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At least 577 records · Page 32

Mechanisms for high creep resistance in alumina forming austenitic (AFA) alloys

Castable alumina forming austenitic (AFA) alloys have demonstrated superior creep life and oxidation resistance at temperatures exceeding 800⁰C. Despite the success in the applicability of these alloys in extreme environments, there is a limited understanding of the deformation modes and the influence of each alloying element guiding the alloy design strategies that could further enhance the creep strength of these AFA alloys, particularly at temperatures at and above 900⁰C. In this study, we reveal the mechanism underpinning the superior creep performance of castable AFA alloys that involves suppressing primary carbide formation through minor compositional modification. This approach results in a three-fold increase in creep strength at 900⁰C and 50 MPa. Here, by employing integrated characterization techniques, we analyzed the microstructures of two AFA alloys, both before and after the creep process. We discovered that the suppression of primary carbides permits the in-situ clustering of now-available interstitial elements such as C, Si, and O during high-temperature creep. This improved solid solution strengthening and reduced stacking fault energy of the alloy. Moreover, it also enabled controlled secondary carbide formation during testing, further improving the creep resistance. These findings underline the important interplay between alloy composition, microstructure, and creep properties, and offer a promising design strategy for developing economical high-temperature Fe-based alloys suitable for advanced applications.

36 MATERIALS SCIENCE↗

Investigating Ternary Li–Mg–Si Zintl Phase Formation and Evolution for Si Anodes in Li-Ion Batteries with Mg(TFSI) 2 Electrolyte Additive

Improved electrochemical performance of Si was recently reported by adding multivalent cation salts (such as Mg 2+ , Al 3+ , Ca 2+, etc.) in the electrolyte. This is achieved via the formation in an in situ manner of relatively more stable Li-M-Si ternary phases with less chemical reactivity. These phases stabilize Si anions and thus reduce side reactions with electrolytes at the surface and eventually benefit the overall electrochemistry. To understand the mechanism of ternary Zintl phase formation and its dynamics upon lithiation/delithiation, high-resolution solid-state 7 Li and 29 Si nuclear magnetic resonance (NMR) are utilized to directly probe the local Li and Si environments on Si electrodes harvested from coin and pouch cells at various states of (de)lithiation. The NMR spectra along with the electrochemical characterization reveal that lithiation of Si starts from the surface Si-O layer further confirmed by 7 Li– 29 Si cross-polarization NMR. Lithiation progresses with heterogeneous silicon clustering with Si -4 anions at high states of lithiation. At a fully lithiated state, the formation of overlithiated Si species is detected. At a low-voltage region (below 100 mV), direct evidence for Mg-ion insertion is found, postulated by two possible mechanisms: ion exchange with fully or overlithiated binary domains (Li 3.75+x Si) and/or a coinsertion with slightly underlithiated domains (similar to Li 3.55 Si). Upon delithiation, Li extraction starts from overlithiated Si domains. No evidence is found for electrochemical Mg removal. Evidence for a lithium-deficient Li y Mg 0.1 Si phase is found as a result of Li removal during charging. This investigation sheds light on the possible mechanisms of a new Si anode chemistry, which could enable the development of stable Si-based anodes for lithium-ion batteries.

25 ENERGY STORAGE↗

Unravelling the mechanism of pressure induced polyamorphic transition in an inorganic molecular glass

The atomic structure of a germanium doped phosphorous selenide glass of composition Ge 2.8 P 57.7 Se 39.5 is determined as a function of pressure from ambient to 24 GPa using Monte-Carlo simulations constrained by high energy x-ray scattering data. The ambient pressure structure consists primarily of P 4 Se 3 molecules and planar edge shared phosphorus rings, reminiscent of those found in red phosphorous as well as a small fraction of locally clustered corner-sharing GeSe 4 tetrahedra. This low-density amorphous phase transforms into a high-density amorphous phase at ~6.3 GPa. The high-pressure phase is characterized by an extended network structure. The polyamorphic transformation between these two phases involves opening of the P 3 ring at the base of the P 4 Se 3 molecules and subsequent reaction with red phosphorus type moieties to produce a cross linked structure. The compression mechanism of the low-density phase involves increased molecular packing, whereas that of the high pressure phase involves an increase in the nearest-neighbor coordination number while the bond angle distributions broaden and shift to smaller angles. The entropy and volume changes associated with this polyamorphic transformation are positive and negative, respectively, and consequently the corresponding Clapeyron slope for this transition would be negative. This result has far reaching implications in our current understanding of the thermodynamics of polyamorphic transitions in glasses and glass-forming liquids.

42 ENGINEERING↗

Constraining primordial non-Gaussianity from the large scale structure two-point and three-point correlation functions

Surveys of cosmological large-scale structure (LSS) are sensitive to the presence of local primordial non-Gaussianity (PNG), and may be used to constrain models of inflation. Local PNG, characterized by f NL ⁠, the amplitude of the quadratic correction to the potential of a Gaussian random field, is traditionally measured from LSS two-point and three-point clustering via the power spectrum and bi-spectrum. We propose a framework to measure f NL using the configuration space two-point correlation function (2pcf) monopole and three-point correlation function (3pcf) monopole of survey tracers. Our model estimates the effect of the scale-dependent bias induced by the presence of PNG on the 2pcf and 3pcf from the clustering of simulated dark matter haloes. We describe how this effect may be scaled to an arbitrary tracer of the cosmological matter density. The 2pcf and 3pcf of this tracer are measured to constrain the value of f NL ⁠. In LSS surveys, the effect of imaging systematics on two-point statistics is often degenerate with the PNG signal. Our proposed model employs three-point statistics primarily to break this degeneracy. Using simulations of luminous red galaxies observed by the Dark Energy Spectroscopic Instrument (DESI), we demonstrate the accuracy and constraining power of our method. Our forecast indicates the ability to constrain f NL to a precision of σf NL ≈ 22 with one year of DESI survey data, as well as the ability to constrain the imaging systematic weights in situ.

early Universe↗

Dipolar Spin Ice Regime Proximate to an All-In-All-Out Néel Ground State in the Dipolar-Octupolar Pyrochlore Ce 2 Sn 2 O 7

The dipolar-octupolar (DO) pyrochlores, R 2 M 2 O 7 ( R = Ce , Sm , Nd ), are key players in the search for realizable novel quantum spin liquid (QSL) states as a large parameter space within the DO pyrochlore phase diagram is theorized to host QSL states of both dipolar and octupolar nature. New single crystals and powders of Ce 2 Sn 2 O 7 , synthesized by hydrothermal techniques, present an opportunity for a new characterization of the exchange parameters in Ce 2 Sn 2 O 7 using the near-neighbor X Y Z model Hamiltonian associated with DO pyrochlores. Utilizing quantum numerical linked cluster expansion fits to heat capacity and magnetic susceptibility measurements, and classical Monte Carlo calculations to the diffuse neutron diffraction of the new hydrothermally grown Ce 2 Sn 2 O 7 samples, we place Ce 2 Sn 2 O 7 ’s ground state within the ordered dipolar all-in-all-out (AIAO) Néel phase, with quantum Monte Carlo calculations showing a transition to long-range order at temperatures below those accessed experimentally. Indeed, our new neutron diffraction measurements on the hydrothermally grown Ce 2 Sn 2 O 7 powders show a broad signal at low scattering wave vectors, reminiscent of a spin ice, in striking contrast from previous powder neutron diffraction on samples grown from solid-state synthesis, which found diffuse scattering at high scattering wave vectors associated with magnetic and suggested an octupolar quantum spin ice state. We conclude that new hydrothermally grown Ce 2 Sn 2 O 7 samples host a finite-temperature proximate dipolar spin ice phase, above the expected transition to AIAO Néel order. Published by the American Physical Society 2024

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Droplets of bosons at a narrow resonance

We consider bosons interacting through a narrow s-wave resonance. Such a resonance is characterized by an infinite scattering length and a large and negative effective range r 0 . We argue that any number N≥3 of bosons can form a self-bound cluster with the binding energy per particle increasing as N 2 for 1≪N≪(−r 0 /a) 1/2 , where abg is the background scattering length (between atoms and molecules). In the opposite limit N≫(−r 0 /a) 1/2 , bosons form droplets with binding energy per particle saturating to a constant value independent of the particle number. Here, the stability of clusters and droplets when the interaction is detuned from the resonance is also studied.

Wang, Ke [University of Chicago, IL (United States↗

Evolutionary transition to the ectomycorrhizal habit in the genomes of a hyperdiverse lineage of mushroom-forming fungi

The ectomycorrhizal (ECM) symbiosis has independently evolved from diverse types of saprotrophic ancestors. In this study, we seek to identify genomic signatures of the transition to the ECM habit within the hyperdiverse Russulaceae. We present comparative analyses of the genomic architecture and the total and secreted gene repertoires of 18 species across the order Russulales, of which 13 are newly sequenced, including a representative of a saprotrophic member of Russulaceae, Gloeopeniophorella convolvens. The genomes of ECM Russulaceae are characterized by a loss of genes for plant cell wall-degrading enzymes (PCWDEs), an expansion of genome size through increased transposable element (TE) content, a reduction in secondary metabolism clusters, and an association of small secreted proteins (SSPs) with TE ‘nests’, or dense aggregations of TEs. Here, some PCWDEs have been retained or even expanded, mostly in a species-specific manner. The genome of G. convolvens possesses some characteristics of ECM genomes (e.g. loss of some PCWDEs, TE expansion, reduction in secondary metabolism clusters). Functional specialization in ECM decomposition may drive diversification. Accelerated gene evolution predates the evolution of the ECM habit, indicating that changes in genome architecture and gene content may be necessary to prime the evolutionary switch.

59 BASIC BIOLOGICAL SCIENCES↗

Neutrons in Structural Biology: Challenges and Opportunities (Workshop Report)

Gaining a thorough understanding of biological systems requires building our knowledge about biological processes from the level of atoms and electrons, and up to whole organisms. Such comprehensive knowledge will allow for a predictive understanding of complex biological systems behavior. It will guide us in the design and development of novel therapeutics and vaccines to tackle existing health threats and to prepare for future pandemics, and it will provide information necessary to create new biomaterials and bio-inspired technologies through manipulation of biological macromolecules, their assemblies, single cells and even microorganisms. Reaching these goals will require a synergistic combination of multiple experimental techniques with molecular calculations and predictive simulations, and the design and development of new techniques and capabilities that bridge current knowledge and technology gaps. Neutron scattering provides unique information about the biomacromolecular structure and function and can play a major role in achieving these goals. A workshop was held to engage the scientific community in identifying pressing challenges in biochemistry, structural biology, enzymology and structure-guided drug design not solved with the current neutron scattering technologies or utilizing other structural biology techniques such as X-ray crystallography, NMR, and cryo-EM. The workshop brought together structural biology, biochemistry and computational experts, as well as early career researchers and students, creating a forum for discussing scientific advancement and collaboration. The workshop included a one-day satellite training workshop where graduate students and postdoctoral researchers were educated in the application of neutron crystallography and small-angle scattering in structural biology. Furthermore, the Instrument Scientific Advisory Board (ISAB) for the development of a macromolecular neutron diffractometer at ORNL’s Second Target Station was introduced at the workshop. The major outcome was that neutrons can provide atomic-level understanding of biomacromolecular structure, function and dynamics which is of paramount importance for addressing the identified challenges. Neutron crystallography, in particular, can resolve long-standing biochemical issues regarding enzyme function by delineating the underlying chemistry and can have a major impact on the design of small-molecule therapeutics, especially in combination with molecular computation (quantum chemistry and molecular dynamics simulations) and the emerging artificial intelligence (AI)-assisted drug design technologies. The unique properties of neutrons, including their high sensitivity to hydrogen and their non-destructive nature, make them ideal probes of biological matter. There is a palpable need in the scientific community to expand and enhance the impact of neutron sciences on biology. Neutron crystallography is the only structural biology method capable of determining positions of all hydrogen atoms in proteins, nucleic acids and their complexes at near-physiological temperatures and of unstable species at cryogenic temperatures. Moreover, neutron analysis is non-ionizing, non-destructive and does not perturb the structure or redox chemistry of active site metal centers and clusters in proteins, which can be invaluable for studying radiation-sensitive metalloprotein complexes. Further, neutron energies used in scattering applications are similar to atomic motions, permitting neutron spectroscopies to characterize the dynamics of biomacromolecules on the picosecond to microsecond timescales. The different sensitivities of neutrons to protium (H) and deuterium (D) isotopes of hydrogen allow enhanced visibility of specific parts of biological complexes through isotopic labeling. The impact of neutrons will be most powerful when neutron scattering is combined with complementary experimental techniques that use photons and electrons, and with high-performance computing. The interconnection and mutuality of the experimental and theoretical capabilities will drive discoveries in biological and health sciences to generate more complete picture of complex biological systems. The major limitation in the field of biological neutron crystallography has been signal-to-noise, demanding large samples that are difficult to produce for the majority of biomacromolecules and limiting the applicability of this technique in biological sciences. A neutron crystallography instrument at the Second Target Station will revolutionize biological science with neutrons by engaging a large scientific community of structural biologists, enabling successful neutron diffraction experiments from radically smaller biomacromolecular crystals, resolving unanswered biochemical questions, and meaningfully contributing to rational drug design. The meeting highlighted 10 grand challenges that will be addressed with this advanced capability over the next decade and beyond, and the recommendations required to help address them are given below.

59 BASIC BIOLOGICAL SCIENCES↗

Machine-Learning Functional Zonation Approach for Characterizing Terrestrial–Aquatic Interfaces: Application to Lake Erie

Ecosystems at coastal terrestrial–aquatic interfaces play a significant role in global biogeochemical cycles. In this study, we aimed to characterize coastal wetlands with particular focus on the co-variability between plant dynamics, topography, soil, and other environmental factors. We proposed a functional zonation approach based on machine learning clustering to identify the spatial regions, i.e., zones that capture these co-varied properties. This approach was applied to publicly available datasets along Lake Erie, in the Great Lakes Region. We investigated the heterogeneity of coastal ecosystem structures as a function of along-shore distance and transverse distance, based on the spatial data layers, including topography, wetland vegetation cover, and the time series of Landsat’s enhanced vegetation index (EVI) between 1990 and 2020. Results showed that the topographic metrics (elevation and slope), soil texture, and plant productivity influence the spatial distribution of wetland land-covers (emergent and phragmites). These results highlight a natural organization along the transverse axis, where the elevation and the EVI increase further away from the coastline. In addition, the clustering analysis allowed us to identify regions with distinct environmental characteristics, as well as the ones that are more sensitive to interannual lake-level variations.

47 OTHER INSTRUMENTATION↗

Active liquid crystals powered by force-sensing DNA-motor clusters

Significance Single-molecule techniques have elucidated how isolated molecular motors generate piconewton forces with unprecedented detail. However, in diverse biological and synthetic settings, force-generating proteins collectively power nonequilibrium dynamics, including continuous large-scale rearrangements and persistent fluid flows. Characterizing motor-generated forces in these dense and dynamical environments remains a challenge. We assembled a reversible DNA-based force-sensing probe that, by an optical readout, reveals the molecular arrangements and the force loads experienced by kinesin motors. These probes provide insight into motor-generated forces that collectively power the unique dynamics of microtubule-based active nematics, a noteworthy example of an internally driven active matter system. DNA-based force probes can be extended to study forces and stresses in various synthetic systems as well as diverse cellular environments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Comments on the SURFplus reactive burn model

The SURFplus reactive burn model is intended for heterogeneous solid HE that produce an excess amount of carbon. It utilizes a fast hotspot reaction (SURF model) plus a second slow reaction for the energy release from carbon clustering. The fast reaction dominates shock initiation, though the fast rate parameters are slightly affected by the late energy release from the slow reaction. The slow reaction has a significant affect on propagating detonation waves. Propagating detonation waves are characterized by the curvature effect; i.e., detonation speed $D_n$ as function of the local front curvature κ. The $D_n(κ)$ curves have a qualitative different shape. This results from the sensitivity of the slope of the $D_n(κ)$ curve to the reaction-zone width up to the sonic point, and the sonic point moving as κ increases from the end of the slow reaction to the neighborhood of the end of the fast reaction. For PBX 9502, the steep slope for small curvature is determined by the slow reaction, while the lower slope for larger curvature is determined by the fast reaction rate in the high detonation pressure regime. The remainder of this paper is organized as follows. In section 2 we review the assumptions of the Shaw and Johnson carbon cluster model used by the SURFplus model for the slow reaction. Section 3 describes in detail the mixture model for a partly burned HE. The form of the slow rate used by the SURFplus model is described in section 4. We conclude with a brief discussion of applying a burn model with 2 rates to either a metalized or a composite PBX.

42 ENGINEERING↗

Leveraging the digital thread for physics-based prediction of microstructure heterogeneity in additively manufactured parts

A major limitation of additive manufacturing (AM) processes is that local conditions of material deposition frequently lead to unintentional heterogeneities in microstructure and properties within a single component, despite nominally uniform process conditions. Up to now, there has been no way to a priori determine the distribution of these heterogeneities, requiring expensive trial-and-error approaches to fabrication, testing, and characterization. Here, a physics-based framework for creating a digital representation of the laser powder bed fusion (PBF) process is proposed to predict the variation in solidification behavior that leads to heterogeneous microstructures in an as-built part. By leveraging in situ process data stored in the part’s digital thread, the scan path and process parameters were input into a heat transfer model which predicted solidification data at the melt pool scale. A two-step unsupervised clustering algorithm was used to first cluster the local solidification conditions (12.5µm 3 voxels) and then to cluster the regional behavior on the scale of multiple scan passes and print layers (250µm 3 super-voxels). This process was used to identify regions with similar solidification characteristics for multiple locations in a Stainless Steel 316-L component. The corresponding as-built part was sectioned and characterized using electron backscatter diffraction (EBSD). Quantitative analysis of the pole figures confirmed that the predicted regions of heterogeneity in the solidification conditions corresponded with differences in the observed microstructure. In conclusion, this work shows a viable path for estimating the microstructural heterogeneity for additively manufactured parts to either limit microstructural variation throughout a part or to enable functionality-based variation of the microstructure.

36 MATERIALS SCIENCE↗

Ferromagnetic cluster-glass phase in Ca(Co 1-x Ir x ) 2-y As 2 crystals

In this study, single crystals of Ca(Co 1-x Ir x ) 2-y As 2 with 0≤x≤0.35 and 0.10≤y≤0.14 have been grown using the self-flux technique and characterized by single-crystal x-ray diffraction (XRD), energy-dispersive x-ray spectroscopy, magnetization M, and magnetic susceptibility χ measurements versus temperature T, magnetic field H, and time t, and heat-capacity C p (H,T) measurements. The XRD refinements reveal that all the Ir-substituted crystals crystallize in a collapsed-tetragonal structure as does the parent CaCo 2-y As 2 compound. A small 3.3% Ir substitution for Co in CaCo 1.86 As 2 drastically lowers the A-type antiferromagnetic (AFM) transition temperature T N from 52 to 23 K with a significant enhancement of the Sommerfeld electronic heat-capacity coefficient. The A-type AFM structure consists of ab-plane layers of spins ferromagnetically aligned along the c axis with AFM alignment of the spins in adjacent layers along this axis. The positive Weiss temperatures obtained from Curie-Weiss fits to the χ(T>T N ) data indicate that the dominant magnetic interactions are ferromagnetic (FM) for all x. A magnetic phase boundary is inferred to be present between x=0.14 and x=0.17 from a discontinuity in the x dependencies of the effective moment and Weiss temperature in the Curie-Weiss fits. FM fluctuations that strongly increase with increasing x are also revealed from the χ(T) data. Furthermore, the magnetic ground state for x≥0.17 is a spin glass as indicated by hysteresis in χ(T) between field-cooled and zero-field-cooled measurements and from the relaxation of M in a small field that exhibits a stretched-exponential time dependence. The spin glass has a small FM component to the ordering and is hence inferred to be comprised of small FM clusters. The competing AFM and FM interactions along with crystallographic disorder associated with Ir substitution are inferred to be responsible for the development of a FM cluster-glass phase. A logarithmic T dependence of Cp at low T for x=0.14 is consistent with the presence of significant FM quantum fluctuations. This composition is near the T=0 boundary at x≈0.16 between the A-type AFM phase containing ferromagnetically-aligned layers of spins and the FM cluster-glass phase.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Control of spin dynamics in artificial honeycomb spin-ice-based nanodisks

In this paper, we report the experimental and theoretical characterization of the angular-dependent spin dynamics in arrays of ferromagnetic nanodisks arranged on a honeycomb lattice. The magnetic field and microwave frequency dependence, measured by broadband ferromagnetic resonance, reveal a rich spectrum of modes that is strongly affected by the microstate of the network. Based on symmetry arguments with respect to the external field, we show that certain parts of the ferromagnetic network contribute to the detected signal. A comparison of the experimental data with micromagnetic simulations reveals that different subsections of the lattice predominantly contribute to the high-frequency response of the array. This is confirmed by optical characterizations using microfocused Brillouin light scattering. Furthermore, we find indications that nucleation and annihilation of vortexlike magnetization configurations in the low-field range affect the dynamics, which is different from clusters of ferromagnetic nanoellipses. Our work opens up new perspectives for designing magnonic devices that combine geometric frustration in gyrotropic vortex crystals at low frequencies with magnonic crystals at high frequencies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Collaborative Research: Vlasov-Maxwell Simulations to Resolve Electron Heating and Dissipation, in Quasi-Perpendicular Shocks (Final Report)

Collisionless shocks are a grand challenge problem in plasma physics and have been the subject of study for more than six decades. Shocks are ubiquitous phenomena in the universe and are responsible for transforming high energy and momentum flows into thermal energy and energetic particles. Understanding how shocks operate is of primary importance to understand the sun-earth coupling, protecting manned missions and spacecrafts from high energy particles, inertial confinement fusion, and radiation observed from astrophysical plasmas, such as supernova remnants and astrophysical jets. A major unanswered question on this frontier is, how does a collisionless plasma transform flow energy and momentum into electron thermal energy? Many potential mechanisms have been proposed to perform the conversion between flow and thermal energy in a collisionless plasma, but the answer has been elusive. To solve the mystery, non-relativistic perpendicular and quasi-perpendicular shocks are studied via a coordinated approach employing cutting-edge numerical simulations with the continuum kinetic code Gkeyll and spacecraft observations supplied by NASA's Magnetospheric Multiscale (MMS) mission. In both sets of data, we employ novel techniques to identify how and where energy is exchanged between electromagnetic fields and plasma particles. By combining cutting-edge spacecraft data and numerical simulations with these diagnostics, we have been able to identify some of the primary mechanisms responsible electron heating and dissipation in heliospheric shocks. In addition to electron dynamics, we have complete access to proton simulation and in situ data, enabling us to characterize proton heating and acceleration in quasi-perpendicular shocks. Many astrophysical quasi-perpendicular shocks have similar parameters to those in this study, including supernova remnants and shocks in galaxy clusters. Additionally, the simulation code, Gkeyll, and associated analysis scripts are openly available for community use. This award has supported a collaborative effort between Princeton University, the University of Arizona - Tucson, and the University of Maryland - College Park. The award funded three early career scientists, including the funding and training of one female postdoctoral researcher, who was involved in all aspects of the MMS data analysis and some portions of the simulation analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Simulation and characterization of cation disorder in ZnGeP 2

New optoelectronic materials are needed for improving the efficiency and reliability of devices such as solar cells. Cation ordering presents one means of controlling optoelectronic properties while introducing potential to also diversify the mineral constituents of electronic devices; however, the mechanisms of ordering are not yet well understood. To better understand cation ordering in a system integratable with current devices, we assess short- and long-range order parameters of ZnGeP 2 , a material closely lattice matched to Si. Structures are simulated using cluster-based Monte Carlo and first-principles calculations to compare structural distortions, periodicity, and local coordination environments in ZnGeP 2 to experimental data both from the literature and presented here. Comparing order parameters, we relate the transition in order parameters of ZnGeP 2 to that of ZnGeP 2 , discuss the reduction of band gaps with disorder, and show that traditional structural characterization alone is insufficient for understanding order in ZnGeP 2 .

14 SOLAR ENERGY↗

Ultrafast Correlation Energy Estimator

A virtually no-cost method is proposed that can compute the correlation energies of general, covalently bonded, organic, and inorganic molecules (including conjugated π-electron systems) with a well-defined dominant Lewis structure at the accuracy of 99.5% of the near-exact values determined by the coupled-cluster singles, doubles, and perturbative triples [CCSD(T)] in the complete-basis-set (CBS) limit. This Correlation Energy Per Bond (CEPB) method assigns a partial correlation energy to each bond type (characterized by the identities of the two atoms forming the bond and its integer bond order) and to a lone pair, regardless of the bond length, bond angle, sp-hybridization, π-electron conjugation, ionicity, noncovalent interactions, etc. At its current stage, the method is mainly suitable for near-equilibrium geometries. The correlation energies per bond are determined by a fit to the CCSD(T)/CBS benchmarks. It can neither improve the equilibrium structures nor discern conformers or positional isomers, yet its accuracy for reaction energies rivals that of the second-order Møller–Plesset perturbation theory, which is far more expensive. Its promising performance underscores the possibility that surprisingly compact, chemically intuitive molecular fragments exist into which correlation energies can be partitioned, leading to various ultrafast correlation-energy estimators tailored to different purposes.

Binding energy↗

Unraveling the Formation Mechanism of a Hybrid Zr-Based Chemical Conversion Coating with Organic and Copper Compounds for Corrosion Inhibition

Environmental-friendly chromate-free, zirconium (Zr)-based conversion coating is a promising green technology for corrosion protection. Additives in the surface treatment provides critical functionalities and performance improvements; however, mechanistic understanding as of how the additives influence the coatings remains unclear. In this study, a new organic-inorganic hybrid Zrbased conversion coating which combines copper (Cu) compounds and polyamidoamine (PAMAM), taking advantages of a complementary nature of organic and inorganic additives. Here, a multimodal approach combining electron and X-ray characterization is applied to study the interaction of Cu 2+ and PAMAM and the resulting impacts on the coating formation. Adding PAMAM changed the surface morphology, thickness, distribution of Cu in the cluster and void formation of the coatings. High PAMAM (100-200 pm) leads to little conversion coating formation, and low PAMAM (0-25 ppm) shows voids formation under the coatings. Moreover, PAMAM incorporates in the coating in a form of PAMAM-Cu complex with a higher concentration towards the surface, provides an organic layer at the surface of the coating. X-ray absorption near-edge structure (XANES) spectroscopy shows a difference between the conventional and hybrid coating treatments in an alkaline solution to simulate the E-coat process, suggesting the contribution of PAMAM in the enhanced chemical stability in an alkaline environment. Therefore, an intermediate range of addition of PAMAM (50 ppm) is optimal to 1) avoid excessive voids formation, 2) promote some Cu cluster formation and thus enhancing the Zr-based coating formation and 3) incorporate organic components into the coating to improve the adhesion of the subsequent coatings. Overall, this work furthers our knowledge on the formation mechanism of an effective and environmentally friendly hybrid conversion coating for corrosion inhibition, demonstrating a critical processing-structureproperty relationship. This study will benefit future development of green and effective surface treatment technology.

77 NANOSCIENCE AND NANOTECHNOLOGY↗