Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “structure preservation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

The Fluid Processing Apparatus: from Flight Hardware to Electron Micrographs

Since the early years of space biology, a major drawback in spaceflight plant experiments has been the inability to fix specimens in microgravity, relying instead on fixation after return to Earth. As there, it is of a growing interest to look at the effect of microgravity on the structure and the developmental polarity of root graviperceptive cells, or columella cells, and so, it is important to use flight hardware which allows specimen fixation in space therefore avoiding the confounding effects of rapid readaptation to gravity after landing. As part of the Bioserve Space Technologies, a Center for the Commercial Development of Space (CCDS), we now have experiment flight opportunities through the Commercial Generic Bioprocessing Apparatus (CGBA) payload. In this study the Fluid Processing Apparatus (FPA) was used to grow seedlings for a limited period of time prior to fixation of the tissue in a microgravity environment. Upon return to Earth, the samples were processed for electron microscopy. This report describes the microscopic data obtained from the two space flights (STS-54 and STS-60). In both cases, the electron micrographs of the columella cells revealed well preserved cell structure, well defined microtubules, and the presence of calcium precipitates formed by a antimonate precipitation method.

Hilaire, Emmanuel↗
NASA NTRS2004

Numerical Modeling of the South Pole-Aitkin Impact

The South Pole-Aitkin (SPA) basin, on the far side of the Moon, is the largest and oldest impact structure still preserved in the solar system. The crater is about 2500 km in diameter and formed in the Pre-Nectarian era of lunar history, over 4 Gyr ago. At this time, the thermal state of the Moon was much hotter than it is today. Accretional energy from the rapidly forming Moon melted the outermost few hundred kilometers of the Moon. As this magma ocean differentiated and cooled a 60 100-km thick low-density crust formed at the surface; below this the residual melt, with a higher density, cooled to form the lunar mantle. The giant SPA impact event punctured the Moon some time during the cooling of the magma ocean and thus provides a unique window for studying the lunar interior and the early formative processes of the Moon. The impact excavated otherwise inaccessible samples of the deep crust and (possibly) upper mantle, which has inspired proposed sample return missions. Furthermore, the thermal and rheologic state of the early Moon played a role in shaping the final structure of the basin. To aid in site selection for future sample return missions to the SPA basin, and to investigate the effect of thermal state on final crater structure, we performed some numerical simulations of the SPA impact event.

Collins, G. S.↗
DOE OSTI2024

Detection of the large-scale tidal field with galaxy multiplet alignment in the DESI Y1 spectroscopic survey

We explore correlations between the orientations of small galaxy groups, or ‘multiplets’, and the large-scale gravitational tidal field. Using data from the Dark Energy Spectroscopic Instrument (DESI) Y1 survey, we detect the intrinsic alignment (IA) of multiplets to the galaxy-traced matter field out to separations of $100\,h^{-1}$ Mpc. Unlike traditional IA measurements of individual galaxies, this estimator is not limited by imaging of galaxy shapes and allows for direct IA detection beyond redshift $z=1$. Multiplet alignment is a form of higher order clustering, for which the scale-dependence traces the underlying tidal field and amplitude is a result of small-scale ($\lt 1h^{-1}$ Mpc) dynamics. Within samples of bright galaxies, luminous red galaxies (LRG) and emission-line galaxies, we find similar scale-dependence regardless of intrinsic luminosity or colour. This is promising for measuring tidal alignment in galaxy samples that typically display no IA. DESI’s LRG mock galaxy catalogues created from the A BACUS S UMMIT N -body simulations produce a similar alignment signal, though with a 33 per cent lower amplitude at all scales. An analytic model using a non-linear power spectrum (NLA) only matches the signal down to 20 $h^{-1}$ Mpc. Our detection demonstrates that galaxy clustering in the non-linear regime of structure formation preserves an interpretable memory of the large-scale tidal field. Multiplet alignment complements traditional two-point measurements by retaining directional information imprinted by tidal forces, and contains additional line-of-sight information compared to weak lensing. This is a more effective estimator than the alignment of individual galaxies in dense, blue, or faint galaxy samples.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Vacancy-driven variations in the phonon density of states of fast neutron irradiated nuclear graphite

Research examining radiation damage and its effects in graphite began in the 1940’s during the development of moderated nuclear reactors. Interest in this topic is expanding because of emerging applications associated with fullerenes and carbon nanostructures as well as its long-standing use as a fission moderator. In this work, we report the measurements of the full phonon density of states of irradiated nuclear graphite using inelastic neutron scattering experiments at room temperature. The samples were previously exposed to different levels of neutron doses and irradiation temperatures. The phonon density of states of perfect and defected graphite supercells including different configurations of vacancies and interstitials were calculated using first-principles direct method. Despite high neutron irradiation doses, the scattering measurements show that the induced damage is localized, and the layered structure is preserved. In conclusion, a comparison of the measured phonon densities of states of irradiated samples with those calculated of defected supercells indicates that the main changes observed are mainly attributed to formation of vacancies.

36 MATERIALS SCIENCE↗
DOE OSTI2024

tLaSDI: Thermodynamics-informed latent space dynamics identification

Here we propose a latent space dynamics identification method, namely tLaSDI, that embeds the first and second principles of thermodynamics. The latent variables are learned through an autoencoder as a nonlinear dimension reduction model. The latent dynamics are constructed by a neural network-based model that precisely preserves certain structures for the thermodynamic laws through the GENERIC formalism. An abstract error estimate is established, which provides a new loss formulation involving the Jacobian computation of autoencoder. The autoencoder and the latent dynamics are simultaneously trained to minimize the new loss. Computational examples demonstrate the effectiveness of tLaSDI, which exhibits robust generalization ability, even in extrapolation. In addition, an intriguing correlation is empirically observed between a quantity from tLaSDI in the latent space and the behaviors of the full-state solution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Sparse-grid discontinuous Galerkin methods for the Vlasov–Poisson–Lenard–Bernstein model

Sparse-grid methods have recently gained interest in reducing the computational cost of solving high-dimensional kinetic equations. In this paper, we construct adaptive and hybrid sparse-grid methods for the Vlasov–Poisson–Lenard–Bernstein (VPLB) model. This model has applications to plasma physics and is simulated in two reduced geometries: a 0x3v space homogeneous geometry and a 1x3v slab geometry. Here we use the discontinuous Galerkin (DG) method as a base discretization due to its high-order accuracy and ability to preserve important structural properties of partial differential equations. We utilize a multiwavelet basis expansion to determine the sparse-grid basis and the adaptive mesh criteria. We analyze the proposed sparse-grid methods on a suite of three test problems by computing the savings afforded by sparse-grids in comparison to standard solutions of the DG method. The results are obtained using the adaptive sparse-grid discretization library ASGarD.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Neural entropy-stable conservative flux form neural networks for learning hyperbolic conservation laws

We propose a neural entropy-stable conservative flux form neural network (NESCFN) for learning hyperbolic conservation laws and their associated entropy functions directly from solution trajectories, without requiring any predefined numerical discretization. While recent neural network architectures have successfully integrated classical numerical principles into learned models, most rely on prior knowledge of the governing equations or assume a fixed discretization. Our approach removes this dependency by embedding entropy-stable design principles into the learning process itself, enabling the discovery of physically consistent dynamics in a fully data-driven setting. By jointly learning both the flux function and a corresponding entropy, NESCFN promotes conservation and entropy dissipation, which is critical for long-term stability and fidelity in the system of hyperbolic conservation laws. Furthermore, numerical results demonstrate that the method achieves stability and conservation over extended time horizons and accurately captures shock propagation speeds, even without oracle access to future-time solution profiles in the training data.

Conservative flux form↗
DOE OSTI2025

Enhancing Dihydrogen Interaction of a Zirconium Metal–Organic Framework by Metal Doping

Advancing efficient hydrogen storage technologies is essential for enabling a sustainable energy future, especially in onboard applications. While hydrogen offers high gravimetric energy density and zero-emission combustion, its low volumetric energy density presents significant storage challenges. Metal-organic frameworks (MOFs), well known for their tunable porosity and high surface areas, have emerged as promising candidates for adsorption-based hydrogen storage. This study investigated a chemically robust zirconium-based MOF, MOF-808, as a representative platform for hydrogen storage enhancement through metal ion doping. Various divalent metal ions were introduced into MOF-808 via one-pot synthesis or post-synthetic modification (PSM) to evaluate their effects on metal doping efficiency, framework stability, and hydrogen adsorption performance. Our findings demonstrate that metal doping enhanced the hydrogen binding affinity of MOF-808 while preserving its structural integrity and excellent stability. A Mg-doped MOF, MOF-808@Mg 2:1, showed a 59% increase in hydrogen uptake, and a Cu-doped MOF, MOF-808-ZrCu, exhibited a 33% increase in isosteric heat of adsorption for H 2 compared to the pristine MOF-808 activated at the same temperature. This work highlights the potential of metal-functionalized stable MOFs for practical hydrogen storage applications. Furthermore, these materials are also being studied for their potential to enhance CO 2 adsorption.

Adsorption↗
DOE OSTI2026

Kinetic Monte Carlo Framework for Coupled Degradation and Dehydration of Anion Exchange Membranes

Kinetic Monte Carlo (kMC) simulations, augmented with temporal-acceleration schemes, can efficiently handle stiff reaction-transport networks when fast processes rapidly relax to quasi-equilibrium on a fixed lattice. However, in glassy anion-exchange membranes (AEM), rare and irreversible chemical degradation events continuously reshape the nanoscale morphology, and the associated hydration and transport degrees of freedom remain far from a well-defined local equilibrium. This combination of evolving state space and nonequilibrated fast dynamics lies outside the scope of existing kMC acceleration frameworks. Here, to address this challenge, we introduce an auxiliary-particle kinetic Monte Carlo (AP-kMC) scheme. In AP-kMC, short-lived mobile particles spawned at degradation sites execute hop, water-elimination, and decay moves, enforcing rapid local relaxation of the hydration structure while preserving the stochastic rules of kMC. Parameterized with molecular-dynamics morphologies and experimental solution degradation kinetics, AP-kMC reproduces the evolution of ion-exchange capacity, water uptake, and conductivity, and reveals a feedback loop in which poorly hydrated sites degrade first and each degradation event induces further local dehydration. The resulting thinning and fragmentation of water channels cause loss of hydrophilic percolation and abrupt conductivity collapse well before complete charge loss. AP-kMC thus reframes AEM durability as a coupled degradation–drying–percolation problem and provides a transferable strategy to simulate reactive, out-of-equilibrium polymer electrolytes where local solvation controls reactivity.

organic↗
DOE OSTI2026

Small Molecule Inhibitor-Modulated Al 2 O 3 Atomic Layer Deposition on Monolayer MoS 2 for Controlled Nucleation

The integration of ultrathin dielectrics on two-dimensional (2D) semiconductors is essential for advancing beyond-Si electronics. However, the intrinsic inertness of van der Waals 2D basal planes remains a primary bottleneck to achieving uniform dielectric nucleation and growth. Here, in this study, we introduce a small molecule inhibitor (SMI)-modulated thermal atomic layer deposition (ALD) strategy, exemplified by aluminum oxide (Al 2 O 3 ) ALD on monolayer molybdenum disulfide (1L MoS 2 ) with acetic acid (HAc) SMI. The ABC-type sequence comprises HAc inhibitor (A), trimethylaluminum (TMA) precursor (B), and deionized H 2 O coreactant (C). In situ quartz crystal microbalance (QCM) studies reveal robust HAc adsorption on Al 2 O 3 and suppression of subsequent oxide growth on HAc-passivated surfaces. When applied to 1L MoS 2 , this inhibitory pathway enables HAc to selectively passivate nascent Al 2 O 3 nuclei formed on the MoS 2 surface, limiting their three-dimensional (3D) island coarsening and redirecting precursor adsorption toward the uncovered basal plane. Consequently, nearly continuous ultrathin (∼1.5 nm) Al 2 O 3 films are achieved on 1L MoS 2 with markedly improved uniformity compared to standard Al 2 O 3 ALD using TMA and H 2 O, as validated by atomic force microscopy (AFM), cross-sectional scanning transmission electron microscopy (STEM), and energy-dispersive X-ray spectroscopy (EDS). Density functional theory (DFT) calculations further provide atomistic insight into HAc-modulated Al 2 O 3 nucleation, corroborating the energetic preference of HAc for Al 2 O 3 over MoS 2 and attenuated TMA adsorption on HAc-passivated surfaces. Spatially resolved Raman spectroscopy also confirms that the HAc-modulated process preserves the structural integrity of 1L MoS 2 , with only minimal strain and doping perturbations observed after dielectric deposition. This SMI-modulated approach offers a broadly applicable framework for controlling ALD nucleation across various inhibitors, ALD chemistries, and 2D materials, opening opportunities for reliable dielectric integration in next-generation nanoelectronics.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Extending Calendar Life of Si-Based Lithium-Ion Batteries by a Localized High Concentration Electrolyte

Silicon (Si) is one of the most promising anode materials for the next generation lithium-ion batteries (LIBs). Although significant progresses have been made on the cycle life of Si-based LIBs, their calendar-life is still far less than those required for electrical vehicle applications. Here, in this work, the fundamental mechanisms behind the limited calendar life of Si-LIBs have been investigated. It is found that the unstable interphase layers formed on electrodes during the formation/cycling of batteries using conventional electrolyte with fluoroethylene carbonate (FEC) additive are responsible for the rapid impedance-increase of Si-LIBs during storage at elevated temperature (55°C). By using an FEC-free localized high concentration electrolyte (lithium bis(fluorosulfonyl)imide:ethyl propionate:ethylene carbonate:1,1,2,2-tetrafluoroethyl-2,2,3,3-tetrafluoropropyl ether (1:2.8:0.2:1 by mol.) with 1 wt.% lithium difluorophosphate), stable interphase layers formed on electrodes can effectively block the crosstalk between cathode and anode, minimize the impedance increase of Si||LiNi 0.6 Mn 0.2 Co 0.2 (NMC622) batteries during storage at elevated temperature (55°C), therefore largely improve their calendar life. Si||NMC622 batteries using this electrolyte also demonstrated a high-capacity retention of ~92.4% after 500 cycles at 45°C with well-preserved electrode structure. Hence, this novel electrolyte is a good candidate to extend the cycling life and calendar life of Si-LIBs.

25 ENERGY STORAGE↗
DOE OSTI2021

DNA origami single crystals with Wulff shapes

DNA origami technology has proven to be an excellent tool for precisely manipulating molecules and colloidal elements in a three-dimensional manner. However, fabrication of single crystals with well-defined facets from highly programmable, complex DNA origami units is a great challenge. Here, we report the successful fabrication of DNA origami single crystals with Wulff shapes and high yield. By regulating the symmetries and binding modes of the DNA origami building blocks, the crystalline shapes can be designed and well-controlled. The single crystals are then used to induce precise growth of an ultrathin layer of silica on the edges, resulting in mechanically reinforced silica-DNA hybrid structures that preserve the details of the single crystals without distortion. The silica-infused microcrystals can be directly observed in the dry state, which allows meticulous analysis of the crystal facets and tomographic 3D reconstruction of the single crystals by high-resolution electron microscopy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Sequence-based generative AI design of versatile tryptophan synthases

Enzymes are powerful and sustainable catalysts, but their widespread application is limited by the difficulty of identifying functional starting points for optimization, creating a major bottleneck in early- stage biocatalyst discovery. Designing libraries of such starting enzymes remains particularly challenging. Here, we use the GenSLM protein language model to generate novel β-subunit of tryptophan synthase (TrpB) enzymes that express in Escherichia coli and are both stable and catalytically active. Many generated TrpBs also display significant substrate promiscuity, outperforming their natural counterparts on non-native substrates. Some even surpass laboratory-evolved TrpBs. Comparison of the most-active and most-promiscuous generated TrpB to its closest natural homolog confirms that the enhanced versatility is absent from the natural enzyme, highlighting the creative potential of generative models. These results demonstrate that the generated TrpBs not only preserve natural structure and function but also acquire non-natural properties, establishing generative models as powerful tools for biocatalyst discovery and engineering.

biocatalysis↗
DOE OSTI2021

Thermal stability and diffusion characteristics of ultrathin amorphous carbon films grown on crystalline and nitrogenated silicon substrates by filtered cathodic vacuum arc deposition

Amorphous carbon (a-C) films are widely used as protective overcoats in many technology sectors, principally due to their excellent thermophysical properties and chemical inertness. The growth and thermal stability of sub-5-nm-thick a-C films synthesized by filtered cathodic vacuum arc on pure (crystalline) and nitrogenated (amorphous) silicon substrate surfaces were investigated in this study. Samples of a-C/Si and a-C/SiN x /Si stacks were thermally annealed for various durations and subsequently characterized by high-resolution transmission electron microscopy (TEM) and electron energy loss spectroscopy (EELS). The TEM images confirmed the continuity and uniformity of the a-C films and the 5-nm-thick SiN x underlayer formed by silicon nitrogenation using radio-frequency sputtering. The EELS analysis of cross-sectional samples revealed the thermal stability of the a-C films and the efficacy of the SiNx underlayer to prevent carbon migration into the silicon substrate, even after prolonged heating. The obtained results provide insight into the important attributes of an underlayer in heated multilayered media for preventing elemental intermixing with the substrate, while preserving the structural stability of the a-C film at the stack surface. An important contribution of this investigation is the establishment of an experimental framework for accurately assessing the thermal stability and elemental diffusion in layered microstructures exposed to elevated temperatures.

42 ENGINEERING↗
DOE OSTI2020

Graphene as reusable substrate for bialkali photocathodes

Bialkali photocathodes, such as cesium potassium antimonide (CsK 2 Sb), can generate a high-brightness electron beam using a high-power green laser. These photocathode materials have potential applications in advanced accelerators and electron microscopes. It is known that the quantum efficiency (QE) of these photocathodes is affected severely by their substrates; however, reusability of the substrates is not well known. Here, we use graphene, silicon (Si), and molybdenum (Mo) substrates to evaluate the effects of substrates on the QE of redeposited CsK 2 Sb photocathodes after thermal cleanings. We found the QE of CsK 2 Sb photocathodes redeposited on a graphene substrate after a thermal cleaning at 500 °C remained largely unchanged. On the other hand, the QE of redeposited photocathodes on Si and Mo substrates after thermal cleaning at the same temperature decreased drastically. We used X-ray photoelectron spectroscopy (XPS) to quantitatively evaluate the residues of photocathodes after thermal cleaning at 400 °C and 500 °C. We found that the Sb, K, and Cs are removed by thermal cleaning at 500 °C for the graphene substrate, but all or the majority of these elements remained on the Si and Mo substrates. The results were consistent with our density functional theory (DFT) calculations for the case of Si, which we investigated. Furthermore, our angle-resolved photoemission spectroscopy (ARPES) on graphene indicated that its intrinsic electronic structure is preserved after photocathode deposition and thermal cleaning at 500 °C. Hence, we attributed the difference in amount of photocathode residue to the unique dangling-bond- free surface of inert graphene. Our results provide a foundation for graphene-based reusable substrates for high-QE semiconductor photocathodes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Reinforcement learning based hybrid bond-order coarse-grained interatomic potentials for exploring mesoscale aggregation in liquid–liquid mixtures

Exploring mesoscopic physical phenomena has always been a challenge for brute-force all-atom molecular dynamics simulations. Although recent advances in computing hardware have improved the accessible length scales, reaching mesoscopic timescales is still a significant bottleneck. Coarse-graining of all-atom models allows robust investigation of mesoscale physics with a reduced spatial and temporal resolution but preserves desired structural features of molecules, unlike continuum-based methods. Here, we present a hybrid bond-order coarse-grained forcefield (HyCG) for modeling mesoscale aggregation phenomena in liquid–liquid mixtures. The intuitive hybrid functional form of the potential offers interpretability to our model, unlike many machine learning based interatomic potentials. We parameterize the potential with the continuous action Monte Carlo Tree Search (cMCTS) algorithm, a reinforcement learning (RL) based global optimizing scheme, using training data from all-atom simulations. The resulting RL-HyCG correctly describes mesoscale critical fluctuations in binary liquid–liquid extraction systems. cMCTS, the RL algorithm, accurately captures the mean behavior of various geometrical properties of the molecule of interest, which were excluded from the training set. The developed potential model along with the RL-based training workflow could be applied to explore a variety of other mesoscale physical phenomena that are typically inaccessible to all-atom molecular dynamics simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Symplectic neural network and its application to charged particle dynamics in electromagnetic fields

Recently, machine learning models have shown many successes in various applications in science and technology. In this work, we focus on the charged particle dynamics, with the development of a class of symplectic neural networks, including a linear version, SympMat, and a nonlinear version, HénonNet. Both are designed to preserve the structure of Hamiltonian systems. We show that they can be used to model relevant Hamiltonian systems of interest in plasma physics and astrophysics, for linear and nonlinear charged particle dynamics, with the potential to bridge multi-scale simulations. These symplectic neural networks are adapted to the applications in plasma simulations and particle-wave interaction with parametric dependence and periodicity, where we have investigated their performance and accuracy. In particular, SympMat is shown to outperform the traditional Boris particle pusher down to the sub-gyroperiod scale in the case of charged particles in uniform magnetic fields. HénonNet successfully predicts the hot electron distribution, which is validated against theoretical results. These results highlight the potential of symplectic neural networks as a trajectory integrator for particle-in-cell simulations or a fast surrogate to replace conventional numerical schemes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗