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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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16 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Conveyor-belt magneto-optical trapping of molecules

Abstract Laser cooling is used to produce ultracold atoms and molecules for quantum science and precision measurement applications. Molecules are more challenging to cool than atoms due to their vibrational and rotational internal degrees of freedom. Molecular rotations lead to the use of type-II transitions ( F ⩾ F ′ ) for magneto-optical trapping (MOT). When typical red detuned light frequencies are applied to these transitions, sub-Doppler heating is induced, resulting in higher temperatures and larger molecular cloud sizes than realized with the type-I MOTs most often used with atoms. To improve type-II MOTs, Jarvis et al (2018 Phys. Rev. Lett. 120 083201) proposed a blue-detuned MOT to be applied after initial cooling and capture with a red-detuned MOT. This was successfully implemented (Burau et al 2023 Phys. Rev. Lett. 130 193401; Jorapur et al 2024 Phys. Rev. Lett. 132 163403; Li et al 2024 Phys. Rev. Lett. 132 233402), realizing colder and denser molecular samples. Very recently, Hallas et al (2024 arXiv:2404.03636) demonstrated a blue-detuned MOT with a ‘1+2’ configuration that resulted in even stronger compression of the molecular cloud. Here, we describe and characterize theoretically the conveyor-belt mechanism that underlies this observed enhanced compression. We perform numerical simulations of the conveyor-belt mechanism using both stochastic Schrödinger equation and optical Bloch equation approaches. We investigate the conveyor-belt MOT characteristics in relation to laser parameters, g -factors and the structure of the molecule, and find that conveyor-belt trapping should be applicable to a wide range of laser-coolable molecules.

Li, Grace K. (ORCID:0000000277223355)↗
DOE OSTI2024

Global Ocean Cooling of 2.3°C During the Last Glacial Maximum

Abstract Quantitative constraints on past mean ocean temperature (MOT) critically inform our historical understanding of Earth's energy balance. A recently developed MOT proxy based on paleoatmospheric Xe, Kr, and N 2 ratios in ice core air bubbles is a promising tool rooted in the temperature dependences of gas solubilities. However, these inert gases are systematically undersaturated in the modern ocean interior, and it remains unclear how air‐sea disequilibrium may have changed in the past. Here, we carry out 30 tracer‐enabled model simulations under varying circulation, sea ice cover, and wind stress regimes to evaluate air‐sea disequilibrium in the Last Glacial Maximum (LGM) ocean. We find that undersaturation of all three gases was likely reduced, primarily due to strengthened high‐latitude winds, biasing reconstructed MOT by −0.38 ± 0.37°C (1σ). Accounting for air‐sea disequilibrium, paleoatmospheric inert gases indicate that LGM MOT was 2.27 ± 0.46°C (1σ) colder than the pre‐industrial era.

Seltzer, A. M.↗
DOE OSTI2026

High Compression Blue-Detuned Magneto-Optical Trap of Polyatomic Molecules

We demonstrate a blue-detuned magneto-optical trap (MOT) of a polyatomic molecule, calcium monohydroxide (CaOH). We identify a novel MOT frequency configuration that produces high spatial compression of the molecular cloud. This high compression MOT achieves a cloud radius of 59⁢(5) μ⁢m and a peak density of 8⁢(2) ×10 8 cm −3 . We experimentally compare several blue-detuned MOT schemes for CaOH and find good agreement between our data and Monte Carlo simulations.

Cold and ultracold molecules↗
DOE OSTI2026

A conveyor-belt magneto-optical trap of CaF

Achieving high-density samples of laser-cooled molecules is a critical step toward advancing applications in precision measurements, ultracold chemistry and quantum science. We report the experimental realization of a high-density conveyor-belt magneto-optical trap for calcium monofluoride (CaF) molecules. The obtained highly-compressed cloud has a mean radius of 64(5) μm and a peak number density of 3.6(5) × 10 10 cm −3 , a 600-fold increase over the conventional red-detuned MOTs of CaF, and the densest molecular MOT observed to date. Subsequent loading of these molecules into an optical dipole trap yields up to 2.6 × 10 4 trapped molecules at a temperature of 14(2) μK with a peak phase-space density of ~ 2.4 × 10 −6 . This opens new possibilities for a range of applications utilizing high-density, optically trapped ultracold molecules.

Yu, Scarlett S. [Harvard Univ., Cambridge, MA (Uni↗
DOE OSTI2023

Pressurized Water Reactor Gadolinia Pin Location Optimization

This report presents the results of lattice optimization studies performed to find optimum locations for gadolinia burnable absorber (BA) rods in pressurized water reactor (PWR) lattice fuel designs. Initial excess reactivity suppression allows core designers to further improve operational economics by extending cycle length. Gadolinia BAs are commonly used in boiling water reactor assembly designs for this purpose. In recent years, gadolinia absorbers have been used in PWR designs owing to their longer effectiveness for reactivity suppression compared with common BAs used in PWR assemblies. This report examines the optimum gadolinia pin placement in 17 × 17 PWR lattices at different fuel and gadolinia concentrations for optimized lattice performance, using the SCALE/Polaris lattice physics code. The completed work is continuation of the Light Water Reactor LEU+ Lattice Optimization (ORNL/TM-2021/2366) project. An optimization driver called the metaheuristic optimization tool (MOT) is used to automate domain space exploration and optimization of the lattice designs. Heuristics from previous light-water reactor (LWR) lattice optimization studies were used to construct the objective function and define the domain space for optimization. This work successfully demonstrated that the optimization algorithms of MOT can generate feasible, nonproprietary PWR lattice designs with gadolinia.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Suspended waveguides on membrane and needle structures towards photonic atom trap integrated platforms

An atom trap integrated platform (ATIP) comprises a substrate, a membrane, and a suspended waveguide. The substrate has an opening formed therein. The membrane extends across a portion of the substrate opening. The suspended waveguide is formed on the membrane such that the suspended waveguide extends from a first edge of the substrate to a second edge. A magneto-optical trap (MOT) is formed around the suspended waveguide by emitting a plurality of cooling beams and a repump through the substrate opening. Evanescent fields are established above the suspended waveguide by coupling two trapping beams through the suspended waveguide, which trapping beams are red-detuned and blue-detuned with respect to the resonant optical transition of the atoms. By forming the MOT within the evanescent fields, an evanescent field optical trap (EFOT) is formed.

Lee, Jongmin↗
DOE OSTI2024

Guided cold atom inertial sensors with membrane integrated photonics on atom trap integrated platforms

A guided cold-atom inertial sensor system comprises an atom trap integrated platform, a laser system, a magnetic field system, a control system, and a computing system. The laser system and magnetic field system are adapted to form a magneto-optical trap (MOT) about a suspended waveguide of the atom trap integrated platform made of membrane integrated photonics. After loading cold atoms from a MOT, the photonic atom trap integrated platform generates one-dimensional guided atoms with an evanescent field optical dipole trap (EF-ODT) along the optical waveguide to create guided atomic accelerometers/gyroscopes. Motion of atomic wavepackets in a superposition state is created along the guided atom geometry by way of state-dependent momentum kicks. The light-pulse sequence of guided atom interferometry splits, redirects, and recombines atomic wavepackets, which allows measurement of atom interference fringes sensitive to inertial forces via a probe laser.

Lee, Jongmin↗
DOE OSTI2023

Implementing an electronic sideband offset lock for isotope shift spectroscopy in radium

We demonstrate laser frequency stabilization with at least 6 GHz of offset tunability using an in-phase/quadrature (IQ) modulator to generate electronic sidebands (ESB) on a titanium sapphire laser at 714 nm and we apply this technique to perform isotope shift spectroscopy of 226 Ra and 225 Ra. By locking the laser to a single resonance of a high finesse optical cavity and adjusting the lock offset, we determine the frequency difference between the magneto-optical trap (MOT) transitions in the two isotopes to be 2630.0 ± 0.3 MHz, a factor of 29 more precise than the previously available data. Using the known value of the hyperfine splitting of the 3 P 1 level, we calculate the isotope shift for the 1 S 0 to 3 P 1 transition to be 2267.0 ± 2.2 MHz, a factor of 8 more precise than the best available value. Our technique could be applied to countless other atomic systems to provide unprecedented precision in isotope shift spectroscopy and other relative frequency comparisons.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Combined Algal Processing for the Synthesis of Liquid Oleofuels and Products (CAPSLOC) - WBS 1.3.4.204

Combined Algal Processing for the Synthesis of Liquid Oleofuels and Products (CAPSLOC) aims to develop a biorefinery concept that is composition-agnostic and enables economically, environmentally, and socially viable biofuel production by maximizing the value from each fraction. To achieve this, we have employed an iterative approach between R&D and TEA/LCA to establish process targets and quantify improvements in the minimum fuel selling price (MFSP), reduce carbon intensity, and support the state of technology (SOT). We have surveyed various methods for biomass pretreatment and successfully demonstrated pre-pilot scale pretreatment in batch mode. Using techniques such as lipid modification, fermentation, mild oxidative treatment (MOT), and carbonization, we have developed biofuel precursors and a range of value-added co-products. Our project has demonstrated significant improvements in key aspects of algae processing, particularly in pretreatment technologies suitable for variable composition, co-products available from lipid and extracted solid streams, conditioning and fermenting high-protein hydrolysates, and recovering nitrogen (N) and phosphorus (P) nutrients for recycling to cultivation ponds. The success of this project will support the commercialization of a sustainable microalgal biorefinery industry.

biofuel↗
DOE OSTI2023

Nutrient Recovery from Algae Residues Using Mild Oxidative Treatment

Algal biorefining to fuels and chemicals frequently requires both fuel production and nutrient recycle pathways. Mild Oxidative Treatment (MOT) is a promising wet oxidation route that simultaneously converts nitrogen and carbon in algae hydrolysate and extracted residues into ammonia and carboxylic acids (up to C5), respectively. The latter can be converted to sustainable aviation fuel by ketonization, condensation, and hydrodeoxygenation. We show that for a Scenedesmus algae under certain oxidation conditions, the nitrogen in the residues can be converted quantitatively to ammonia and recovered by cation exchange, while almost half of the carbon can be converted to carboxylic acids, mainly acetic acid. At the same time, we also show that soluble phosphorus in the form of phosphate can be selectively recovered by anion exchange, leaving a clean aqueous carboxylic acid stream for upgrading to fuels.

algae↗
DOE OSTI2025

The Martini 3 Lipidome: Expanded and Refined Parameters Improve Lipid Phase Behavior

Lipid membranes are central to cellular life. Complementing experiments, computational modeling has been essential in unraveling complex lipid-biomolecule interactions, crucial in both academia and industry. The Martini model, a coarse-grained force field for efficient molecular dynamics simulations, is widely used to study membrane phenomena but has faced limitations, particularly in capturing realistic lipid phase behavior. Here, we present refined Martini 3 lipid models with a mapping scheme that distinguishes lipid tails that differ by just two carbon atoms, enhancing the structural resolution and thermodynamic accuracy of model membrane systems including ternary mixtures. The expanded Martini lipid library includes thousands of models, enabling simulations of complex and biologically relevant systems. These advancements establish Martini as a robust platform for lipid-based simulations across diverse fields.

Lipids↗
DOE OSTI2023

Tensor-to-scalar ratio forecasts for extended LiteBIRD frequency configurations

LiteBIRD is a planned JAXA-led cosmic microwave background (CMB) B-mode satellite experiment aiming for launch in the late 2020s, with a primary goal of detecting the imprint of primordial inflationary gravitational waves. Its current baseline focal-plane configuration includes 15 frequency bands between 40 and 402 GHz, fulfilling the mission requirements to detect the amplitude of gravitational waves with the total uncertainty on the tensor-to-scalar ratio, δr, down to δr < 0.001. A key aspect of this performance is accurate astrophysical component separation, and the ability to remove polarized thermal dust emission is particularly important. In this paper we note that the CMB frequency spectrum falls off nearly exponentially above 300 GHz relative to the thermal dust spectral energy distribution, and a relatively minor high frequency extension can therefore result in even lower uncertainties and better model reconstructions. Specifically, we compared the baseline design with five extended configurations, while varying the underlying dust modeling, in each of which the High-Frequency Telescope (HFT) frequency range was shifted logarithmically toward higher frequencies, with an upper cutoff ranging between 400 and 600 GHz. In each case, we measured the tensor-to-scalar ratio r uncertainty and bias using both parametric and minimum-variance component-separation algorithms. When the thermal dust sky model includes a spatially varying spectral index and temperature, we find that the statistical uncertainty on r after foreground cleaning may be reduced by as much as 30–50% by extending the upper limit of the frequency range from 400 to 600 GHz, with most of the improvement already gained at 500 GHz. We also note that a broader frequency range leads to higher residuals when fitting an incorrect dust model, but also it is easier to discriminate between models through higher χ 2 sensitivity. Even in the case in which the fitting procedure does not correspond to the underlying dust model in the sky, and when the highest frequency data cannot be modeled with sufficient fidelity and must be excluded from the analysis, the uncertainty on r increases by only about 5% for a 500 GHz configuration compared to the baseline.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Requirements on the gain calibration for LiteBIRD polarisation data with blind component separation

The detection of primordial B modes of the cosmic microwave background (CMB) could provide information about the early stages of the Universe's evolution. The faintness of this signal requires exquisite calibration accuracy and control of instrumental systematic effects which otherwise could bias the measurements. In this work, we study the impact of an imperfect relative polarisation gain calibration on the recovered value of the tensor-to-scalar ratio r for the LiteBIRD experiment, through the application of the blind Needlet Internal Linear Combination (NILC) foreground-cleaning method. We derive requirements on the relative calibration accuracy of the overall polarisation gain (Δg ν ) for each LiteBIRD frequency channel. Our results show that minimum variance techniques, as NILC, are less sensitive to systematic gain calibration uncertainties compared to a parametric approach, if the latter is not equipped with a proper modelling of these instrumental effects. In this study, the most stringent requirements are found in the channels where the CMB signal is relatively brighter, with the tightest constraints at 166 GHz (Δg ν ≈ 0.16%). This differs from the outcome of an analogous analysis performed with a parametric method, where the tightest requirements are obtained for the foreground-dominated channels. Gain calibration uncertainties, corresponding to the derived requirements, are then simultaneously propagated into all frequency channels. By doing so, we find that the overall impact on estimated r is lower than the total gain systematic budget for LiteBIRD approximately by a factor 5, due to the correlations of the impacts of gain calibration uncertainties in different frequency channels. In order to decouple the systematic effect from the specific choice of the model, we derive the requirements assuming constant spectral parameters for the foreground emission. To assess the robustness of the obtained results against more realistic scenarios, we repeat the analysis assuming sky models of intermediate and high complexity. In these further cases, we adopt an optimised NILC pipeline, called the Multi-Clustering NILC (MC-NILC). We find that the impact of gain calibration uncertainties on r is lower than the LiteBIRD gain systematics budget for the intermediate-complexity sky model. For the high-complexity case, instead, it would be necessary to tighten the requirements by a factor 1.8.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Estimating CO 2 fluxes through integrating spatial and temporal input layers via deep learning algorithms

Background Accurate estimation of net ecosystem exchange of CO 2 fluxes (Fc) is essential for understanding carbon cycle processes and assessing ecosystem carbon budgets. However, conventional modeling approaches often emphasize temporal dynamics while overlooking the pronounced spatial heterogeneity within the footprint of eddy covariance (EC) towers, potentially limiting predictive accuracy and interpretability of Fc estimates. To address this challenge, we developed a spatiotemporal model that integrates high-resolution footprint-weighted spatial information with sequential environmental drivers. Results The integrated model combines a deeper graph convolutional network to characterize fine-scale spatial variability within EC footprints and a gated recurrent unit network to capture temporal dependencies in biophysical conditions. Using multi-year flux tower observations, remote sensing vegetation indices and footprint modeling, we evaluate the proposed method across three land cover types. This spatiotemporal model consistently outperforms temporal-only and spatial-only baselines, achieving the highest overall accuracy (R 2 = 0.9569) and the lowest RMSE (1.8128 μmol m −2 s −1 ) and MAE (1.1939 μmol m −2 s −1 ). Performance gains are particularly evident in ecosystems with strong vegetation heterogeneity, where spatial structure substantially modulates Fc variability. Conclusions This study demonstrates the importance of joint modeling spatial heterogeneity and temporal dynamics for improving Fc estimation and provides a robust method for advancing footprint-based Fc estimates across diverse ecosystems, supporting refined assessments of terrestrial carbon fluxes, and enhancing scientific foundations for carbon studies.

CO2 flux estimate↗
DOE OSTI2025

Ambient field seismology in critical zone hydrological sciences

Passive ambient noise monitoring is an emerging tool in environmental seismology, leveraging the ambient seismic field to assess temporal variations in shallow subsurface properties. This review focuses on the potential and challenges of using scattered coda waves from noise correlation functions to monitor critical zone dynamics. The sensitivity of seismic velocities to various environmental factors, including precipitation, snowmelt, atmospheric pressure, and groundwater fluctuations, underscores the method’s versatility. While coda waves excel in detecting subtle changes due to their scattered nature, ballistic waves provide higher spatial resolution, albeit with challenges in source stability. Advances in seismic sensing, including distributed acoustic sensing and low-cost geophone networks, have enabled high-resolution monitoring of hydrological processes, subsurface deformation, and seismic hazards. Integrating seismic data with hydrological models provides insights into water storage, pore pressure changes, and soil moisture dynamics. However, limitations in spatial resolution, calibration with ground truth data, and coupled effects between environmental factors remain key challenges. This review emphasizes the importance of interdisciplinary approaches in refining methodologies, enhancing sensor deployments, and addressing data gaps. Passive seismic monitoring offers opportunities to understand critical zone processes and their broader impacts on seismic hazards and environmental sustainability.

58 GEOSCIENCES↗
DOE OSTI2023

Lipids from High-Protein Algae Biomass

Biofuels from renewable and sustainable sources will be a critical component of reducing greenhouse gasses. To this end, in achieving maximum biomass productivity in outdoor ponds at a reasonable cost, algae must be grown at a maximal rate. This current algae cultivation strategy results in high-protein biomass because there is insufficient time for deplete-hold steps that increase lipids but also cost. Thus methods to convert high-protein (>50%) need to be developed for biofuels. The Consolidated Algae Processing (CAP) strategy has previously shown utility on high-carbohydrate algae biomass and has now been expanded to include methods aimed at converting the protein fraction to lipids. After acid-pretreatment, hydrolysate liquor is oxidatively treated to deaminate and convert soluble proteins and amino acids into four main carboxylate acids; formic, acetic, succinic, and propionic. These acids are readily and completely fermented into intracellular lipids using oleaginous yeast. Using a fed-batch fermentation strategy and no added nutrients, we achieved nearly 30% intracellular lipids and 1.3 g/L lipids demonstrating the potential of our expanded CAP process to generate additional lipids for conversion to biofuels as part of an algae-focused biorefinery.

AAD↗