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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 145 records · Page 8

Combining Three-Dimensional Modeling with Artificial Intelligence to Increase Specificity and Precision in Peptide–MHC Binding Predictions

The reliable prediction of the affinity of candidate peptides for the MHC is important for predicting their potential antigenicity and thus influences medical applications, such as decisions on their inclusion in T cell–based vaccines. In this study, we present a rapid, predictive computational approach that combines a popular, sequence-based artificial neural network method, NetMHCpan 4.0, with three-dimensional structural modeling. We find that the ensembles of bound peptide conformations generated by the programs MODELLER and Rosetta FlexPepDock are less variable in geometry for strong binders than for low-affinity peptides. In tests on 1271 peptide sequences for which the experimental dissociation constants of binding to the well-characterized murine MHC allele H-2D b are known, by applying thresholds for geometric fluctuations the structure-based approach in a standalone manner drastically improves the statistical specificity, reducing the number of false positives. Furthermore, filtering candidates generated with NetMHCpan 4.0 with the structure-based predictor led to an increase in the positive predictive value (PPV) of the peptides correctly predicted to bind very strongly (i.e., Kd < 100 nM) from 40 to 52% (p = 0.027). The combined method also significantly improved the PPV when tested on five human alleles, including some with limited data for training. Overall, an average increase of 10% in the PPV was found over the standalone sequence-based method. The combined method should be useful in the rapid design of effective T cell–based vaccines.

60 APPLIED LIFE SCIENCES↗

Predictive dynamic wetting, fluid–structure interaction simulations for braze run-out

Brazing and soldering are metallurgical joining techniques that use a wetting molten metal to create a joint between two faying surfaces. Here, the quality of the brazing process depends strongly on the wetting properties of the molten filler metal, namely the surface tension and contact angle, and the resulting joint can be susceptible to various defects, such as run-out and underfill, if the material properties or joining conditions are not suitable. In this work, we implement a finite element simulation to predict the formation of such defects in braze processes. This model incorporates both fluid–structure interaction through an arbitrary Eulerian–Lagrangian technique and free surface wetting through conformal decomposition finite element modeling. Upon validating our numerical simulations against experimental run-out studies on a silver-Kovar system, we then use the model to predict run-out and underfill in systems with variable surface tension, contact angles, and applied pressure. Finally, we consider variable joint/surface geometries and show how different geometrical configurations can help to mitigate run-out. This work aims to understand how brazing defects arise and validate a coupled wetting and fluid–structure interaction simulation that can be used for other industrial problems.

36 MATERIALS SCIENCE↗

A separations and purification process for improving yields and meeting fuel contaminant specifications for high-octane gasoline produced from dimethyl-ether over a Cu/BEA catalyst

In this work, we have been developing a three-step conversion of biomass-derived syngas to methanol to dimethyl-ether (DME) to non-aromatic hydrocarbons for use as high-octane gasoline and sustainable aviation fuel. This process produces branched alkanes from DME using a Cu/BEA catalyst and is a promising alternative to other syngas conversion processes such as Fischer-Tropsch to linear alkanes and traditional ZSM-5 catalyzed methanol to aromatic gasoline. In this short article we describe some advances in our understanding related to separations and purification via the use of more detailed experimental speciation in an updated process model involving multiple phase equilibrium-based separation steps. Primary modeled reactor outlet constituents (and weight %) are: C3 and lighter hydrocarbon gases (11.1%), C4s (54.5%), H 2 (1.2%), CO 2 (2.9%), water (5.0%), unreacted DME (16.5%), methanol (2.3%), and C5+ hydrocarbons (6.4%). DME (the primary reactant) and H 2 recycle and reuse are important for the overall process efficiency, and the recycle of C4s is important to increase the C5+ yield via reactivation and homologation. Thus H 2 , C4s, and DME are targeted for recycle, while methanol and water need to be removed from the product to conform with fuel specifications. Model predictions from Aspen Plus using the NRTL-RK property method indicate a fuel composition with C5+ content of 97.1 wt%, with minor constituents: 2.4 wt% C4s, 0.3 wt% methanol, 0.1 wt% DME, 0.03 wt% water, and 0.01 wt% C3s. These ranges of minor components conform with fuel quality requirements, and the modeled product is amenable for unconstrained blending to boost gasoline octane ratings.

09 BIOMASS FUELS↗

An exploration of machine learning models for the determination of reaction coordinates associated with conformational transitions

Determining collective variables (CVs) for conformational transitions is crucial to understanding their dynamics and targeting them in enhanced sampling simulations. Often, CVs are proposed based on intuition or prior knowledge of a system. However, the problem of systematically determining a proper reaction coordinate (RC) for a specific process in terms of a set of putative CVs can be achieved using committor analysis (CA). Identifying essential degrees of freedom that govern such transitions using CA remains elusive because of the high dimensionality of the conformational space. Various schemes exist to leverage the power of machine learning (ML) to extract an RC from CA. Here, we extend these studies and compare the ability of 17 different ML schemes to identify accurate RCs associated with conformational transitions. We tested these methods on an alanine dipeptide in vacuum and on a sarcosine dipeptoid in an implicit solvent. Our comparison revealed that the light gradient boosting machine method outperforms other methods. In order to extract key features from the models, we employed Shapley Additive exPlanations analysis and compared its interpretation with the “feature importance” approach. For the alanine dipeptide, our methodology identifies ϕ and θ dihedrals as essential degrees of freedom in the C7ax to C7eq transition. For the sarcosine dipeptoid system, the dihedrals ψ and ω are the most important for the cisαD to transαD transition. We further argue that analysis of the full dynamical pathway, and not just endpoint states, is essential for identifying key degrees of freedom governing transitions.

Chemistry↗

Peculiarities of beta functions in sigma models

In this paper we consider perturbation theory in generic two-dimensional sigma models in the so-called first-order formalism, using the coordinate regularization approach. Our goal is to analyze the first-order formalism in application to β functions and compare its results with the standard geometric calculations. Already in the second loop, we observe deviations from the geometric results that cannot be explained by the regularization/renormalization scheme choices. Moreover, in certain cases the first-order calculations produce results that are not symmetric under the classical diffeomorphisms of the target space. Although we could not present the full solution to this remarkable phenomenon, we found some indirect arguments indicating that an anomaly similar to that established in supersymmetric Yang-Mills theory might manifest itself starting from the second loop. We discuss why the difference between two answers might be an infrared effect, similar to that in β functions in supersymmetric Yang-Mills theories.

Sigma Models↗

Frank–Kasper Phases of Diblock Copolymer Melts: Self-Consistent Field Results of Two Commonly Used Models

We constructed phase diagrams of conformationally asymmetric diblock copolymer A-B melts using the polymer self-consistent field (SCF) calculations of both the dissipative particle dynamics chain (DPDC) model (i.e., compressible melts of discrete Gaussian chains with the DPD non-bonded potential) and the “standard” model (i.e., incompressible melts of continuous Gaussian chains with the Dirac δ-function non-bonded potential) in the χN-ε plane, where χN and ε characterize, respectively, the repulsion and conformational asymmetry between the A and B blocks, at the A-block volume fraction f = 0.2 and 0.3. Consistent with previous SCF calculations of the “standard” model, σ and A15 are the only stable Frank–Kasper (FK) phases among the five FK (i.e., σ, A15, C14, C15 and Z) phases considered. The stability of σ and A15 is due to their delicate balance between the energetic and entropic contributions to the Helmholtz free energy per chain of the system, which, within our parameter range, increases in the order of σ/A15, Z, and C14/C15. While in general the SCF phase diagrams of these two models are qualitatively consistent, A15 is not stable for the DPDC model at the copolymer chain length N = 10 and f = 0.3; any differences in the SCF phase diagrams are solely due to the differences between these two models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Neutrino Dipole Moments and Radiative Signatures from Partial Compositeness

We investigate composite neutrino models where heavy neutrinos emerge as bound states from a near-conformal strongly coupled sector. Standard Model neutrinos mix with these composite singlets via an inverse seesaw mechanism, where the anomalous scaling dimensions of the composite-sector operators naturally suppress light neutrino masses to sub-eV scales. Matching the conformal dynamics onto low-energy theory yields enhanced electromagnetic transition dipole operators with couplings $d_{μN} \sim 10^{-6}$-$10^{-8}\,\mathrm{GeV}^{-1}$, parametrically larger than the loop-level predictions of minimal Dirac or Majorana models. We carry out a dedicated event-level simulation of the production-and-decay chain $νX \to \mathcal{U} X \to νγX$ and compute the resulting event rates at MiniBooNE and MINERvA within the model, accounting for the composite production cross section and decay kinematics in detail. We further present predictions for the photon energy, angular, and multiplicity distributions. For the benchmark scenarios accessible at these experiments the radiative signal is predominantly single-photon; the composite structure additionally permits fragmentation of the up-scattered state into multiple heavy neutrinos, each decaying as $N\toνγ$, with multi-photon final states emerging for lighter compositeness scales or higher beam energies as a qualitatively new probe of the composite dynamics.

Assi, Benoît [Cincinnati U.; Fermilab] (ORCID:0000↗

Lunar conductivity models from the Apollo 12 magnetometer experiment

A number of conductivity models were investigated for compatibility with Apollo 12 magnetometer data. Except at the highest frequencies, a simple core-crust model is compatible with the observed dayside transfer function, which is expressed as the ratio of the lunar surface field spectrum to the interplanetary magnetic field spectrum. All conductivity profiles exhibit a peak near 1500 km, when the models are constrained to conform to the observed flat response at the higher frequencies. However, at frequencies above .01 Hz the long wavelength limitation of the theoretical model is no longer valid. A plausible explanation for the difference between the north-south and east-west transfer functions is that it is due to a time-varying compression of the remanent (dc) field at the Apollo 12 site by fluctuations in the solar wind plasma.

Sill, W. R.↗

Fun with F24

We study some special features of F 24 , the holomorphic c = 12 superconformal field theory (SCFT) given by 24 chiral free fermions. We construct eight different Lie superalgebras of “physical” states of a chiral superstring compactified on F 24 , and we prove that they all have the structure of Borcherds-Kac-Moody superalgebras. This produces a family of new examples of such superalgebras. The models depend on the choice of an \( \mathcal{N} \) = 1 supercurrent on F 24 , with the admissible choices labeled by the semisimple Lie algebras of dimension 24. We also discuss how F 24 , with any such choice of supercurrent, can be obtained via orbifolding from another distinguished c = 12 holomorphic SCFT, the \( \mathcal{N} \) = 1 supersymmetric version of the chiral CFT based on the E 8 lattice.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Dielectric Properties of Poly(ethylene oxide) from Molecular Dynamics Simulations

The order, conformations and dynamics of poly(oxyethylene) (POE) melts have been investigated through molecular dynamics simulations. The potential energy functions were determined from detailed ab initio electronic structure calculations of the conformational energies of the model molecules 1,2-dimethoxyethane (DME) and diethylether. The x-ray structure factor for POE from simulation will be compared to experiment. In terms of conformation, simulations reveal that chains are extended in the melt relative to isolated chains due to the presence of strong intermolecular O...H interactions, which occur at the expense of intramolecular O...H interactions. Conformational dynamics about the C-C bond were found to be significantly faster than in polymethylene, while conformational dynamics about the C-O bond even faster than the C-C dynamics. The faster local dynamics in POE relative to polymethylene is consistent with C-13 NMR spin-lattice relaxation experiments. Conformational transitions showed significant second-neighbor correlation, as was found for polymethylene. This correlation of transitions with C-C neighbors was found to be reduced relative to C-O neighbors. Dielectric relaxation from simulation will also be compared with experiment.

Smith, Grant D.↗

Bootstrapping boundaries and branes

The study of conformal boundary conditions for two-dimensional conformal field theories (CFTs) has a long history, ranging from the description of impurities in one-dimensional quantum chains to the formulation of D-branes in string theory. Nevertheless, the landscape of conformal boundaries is largely unknown, including in rational CFTs, where the local operator data is completely determined. We initiate a systematic bootstrap study of conformal boundaries in 2d CFTs by investigating the bootstrap equation that arises from the open-closed consistency condition of the annulus partition function with identical boundaries. We find that this deceivingly simple bootstrap equation, when combined with unitarity, leads to surprisingly strong constraints on admissible boundary states. In particular, we derive universal bounds on the tension (boundary entropy) of stable boundary conditions, which provide a rigorous diagnostic for potential D-brane decays. We also find unique solutions to the bootstrap problem of stable branes in a number of rational CFTs. Along the way, we observe a curious connection between the annulus bootstrap and the sphere packing problem, which is a natural extension of previous work on the modular bootstrap. We also derive bounds on the boundary entropy at large central charge. These potentially have implications for end-of-the-world branes in pure gravity on AdS 3 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Development of a microstrip UHF conformal antenna

Low profile, engineering model EMU antennas were constructed. Final data for these antennas meet most of the electrical requirements in a 6 in. x 18 in. x 1.4 in. package which weighs under 2.0 lbs. Coverage data calculated at the design frequencies very nearly meets the design goal of providing a gain greater than or equal to -10 dBi over 80% of a sphere. Recommendations are made for future work directed toward producing an efficient quality design capable of operating in a space environment.

Shields, M. W.↗

Investigation of turbulent flow in highly curved ducts with application to turbomachinery components

Numerical predictions were performed using a semi-elliptic calculation procedure for the case of turbulent flow in passage through a 90 deg bend of square cross section. Two versions of the isotropic turbulent viscosity two equation k-epsilon model were used. The first, the wall function model (WFM), employs the logarithmic law-of-the-wall relation and the notion of equilibrium flow to set all the necessary boundary conditions at the first grid point adjacent to a solid wall. The second model, the Van Driest model (VDM), employs Prandtl's original mixing length formulation, in conjunction with Van Driest's semi-empirical relation for the mixing length, to calculate the turbulent viscosity in the near wall regions of the flow. In this case, boundary conditions for k and epsilon, required to calculate these quantities in the core of the flow, are obtained by matching the mixing length and Reynolds number model formulations in an overlapping region of the flow near the walls. In both cases the results obtained show an improvement over earlier calculations using an elliptic numerical procedure. This is attributed to the finer grids possible in the present work. Of the two models, the VDM formulation shows better overall conformity with the mean flow measurements. Neither model reproduces well the details of the stress distribution as a result of the implied isotropic turbulent viscosity.

Humphrey, J. A. C.↗

Adaptive Conformer Sampling for Property Prediction Using the Conductor-like Screening Model for Real Solvents

The valorization of lignocellulose-derived bioproducts requires effective separation from excessive water. Liquid–liquid extraction is a promising low-energy separation technology, but effective extraction requires solvent selection based on the thermodynamic properties of the bioproduct and solvent components. We propose a computational framework for predicting such properties by developing an adaptive conformer selection approach for use with COSMO-RS (conductor-like screening model for real solvents) calculations. In this framework, molecular dynamics simulations are used to generate many molecular structures (conformers) at representative temperatures in varying solvent environments. Conformers are then clustered based on structural metrics in a low-dimensional space and selected using a mixed-integer quadratic programming problem to iteratively insert a sampled conformer. At each iteration, we determine bioproduct properties using COSMO-RS. Here, we demonstrate the capability of the proposed framework on representative bioproducts to show convergence of the adaptive sampling toward experimentally measured properties with fewer calculations than required by random conformer sampling, enabling the improved screening of solvent systems for liquid-phase separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Coupling between Emissive Defects on Carbon Nanotubes: Modeling Insights

Covalent functionalization of single-walled carbon nanotubes (SWCNTs) with organic molecules results in red-shifted emissive states associated with sp 3 -defects in the tube lattice, which facilitate their improved optical functionality, including single-photon emission. The energy of the defect-based electronic excitations (excitons) depends on the molecular adducts, the configuration of the defect, and concentration of defects. In this work, we model the interactions between two sp 3 -defects placed at various distances in the (6,5) SWCNT using time-dependent density functional theory. Calculations reveal that these interactions conform to the effective model of J-aggregates for well-spaced defects (>2 nm), leading to a red-shifted and optically allowed (bright) lowest energy exciton. H-aggregate behavior is not observed for any defect orientations, which is beneficial for emission. The splitting between the lowest energy bright and optically forbidden (dark) excitons and the pristine excitonic band are controlled by the single-defect configurations and their axial separation. These findings enable a synthetic design strategy for SWCNTs with tunable near-infrared emission.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Satellite Enveloped with STITCHED Engineering Sensors for Detection of Approaching Objects

Today as well as tomorrows spaceborne assets impact almost all areas of national and nuclear security. Spaceborne assets can not only collect and disseminate valuable data, well beyond just the visual, but also track terrestrial-based mobile assets in real-time, and active spaceborne platforms potentially pose serious risk to vulnerable earth-based systems and infrastructures. The capability to defend national spaceborne assets from attack/interference is critical for security interests. This effort supports this mission through the cost-effective preeminent detection of approaching threats to our nation’s vital resources, in order to help secure and trust these high-value assets against the threats of tomorrow. This project develops novel fabrication techniques for conformal, low-profile and lightweight leakywave antenna (LWA) detection/imaging systems, which fuses technical embroidery (TE) and laser ablation (LA) processes with LWA design. Technical embroidery is an emerging field in additive textile manufacturing where flexible materials and functionalized fabrics are created for a wide variety of uses and purposes, while laser ablation is the process of removing material from a solid surface by irradiating it with a laser beam. Here, thin, conformal antenna designs are designed, modeled and fabricated using both TE and LA, to create lightweight, flexible and conformal object detection and imaging radars. This novel development ensures our nation’s ability to field advanced lightweight and conformal technologies to protect spaceborne assets.

42 ENGINEERING↗