties and provide new insight into the structure-based design of solution-processable silicon-based polymeric materials.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Non-classical nuclei and growth kinetics of Cr precipitates in FeCr alloys during ageing

In this manuscript, we quantitatively calculated the thermodynamic properties of critical nuclei of Cr precipitates in FeCr alloys. The concentration profiles of the critical nuclei and nucleation energy barriers were predicted by the constrained shrinking dimer dynamics (CSDD) method. It is found that Cr concentration distribution in the critical nuclei strongly depend on the overall Cr concentration as well as temperature. The critical nuclei are non-classical because the concentration in the nuclei is smaller than the thermodynamic equilibrium value. These results are in agreement with atomic probe observation. The growth kinetics of both classical and non-classical nuclei was investigated by the phase field approach. The simulations of critical nucleus evolution showed a number of interesting phenomena: 1) a critical classical nucleus first shrinks toward its non-classical nucleus and then grows; 2) a non-classical nucleus has much slower growth kinetics at its earlier growth stage compared to the diffusion-controlled growth kinetics. 3) a critical classical nucleus grows faster at the earlier growth stage than the non-classical nucleus. All of these results demonstrate that it is critical to introduce the correct critical nuclei in order to correctly capture the kinetics of precipitation.

Critical nucleus↗
DOE OSTI2014

Form factor effects in the direct detection of isospin-violating dark matter

Isospin-violating dark matter (IVDM) provides a possible mechanism to ameliorate the tension among recent direct detection experiments. For IVDM, we demonstrate that the results of direct detection experiments based on neutron-rich target nuclei may depend strongly on the density dependence of the symmetry energy which is presently largely unknown and controls the neutron skin thickness that reflects the relative difference of neutron and proton form factors in the neutron-rich nuclei. In particular, using the neutron and proton form factors obtained from Skyrme-Hartree-Fock calculations by varying the symmetry energy within the uncertainty region set by the latest model-independent measurement of the neutron skin thickness of {sup 208}Pb from PREX experiment at JLab, we find that, for IVDM with neutron-to-proton coupling ratio fixed to f{sub n}/f{sub p}=-0.7, the form factor effect may enhance the sensitivity of Xe-based detectors (e.g., XENON100 and LUX) to the DM-proton cross section by a factor of 3 in the DM mass region constrained by CMDS-II(Si) and even by more than an order of magnitude for heavy DM with mass larger than 80 GeV, compared with the results using the empirical Helm form factor. Our results further indicate that the form factor effect can significantly modify the recoil spectrum of Xe-based detectors for heavy IVDM with f{sub n}/f{sub p}=-0.7.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2020

Untangling causality in midlatitude aerosol–cloud adjustments

Aerosol–cloud interactions represent the leading uncertainty in our ability to infer climate sensitivity from the observational record. The forcing from changes in cloud albedo driven by increases in cloud droplet number (Nd) (the first indirect effect) is confidently negative and has narrowed its probable range in the last decade, but the sign and strength of forcing associated with changes in cloud macrophysics in response to aerosol (aerosol–cloud adjustments) remain uncertain. This uncertainty reflects our inability to accurately quantify variability not associated with a causal link flowing from the cloud microphysical state to the cloud macrophysical state. Once variability associated with meteorology has been removed, covariance between the liquid water path (LWP) averaged across cloudy and clear regions (here characterizing the macrophysical state) and Nd (characterizing the microphysical) is the sum of two causal pathways linking Nd to LWP: Nd altering LWP (adjustments) and precipitation scavenging aerosol and thus depleting Nd. Only the former term is relevant to constraining adjustments, but disentangling these terms in observations is challenging. We hypothesize that the diversity of constraints on aerosol–cloud adjustments in the literature may be partly due to not explicitly characterizing covariance flowing from cloud to aerosol and aerosol to cloud. Here, we restrict our analysis to the regime of extratropical clouds outside of low-pressure centers associated with cyclonic activity. Observations from MAC-LWP (Multisensor Advanced Climatology of Liquid Water Path) and MODIS are compared to simulations in the Met Office Unified Model (UM) GA7.1 (the atmosphere model of HadGEM3-GC3.1 and UKESM1). The meteorological predictors of LWP are found to be similar between the model and observations. There is also agreement with previous literature on cloud-controlling factors finding that increasing stability, moisture, and sensible heat flux enhance LWP, while increasing subsidence and sea surface temperature decrease it. A simulation where cloud microphysics are insensitive to changes in Nd is used to characterize covariance between Nd and LWP that is induced by factors other than aerosol–cloud adjustments. By removing variability associated with meteorology and scavenging, we infer the sensitivity of LWP to changes in Nd. Application of this technique to UM GA7.1 simulations reproduces the true model adjustment strength. Observational constraints developed using simulated covariability not induced by adjustments and observed covariability between Nd and LWP predict a 25 %–30 % overestimate by the UM GA7.1 in LWP change and a 30 %–35 % overestimate in associated radiative forcing.

Daniel T. McCoy↗
DOE OSTI2014

Optimal charging profiles for mechanically constrained lithium-ion batteries

The cost and safety related issues of lithium-ion batteries require intelligent charging profiles that can efficiently utilize the battery. This paper illustrates the application of dynamic optimization in obtaining the optimal current profile for charging a lithium-ion battery using a single-particle model while incorporating intercalation-induced stress generation. In this paper, we focus on the problem of maximizing the charge stored in a given time while restricting the development of stresses inside the particle. Conventional charging profiles for lithium-ion batteries (e.g., constant current followed by constant voltage) were not derived by considering capacity fade mechanisms. These charging profiles are not only inefficient in terms of lifetime usage of the batteries but are also slower since they do not exploit the changing dynamics of the system. Dynamic optimization based approaches have been used to derive optimal charging and discharging profiles with different objective functions. The progress made in understanding the capacity fade mechanisms has paved the way for inclusion of that knowledge in deriving optimal controls. While past efforts included thermal constraints, this paper for the first time presents strategies for optimally charging batteries by guaranteeing minimal mechanical damage to the electrode particles during intercalation. In addition, an executable form of the code has been developed and provided. This code can be used to identify optimal charging profiles for any material and design parameters.

Suthar, B↗
DOE OSTI2026

Taylor approximation variance reduction for approximation errors in PDE-constrained Bayesian inverse problems

In numerous applications, surrogate models are used as a replacement for accurate parameter-to-observable mappings when solving large-scale inverse problems governed by partial differential equations (PDEs). The surrogate model may be a computationally cheaper alternative to the accurate parameter-to-observable mappings and/or may ignore additional unknowns or sources of uncertainty. The Bayesian approximation error (BAE) approach provides a means to account for the induced uncertainties and approximation errors, i.e. the errors between the accurate parameter-to-observable mapping and the surrogate. The statistics of these errors are, however, in general unknown a priori, and are thus calculated using Monte Carlo sampling. Although the sampling is typically carried out offline, i.e. before considering the data, the process can still represent a computational bottleneck. In this work, we develop a scalable computational approach for reducing the costs associated with the sampling stage of the BAE approach. Specifically, we consider the Taylor expansion of the accurate and surrogate forward models with respect to the uncertain parameter fields either as a control variate for variance reduction or as a means to directly and efficiently approximate the mean and covariance of the approximation errors. We propose efficient methods for evaluating the expressions for the mean and covariance of the Taylor approximations based on linear(-ized) PDE solves. Furthermore, the proposed approach is independent of the dimension of the uncertain parameter, depending instead on the intrinsic dimension of the data, ensuring scalability to high-dimensional problems. The potential benefits of the proposed approach are demonstrated for two high-dimensional inverse problems governed by PDE examples, namely for the estimation of a distributed Robin boundary coefficient in a linear diffusion problem, and for a coefficient estimation problem governed by a nonlinear diffusion problem.

Bayesian approximation error↗
NASA NTRS2011

Operational Parameters, Considerations, and Design Decisions for Resource-Constrained Ion Trap Mass Spectrometers

Mass spectrometers are increasingly finding applications in new and unique areas, often in situations where key operational resources (i.e. power, weight and size) are limited. One such example is the Mars Organic Molecule Analyzer (MOMA). This instrument is a joint venture between NASA and the European Space Agency (ESA) to develop an ion trap mass spectrometer for chemical analysis on Mars. The constraints on such an instrument are significant as are the performance requirements. While the ideal operating parameters for an ion trap are generally well characterized, methods to maintain analytical performance with limited power and system weight need to be investigated and tested. Methods Experiments have been performed on two custom ion trap mass spectrometers developed as prototypes for the MOMA instrument. This hardware consists of quadrupole ion trap electrodes that are 70% the size of common commercial instrumentation. The trapping RF voltage is created with a custom tank circuit that can be tuned over a range of RF frequencies and is driven using laboratory supplies and amplifiers. The entire instrument is controlled with custom Lab VIEW software that allows a high degree of flexibility in the definition of the scan function defining the ion trap experiment. Ions are typically generated via an internal electron ionization source, however, a laser desorption source is also in development for analysis of larger intact molecules. Preliminary Data The main goals in this work have been to reduce the power required to generate the radio frequency trapping field used in an ion trap mass spectrometer. Generally minimizing the power will also reduce the volume and mass of the electronics to support the instrument. In order to achieve optimum performance, commercial instruments typically utilize RF frequencies in the 1 MHz range. Without much concern for power usage, they simply generate the voltage required to access the mass range of interest. In order to reduce the required RF voltage (and power), operation of the ion trap at lower RF frequencies has been investigated. Surprisingly, the performance of the instrument has only been slightly degraded at RF frequencies all the way down to 500 kHz. Mass resolution is relatively stable to this point and depending on the resonant ejection point used, the peak intensity is also quite stable. To date only masses up to m/z 200 have been fully investigated, however, additional studies are planned to verify the performance with higher mass ions. The lower frequency and voltage should reduce the pseudo potential well depth, eventually affecting the trapping efficiency of the instrument -- effect that could manifest itself in significantly limiting the mass range of trapped ions. Other methods to reduce the RF power while maintaining analytical performance are also under investigation. This includes ion ejection at lower q(sub z) values to access a given mass with a lower RF voltage. The loss of mass resolution at lower q(sub eject) points has been measured and current work is underway to leverage scan speed and the use of non-linear resonances in order to counter this trend. The overall trap performance under this range of operating conditions will be presented with a goal of identifying what trade-offs are acceptable.

Danell, Ryan M.↗