Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “predictive analytics”

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 1,297 records · Page 72

Predicting a Sharp Decline in Selectivity for Catalytic Esterification of Alcohols from van der Waals Interactions

Controlling the selectivity of catalytic reactions is a critical aspect of improving energy efficiency in the chemical industry; thus, predictive models are of key importance. Herein the performance of a heterogeneous, nanoporous Au catalyst is predicted for the complex catalytic self-coupling of the series of C 2 -C 4 alkyl alcohols, based solely on the known kinetics of the elementary steps of the catalytic cycle for methanol coupling, using scaling methods augmented by density functional theory. Notably, a sharp decrease in selectivity for ester formation with increasing molecular weight to favor the aldehyde due to van der Waals interactions of reaction intermediates with the surface was predicted and subsequently verified quantitatively by experiment. Furthermore, the agreement between theory and experiment clearly demonstrates the efficacy of this approach for building a predictive model of catalytic behavior for a homologous set of reactants using a small set of experimental information.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Predicting a Sharp Decline in Selectivity for Catalytic Esterification of Alcohols from van der Waals Interactions

Controlling the selectivity of catalytic reactions is a critical aspect of improving energy efficiency in the chemical industry; thus, predictive models are of key importance. Herein the performance of a heterogeneous, nanoporous Au catalyst is predicted for the complex catalytic self-coupling of the series of C 2 –C 4 alkyl alcohols, based solely on the known kinetics of the elementary steps of the catalytic cycle for methanol coupling, using scaling methods augmented by density functional theory. Notably, a sharp decrease in selectivity for ester formation with increasing molecular weight to favor the aldehyde due to van der Waals interactions of reaction intermediates with the surface was predicted and subsequently verified quantitatively by experiment. Further, the agreement between theory and experiment clearly demonstrates the efficacy of this approach for building a predictive model of catalytic behavior for a homologous set of reactants using a small set of experimental information.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Assessing the role of surface carbon on the surface stability and reactivity of β-Mo 2 C catalysts

Transition-metal carbides, e.g., Mo 2 C, promote industrially important catalytic reactions with activities comparable to precious-metal catalysts. Yet, the nature of the catalytically active sites remains unclear. Herein, density functional theory calculations are applied to systematically assess the stability of low-Miller index facets of β-Mo 2 C as a function of carbon chemical potential (uC) and surface-carbon coverage (nC). When reconstruction of surface carbon is considered to characterize β-Mo 2 C under varying environments, the (111) and (101) surfaces are predicted to be most stable, dominating the Wulff particle surface area across a broad range of uC. The surface-carbon coverage is predicted to steadily increase for all low-index facets under more carburizing reaction conditions, leading to distinct effects on the adsorption energetics for atomic hydrogen and oxygen. Whereas H binding is only slightly affected by surface carbon, O is systematically destabilized. The findings reported indicate that consideration of only bulk-terminated surfaces, and the common focus of theoretical studies on the bulk-truncated, close-packed (100) surface, is likely insufficient to capture the reactivity of the working ..beta..-Mo 2 C catalyst. Similar to metal oxides, β-Mo2C catalysts are predicted to be dynamic materials with surface compositions and reactivities that evolve in response to the environment.

36 MATERIALS SCIENCE↗

Dynamic stability of a crude oil/brine interface: Effect of anion type

The chemical composition of the aqueous phase plays an essential role in water-based enhanced-oil recovery processes. The aqueous phase ionic profile affects the snap-off response of a crude oil-brine system by linking it to the brine-crude oil interfacial rheology. In this work, we focus on the effect of the anion on the snap-off response. To this end, a sample of crude oil from the Minnelusa Sandstone formation in Wyoming was selected, and several aqueous solutions were prepared with salts containing sodium cation and different anions (chlorides, sulfates, and phosphates) at two ionic strength values, 0.6 M and 6 mM, as cases of high- and low-salinity water. Interfacial tension, interfacial viscoelasticity and interface stability were analyzed as functions of aging time using pendant drop, dilatational rheology, and liquid bridge techniques, respectively. Here the results show that solutions with higher ionic strength led to the formation of more rigid interfaces, i.e. higher elastic modulus, and faster formation kinetics. In the low-salinity regime, solutions with polyvalent anions produce more viscoelastic interfaces at faster rates than solutions with monovalent anions. Finally, an excellent correlation (R 2 greater than 0.97) between the relative stability of the interfacial film, predicted in liquid bridge tests, and the ratio of interfacial tension and interfacial elastic modulus was found.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Covalent Functionalization of Nickel Phosphide Nanocrystals with Aryl-Diazonium Salts

Covalent functionalization of Ni 2 P nanocrystals was demonstrated using aryl-diazonium salts. Spontaneous adsorption of aryl functional groups was observed, with surface coverages ranging from 20 to 96% depending on the native reactivity of the salt as determined by the aryl substitution pattern. Increased coverage was possible for low reactivity species using a sacrificial reductant. Functionalization was confirmed using thermogravimetric analysis, Fourier transform infrared spectroscopy, and X-ray photoelectron spectroscopy. The structure and energetics of this nanocrystal electrocatalyst system, as a function of ligand coverage, were explored with density functional theory calculations. The Hammett parameter of the surface functional group was found to linearly correlate with the change in Ni and P core-electron binding energies and the nanocrystal's experimentally and computationally determined work function. The electrocatalytic activity and stability of the functionalized nanocrystals for hydrogen evolution were also improved when compared to the unfunctionalized material, but a simple trend based on electrostatics was not evident. Density functional theory was used to understand this discrepancy, revealing that H adsorption energies on the covalently functionalized Ni 2 P also do not follow the electrostatic trend and are predictive descriptors of the experimental results.

14 SOLAR ENERGY↗

Structure of chalcogen overlayers on Au(111): Density functional theory and lattice-gas modeling

Ordering of different chalcogens, S, Se, and Te, on Au(111) exhibit broad similarities but also some distinct features, which must reflect subtle differences in relative values of the long-range pair and many-body lateral interactions between adatoms. We develop lattice-gas (LG) models within a cluster expansion framework, which includes about 50 interaction parameters. These LG models are developed based on density functional theory (DFT) analysis of the energetics of key adlayer configurations in combination with the Monte Carlo (MC) simulation of the LG models to identify statistically relevant adlayer motifs, i.e., model development is based entirely on theoretical considerations. The MC simulation guides additional DFT analysis and iterative model refinement. Given their complexity, development of optimal models is also aided by strategies from supervised machine learning. The model for S successfully captures ordering motifs over a broader range of coverage than achieved by previous models, and models for Se and Te capture the features of ordering, which are distinct from those for S. More specifically, the modeling for all three chalcogens successfully explains the linear adatom rows (also subtle differences between them) observed at low coverages of ~0.1 monolayer. The model for S also leads to a new possible explanation for the experimentally observed phase with a (5 × 5)-type low energy electron diffraction (LEED) pattern at 0.28 ML and to predictions for LEED patterns that would be observed with Se and Te at this coverage.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effect of void positioning on the detonation sensitivity of a heterogeneous energetic material

We show although it is well-established that voids profoundly influence the initiation and reaction behaviors of heterogeneous energetic materials such as polymer-bonded explosives (PBX) and propellants, there has been little study of how void location in different constituents in the microstructures of such materials affect the macroscale behavior. Here, we use three-dimensional (3D) mesoscale simulations to study how void placement within the reactive grains versus the polymer binder influences the shock-to-detonation transition (SDT) in a polymer-bonded explosive. The material studied here has a microstructure comprised of 75% PETN (pentaerythritol tetranitrate) grains and 25% HTPB (hydroxyl-terminated polybutadiene) polymer binder by volume. Porosities up to 10% in the form of spherical voids distributed in both the grains and polymer are considered. An Arrhenius reactive burn relation is used to model the chemical kinetics of the PETN grains under shock loading, thereby resolving the heterogeneous detonation behavior of the PBX. The influence of void location on the shock initiation sensitivity of the material is quantitatively ranked by comparing the predicted run distance to detonation (RDD) for each sample. The analysis includes inherent quantification of uncertainties arising from the stochastic variations in the microstructure morphologies and void distributions by using statistically equivalent microstructure sample sets (SEMSS), leading to probabilistic formulations for the RDD as a function of shock pressure. The calculations reveal that the location of voids in the composite microstructure significantly affects the RDD. Specifically, voids exclusively within the grains cause the PBX to be more sensitive (having shorter RDD) than voids in the polymer binder. Unique probabilistic relationships are derived to map the probability of observing RDD for each void location material case, allowing for prediction of initiation behavior anywhere in the shock pressure – RDD space. These findings agree with trends reported in the literature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Gaussian approximation of dispersion potentials for efficient featurization and machine-learning predictions of metal–organic frameworks

Energy-related descriptors in machine learning are a promising strategy to predict adsorption properties of metal–organic frameworks (MOFs) in the low-pressure regime. Interactions between hosts and guests in these systems are typically expressed as a sum of dispersion and electrostatic potentials. The energy landscape of dispersion potentials plays a crucial role in defining Henry’s constants for simple probe molecules in MOFs. To incorporate more information about this energy landscape, we introduce the Gaussian-approximated Lennard-Jones (GALJ) potential, which fits pairwise Lennard-Jones potentials with multiple Gaussians by varying their heights and widths. The GALJ approach is capable of replicating information that can be obtained from the original LJ potentials and enables efficient development of Gaussian integral (GI) descriptors that account for spatial correlations in the dispersion energy environment. GI descriptors would be computationally inconvenient to compute using the usual direct evaluation of the dispersion potential energy surface. Here, we show that these new GI descriptors lead to improvement in ML predictions of Henry’s constants for a diverse set of adsorbates in MOFs compared to previous approaches to this task.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Role of n-phenyl-β-naphthylamine in the Acid-Nitroplasticizer Thermal Aging (ANTA) Experiment

A short-term aging study, which was named as Acid-Nitroplasticizer Thermal Aging (ANTA), was conducted to explore the complex chemistry between n-phenyl-β-naphthylamine (PBNA), HNO x , and nitroplasticizer (NP). Aging of NP with PBNA and acid treatments have demonstrated that PBNA is an effective antioxidant and an anti-hydrolytic agent (e.g., inhibits HNO 3 ) and have allowed the identification of nitroso-PBNA (PBNA-NO). The direct conversion of PBNA to PBNA-NO via scavenging of HONO, known as nitrosation, is a preceding event of PBNA nitration, which provides evidence to the HONO elimination as the key mechanism in the early stage of NP aging. Through the kinetics of both nitrosation and nitration, the accuracy of a prediction on PBNA consumption in NP degradation is further improved.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Drell-Yan q T resummation of fiducial power corrections at N 3 LL

We consider Drell-Yan production pp → V*X → LX at small q T << Q, where q T and Q are the total transverse momentum and invariant mass of the leptonic final state L. Experimental measurements require fiducial cuts on L, which in general introduce enhanced, linear power corrections in q T /Q. We show that they can be unambiguously predicted from factorization, and resummed to the same order as the leading-power contribution. For the fiducial q T spectrum, they constitute the complete linear power corrections. We thus obtain predictions for the fiducial q T spectrum to N 3 LL and next-to-leading-power in q T /Q. Matching to full NNLO ($α$$^{2}_{s}$), we find that the linear power corrections are indeed the dominant ones, and once included by factorization, the remaining fixed-order corrections become almost negligible below q T ≲ 40 GeV. We also discuss the implications for more complicated observables, and provide predictions for the fiducial Φ* spectrum at N 3 LL+NNLO. We find excellent agreement with ATLAS and CMS measurements of q T and Φ*. We also consider the $p$$^{ℓ}_{T}$ spectrum. We show that it develops leptonic power corrections in q T /(Q – 2$p$$^{ℓ}_{T}$), which diverge near the Jacobian peak $p$$^{ℓ}_{T}$ ~ Q/2 and must be kept to all powers to obtain a meaningful result there. Doing so, we obtain for the first time an analytically resummed result for the $p$$^{ℓ}_{T}$ spectrum around the Jacobian peak at N 3 LL+NNLO. Our method is based on performing a complete tensor decomposition for hadronic and leptonic tensors. We show that in practice this is equivalent to often-used recoil prescriptions, for which our results now provide rigorous, formal justification. Our tensor decomposition yields nine Lorentz-scalar hadronic structure functions, which for Z/γ* → ℓℓ or W → ℓν directly map onto the commonly used angular coefficients, but also holds for arbitrary leptonic final states. In particular, for suitably defined Born-projected leptons it still yields a LO-like angular decomposition even when including QED final-state radiation. Finally, we also discuss the application to q T subtractions. Including the unambiguously predicted fiducial power corrections significantly improves their performance, and in particular makes them applicable near kinematic edges where they otherwise break down due to large leptonic power corrections.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Two-Dimensional Uranyl Borates: From Conventional to Extreme Synthetic Conditions: Two-Dimensional Uranyl Borates: From Conventional to Extreme Synthetic Conditions

A systematic investigation of uranyl borates under different synthetic conditions resulted in five new 2D compounds, namely, (H 3 O)[(UO 2 )(BO 3 )], Li[(UO 2 )(BO 3 )] · (H 2 O), α-K 4 [(UO 2 ) 5 (BO 3 ) 2 O 4 ], β-K 4 [(UO 2 ) 5 (BO 3 ) 2 O 4 ] and K 2.5 [(UO 2 ) 5 (BO 3 ) 2 O 2.5 (OH) 1.5 ] · (H 2 O) 2.5 . (H 3 O)[(UO 2 )(BO 3 )] and Li[(UO 2 )(BO 3 )] · (H 2 O) were obtained from hydrothermal reactions at 220 °C using the same mineralizer. Both materials possess the uranophane sheet topology with different symmetry of the unit cells. In the structure of (H 3 O)[(UO 2 )(BO 3 )] and Li[(UO 2 )(BO 3 )] · (H 2 O), UO 7 pentagonal bipyramids share edges and vertexes with four BO 3 planar triangles. α-K 4 [(UO 2 ) 5 (BO 3 ) 2 O 4 ] and β-K 4 [(UO 2 ) 5 (BO 3 ) 2 O 4 ] are polytypes. α-K 4 [(UO 2 ) 5 (BO 3 ) 2 O 4 ] was synthesized from a high-temperature solid-state reaction under ambient pressure; whereas β-K 4 [(UO 2 ) 5 (BO 3 ) 2 O 4 ] was obtained from a high-temperature/high-pressure (HT/HP) reaction. Both structures have an identical anion topology, but β-K 4 [(UO 2 ) 5 (BO 3 ) 2 O 4 ] crystallizes in space group with higher symmetry. In K 2.5 [(UO 2 ) 5 (BO 3 ) 2 O 2.5 (OH) 1.5 ] · (H 2 O) 2.5 , which was obtained from a hydrothermal reaction, UO 7 polyhedra share vertexes and edges with two independent BO 3 triangles, forming the most complex uranyl borate layers among all five compounds. The different synthetic routes, novel topologies, thermal behavior and Raman spectra are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Brain ageing in schizophrenia: evidence from 26 international cohorts via the ENIGMA Schizophrenia consortium

Schizophrenia (SZ) is associated with an increased risk of life-long cognitive impairments, age-related chronic disease, and premature mortality. We investigated evidence for advanced brain ageing in adult SZ patients, and whether this was associated with clinical characteristics in a prospective meta-analytic study conducted by the ENIGMA Schizophrenia Working Group. The study included data from 26 cohorts worldwide, with a total of 2803 SZ patients (mean age 34.2 years; range 18–72 years; 67% male) and 2598 healthy controls (mean age 33.8 years, range 18–73 years, 55% male). Brain-predicted age was individually estimated using a model trained on independent data based on 68 measures of cortical thickness and surface area, 7 subcortical volumes, lateral ventricular volumes and total intracranial volume, all derived from T1-weighted brain magnetic resonance imaging (MRI) scans. Deviations from a healthy brain ageing trajectory were assessed by the difference between brain-predicted age and chronological age (brain-predicted age difference [brain-PAD]). On average, SZ patients showed a higher brain-PAD of +3.55 years (95% CI: 2.91, 4.19; I 2 = 57.53%) compared to controls, after adjusting for age, sex and site (Cohen’s d = 0.48). Among SZ patients, brain-PAD was not associated with specific clinical characteristics (age of onset, duration of illness, symptom severity, or antipsychotic use and dose). This large-scale collaborative study suggests advanced structural brain ageing in SZ. Longitudinal studies of SZ and a range of mental and somatic health outcomes will help to further evaluate the clinical implications of increased brain-PAD and its ability to be influenced by interventions.

59 BASIC BIOLOGICAL SCIENCES↗

Automated calculation and convergence of defect transport tensors

Defect diffusion is a key process in materials science and catalysis, but as migration mechanisms are often too complex to enumerate a priori, calculation of transport tensors typically have no measure of convergence and require significant end-user intervention. These two bottlenecks prevent high-throughput implementations essential to propagate model-form uncertainty from interatomic interactions to predictive simulations. In order to address these issues, we extend a massively parallel accelerated sampling scheme, autonomously controlled by Bayesian estimators of statewide sampling completeness, to build atomistic kinetic Monte Carlo models on a state-space irreducible under exchange and space group symmetries. Focusing on isolated defects, we derive analytic expressions for drift and diffusion coefficients, providing a convergence metric by calculating the Kullback–Leibler divergence across the ensemble of diffusion processes consistent with the sampling uncertainty. The autonomy and efficacy of the method is demonstrated on surface trimers in tungsten and Hexa-interstitials in magnesium oxide, both of which exhibit complex, correlated migration mechanisms.

36 MATERIALS SCIENCE↗

Connecting primordial gravitational waves and dark energy

Cosmic acceleration manifested in the early universe as inflation, generating primordial gravitational waves detectable in the cosmic microwave background (CMB) radiation. Cosmic acceleration is occurring again at present as dark energy, detectable in cosmic distance and structure surveys. We explore the intriguing idea of connecting the two occurrences through quintessential inflation by an α-attractor potential without a cosmological constant. For this model we demonstrate robustness of the connection 1 + w 0 ≈ 4/(3N 2 r) between the present day dark energy equation of state parameter w 0 and the primordial tensor to scalar ratio r for a wide range of initial conditions. Analytic and numerical solutions produce current thawing behavior, resulting in a tight relation w a ≈ -1.53(1 + w 0 )≈ -0.2 (4 × 10 -3 /r). Upcoming CMB and galaxy redshift surveys can test this consistency condition. In conclusion, within this model, lack of detection of a dark energy deviation from Λ predicts a higher r, and lack of detection of r predicts greater dark energy dynamics.

79 ASTRONOMY AND ASTROPHYSICS↗

SYMBA: symbolic computation of squared amplitudes in high energy physics with machine learning

The cross section is one of the most important physical quantities in high-energy physics and the most time consuming to compute. While machine learning has proven to be highly successful in numerical calculations in high-energy physics, analytical calculations using machine learning are still in their infancy. In this work, we use a sequence-to-sequence model, specifically, a transformer, to compute a key element of the cross section calculation, namely, the squared amplitude of an interaction. We show that a transformer model is able to predict correctly 97.6% and 99% of squared amplitudes of quantum chromodynamics and quantum electrodynamics processes, respectively, at a speed that is up to orders of magnitude faster than current symbolic computation frameworks. We discuss the performance of the current model, its limitations and possible future directions for this work.

97 MATHEMATICS AND COMPUTING↗

The Polarized Image of a Synchrotron-emitting Ring of Gas Orbiting a Black Hole

Synchrotron radiation from hot gas near a black hole results in a polarized image. The image polarization is determined by effects including the orientation of the magnetic field in the emitting region, relativistic motion of the gas, strong gravitational lensing by the black hole, and parallel transport in the curved spacetime. We explore these effects using a simple model of an axisymmetric, equatorial accretion disk around a Schwarzschild black hole. By using an approximate expression for the null geodesics derived by Beloborodov and conservation of the Walker–Penrose constant, we provide analytic estimates for the image polarization. We test this model using currently favored general relativistic magnetohydrodynamic simulations of M87*, using ring parameters given by the simulations. For a subset of these with modest Faraday effects, we show that the ring model broadly reproduces the polarimetric image morphology. Our model also predicts the polarization evolution for compact flaring regions, such as those observed from Sgr A* with GRAVITY. With suitably chosen parameters, our simple model can reproduce the EVPA pattern and relative polarized intensity in Event Horizon Telescope images of M87*. Under the physically motivated assumption that the magnetic field trails the fluid velocity, this comparison is consistent with the clockwise rotation inferred from total intensity images.

79 ASTRONOMY AND ASTROPHYSICS↗