Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “angle”

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 91 records · Page 5

Simulation and analysis of small angle scattering (SAS) patterns of Ni-based superalloy microstructures generated by a phase-field model

This paper investigates the relationship between microstructural features and small-angle scattering (SAS) patterns in Ni-based superalloys using a combined phase-field and SAS simulation approach coupled with microstructure analyses. The simulated SAS patterns accurately capture key experimental observations previously reported in the literature, including the time-dependent transition from circular to square-shaped precipitates and the development of anisotropic SAS patterns. Importantly, our analysis reveals the correlations between characteristic length scales extracted from SAS profiles and microstructural descriptors, such as precipitate size and inter-precipitate distance. These findings provide a comprehensive understanding of the link between SAS profiles and microstructure evolution in Ni-based superalloys, offering valuable insights for materials characterization and design.

Microstructure↗

Quasiparticle description of angle-resolved photoemission spectroscopy for SrCuO 2

SrCuO 2 has long been considered a near-archetypal realization of a quasi-one-dimensional (1D) system of interacting electrons with short-range interactions. Within this framework, experimental observations - interpreted through the lens of the 1D Hubbard model - suggest that electron and hole excitations decay into two types of (unphysical) collective bosonic modes: "spinons", which carry the spin degree of freedom, and "holons", which carry the charge degree of freedom. This model, known as spin-charge separation, is most directly evidenced by angle-resolved photoemission spectroscopy (ARPES), where a photo-induced hole decays into a continuum of these excitations. Here we present an alternative perspective grounded in first-principles, self-consistent, and parameter-free many-body perturbation theory. In this revised quasiparticle framework, ARPES can be understood as a one-body effect arising from mild disorder in a long-range antiferromagnetic ground state. the emergence of the so-called spinon branch arises naturally from spin disorder, the anomalous linewidths are accurately captured, and we provide a compelling explanation for the spectral weight observed at the non-magnetic zone boundary. This reinterpretation provides a unified explanation for key experimental signatures previously attributed to spin-charge separation, including features observed in optical conductivity. Additionally, we show that SrCuO 2 exhibits a nontrivial interchain coupling that significantly influences both its one-particle and two-particle spectral functions. By comparing the spectral features of SrCuO 2 with those of La 2 CuO 4 , we argue that SrCuO 2 shares notable similarities with the two-dimensional cuprates-both being rooted in a common CuO 4 plaquette-based molecular orbital framework.

1D cuprates↗

Measurement of the Drell–Yan forward-backward asymmetry and of the effective leptonic weak mixing angle in proton-proton collisions at $\sqrt{s}$ 13 TeV

The forward-backward asymmetry in Drell-Yan production and the effective leptonic electroweak mixing angle are measured in proton-proton collisions at $\sqrt{s}$ = 13 TeV, collected by the CMS experiment and corresponding to an integrated luminosity of 138 fb$^{-1}$. The measurement uses both dimuon and dielectron events, and is performed as a function of the dilepton mass and rapidity. The unfolded angular coefficient $A_4$ is also extracted, as a function of the dilepton mass and rapidity. Using the CT18Z set of parton distribution functions, we obtain $\sin^{2}\theta^\ell_\text{eff}$ = 0.23152 $\pm$ 0.00031, where the uncertainty includes the experimental and theoretical contributions. The measured value agrees with the standard model fit result to global experimental data. This is the most precise $\sin^{2}\theta^\ell_\text{eff}$ measurement at a hadron collider, with a precision comparable to the results obtained at LEP and SLD.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Modulating the Contact Angle between Nonpolar Polymers and SiO 2 Nanoparticles

Polymer–nanoparticle interactions play an important role in determining the morphology and properties of polymer nanocomposites and controlling the polymeric reactions involving heterogeneous catalysts. Here, in this study, we modulate the interactions between nonpolar polymers and nanoparticles by modifying the nanoparticle surface chemistry and quantify the interaction strength through direct contact angle measurements. We investigate the interactions of three nonpolar polymers, polystyrene, polyethylene, and polycyclooctene, with silica nanoparticles whose surface chemistry has been modified by atomic layer deposition of titania and calcium carbonate and by alkyl silanization. Significant differences in polymer–nanoparticle interactions are observed, which can be attributed to differences in the polarizability of the polymers and oxide surface composition. Compared to fully hydrogenated polycyclooctene, polycyclooctene is shown to have stronger interactions with most metal oxides; however, this trend is reversed following alkyl silanization of the silica nanoparticles, which makes the surface of the particles less polar. These differences in interactions can be leveraged to make polymer nanocomposites with unique properties and enable the selective conversion of polymers without the need for separations.

36 MATERIALS SCIENCE↗

Investigating Lignin Aggregation and Interactions with Solvents during γ-Valerolactone (GVL) Pretreatment: A Combined Small Angle Neutron Scattering and Molecular Simulations Study

The strong tendency of lignin to aggregate in solution, coupled with limited understanding of how its molecular structure governs this behavior, hinders its effective utilization in biorefineries. Here, in this study, we investigated the solution behavior of lignin extracted from poplar using γ-valerolactone/water (GVL/H2O, 9:1 wt/wt) through combined small-angle neutron scattering (SANS) and molecular dynamics (MD) simulations. Lignin samples obtained at 100 °C (L100) and 120 °C (L120) differed in β–O–4 content, hydroxyl distribution, and S/G ratio, enabling direct assessment of how molecular composition governs solvation and aggregation. SANS showed that L120 formed rigid and elongated cylindrical aggregates at 25 °C that transitioned to more flexible spheroidal structures by 50 °C and remained stable up to 80 °C, whereas L100 adopted globular aggregates that progressively collapsed with increasing temperature. MD simulations reinforced these observations by showing that S-rich (L120-like) oligomers had larger radii of gyration, stronger solvent coordination driven by methoxy groups, and fewer lignin–lignin contacts. In contrast, G-rich (L100-like) oligomers displayed persistent aggregation and lower solubility. Collectively, these results reveal that increased aromatic methoxylation enhances lignin–solvent interactions and suppresses self-association, whereas reduced methoxylation and higher β–O–4 content promote persistent aggregation into colloid-like structures with restricted solvent penetration into the aggregate interior.

biorefinery pretreatment↗

Uncertainty-Aware Machine Learning for Small-Angle X-ray Scattering Analysis in Autonomous Experimentation

Small-angle X-ray scattering (SAXS) is a powerful high-throughput characterization tool for probing nanoscale structure in native sample environments, providing real-time morphological information such as nanoparticle size and shape during synthesis. However, automated SAXS data analysis for extracting meaningful structural parameters is non-trivial and remains a bottleneck in closed-loop experimentation towards autonomous materials discovery, which demands fast, reliable, and uncertainty-aware data analysis. Here, we develop a machine-learning approach for automated SAXS analysis tailored to closed-loop nanoparticle synthesis. A Random Forest (RF) regression model is trained on 100,000 synthetic SAXS curves generated from polydisperse spherical nanoparticles with realistic background contributions. Using normalized one-dimensional SAXS intensity profiles as input, the RF model directly predicts nanoparticle radius, size polydispersity, and background parameters, while the ensemble standard deviation across trees provides built-in uncertainty quantification (UQ). On synthetic data, we show that combining fit-quality metrics (R 2 , MAE) with thresholds on prediction uncertainty reliably identifies accurate parameter estimates without access to ground truth. We then apply the trained model to 365 experimental SAXS profiles of citrate-reduced gold nanoparticles synthesized using an automated droplet-flow microreactor with in situ SAXS at a synchrotron beamline, classifying the results into high- and low-confidence subsets based on UQ metrics. Finally, we integrate RF-based SAXS analysis into a simulated closed-loop optimization campaign using Gaussian process Bayesian optimization to minimize nanoparticle polydispersity, benchmarking against conventional automated Levenberg–Marquardt fitting. The RF-guided campaign exhibits substantially faster convergence and lower relative opportunity cost (∼0.07 vs ∼0.3), demonstrating that uncertainty-aware machine-learning SAXS analysis significantly enhances the efficiency and robustness of autonomous nanomaterials synthesis workflows.

Bayesian optimization↗

Prediction of the Wave Normal Angle of Proton‐Band EMIC Waves Near Geosynchronous Orbit

We investigate how the wave normal angle (WNA) and polarization of proton-band electromagnetic ion cyclotron (EMIC) waves change as they travel from their source to Earth. This paper marks a significant milestone as the first full-wave simulation of proton-band EMIC waves reflecting from the ionosphere. Our findings show that the WNA can change rapidly during propagation, primarily due to plasma inhomogeneities, such as variations in the Alfvén speed. The wave polarization is strongly related to the WNA, consistent with theory. Newly generated EMIC waves near the equator propagate with a WNA of 0° , then the WNA gradually shifts to 90° as they move toward Earth. In contrast, reflecting waves having 90° of WNA at Earth maintain a relatively larger WNA even near the magnetic equator. As a result, only the newly generated waves close to the source, where the magnetic latitude is less than approximately 20° , show left-handed polarization, while linear polarization remains dominant throughout the rest of the propagation.

EMIC wave↗

Particle dynamics of nanoplastics suspended in water with soil microparticles: insights from small angle neutron scattering (SANS) and ultra-SANS

Small-angle neutron scattering (SANS) and ultra-SANS (USANS) were employed to understand the aggregation behavior and observe the size reduction for nanoplastics (NPs) formed from a biodegradable mulch film, and microparticles of vermiculite (V), an artificial soil, suspended in water in the presence of low convective shear (ex situ stirring) prior to measurements. Neutron contrast matching was employed to minimize the signal of V (by 100-fold) and thereby isolate the signal due to NPs in the neutron beam, as the contrast match point (CMP) for V (67 vol% deuteration of water) differed from that of NPs by more than 20%. The original NPs' size distribution was bimodal: <200 nm and 500–1200 nm, referred to as small and large NPs, i.e., SNPs and LNPs, respectively. In the absence of V, SNPs formed homoaggregates at higher concentrations that decreased with stirring time, while the size of LNPs remained unchanged. The presence of V at 2-fold lower concentration than NPs did not change the size of SNPs but reduced the size of LNPs by nearly 2-fold as stirring time increased. Because the size of SNPs and LNPs did not differ substantially between CMP and 100% D 2 O solvents, it is evident that SNPs and LNPs are mainly composed of NPs and not V. In conclusion, the results suggest that LNPs are susceptible to size reduction through collisions with soil microparticles via convection, yielding SNPs near soil–water interfaces within vadose zones.

Nanoplastics↗

High-throughput small-angle X-ray scattering reveals effective structure factor transitions linked to high-concentration antibody viscosity

High-concentration monoclonal antibody (mAb) formulations are often constrained by elevated viscosity, largely driven by protein–protein interactions, which complicates manufacturing and limits subcutaneous delivery. Early viscosity risk assessment is essential during discovery, yet traditional measurements require large sample volumes, and lack high-throughput capability. Here, we develop a high-throughput small-angle X-ray scattering (SAXS) protocol to detect mAb self-association at dilute concentrations, enabling early predictive insights into high-concentration viscosity. Synchrotron SAXS measurements were conducted for 21 mAbs formulated in a histidine buffer at pH 6.0. An initial subset of 10 mAbs analyzed across 1–150 mg/mL revealed that effective structure factor transitions in the low-q region, indicative of interparticle interactions, consistently emerged below 25 mg/mL. Subsequently, 11 additional mAbs were analyzed at 1–25 mg/mL using automated liquid handling and flow cells to enable high-throughput screening. High-viscosity mAbs exhibited detectable low-q upturns at concentrations ≤10 mg/mL, whereas low-viscosity mAbs showed downturns. A classification criterion based on effective structure factor transitions accurately classified all high- and low-viscosity mAbs at 150 mg/mL, offering a scalable, sample-efficient alternative to conventional methods. These results extend recent findings on the concentration-dependent sensitivity of SAXS to short-range attractions, demonstrating that they can emerge at lower concentrations than previously reported. This study presents the most comprehensive and diverse SAXS dataset for mAbs reported to date within a single formulation, providing a valuable resource for developing and validating coarse-grained models that can more accurately capture intermolecular interactions governing high-concentration solution behavior, thereby enabling rational antibody engineering and improved developability.

36 MATERIALS SCIENCE↗

Assessment of diagenesis in archaeological human second metacarpal bones using the intensity of the small angle X-ray scattering D -period peak

Bone consists mainly of carbonated apatite (cAp) nanoplatelets embedded in a matrix of collagen fibrils. Earlier, high-energy small angle X-ray scattering (SAXS) studies of archaeological adult human second metacarpal bones (mc2) found collagen D-period peaks with high-intensity I D in specimens in which microcomputed tomography (microCT) showed little diagenesis and I D ~ 0 for specimens where microCT revealed severe diagenesis (Park et al. 2022 Int. J. Osteoarchaeol. 32, 170–181 (doi:10.1002/oa.3053); Stock et al. 2022 Int. J. Osteoarchaeol. 32, 120–131 (doi:10.1002/oa.3049)). Here, the present paper uses SAXS at beamline 1-ID, Advanced Photon Source, Argonne National Laboratory and other techniques to study a set of 10 mc2 from an early Medieval cemetery at Greding, Germany. We hypothesized that non-invasive measurement of I D would provide an accurate and rapid (approx. 6 min/specimen) assessment of diagenesis in archaeological mc2. Results of Raman spectroscopy, laboratory microCT and backscattered electron, reflected light and polarized transmitted light microscopies confirmed the SAXS determinations, but lattice parameter values from X-ray diffraction were uncorrelated with I D value. Age-at-death estimates placed the 10 mc2 in three age categories (young adult, middle adult, old adult): lattice parameters from X-ray diffraction were uncorrelated with age at death. Cross-sectional bone area fraction from microCT dropped noticeably for the older age cohort.

Raman spectroscopy↗

Three-dimensional dispersion in the type-II Dirac semimetals PtTe 2 and PdTe 2 revealed through circular dichroism in angle-resolved photoemission spectroscopy

PtTe 2 and PdTe 2 are among the first transition metal dichalcogenides that were predicted to host type-II Dirac fermions, exotic particles prohibited in free space. These materials are layered and air stable, which makes them top candidates for technological applications that take advantage of their anisotropic magnetotransport properties. Here, in this work, we provide a detailed characterization of the electronic structure of PtTe 2 and PdTe 2 using angle-resolved photoemission spectroscopy (ARPES) and density functional theory calculations, offering an alternative interpretation for one of the Dirac-like dispersions in these materials. Through the use of circularly polarized light, we report a different behavior of such dispersion in PdTe 2 compared to PtTe 2 , that we relate to a symmetry analysis of the dipole matrix element. Such analysis reveals a link between the observed circular dichroism and the different momentum-dependent terms in the dispersion of these two compounds, despite their close similarity in crystal structure. Additionally, our data show a clear difference in the circular dichroic signal for the type-II Dirac cones characteristic of these materials, compared to their topologically protected surface states. Our paper provides a useful reference for the ARPES characterization of other transition metal dichalcogenides with topological properties and illustrates the use of circular dichroism as a guide to identify the topological character and attributes of two otherwise equivalent band dispersions.

angle-resolved photoemission spectroscopy↗

A science-driven approach to optimize the design for a biological small-angle neutron scattering instrument

Biological small-angle neutron scattering (SANS) instruments facilitate critical analysis of the structure and dynamics of complex biological systems. However, with the growth of experimental demands and the advances in optical systems design, a new neutron optical concept is necessary to overcome the limitations of current instruments. This work presents an approach to include experimental objectives ( i.e. the science to be supported by a specific neutron scattering instrument) in the optimization of the neutron optical concept. The approach for a proposed SANS instrument at the Second Target Station of the Spallation Neutron Source at Oak Ridge National Laboratory, USA, is presented here. Further, the instrument is simulated with the McStas software package. The optimization process is driven by an evolutionary algorithm using McStas output data, which are processed to calculate an objective function designed to quantify the expected performance of the simulated neutron optical configuration for the intended purpose. Each McStas simulation covers the complete instrument, from source to detector, including realistic sample scattering functions. This approach effectively navigates a high-dimensional parameter space that is otherwise intractable; it allows the design of next-generation SANS instruments to address specific scientific cases and has the potential to increase instrument performance compared with traditional design approaches.

47 OTHER INSTRUMENTATION↗

Insights into distorted lamellar phases with small-angle scattering and machine learning

Lamellar phases are essential in various soft matter systems, with topological defects significantly influencing their mechanical properties. In this report, we present a machine-learning approach for quantitatively analyzing the structure and dynamics of distorted lamellar phases using scattering techniques. By leveraging the mathematical framework of Kolmogorov–Arnold networks, we demonstrate that the conformations of these distorted phases – expressed as superpositions of complex waves – can be reconstructed from small-angle scattering intensities. Through the contour analysis of wave field phase singularities, we obtain the statistics of the spatial distribution of topological defects. Furthermore, we establish that the temporal evolution of these defects can be derived from the time-dependent traveling wave field, informed by the dispersion relation of spectral components. This method opens new avenues for investigating the dynamics of distorted lamellar phases using various dynamic scattering techniques such as neutron spin echo and X-ray photon correlation spectroscopy. These findings enhance our microscopic understanding of how defects influence the physical properties of lamellar materials, with implications for both equilibrium and non-equilibrium states in general lamellar systems.

36 MATERIALS SCIENCE↗

Elongated particles in flow: commentary on small-angle scattering investigations

Here, this work thoroughly examines several analytical tools, each possessing a different level of mathematical intricacy, for the purpose of characterizing the orientation distribution function of elongated objects under flow. Our investigation places an emphasis on connecting the orientation distribution to the small-angle scattering spectra measured experimentally. The diverse range of mathematical approaches investigated herein provide insights into the flow behavior of elongated particles from different perspectives and serve as powerful tools for elucidating the complex interplay between flow dynamics and the orientation distribution function.

36 MATERIALS SCIENCE↗

Shielded magnetic small-angle neutron scattering for characterization of radioactive samples

The development of a Pb-shielded fixture for the execution of a small-angle neutron scattering (SANS)-based workflow for interrogation of highly irradiated nuclear materials has been explored. The Pb shielding was specially designed to reduce the detected radioactivity from the specimen during SANS experiments, and the overall configuration is termed shielded magnetic SANS (SM-SANS). Two FeCrAl-based alloys, C35M and 125YF, were examined with the SM-SANS technique using a free-form size distribution locally monodisperse model in both the as-received and irradiated states. Quantitative values derived from the free-form size distribution were compared with atom probe tomography experiments. Microstructural and compositional parameters determined using the two characterization techniques were complements of each other. The results demonstrate that the SM-SANS technique is an effective means of characterizing nanoscale clustering in irradiated material systems and provides new avenues for investigating radioactive material microstructures.

FeCrAl↗

Quantifying dispersity in size and shape of nanoparticles from small-angle scattering data using machine learning based CREASE

Here, we use machine learning (ML) enhanced computational reverse engineering analysis of scattering experiments (CREASE) to interpret small-angle X-ray scattering (SAXS) data obtained from a system of nanoparticles without a priori knowledge of their exact shapes (e.g. spheres or ellipsoids), sizes (0.5–50 nm) and distributions. The SAXS measurements yielded three categories of scattering profiles exhibiting 'strong', 'weak' and 'no' features. Diminishing features (e.g. broadening or disappearing peaks) in scattering profiles have always been attributed to the presence of significant dispersity in the system. Such featureless SAXS data are not suitable for traditional analysis using analytical models. If one were to fit a relevant analytical model (e.g. the lmfit analytical model for polydisperse spheres) to these 'weak' and 'no' SAXS profiles from our nanoparticle systems, one would obtain non-unique interpretations of the data. Relying on electron microscopy to identify the distributions of nanoparticle shapes and sizes is also unfeasible, especially in high-throughput synthesis and characterization loops. In such situations, to identify the distributions of particle sizes and shapes that could be present in the sample, one must rely on methods like ML-CREASE to interpret the data quickly and output all relevant interpretations about the structure present in the system. The ML-CREASE optimization loop takes the experimental scattering profile as input and outputs multiple candidate solutions whose computed scattering profiles match the SAXS profile input. The ML-CREASE method outputs distributions of relevant structural features, such as the volume fraction of the nanoparticles in the system and the mean and standard deviation of the particle size and aspect ratio, assuming a type of distribution (e.g. normal, log-normal) for size and aspect ratio. We find that, for the SAXS profiles analyzed here, accounting for the shape dispersity along with size dispersity of the nanoparticles using ML-CREASE improved the match between the computed scattering profiles and input experimental profiles.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Desmearing two-dimensional small-angle neutron scattering data by central moment expansions

Resolution smearing is a critical challenge in the quantitative analysis of two-dimensional small-angle neutron scattering (SANS) data, particularly in studies of soft-matter flow and deformation using SANS. Here, we present a central moment expansion technique to address smearing in anisotropic scattering spectra, offering a model-free desmearing methodology. By accounting for directional variations in resolution smearing and enhancing computational efficiency, this approach reconstructs desmeared intensity distributions from smeared experimental data. Computational benchmarks using interacting hard-sphere fluids and Gaussian chain models validate the accuracy of the method, while simulated noise analyses confirm its robustness under experimental conditions. Experimental validation using rheological SANS data from shear-induced micellar structures demonstrates the practicality and effectiveness of the proposed algorithm. The desmearing technique provides a powerful tool for advancing the quantitative analysis of anisotropic scattering patterns, enabling precise insights into the interplay between material microstructure and macroscopic flow behavior.

anisotropic scattering spectra↗

Bridging length scales in hard materials with ultra-small angle X-ray scattering – a critical review

Owing to their exceptional properties, hard materials such as advanced ceramics, metals and composites have enormous economic and societal value, with applications across numerous industries. Understanding their microstructural characteristics is crucial for enhancing their performance, materials development and unleashing their potential for future innovative applications. However, their microstructures are unambiguously hierarchical and typically span several length scales, from sub-ångstrom to micrometres, posing demanding challenges for their characterization, especially for in situ characterization which is critical to understanding the kinetic processes controlling microstructure formation. This review provides a comprehensive description of the rapidly developing technique of ultra-small angle X-ray scattering (USAXS), a nondestructive method for probing the nano-to-micrometre scale features of hard materials. USAXS and its complementary techniques, when developed for and applied to hard materials, offer valuable insights into their porosity, grain size, phase composition and inhomogeneities. We discuss the fundamental principles, instrumentation, advantages, challenges and global status of USAXS for hard materials. Using selected examples, we demonstrate the potential of this technique for unveiling the microstructural characteristics of hard materials and its relevance to advanced materials development and manufacturing process optimization. We also provide our perspective on the opportunities and challenges for the continued development of USAXS, including multimodal characterization, coherent scattering, time-resolved studies, machine learning and autonomous experiments. Our goal is to stimulate further implementation and exploration of USAXS techniques and inspire their broader adoption across various domains of hard materials science, thereby driving the field toward discoveries and further developments.

36 MATERIALS SCIENCE↗