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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Fisher Forecasting for the DESC with $\texttt{Augur}$

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) has begun its ten-year survey of the entire visible southern hemisphere. To ensure robust cosmological measurements, computationally inexpensive investigations of modeling choices must be made to gauge the performance of proposed cosmological analyses. In this paper, we introduce the $\texttt{Augur}$ tool of the Dark Energy Science Collaboration (DESC), which provides Fisher forecasts for cosmological inference for the LSST using software frameworks designed for DESC science. We test the pipeline by comparing it to forecasts produced by external code and direct sampling of the posterior via nested sampling methods, finding good agreement between all methods. We additionally investigate a range of modeling and hyperparameter choices for a 3$\times$2pt investigation in harmonic space, providing users with diagnostics to obtain reliable forecasts. $\texttt{Augur}$ will be continually updated to be compatible with the other tools in the DESC software ecosystem as additional probes and functionality become available.

Rogozenski, Paul [Carnegie Mellon U.; Arizona U.] ↗
DOE OSTI2022

Mechanically and Thermally Enhanced 3D-Printed Photocurable Polymer Nanocomposites Containing Functionalized Chitin Nanowhiskers by Stereolithography

Additive manufacturing, or simply 3D printing (3DP), where objects are built through layer-wise material deposition, has gained significant academic and industrial attention as a result of the development of advanced and functional materials requiring rapid, customized, and flexible solutions. In the context of green manufacturing, diversifying environmentally and economically sustainable material portfolios is an essential endeavor for the success of 3DP technology that uses widely available, highly valuable, and renewable materials. Here, we used stereolithography (SLA) for processing methacrylate-based photocurable resins containing crab shell-derived chitin nanowhiskers (CNWs), which are surface-functionalized by reactive acrylate groups. Results from full spectral, thermal, structural, and topological analyses corroborate not only the surface functionalization of CNWs but also indicate the presence of these photocurable CNW (pCNW) fillers in the 3D-printed nanocomposites. Owing to the strong interfacial bond induced by the physical and chemical crosslinking between the pCNW and methacrylate (MA) polymer matrix, the internally formulated nanocomposites displayed enhanced thermomechanical properties (e.g., storage modulus and glass transition temperature) compared to those of commercially available pure SLA resins. For instance, the inclusion of 0.5 wt % pCNW improved the tensile strength and stiffness to up to 78 and 71%, respectively, without compromising the toughness and ductility of the printed material. Accordingly, this result also evidences the compatibility between the filler and resin materials. Consequently, the formation of a crosslinked network in the nanocomposite structure results in a higher thermal stability and activation energy (i.e., up to ~79%) for all the hybrid materials than the pristine MA. Finally, the high-resolution SLA print features, dimensional accuracy, and enhanced mechanical performance of our microstructure-forming functionalized chitin-based nanocomposites make them promising materials for a wide range of robust and high-performance industrial applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Incorporating Electronic Information into Machine Learning Potential Energy Surfaces via Approaching the Ground-State Electronic Energy as a Function of Atom-Based Electronic Populations

Machine learning (ML) approximations to density functional theory (DFT) potential energy surfaces (PESs) are showing great promise for reducing the computational cost of accurate molecular simulations, but at present, they are not applicable to varying electronic states, and in particular, they are not well suited for molecular systems in which the local electronic structure is sensitive to the medium to long-range electronic environment. With this issue as the focal point, we present a new machine learning approach called "BpopNN" for obtaining efficient approximations to DFT PESs. Conceptually, the methodology is based on approaching the true DFT energy as a function of electron populations on atoms; in practice, this is realized with available density functionals and constrained DFT (CDFT). Additionally, the new approach creates approximations to this function with neural networks. These approximations thereby incorporate electronic information naturally into a ML approach, and optimizing the model energy with respect to populations allows the electronic terms to self-consistently adapt to the environment, as in DFT. We confirm the effectiveness of this approach with a variety of calculations on LinHn clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Evaluation of accuracy and resolution of the electron beam profile scanner at the Fermilab Main Injector

The objective of this work is to assess the accuracy of measurements made by the Electron Beam Profile Scanner (EBPS), which captures the trajectory of an electron beam with and without a proton beam present. The proton beam induces deflection in the electron beam, which is influenced by proton charges.For high-resolution images, the probe beam needs to be of high intensity, small diameter, and small divergence, evaluated using a YAG screen and an optical transition radiation (OTR) screen. Additionally, the point spread function (PSF) will be calculated to characterize the optical system's properties using ZEMAX software. The capabilities of the Hamamatsu Charge-Injection Device (CID) camera and Kimball Physics electron gun (e-gun) will be considered for accuracy.

Mwaniki, Matilda [IIT, Chicago; Fermilab]↗
DOE OSTI2026

Tailored Silicone Network Architecture for Ultimate Mechanical Reinforcement

Hydrosilylation cured silicone elastomers are subject to reaction inefficiency, leading to incomplete and non-uniform crosslink networks, restricting the potential of mechanical reinforcement. This work investigates pre-synthesized, functional PDMS architectures as additives to improve ultimate mechanical performance relative to conventional single-step curing. Three custom, functional structures were prepared: a partially crosslinked PDMS scaffold (Structure A), a bottle-brush PDMS (Structure B), and a star-shaped PDMS derived from an MQ resin (Structure C). Rheological characterization was used to identify the ultimate design space and proper stoichiometric ratio for Structure A, and confirm successful formation of all structures for suitable incorporation into a base silicone formulation at 30wt%. Mechanical tests indicated that all three structures increased in ultimate tensile strength relative to their single-step counterparts, with Structure A providing additional improvements to toughness (432 vs. 258 kJ/m3) and ultimate elongation (158 vs. 115%). Furthermore, Structure B remained very soft in the unfilled state, while Structure C provided hardness (23 vs. 18 Shore A) and stiffness (780 vs. 420 kPa Young’s modulus) increases. In silica filled systems, Structure A retained increased strength but reduced elongation, while Structure B indicated strong reinforcement in terms of strength, toughness, and stiffness. Thermal analysis on the cure profiles of these materials suggested that pre-formation of network architectures enable a more complete reaction than a single-step process (15.9 vs. 15.1 J/g). Ultimately, these results indicate that tailoring PDMS architecture before the final cure can improve ultimate mechanical properties via improved network development in silicone elastomers. Furthermore, this work offers a promising strategy for designing higher-performance, more tunable silicone formulations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Material properties and mechanical behaviour of functionally graded steel produced by wire-arc additive manufacturing

Metal Big Area Additive Manufacturing is an additive manufacturing technique based on Gas Metal Arc Welding (GMAW) with the option to use many shielding gases, and materials. The system is equipped with a dual torch design allowing for printing different materials; in our study, AISI 410 stainless steel and AWS ER70S-6 mild steel are both printed in the same component. Different print strategies were designed to highlight changes in material and mechanical properties. Deformation behaviour of a materials’ interface was analysed by two-dimensional digital image correlation of uniaxial tensile specimens in displacement-controlled tests. Instances of non-homogeneous local strains adjacent to the interface are observed, as well as variability in mechanical behaviour and microstructure based on location within the print. Optical and electron microscopy are used to evaluate three microstructural zones in a 5 mm range of the interface between mild steel and stainless steel. Areas far from the interface produced polygonal ferrite and pearlite, while areas close to the interface produced acicular ferrite and bainite. Chromium redistribution profiles are dependent on the print strategy used, as shown by scanning electron microscopy with Energy dispersive spectroscopy. Evidence produced via electron backscatter diffraction is shown to support the argument that transformation induced plasticity is not the cause for the non-homogeneous deformation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Loss of Multiple ABCB Auxin Transporters Recapitulates the Major twisted dwarf 1 Phenotypes in Arabidopsis thaliana

FK506-BINDING PROTEIN 42/TWISTED DWARF 1 (FKBP42/TWD1) directly regulates cellular trafficking and activation of multiple ATP-BINDING CASSETTE (ABC) transporters from the ABCB and ABCC subfamilies. abcb1 abcb19 double mutants exhibit remarkable phenotypic overlap with twd1 including severe dwarfism, stamen elongation defects, and compact circinate leaves; however, twd1 mutants exhibit greater loss of polar auxin transport and additional helical twisting of roots, inflorescences, and siliques. As abcc1 abcc2 mutants do not exhibit any visible phenotypes and TWD1 does not interact with PIN or AUX1/LAX auxin transporters, loss of function of other ABCB auxin transporters is hypothesized to underly the remaining morphological phenotypes. Here, gene expression, mutant analyses, pharmacological inhibitor studies, auxin transport assays, and direct auxin quantitations were used to determine the relative contributions of loss of other reported ABCB auxin transporters (4, 6, 11, 14, 20, and 21) to twd1 phenotypes. From these analyses, the additional reduction in plant height and the twisted inflorescence, root, and silique phenotypes observed in twd1 compared to abcb1 abcb19 result from loss of ABCB6 and ABCB20 function. Additionally, abcb6 abcb20 root twisting exhibited the same sensitivity to the auxin transport inhibitor 1-napthalthalamic acid as twd1 suggesting they are the primary contributors to these auxin-dependent organ twisting phenotypes. The lack of obvious phenotypes in higher order abcb4 and abcb21 mutants suggests that the functional loss of these transporters does not contribute to twd1 root or shoot twisting. Analyses of ABCB11 and ABCB14 function revealed capacity for auxin transport; however, their activities are readily outcompeted by other substrates, suggesting alternate functions in planta, consistent with a spectrum of relative substrate affinities among ABCB transporters. Overall, the results presented here suggest that the ABCB1/19 and ABCB6/20 pairs represent the primary long-distance ABCB auxin transporters in Arabidopsis and account for all reported twd1 morphological phenotypes. Other ABCB transporters appear to participate in highly localized auxin streams or mobilize alternate transport substrates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Pulsed Light Synthesis of High Entropy Nanocatalysts with Enhanced Catalytic Activity and Prolonged Stability for Oxygen Evolution Reaction

The ability to synthesize compositionally complex nanostructures rapidly is a key to high-throughput functional materials discovery. In addition to being time-consuming, a majority of conventional materials synthesis processes closely follow thermodynamics equilibria, which limit the discovery of new classes of metastable phases such as high entropy oxides (HEO). Herein, a photonic flash synthesis of HEO nanoparticles at timescales of milliseconds is demonstrated. By leveraging the abrupt heating and cooling cycles induced by a high-power-density xenon pulsed light, mixed transition metal salt precursors undergo rapid chemical transformations. Hence, nanoparticles form within milliseconds with a strong affinity to bind to the carbon substrate. Oxygen evolution reaction (OER) activity measurements of the synthesized nanoparticles demonstrate two orders of magnitude prolonged stability at high current densities, without noticeable decay in performance, compared to commercial IrO 2 catalyst. This superior catalytic activity originates from the synergistic effect of different alloying elements mixed at a high entropic state. It is found that Cr addition influences surface activity the most by promoting higher oxidation states, favoring optimal interaction with OER intermediates. The proposed high-throughput method opens new pathways toward developing next-generation functional materials for various electronics, sensing, and environmental applications, in addition to renewable energy conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Additive Manufacturing of Controlled Porous Elastomeric Nanocomposites for Enhanced Sensing Function

Sensors manufactured using piezoresistive elastomeric nanocomposites have a wide range of applications in many fields such as structural health monitoring, robotics, and biomedical industries. Additive manufacturing of these sensors, achieved using Direct Ink Writing (DIW), has provided numerous advantages including increased sensitivity and the fabrication of complex geometry. However, solid sensors manufactured either additively or using conventional methods, display a greater level of hysteresis, especially at strains higher than 10%, which limits their sensitivity. The solid sensors also display a greater level of piezoresistive relaxation where the resistance change with time either in a static or dynamic loading environment. Porosity can be introduced in the form of varying infill patterns and densities to reduce bulk material effects. In this paper, a lattice structure with four infill densities are investigated, and the samples are printed using a grid infill pattern. The fabricated samples are characterized using a scanning electron microscope (SEM) to validate the microstructural features and layer bonding. The pressure-sensing capability of each sensor is investigated using cyclic compression loading at various strain levels. Sensing results show that an increase in sensitivity, as well as a decrease in hysteresis with an increase in porosity, compared to solid samples (100% in-fill). The highest porosity was measured to be 62.3% with a corresponding 112% increase in the gauge factor compared to the solid bulk. These results indicate that introducing porosity using DIW is a sensible strategy to improve the piezoresistive performance of nanocomposites and to allow for the tunability of sensing capacity in pressure sensors

Sukati, Musa↗
DOE OSTI2024

Tailoring Hierarchical Structure and Rare Earth Affinity of Compositionally Identical Polymers via Sequence Control

Macromolecule sequence, structure, and function are inherently intertwined. While well-established relationships exist in proteins, they are more challenging to define for synthetic polymer nanoparticles due to their molecular weight, sequence, and conformational dispersities. Furthermore, to explore the impact of sequence on nanoparticle structure, we synthesized a set of 16 compositionally identical, sequence-controlled polymers with distinct monomer patterning of dimethyl acrylamide and a bioinspired, structure-driving di(phenylalanine) acrylamide (FF). Sequence control was achieved through multiblock polymerizations, yielding unique ensembles of polymer sequences which were simulated by kinetic Monte Carlo simulations. Systematic analysis of the global (tertiary- and quaternary-like) structure in this amphiphilic copolymer series revealed the effect of multiple sequence descriptors: the number of domains, the hydropathy of terminal domains, and the patchiness (density) of FF within a domain, each of which impacted both chain collapse and the distribution of single- and multichain assemblies. Furthermore, both the conformational freedom of chain segments and local-scale, β-sheet-like interactions were sensitive to the patchiness of FF. To connect sequence, structure, and target function, we evaluated an additional series of nine sequence-controlled copolymers as sequestrants for rare earth elements (REEs) by incorporating a functional acrylic acid monomer into select polymer scaffolds. We identified key sequence variables that influence the binding affinity, capacity, and selectivity of the polymers for REEs. Collectively, these results highlight the potential of and boundaries of sequence control via multiblock polymerizations to drive primary sequence ensembles hierarchical structures, and ultimately the functionality of compositionally identical polymeric materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Solution and sensitivity analysis of nonlinear equations using a hypercomplex-variable Newton-Raphson method

Here, the classical Newton-Raphson (NR) method for solving nonlinear equations is enhanced in two ways through the use of hypercomplex variables and algebra. In particular, i) the Jacobian is computed in a highly accurate and automated way, and ii) the derivative of the solution to the nonlinear equations is computed with respect to any parameter contained within the system of equations. These advances provide two significant enhancements in that it is straightforward to provide an accurate Jacobian and to construct a reduced order model (ROM) of arbitrary order with respect to any parameter of the system. The ROM can then be used to approximate the solution for other parameter values without requiring additional solutions of the nonlinear equations. Several case studies are presented including 1D and 2D academic examples with fully functioning Python code provided. Additionally, a case of study of the catenary of an elastic cable subject to its own weight and a vertical point load. Derivatives up to 10th order were computed with respect to material, loading, and geometrical parameters. The derivatives were used to generate reduced order models of the cable deformation and reaction forces at its ends with respect to multiple input parameters. Results show that from a single hypercomplex evaluation of the cable under a single vertical point load, it is possible to generate an accurate reduced order model capable of predicting the cable deformation with 1.5 times the load in the opposite direction and with 3.5 times the load in the same direction without resolving the system of equations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

On the Robustness of Network Community Structure Under Addition of Edges

Communities represent important functional modules in networked systems. A key goal in preserving such communities is understanding their robustness under perturbations. Previous research has studied the impact of node removals and edge removals on the community structure. However, the impact of edge additions on the robustness of the community structure is relatively unknown. Edge additions or false positive edges may simulate measurement errors or external exceptional events that threaten the functionality of networked systems. Here, we study the impact of edge additions on the community structure using Lancichinetti-Fortunato-Radicchi (LFR) benchmark networks. We show that, for a fixed network size, the impact of edge additions is greater on networks with initially weak community structure than on networks with strongly clustered structures. In addition, we find that the perception of the impact is also dependent on the community detection algorithm used to uncover communities. In particular, we found that modularity-based methods such as Leiden and Louvain are less affected than information-theoretic and message passing-based methods such as Infomap and Label Propagation. Our results demonstrate that edge addition can (a) significantly impact the community structure of networks based on their initial conditions, and (b) the perception of the impact is dependent on the community detection algorithm used. We describe limitations, open challenges, and how this methodology can inform the design of resilient networked systems under edge additions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Structural heterogeneity in non-crystalline Te x Se1−x thin films

Rapid crystallization behavior of amorphous TexSe1−x thin films limits the use of these alloys as coatings and in optoelectronic devices. Understanding the short- and medium-range ordering of the amorphous structure and the fundamental physics governing the crystallization of the films is crucial. Although the lack of long range crystalline order restricts the characterization of the amorphous films, electron microscopy offers a way to extract information about the nanoscale ordering. In this paper, the local ordering of amorphous TexSe1−x thin films with x=0.22, 0.61, 0.70, 0.90, and 1 grown by thermal evaporation is investigated using radial distribution function (RDF) and fluctuation electron microscopy (FEM) analysis. RDF results show that the nearest-neighbor distances of selenium (Se) and tellurium (Te) in their crystalline structure are preserved, and their bond lengths increase with the addition of Te. Density functional theory (DFT) calculations predict structures with interatomic distances similar to those measured experimentally. Additionally, fluctuations in atomic coordination are analyzed. Medium range order (MRO) analysis obtained from FEM and DFT calculations suggests that there are at least two populations within the chain network structure, which are close to the Se–Se and Te–Te intrachain distances. For the binary alloy with x > 0.61, TexSe1−x, Te–Te like populations increase and Te fragments might form, suggesting that the glass forming ability decreases rapidly.

Sari, Bengisu (ORCID:0000000244217098)↗
DOE OSTI2021

Unveiling the Dynamics of KRAS4b on Lipid Model Membranes

Abstract Small GTPase proteins are ubiquitous and responsible for regulating several processes related to cell growth and differentiation. Mutations that stabilize their active state can lead to uncontrolled cell proliferation and cancer. Although these proteins are well characterized at the cellular scale, the molecular mechanisms governing their functions are still poorly understood. In addition, there is limited information about the regulatory function of the cell membrane which supports their activity. Thus, we have studied the dynamics and conformations of the farnesylated KRAS4b in various membrane model systems, ranging from binary fluid mixtures to heterogeneous raft mimics. Our approach combines long time-scale coarse-grained (CG) simulations and Markov state models to dissect the membrane-supported dynamics of KRAS4b. Our simulations reveal that protein dynamics is mainly modulated by the presence of anionic lipids and to some extent by the nucleotide state (activation) of the protein. In addition, our results suggest that both the farnesyl and the polybasic hypervariable region (HVR) are responsible for its preferential partitioning within the liquid-disordered (Ld) domains in membranes, potentially enhancing the formation of membrane-driven signaling platforms. Graphic Abstract

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Post synthetic amine functionalization of MOF-808 for CO 2 sorption via ligand exchange and Michael addition

Post synthetic modification of metal organic frameworks presents a viable route for amine functionalization which can significantly enhance CO 2 sorption capacity. We present a facile means of amine incorporation using limited synthetic steps and low-cost reagents that results in a high density of primary alkyl amines distributed through a zirconium-based metal organic framework (MOF). Both the MOF synthesis and the post synthetic modification take place under aqueous conditions and result in strongly bound molecular amines available for sorbate interaction throughout the MOF pores. Furthermore, this amine incorporation protocol results in a significantly increased CO 2 capacity compared with the unmodified MOF-808. Specifically, CO 2 isotherms collected at 298 K for the unmodified MOF-808 show uptakes of 0.06, 0.2, and 1.2 mmol/g at 4, 15, and 100 kPa, respectively, which can be compared with 0.3, 0.7, and 2.5 mmol/g for the glycine grafted MOF-808 and 0.5, 0.9, and 2.3 mmol/g for ethylenediamine grafted MOF-808.

Amine sorbent↗
DOE OSTI2024

STAT7 v1.2 User Guide: The STAT7 Code for Statistical Propagation of Uncertainties in Steady-State Thermal Hydraulics Analysis of Plate-Fueled Reactors

The STAT7 software was developed to perform steady-state, single-phase thermal hydraulics analysis of plate-fueled reactors based on statistical propagation of uncertainties. Application of the software is for non-power research and test reactors, including conversion to low-enriched uranium fuel of U.S. High-Performance Research Reactors such as Massachusetts Institute of Technology Research Reactor. Since it can be necessary to repeat analysis during fuel reloading, STAT7 accommodates flexibility in analyzing many realistic aspects of reactor fuel management. STAT7 uses a Monte Carlo approach to model uncertainty in common fuel fabrication parameters and other key reactor operating parameters required for thermal hydraulics analyses of research and test reactors. These safety calculations are ultimately intended to protect against high fuel plate temperatures due to critical heat flux, or onset of flow instability. STAT7 supports water properties based on the IAPWS-IF97 functions (The International Association for the Properties of Water and Steam Industrial Formulation 1997 for the Thermodynamic Properties of Water and Steam) in addition to the fit functions. STAT7 predicts axial profiles of fuel, cladding, and coolant temperature along a lateral stripe that runs the full length of the fuel plate from the bottom to the top. STAT7 can simultaneously analyze all of the axial nodes of all of the fuel plates and all of the coolant channels for one latera stripe of a fuel element. Power splits are calculated for each axial node of each plate to determine how much of the power goes out each face of the plate. By running STAT7 multiple times, full core analysis can be performed by analyzing the margin to onset of nucleate boiling and onset of flow instability for each axial node of each stripe of each plate of each fuel element in the core.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Remote Hydroamination of Disubstituted Alkenes by a Combination of Isomerization and Regioselective N–H Addition

Remote hydrofunctionalizations of alkenes incorporate functional groups distal to existing carbon–carbon double bonds. While remote carbonylations are well-known, remote hydrofunctionalizations are most common for addition of relatively nonpolar B–H, Si–H, and C–H bonds with alkenes. We report a system for the remote hydroamination of disubstituted alkenes to functionalize an alkyl chain selectively at the subterminal, unactivated, methylene position. Critical to the high regioselectivity and reaction rates are the electronic properties of the substituent on the amine and the development of the ligand DIP-Ad-SEGPHOS by evaluating the steric and electronic effects of ligand modules on reactivity and selectivity. The remote hydroamination is compatible with a broad scope of alkenes and aminopyridines and enables the regioconvergent synthesis of amines from an isomeric mixture of alkenes. In conclusion, the products can be derivatized by nucleophilic aromatic substitution on the amino substituent with a variety of nucleophiles.

Hydrocarbons↗
DOE OSTI2020

Sensitivity of D meson azimuthal anisotropies to system size and nuclear structure

Recent experimental data at the Large Hadron Collider (LHC) confirmed that the soft sector azimuthal anisotropies in central XeXe collisions are sensitive to deformations in the wave function of the Xenon nucleus. Additionally, the CMS experiment found that D meson flow is slightly suppressed compared to other particle species when considering quark number scaling in small systems of pPb compared to PbPb. In this talk we used the D and B Mesons Modular (DAB-MOD) code coupled to Trento+v-USPhydro to calculate the R AA and v n ’s of D mesons using different energy loss models and Langevin techniques. Comparing D mesons R AA and v n in PbPb to XeXe collisions it is found that in central collisions D meson azimuthal anisotropies are sensitive to details in the nuclear structure wave function of Xenon. Additionally, we find that in mid-central collisions the smaller system size of XeXe suppresses D meson flow.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗