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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 793 records · Page 44

Targeting the Y-box Binding Protein-1 Axis to Overcome Radiochemotherapy Resistance in Solid Tumors

Multifunctional Y-box binding protein-1 (YB-1) is highly expressed in different human solid tumors and is involved in various cellular processes. DNA damage is the major mechanism by which radiochemotherapy (RCT) induces cell death. On induction of DNA damage, a multicomponent signal transduction network, known as the DNA damage response, is activated to induce cell cycle arrest and initiate DNA repair, which protects cells against damage. YB-1 regulates nearly all cancer hallmarks described to date by participating in DNA damage response, gene transcription, mRNA splicing, translation, and tumor stemness. YB-1 lacks kinase activity, and p90 ribosomal S6 kinase and AKT are the key kinases within the RAS/mitogen-activated protein kinase and phosphoinositide 3-kinase pathways that directly activate YB-1. Thus, the molecular targeting of ribosomal S6 kinase and AKT is thought to be the most effective strategy for blocking the cellular function of YB-1 in human solid tumors. In this review, after describing the prosurvival effect of YB-1 with a focus on DNA damage repair and cancer cell stemness, clinical evidence will be provided indicating an inverse correlation between YB-1 expression and the treatment outcome of solid tumors after RCT. In the interest of being concise, YB-1 signaling cascades will be briefly discussed and the current literature on YB-1 posttranslational modifications will be summarized. Finally, the current status of targeting the YB-1 axis, especially in combination with RCT, will be highlighted.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

On plasticity-enhanced interfacial toughness in bonded joints

Here, the performance and reliability of many structures and components depend on the integrity of interfaces between dissimilar materials. Interfacial toughness Γ is the key material parameter that characterizes resistance to interfacial crack growth, and Γ is known to depend on many factors including temperature. For example, previous work showed that the toughness of an epoxy/aluminum interface decreased 40 % as the test temperature was increased from -60 °C to room temperature (RT). Interfacial integrity at elevated temperatures is of considerable practical importance. Recent measurements show that instead of continuing to decrease with increasing temperature, Γ increases when test temperature is above RT. Cohesive zone finite element calculations of an adhesively bonded, asymmetric double cantilever beam specimen of the type used to measure Γ suggest that this increase in toughness may be a result of R-curve behavior generated by plasticity-enhanced toughening during stable subcritical crack growth with interfacial toughness defined as the critical steady-state limit value. In these calculations, which used an elastic-perfectly plastic epoxy model with a temperature-dependent yield strength, the plasticity-enhanced increase in Γ above its intrinsic value Γ o depended on the ratio of interfacial strength σ* to the yield strength σyb of the bond material. There is a nonlinear relationship between Γ/Γ o and σ*/σ yb with the value Γ/Γ o increasing rapidly above a threshold value of σ*/σ yb . The predicted increase in toughness can be significant. For example, there is nearly a factor of two predicted increase in Γ/Γ o during micrometer-scale crack-growth when σ*/σ yb = 2 (a reasonable choice for σ*/σ yb ). Furthermore, contrary to other reported results, plasticity-enhanced toughening can occur prior to crack advance as the cohesive zone forms and the peak stress at the tip of the original crack tip translates to the tip of the fully formed cohesive zone. These results suggest that plasticity-enhanced toughening should be considered when modeling interfaces at elevated temperatures.

36 MATERIALS SCIENCE↗

Evaluation of the cytotoxic and cellular proteome impacts of food-grade TiO2 (E171) using simulated gastrointestinal digestions and a tri-culture small intestinal epithelial model

Engineered nanomaterials (ENMs) are widely used in the food industry; however, regulations for ENMs in food are still in the early stages of development due to insufficient health data. This study investigated the cytotoxicity and changes to the proteomic profile in an in vitro small intestinal epithelium model after exposure to digested food models containing the ubiquitous engineered particulate food additive, TiO2 (E171). TiO2 at 0.75% or 1.5% (w/w) concentrations in either a fasting food model (FFM) or a standardized food model (SFM) based on American diet were digested using an in vitro oral-gastric-small intestinal simulator, and the resulting digestas were applied to a small intestinal epithelium tri-culture cellular model. Effects on cell layer integrity, cytotoxicity, and oxidative stress were assessed. In order to explore impact on cellular processes beyond basic cytotoxicity, mass spectrometrybased quantitative proteomic analyses of control and exposed tri-culture cells was performed. TiO2 in FFM, but not in SFM, produced significant, dose-dependent cytotoxicity, and at the higher dose caused significant oxidative stress, indicative of a food matrix effect. No significant perturbations of the cellular proteome were observed with TiO2 in either FFM or SFM food models. However, proteins involved in the tricarboxylic acid (TCA) cycle, gluconeogenesis, and translation were up-regulated by digestas from SFM compared to those from FFM, also indicative of food matrix effects in the case of food models alone. Interestingly, the differences in profiles between the two food models was more pronounced in the presence of TiO2 indicative of food matrix effects. Together, these results indicate that TiO2 in a fasting diet may be slightly cytotoxic, and that ingested TiO2 does not significantly alter the epithelial proteome, whereas the food matrix alone can have a dramatic effect on the proteome.

Cao, Xiaoqiong↗

Multimodal analysis for human ex vivo studies shows extensive molecular changes from delays in blood processing

Multi-omic profiling of human peripheral blood is increasingly utilized to identify biomarkers and pathophysiologic mechanisms of disease. The importance of these platforms in clinical and translational studies led us to investigate the impact of delayed blood processing on the numbers and state of peripheral blood mononuclear cells (PBMC) and on the plasma proteome. Similar to previous studies, we show minimal effects of delayed processing on the numbers and general phenotype of PBMCs up to 18 hours. In contrast, profound changes in the single-cell transcriptome and composition of the plasma proteome become evident as early as 4 hours after blood draw. These reflect patterns of cellular activation across diverse cell types that lead to progressive distancing of the gene expression state and plasma proteome from native in situ biology. Differences accumulating during an overnight rest (18 hours) would confound relevant biologic variance related to many underlying disease states.

59 BASIC BIOLOGICAL SCIENCES↗

Implementation of dietary methionine restriction using casein after selective, oxidative deletion of methionine

Dietary methionine restriction (MR) is normally implemented using diets formulated from elemental amino acids (AA) that reduce methionine content to 0.17%. However, translational implementation of MR with elemental AA-based diets is intractable due to poor palatability. To solve this problem and restrict methionine using intact proteins, casein was subjected to mild oxidation to selectively reduce methionine. Diets were then formulated using oxidized casein, adding back methionine to produce a final concentration of 0.17%. The biological efficacy of dietary MR using the oxidized casein (Ox Cas) diet was compared with the standard elemental MR diet in terms of the behavioral, metabolic, endocrine, and transcriptional responses to the four diets. The Ox Cas MR diet faithfully reproduced the expected physiological, biochemical, and transcriptional responses in liver and inguinal white adipose tissue. Collectively, these findings demonstrate that dietary MR can be effectively implemented using casein after selective oxidative reduction of methionine.

59 BASIC BIOLOGICAL SCIENCES↗

A scalable and tunable thermoreversible polymer for 3D human pluripotent stem cell biomanufacturing

Human pluripotent stem cells (hPSCs) are an exciting and promising source to enable cell replacement therapies for a variety of unmet medical needs. Though hPSCs can be successfully derived into numerous physiologically relevant cell types, effective translation to the clinic is limited by challenges in scalable production of high-quality cells, cellular immaturity following the differentiation process, and the use of animal-derived components in culture. To address these limitations, we have developed a fully defined, reproducible, and tunable thermoreversible polymer for high-quality, scalable 3D cell production. Our reproducible synthesis method enables precise control of gelation temperature (24°C–32°C), hydrogel stiffness (100–4000 Pa), and the prevention of any unintended covalent crosslinking. After material optimization, we demonstrated hPSC expansion, pluripotency maintenance, and differentiation into numerous lineages within the hydrogel. Overall, this 3D thermoreversible hydrogel platform has broad applications in scalable, high-quality cell production to overcome the biomanufacturing burden of stem cell therapy.

59 BASIC BIOLOGICAL SCIENCES↗

Overcoming barriers to improved decision-making for battery deployment in the clean energy transition

Decarbonization plans depend on the rapid, large-scale deployment of batteries to sufficiently decarbonize the electricity system and on-road transport. This can take many forms, shaped by technology, materials, and supply chain selection, which will have local and global environmental and social impacts. Current knowledge gaps limit the ability of decision-makers to make choices in facilitating battery deployment that minimizes or avoids unintended environmental and social consequences. These gaps include a lack of harmonized, accessible, and up-to-date data on manufacturing and supply chains and shortcomings within sustainability and social impact assessment methods, resulting in uncertainty that limits incorporation of research into policy making. These gaps can lead to unintended detrimental effects of large-scale battery deployment. To support decarbonization goals while minimizing negative environmental and social impacts, we elucidate current barriers to tracking how decision-making for large-scale battery deployment translates to environmental and social impacts and recommend steps to overcome them.

25 ENERGY STORAGE↗

Tutorial: Langevin Dynamics methods for aerosol particle trajectory simulations and collision rate constant modeling

The Langevin Dynamics (LD) method (also known in the literature as Brownian Dynamics) is routinely used to simulate aerosol particle trajectories for transport rate constant calculations as well as to understand aerosol particle transport in internal and external fluid flows. This tutorial intends to explain the methodological details of setting up a LD simulation of a population of aerosol particles and to deduce rate constants from an ensemble of classical trajectories. We discuss the applicability and limitations of the translational Langevin equation to model the combined stochastic and deterministic motion of particles in fields of force or fluid flow. The drag force and stochastic “diffusion” force terms that appear in the Langevin equation are discussed elaborately, along with a summary of common forces relevant to aerosol systems (electrostatic, gravity, van der Waals, …); a commonly used first order and a fourth order Runge-Kutta time stepping schemes for linear stochastic ordinary differential equations are presented. A MATLAB® implementation of a LD code for simulating particle settling under gravity using the first order scheme is included for illustration. Scaling analysis of aerosol transport processes and the selection of timestep and domain size for trajectory simulations are demonstrated through two specific aerosol processes: particle diffusion charging and coagulation. Fortran® implementations of the first order and fourth order time-stepping schemes are included for simulating the 3D motion of a particle in a periodic domain. Lastly, potential applications and caveats to the usage of LD are included as a summary.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Selective activation of methane C–H bond in the presence of methanol

Direct methane to methanol (MTM) conversion over heterogeneous catalysts is a promising route for valorization of methane. The methane C-H bond activation is considered as the key step of the MTM and is the focus of considerable research activity. However, the formed methanol typically suffers from overoxidation largely due to the cleavage of a methanol C-H bond, whose bond dissociation energy is ca. 0.5 eV lower than that of the methane C-H bond, which usually translates to a transition state energy of the methanol C-H bond cleavage that is ca. 0.55 eV lower than that of methane whenever the reactions proceed through a radical mechanism. Furthermore, we propose a general approach for decreasing the transition state energy difference between the CH 4 and CH 3 OH C-H bond dissociation. When a metal-oxide supported cationic transition metal atom and a neighboring oxygen on the oxide surface serve as the active site, the transition state energy difference through a surface-stabilized pathway can be noticeably narrowed as compared with that of a radical pathway. For Ir, Pt and Rh-doped anatase TiO 2 (101), the CH 4 C-H bond activation can be preferred over that of CH 3 OH at significant methanol mole fraction. Also, for PdAu alloys containing adsorbed oxygen and positively charged Pd, calculations suggest in agreement with recent experiments (Science 367 (6474), 193-197) that the CH 4 C-H bond can be selectively activated in the presence of CH 3 OH.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Towards understanding and predicting the hydronium ion catalyzed dehydration of cyclic-primary, secondary and tertiary alcohols

The varying steric environment of zeolites subtly influences the rates of hydronium-ion-catalyzed dehydration of alcohols containing a cyclohexyl group in aqueous phase. Here, the investigated primary, secondary, and tertiary alcohols show an increasing stabilization of an ionic transition state in this sequence, i.e., an increasing tendency to move from a concerted (E2 mechanism) to a stepwise dehydration (E1 mechanism). Hydronium ions confined in the micropores of MFI and BEA zeolites induced much higher catalyzed rates than those in the aqueous phase. Independent of the reaction mechanism and the environment, however, all alcohols investigated follow one compensation correlation between activation enthalpy and entropy for primary, secondary, and tertiary alcohols, respectively. For a given transition enthalpy, the rate of dehydration is the higher the larger the reaction space (translated to the reaction entropy). Surprisingly, all compensation relations intersect in one point. These dependences for the different alcohols are also reflected in the turnover rates, for which all alcohols also intersect in a common point, which appears to mark the highest reaction rate for dehydration catalyzed by hydronium ions at the investigated temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Superhydrophilicity of $α$-alumina surfaces results from tight binding of interfacial waters to specific aluminols

Understanding the microscopic driving force of water wetting is challenging and important for design of materials. The relations between structure, dynamics and hydrogen bonds of interfacial water can be investigated using molecular dynamics simulations. Here, contact angles at the alumina (0001) and ($11\bar{2}0$) surfaces are studied using both classical molecular dynamics simulations and experiments. To test the superhydrophilicity, the free energy cost of removing waters near the interfaces are calculated using the density fluctuations method. The strength of hydrogen bonds is determined by their lifetime and geometry. Both surfaces are superhydrophilic and the (0001) surface is more hydrophilic. Interactions between surfaces and interfacial waters promote a templating effect whereby the latter are aligned in a pattern that follows the underlying lattice of the surfaces. Translational and rotational dynamics of interfacial water molecules are slower than in bulk water. Hydrogen bonds between water and both surfaces are asymmetric, water-to-aluminol ones are stronger than aluminol-to-water ones. Molecular dynamics simulations eliminate the impacts of surface contamination when measuring contact angles and the results reveal the microscopic origin of the macroscopic superhydrophilicity of alumina surfaces: strong water-to-aluminol hydrogen bonds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Efficient hybrid explicit-implicit learning for multiscale problems

Splitting method is a powerful method to handle application problems by splitting physics, scales, domain, and so on. Many splitting algorithms have been designed for efficient temporal discretization. Here, in this paper, our goal is to use temporal splitting concepts in designing machine learning algorithms and, at the same time, help splitting algorithms by incorporating data and speeding them up. We propose a machine learning assisted splitting scheme which improves the efficiency of the scheme meanwhile preserves the accuracy. We consider a recently introduced multiscale splitting algorithms, where the multiscale problem is solved on a coarse grid. To approximate the dynamics, only a few degrees of freedom are solved implicitly, while others explicitly. This splitting concept allows identifying degrees of freedom that need implicit treatment. In this paper, we use this splitting concept in machine learning and propose several strategies. First, the implicit part of the solution can be learned as it is more difficult to solve, while the explicit part can be computed. This provides a speed-up and data incorporation for splitting approaches. Secondly, one can design a hybrid neural network architecture because handling explicit parts requires much fewer communications among neurons and can be done efficiently. Thirdly, one can solve the coarse grid component via PDEs or other approximation methods and construct simpler neural networks for the explicit part of the solutions. We discuss these options and implement one of them by interpreting it as a machine translation task. This interpretation of the splitting scheme successfully enables us using the Transformer since it can perform model reduction for multiple time series and learn the connection between them. We also find that the splitting scheme is a great platform to predict the coarse solution with insufficient information of the target model: the target problem is partially given and we need to solve it through a known problem which approximates the target. Our machine learning model can incorporate and encode the given information from two different problems and then solve the target problems. We conduct four numerical examples and the results show that our method is stable and accurate.

97 MATHEMATICS AND COMPUTING↗

A conservative, interface-resolved, compressible framework for the modeling and simulation of liquid/gas phase change

This paper presents a method for simulating evaporation in a compressible, interface-resolved framework appropriate for modeling problems of engineering interest. In order to achieve robustness and broad applicability, the method has been designed to discretely enforce consistent mass and thermal energy transport at the phase interface, to globally conserve mass, momentum, and energy, and to be capable of modeling compressible and incompressible systems. Verification is performed via the Sod-shock test, one-dimensional heat conduction, evaporation from a planar interface, and evaporation of three-dimensional droplets. Convergence with increasing mesh resolution is demonstrated in all tested configurations, and conservation is maintained near machine precision for a translating droplet. Conservation and accurate phase change rates are preserved at the low numerical resolutions commonly encountered in engineering calculations. Following verification, the method is validated by comparison to an empirical correlation for evaporating droplets in high temperature crossflow, and the presentation concludes with the simulation of an iso-octane spray at conditions representative of gasoline direct injection. In conclusion, successful verification, validation, and demonstrated practical utility suggest the method to be an accurate, efficient, and robust approach for the study of phase change in engineering systems.

97 MATHEMATICS AND COMPUTING↗

Scalable semidefinite programming approach to variational embedding for quantum many-body problems

In quantum embedding theories, a quantum many-body system is divided into localized clusters of sites which are treated with an accurate ‘high-level’ theory and glued together self-consistently by a less accurate ‘low-level’ theory at the global scale. The recently introduced variational embedding approach for quantum many-body problems combines the insights of semidefinite relaxation and quantum embedding theory to provide a lower bound on the ground-state energy that improves as the cluster size is increased. The variational embedding method is formulated as a semidefinite program (SDP), which can suffer from poor computational scaling when treated with black-box solvers. Here, we exploit the interpretation of this SDP as an embedding method to develop an algorithm which alternates parallelizable local updates of the high-level quantities with updates that enforce the low-level global constraints. Moreover, we show how translation invariance in lattice systems can be exploited to reduce the complexity of projecting a key matrix to the positive semidefinite cone.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Sharp front tracking with geometric interface reconstruction

Here, this paper presents a novel sharp front-tracking method designed to address limitations in classical front-tracking approaches, specifically their reliance on smooth interpolation kernels and extended stencils for coupling the front and fluid mesh. In contrast, the proposed method employs exclusively sharp, localized interpolation and spreading kernels, restricting the coupling to the interfacial fluid cells–those containing the interface/front. This localized coupling is achieved by integrating a divergence-preserving velocity interpolation method with a piecewise parabolic interface calculation (PPIC) and a polyhedron intersection algorithm to compute the indicator function and local interface curvature. Surface tension is computed using the Continuum Surface Force (CSF) method, maintaining consistency with the sharp representation. Additionally, we propose an efficient local roughness smoothing implementation to account for surface mesh undulations, which is easily applicable to any triangulated surface mesh. Building on our previous work, the primary innovation of this study lies in the localization of the coupling for both the indicator function and surface tension calculations. By reducing the interface thickness on the fluid mesh to a single cell, as opposed to the 4–5 cell spans typical in classical methods, the proposed sharp front-tracking method achieves a highly localized and accurate representation of the interface. This sharper representation mitigates parasitic currents and improves force balancing, making it particularly suitable for scenarios where the interface plays a critical role, such as microfluidics, fluid-fluid interactions, and fluid-structure interactions. The proposed method is comprehensively validated and tested on canonical interfacial flow problems, including stationary and translating Laplace equilibria, oscillating droplets, and rising bubbles. The presented results demonstrate that the sharp front-tracking method significantly outperforms the classical approach in terms of accuracy, stability, and computational efficiency. Notably, parasitic currents are reduced by approximately two orders of magnitude and stable results are obtained for parameter ranges where classical front tracking fails to converge.

42 ENGINEERING↗

An explicit, energy-conserving particle-in-cell scheme

We present an explicit temporal discretization of particle-in-cell schemes for the non-relativistic Vlasov equation that results in exact energy conservation when combined with an appropriate spatial discretization. The scheme is inspired by a simple, second-order explicit scheme that conserves energy exactly in the Eulerian context. We show that direct translation to particle-in-cell does not result in strict conservation, but derive a simple correction based on an analytically solvable optimization problem that recovers conservation. While this optimization problem is not guaranteed to have a real solution for every particle, we provide a correction that makes imaginary values extremely rare and still admits $\mathcal{O}$(10 –12 ) fractional errors in energy for practical simulation parameters. We present the scheme in both electrostatic – where we use the Ampère formulation – and electromagnetic contexts. With an electromagnetic field solve, the field update is most naturally linearly implicit, but the more computationally intensive particle update remains fully explicit. Here, we also show how the scheme can be extended to use the fully explicit leapfrog and pseudospectral analytic time-domain (PSATD) field solvers. The scheme is tested on standard kinetic plasma problems, confirming its conservation properties.

Energy conservation↗

The life and accomplishments of Alex Chernov

We report in the last two decades, crystal growth science has experienced explosive expansion. The primary driver has been the vast range of natural and engineered materials whose understanding and optimization require in-depth knowledge of how molecules cooperate to erect perfect three dimensional translationally-symmetric arrays - the miracle that we call crystallization. These huge fundamental and applied advances were possible only because we, the current generation of researchers, stand on the shoulders of our giant forefathers. Alex Chernov is among the tallest of the crystal growth giants.

99 GENERAL AND MISCELLANEOUS↗

Review of particle deposition to and removal from clothing, skin, and hair after a radioactive airborne dispersal event

Explosive Radiological Dispersal Devices (RDD) – aka dirty bombs – are seen as a credible method to carry out a radiological terror attack. After exploding a radioactive source, the radionuclide-laden plume will be blown downwind of ground zero, with particles falling out and potentially depositing on people caught in and under the cloud. Some of these people may not show any sign of radiation sickness and therefore not realize they have been contaminated and may take the radioactive particulate with them on their daily activities, thus spreading the radioactive particulate outside the initially contaminated area. This paper reviews the scientific literature to better understand the rate at which particulate deposits on and is removed from the different “surfaces” of a person, i.e., hair, skin, and clothing. Prior research indicates that: 1) particle deposition is usually higher on skin than on hair and clothing; 2) particle deposition is greater for a person with higher skin moisture, 3) stronger wind increases the deposition flux onto a person, and 4) the fraction of particulate deposited on the hair, skin, and clothing respectively depends on the length of the hair, assuming all the hair surface is available for deposition. The studies taken into consideration show that the largest uncertainty in particulate deposition onto a person is due to clothing type because of the different possible weave arrangements and tightness which translate into differences in actual surface area and surface roughness. A factor of 2-to-20 variation in deposition rate was found. Removal of the particulate from the contaminated person may be due to wind, a person's movement, and/or contact transfer, i.e., by touching a different clean surface. Experiments show that the majority of the particulate is resuspended within 2–6 h mostly depending on the intensity of physical activity. The largest uncertainty in particulate removal from skin depends on the skin moisture, transfer rate of single-contact, and how many objects/people a person touches per hour. No data for hair were found for particle removal and resuspension. The studies considered did not utilize radionuclides directly; however, data on adhesion of radioactive vs. their non-radioactive counterpart have shown that the uncertainty due to the radioactivity of the particles is lower than that due to other factors. In conclusion, an idealized scenario involving a single building in the path of the cloud showed the impact of building-influenced flow on the cloud transport path and mixing, which affects the radiological dose the downwind population is exposed to and consequently the health effects.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗