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At least 523 records · Page 29

Linking transportation agent-based model ($\mathrm{ABM}$) outputs with micro-urban social types ($\mathrm{MUSTs}$) via typology transfer for improved community relevance

The human relationship with transportation is shaped by social, economic, demographic, and urban form variables, or socio-spatial factors. The spatial dynamics of these are key to generating and interpreting outputs of transportation models that are most relevant for a community and the diverse mobility needs of its members. Here we present a typology transfer framework, grounded in socio-spatial dynamics shaping people's mobility, to take transportation-themed regional mobility model outcomes, in this case from two agent-based models (ABMs), and extrapolate them to other cities, with less time and resource intensity than new ABM development. The typology transfer process first identifies micro-urban social types (MUSTs) using socio-spatial factors, then defines city types based on spatial patterns of MUSTs to assess across which cities transfer results are likely to best hold. Lastly, a typology transfer multiplier matrix extrapolates a given variable, in our case the Mobility Energy Productivity (MEP) metric, to another city. The full process demonstration uses ABM results from Chicago (POLARIS model) and San Francisco (BEAM model), applying them to New York City. We discuss how MEP or other outputs can be appropriately estimated and used for integrated, human-centered mobility analysis. Key findings include that this MUST framework of user-defined dependent and independent variables allows tailoring ABM results and interpretations to specific community needs and data availability. Findings clarify that positive outcomes can be targeted towards user groups, based on sociospatial characteristics, using a typology approach, such as inclusive access to mobility choices, transportation affordability, and greater efficiency in resource use.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Knowledge-guided graph machine learning for spatially distributed prediction of daily discharge and nitrogen export dynamics

Spatially distributed prediction of streamflow and nitrogen export dynamics is essential for precision management of agricultural watersheds. While temporal deep learning models such as Long Short-Term Memory (LSTM) have shown strong performance at basin scales, their ability to generalize spatially is limited by insufficient representation of spatial dependencies and flow paths, particularly under data-scarce conditions. To address this gap, we propose HydroGraphNet, a knowledge-guided graph machine learning framework that integrates process-based knowledge and explicit spatial learning into temporal modeling. This framework incorporates directed graph topology to encode watershed connectivity and upstream inflows, with mass balance constraints to improve physical consistency. To enhance generalization in sparsely monitored regions, HydroGraphNet is pretrained on synthetic data generated by the SWAT+ (Soil and Water Assessment Tool Plus) model. We evaluated HydroGraphNet in the Upper Sangamon River Basin (44 HUC-12 subwatersheds, 2001–2020) against two LSTM baselines: a lumped basin-level model and a distributed variant. When benchmarked on SWAT+ simulations in pretraining, HydroGraphNet improved test NSEs by 8.9% (discharge) and 13.7% (NO₃–N load) in temporal extrapolation, and by 27.1% and 34.7% in spatial extrapolation, relative to the Lumped LSTM baseline. After fine-tuning with USGS monitoring data, the model achieved mean test NSE (KGE) scores of 0.768 (0.861) for discharge and 0.626 (0.664) for NO₃–N load, substantially outperforming baselines. Attribution analysis further highlighted the importance of upstream inflow representation and graph-based spatial learning in capturing cross-subwatershed dependencies. The model also reproduced seasonal hydrological and biogeochemical patterns consistent with known processes, demonstrating its robustness and process fidelity for spatially distributed prediction. Altogether, HydroGraphNet advances the integration of physical knowledge and spatially explicit learning in hydrological modeling, offering a generalizable framework for distributed modeling to support spatially targeted water quality management in data-scarce watersheds.

54 ENVIRONMENTAL SCIENCES↗

Structural and Spectroscopic Characterization of Plutonium and Other Tetravalent Metals Complexed to a Keggin Ion

Here, we report the isolation of the first plutonium(IV) complex with a Keggin ion chelator: Cs 20 [Pu(PW 11 O 39 ) 2 ] 2 ·13H 2 O. Single crystal XRD and solid-state UV–vis absorbance analysis demonstrate the stabilization of Pu 4+ by the Keggin ligand. The unit cell contains two [Pu(PW 11 O 39 ) 2 ] 10– complexes (Pu(PW 11 ) 2 ) bridged by Cs + . Raman and 31 P NMR spectra of Pu(PW 11 ) 2 are consistent with the analogous Zr 4+ , Hf 4+ , Ce 4+ , and Th 4+ complexes. The Pu–O bond distances at the two Pu sites are 2.35(3) and 2.34(3) Å, matching the value extrapolated from the bonding trend built with the other 8-coordinated tetravalent cations. However, the long-range arrangement of the Pu(PW 11 ) 2 complexes within the lattice is unique in the series of M IV (PW 11 ) 2 compounds: pairs of Pu(PW 11 ) 2 are organized perpendicular to each other. Based on solution-state UV–visible absorbance, small-angle X-ray scattering (SAXS), and 31 P NMR, the tetravalent cations quantitatively form the 1:2 species in solution ([Pu(PW 11 O 39 ) 2 ] 10– (aq) ) and no 1:1 species ([Pu(PW 11 O 39 )(H 2 O) x ] 3– (aq) ). Finally, a linear correlation exists between the metal–oxygen distances in the M IV (PW 11 ) 2 compounds and the corresponding metal dioxides, allowing for extrapolation for Pa 4+ , Am 4+ , and Bk 4+ . The results indicate that our microscale POM approach represents a viable pathway to probe properties of rare actinide ions in discrete molecules, beyond the traditional oxide extended solids.

and nuclear chemistry↗

Benchmarking the GW Approximation and Bethe–Salpeter Equation for Groups IB and IIB Atoms and Monoxides

Energies from the GW approximation and the Bethe–Salpeter equation (BSE) are benchmarked against the excitation energies of transition-metal (Cu, Zn, Ag, and Cd) single atoms and monoxide anions. We demonstrate that best estimates of GW quasiparticle energies at the complete basis set limit should be obtained via extrapolation or closure relations, while numerically converged GW -BSE eigenvalues can be obtained on a finite basis set. Calculations using real-space wave functions and pseudopotentials are shown to give best-estimate GW energies that agree (up to the extrapolation error) with calculations using all-electron Gaussian basis sets. We benchmark the effects of a vertex approximation (ΓLDA) and the mean-field starting point in GW and the BSE, performing computations using a real-space, transition-space basis and scalar-relativistic pseudopotentials. Here, while no variant of GW improves on perturbative G 0 W 0 at predicting ionization energies, G 0 W 0 Γ LDA -BSE computations give excellent agreement with experimental absorption spectra as long as off-diagonal self-energy terms are included. We also present G 0 W 0 quasiparticle energies for the CuO – , ZnO – , AgO – , and CdO – anions, in comparison to available anion photoelectron spectra.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Flat-Histogram Monte Carlo as an Efficient Tool To Evaluate Adsorption Processes Involving Rigid and Deformable Molecules

Monte Carlo simulations are the foundational technique for predicting thermodynamic properties of open systems where the process of interest involves the exchange of particles. Thus, they have been used extensively to computationally evaluate the adsorption properties of nanoporous materials and are critical for the in silico identification of promising materials for a variety of gas storage and chemical separation applications. In this work we demonstrate that a well-known biasing technique, known as “flat-histogram” sampling, can be combined with temperature extrapolation of the free energy landscape to efficiently provide significantly more useful thermodynamic information than standard open ensemble MC simulations. Namely, we can accurately compute the isosteric heat of adsorption and number of particles adsorbed for various adsorbates over an extremely wide range of temperatures and pressures from a set of simulations at just one temperature. We extend this derivation of the temperature extrapolation to adsorbates with intramolecular degrees of freedom when Rosenbluth sampling is employed. Consequently, the working capacity and isosteric heat can be computed for any given combined temperature/pressure swing adsorption process for a large range of operating conditions with both rigid and deformable adsorbates. Finally, continuous thermodynamic properties can be computed with this technique at very moderate computational cost, thereby providing a strong case for its application to the in silico identification of promising nanoporous adsorbents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Approximate Green’s Function Coupled Cluster A Method Employing Effective Dimension Reduction

The Green’s function coupled cluster (GFCC) method, originally proposed in the early 1990s, is a powerful many-body tool for computing and analyzing the electronic structures of molecular structures and periodic systems, especially when electrons are strongly correlated. However, in order for the GFCC method to become an approach that can be routinely used in the electronic structure calculations, more robust linear algebraic techniques and approximations need to be employed to reduce its extremely high computational overhead. In our recent studies, we showed that the GFCC equation can be numerically solved by seeking solutions of multiple linear systems in the frequency regime of interest, which can be easily distributed in a massively parallel environment, and broaden the avenue for more state-of-the-art numerical linear algebraic tools associated with multiple linear systems to be kicked in to this field. In the present pursuit of this practice, we show a successful application of model order reduction (MOR) techniques in the GFCC framework. Briefly speaking, for a frequency regime of interest that requires a high resolution of spectral function, instead of solving GFCC linear equation in the original dimension for every single frequency point, an easily-solvable linear system model with reduced dimension can be built upon projecting the original GFCC linear system into a subspace, from which the interpolation and extrapolation can give a reasonable approximation to the results of the original GFCC linear equations. Here, we show that the subspace can be properly constructed in an iterative manner from the auxiliary vectors of the GFCC linear equations at some select frequencies inside the frequency regime. During the iterations, the quality of the subspace, as well as the linear system model, can be systematically improved. The approach is tested in this work in terms of the efficiency and accuracy of computing spectral functions for some typical molecular systems including carbon monoxide, 1,3-butadiene, benzene, and adenine molecules. As a byproduct, the high quality linear system model is also found to be able to provide high quality initial guess for the existing linear solver to improve the convergence performance.

Peng, Bo↗

Quantum Package 2.0: An Open-Source Determinant-Driven Suite of Programs

Quantum chemistry is a discipline which relies heavily on very expensive numerical computations. The scaling of correlated wave function methods lies, in their standard implementation, between O(N-5) and O(e(N)), where N is proportional to the system size. Therefore, performing accurate calculations on chemically meaningful systems requires (i) approximations that can lower the computational scaling and (ii) efficient implementations that take advantage of modern massively parallel architectures. QUANTUM PACKAGE is an open-source programming environment for quantum chemistry specially designed for wave function methods. Its main goal is the development of determinant-driven selected configuration interaction (sCI) methods and multireference second-order perturbation theory (PT2). The determinant-driven framework allows the programmer to include any arbitrary set of determinants in the reference space, hence providing greater methodological freedom. The sCI method implemented in QUANTUM PACKAGE is based on the CIPSI (Configuration Interaction using a Perturbative Selection made Iteratively) algorithm which complements the variational sCI energy with a PT2 correction. Additional external plugins have been recently added to perform calculations with multireference coupled cluster theory and range-separated density-functional theory. All the programs are developed with the IRPF90 code generator, which simplifies collaborative work and the development of new features. QUANTUM PACKAGE strives to allow easy implementation and experimentation of new methods, while making parallel computation as simple and efficient as possible on modern supercomputer architectures. Currently, the code enables, routinely, to realize runs on roughly 2 000 CPU cores, with tens of millions of determinants in the reference space. Moreover, we have been able to push up to 12 288 cores in order to test its parallel efficiency. In the present manuscript, we also introduce some key new developments: (i) a renormalized second-order perturbative correction for efficient extrapolation to the full CI limit and (ii) a stochastic version of the CIPSI selection performed simultaneously to the PT2 calculation at no extra cost.

Garniron, Yann↗

Vapor Pressures of RDX and HMX Explosives Measured at and Near Room Temperature: 1,3,5-Trinitro-1,3,5-triazinane and 1,3,5,7-Tetranitro-1,3,5,7-tetrazocane

Knowing accurate saturated vapor pressures of explosives at ambient conditions is imperative to provide realistic boundaries on available vapor for ultra-trace detection. In quantifying vapor content emanating from low-volatility explosives, we observed discrepancies between the quantity of explosive expected based on literature vapor pressure values and the amount detected near ambient temperatures. Most vapor pressure measurements for low-volatility explosives, such as RDX (1,3,5-trinitro-1,3,5-triazinane) and HMX (1,3,5,7-tetranitro-1,3,5,7-tetrazocane), have been made at temperatures far exceeding 25 °C and linear extrapolation of these higher temperature trends appears to underestimate vapor pressures near room temperature. Our goal was to measure vapor pressures as a function of temperature closer to ambient conditions. We used saturated RDX and HMX vapor sources at controlled temperatures to produce vapors that were then collected and analyzed via atmospheric flow tube-mass spectrometry (AFT-MS). The parts-per-quadrillion (ppqv) sensitivity of AFT-MS enabled measurement of RDX vapor pressures at temperatures as low as 7 °C and HMX vapor pressures at temperatures as low as 40 °C for the first time. Furthermore, these vapor pressures were corroborated with analysis of vapor generated by nebulizing low concentration solutions of RDX and HMX. We report updated vapor pressure values for both RDX and HMX. Based on our measurements, the vapor pressure of RDX at 25 °C is 3 ± 1 x 10-11 atm (i.e. 30 parts per trillion by volume, pptv), the vapor pressure of HMX is 1.0 ± 0.6 x 10-14 atm (10 ppqv) at 40 °C and, with extrapolation, HMX has a vapor pressure of 1.0 ± 0.6 x 10-15 atm (1.0 ppqv) at 25 °C.

RDX, HMX, explosives, vapor pressure, vapor detect↗

Anomalous Intensities in the 2+1 REMPI Spectrum of the E 1 Π–X 1 Σ + Transition of CO

We report here on one-color experiments near 214 nm involving the photodissociation of jet-cooled OCS to produce high rotational states (40 < J < 80) of CO (X 1 Σ + , v = 0, 1) which were then ionized by 2+1 resonance-enhanced multiphoton ionization via the E 1 Π state. The nominally forbidden Q-branch of the two-photon E 1 Π–X 1 Σ + transition is observed with intensity comparable to the allowed R-branch. The bright character of the high-J Q-branch lines can be described quantitatively as intensity borrowing due to mixing of the E 1 Π and C 1 Σ + states, using J-dependent mixing coefficients extrapolated from the observed Λ-doubling in the lower rotational levels of the E state. In addition to the significant enhancement of Q-branch intensities above the values predicted by conventional two-photon line strengths for a 1 Π– 1 Σ + transition, the high-J lines of the R- and P-branches appear to be suppressed in intensity by approximately a factor of 3 compared to the unperturbed low-J line strengths, most likely due to perturbations associated with a 1 Σ – state. The E-state rotational term values for J < 80, v = 0 derived from the present spectra agree within our measurement and calibration uncertainties with the extrapolations based on the molecular constants previously derived from rotational levels with J < 50. The E–X transition is attractive for future application to photodissociation dynamics and rotational polarization measurements of CO photofragments, with convenient access to state-selective probing on multiple rotational branches, which exhibit different sensitivity to fragment alignment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Photodissociation of H 2 on Ag and Au Nanoparticles: Effect of Size and Plasmon versus Interband Transitions on Threshold Intensities for Dissociation

This Article provides new insights concerning the simulation of plasmon-driven chemical reactions using real-time TDDFT based on the tight-binding electronic structure code DFTB+, with applications to the dissociation of H 2 on octahedral silver and gold nanoparticles with 19–489 atoms. A new component of these calculations involves sampling a 300 K canonical ensemble to determine the distribution of possible outcomes of the calculations, and with this approach we are able to determine the threshold for dissociation as a function of laser intensity, wavelength, and nanocluster size. We show that the threshold intensity varies as an inverse power of nanocluster size, which makes it possible to extrapolate the results to sizes that are more typical of experimental studies. The intensities obtained from this extrapolation are around a factor of 100 above powers used in the pulsed experiments. This is a closer comparison of theory and experiment than has been obtained in previous real-time simulations, and the remaining discrepancy can be understood in terms of electromagnetic hot spots that are associated with cluster formation. Here, we also compare the influence of plasmon excitation versus interband excitation on reaction thresholds, revealing that for silver clusters plasmon excitation leads to lower thresholds, but for gold clusters interband excitation is more effective. Our study also includes an analysis of charge transfer to and from the H 2 molecule, and a determination of orbital populations during and after the pulse, showing the correlation between metal excitations and the location of the antibonding level of H 2 .

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Competitive B2 and B33 Nucleation during Solidification of Ni 50 Zr 50 Alloy: Molecular Dynamics Simulation and Classical Nucleation Theory

We studied the homogenous nucleation of the stoichiometric B2 and B33 phases in the Ni 50 Zr 50 alloy using the persistent embryo method and the classical nucleation theory. The two phases become very close competitors at large supercoolings, which is consistent with the experimental observations. In the case of the B2 phase, the linear temperature dependence of the solid–liquid interface (SLI) free energy extrapolated to the melting temperature leads to the same value as the one obtained from the capillarity fluctuation method (CFM). In the case of the B33 phases, the SLI free energy is also a linear function of temperature at large supercoolings, but the extrapolation to the melting temperature leads to a value which is considerably different from the CFM value. This is persistent with the large anisotropy of the SLI properties of the B33 phase nearby the melting temperature observed in the simulation of the nominally flat interface migration.

36 MATERIALS SCIENCE↗

Local Excitations of a Charged Nitrogen Vacancy in Diamond with Multireference Density Matrix Embedding Theory

Here, we investigate the negatively charged nitrogen-vacancy center in diamond using periodic density matrix embedding theory (pDMET). To describe the strongly correlated excited states of this system, the complete active space self-consistent field (CASSCF) followed by n-electron valence state second-order perturbation theory (NEVPT2) was used as the impurity solver. Since the NEVPT2-DMET energies show a linear dependence on the inverse of the size of the embedding subspace, we performed an extrapolation of the excitation energies to the nonembedding limit using a linear regression. The extrapolated NEVPT2-DMET first triplet–triplet excitation energy is 2.31 eV and that for the optically inactive singlet–singlet transition is 1.02 eV, both in agreement with the experimentally observed vertical excitation energies of ∼2.18 eV and ∼1.26 eV, respectively. This is the first application of pDMET to a charged periodic system and the first investigation of the NV – defect using NEVPT2 for periodic supercell models.

36 MATERIALS SCIENCE↗

The Back Door to the Surface Hydrated Electron

We use a Mg + metal to extend the size regime of water clusters to extrapolate to the bulk limit of the Vertical Detachment Energy (VDE) of the solvated electron to >3,200, a value between one to over two orders of magnitude for clusters previously measured experimentally or computed theoretically. We relate the VDE to the energy difference between the Mg + (H 2 O) $n$ and Mg 2+ (H 2 O) $n$ systems and the metal’s second ionization potential. The extrapolated bulk VDEs of the localized surface electron, which moves away from the metal as n increases, are 1.89 ± 0.01 eV for semiempirical ($n$ ~ 3,200; PM6-D 3 H 4 ) and 1.73 ± 0.03 eV ($n$ ~ 150; HF), 1.83 ± 0.02 eV ($n$ ~ 150; MP2) for ab-initio, in excellent agreement with the 1.6 – 1.8 eV range of experimental results. In conclusion, the VDEs converge from above (larger values) to the bulk limit, in a manner qualitatively different than previous studies and experiments, a fact justifying the “back door” approach to the solvated electron.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optical Properties of Neutral F Centers in Bulk MgO with Density Matrix Embedding

The optical spectra of neutral oxygen vacancies (F 0 centers) in the bulk MgO lattice are investigated using density matrix embedding theory. The impurity Hamiltonian is solved with the complete active space self-consistent field and second-order n-electron valence state perturbation theory (NEVPT2-DMET) multireference methods. Here, to estimate defect-localized vertical excitation energies at the nonembedding and thermodynamic limits, a double extrapolation scheme is employed. The extrapolated NEVPT2-DMET vertical excitation energy value of 5.24 eV agrees well with the experimental absorption maxima at 5.03 eV, whereas the excitation energy value of 2.89 eV at the relaxed triplet defect-localized state geometry overestimates the experimental emission at 2.4 eV by only nearly 0.5 eV, indicating the involvement of the triplet–singlet decay pathway.

embedding↗

Structure and Superconductivity of Hydrogenated TiZr Alloys Under High Pressure

The effects of pressure on the structure and electrical transport properties, including electrical resistance and critical magnetic field values for superconductivity in pristine and hydrogenated TiZr alloys, were investigated. As pressure increased from ambient to 55 GPa, the structure of the pristine TiZr alloys transformed from hcp to bcc via an intermediate ω phase. The superconducting transition temperature (T c ) significantly increased from 1.76 K at ambient pressure to 15.5 K at 52.2 GPa, accompanied by an extrapolated upper critical field of 24.5 T at T = 0 K. In contrast, the hydrogenated samples exhibited substantially lower T c values compared to the pristine ones, with a T c of 4.6 K at 50.5 GPa and an extrapolated upper critical field of 1.8 T at T = 0 K. Upon decompression, the superconductivity in the hydrogenated sample persisted down to 25 GPa, disappearing when the pressure was reduced to 19 GPa. Synchrotron X-ray diffractions (XRD) analysis revealed the formation of three hydrides: I4/mmm-(Ti, Zr)H 2 , P6 3 /mmc-(Ti, Zr)H 3 , and I4̅3d-(Ti,Zr) 4 H 15 . Finally, by combining XRD and electrical resistance data, we tentatively propose that the P6 3 /mmc-(Ti, Zr)H 3 predominantly induces superconductivity. In contrast to superhydrides, where electron–phonon interactions increase the superconducting temperature at high pressure, hydrogen atoms in hcp-(Ti, Zr)H 3 reduce T c .

36 MATERIALS SCIENCE↗

Shallow Rate-Redox Potential Scaling in Aqueous Molecular Oxygen Reduction Electrocatalysis Across a Family of Iron Macrocycles

Rate-overpotential scaling relationships have been employed widely to understand trends in oxygen reduction reaction (ORR) electrocatalysis by dissolved metal macrocycles in organic electrolytes. Similar scaling relationships remain unknown for surface-adsorbed ORR electrocatalysts in the acidic aqueous environments germane to proton-exchange membrane (PEM) fuel cells. Herein, we examine ORR catalysis in aqueous perchloric acid media for a structurally diverse array of iron macrocycle complexes adsorbed on Vulcan carbon black. The macrocycles encompass Fe– N 4 , Fe–N 2 N' 2 and Fe–N x C 4-x motifs bearing pyrrolic, pyridinic, and N-heterocyclic carbene (NHC) moieties in the primary ligation sphere, giving rise to a 670 mV range in Fe(III/II) redox potentials, E Fe(III/II) . Experimental Tafel data in the micropolarization regime were extrapolated to the E Fe(III/II) to furnish estimated per-site-normalized current density (j per-site ) values that span ~4.6 orders of magnitude across the family of compounds. Despite the structural diversity of this family of compounds, extrapolated j per-site values correlate with the Fe(III/II) redox potentials in a roughly log-linear fashion with a shallow scaling factor of approximately 145 mV/decade. Further, these findings highlight that negative shifts in E Fe(III/II) lead to diminishing returns in catalytic rate promotion and suggest that changes to the primary ligating environment in a macrocycle are insufficient to break fundamental rate-potential scaling relationships in aqueous ORR catalysis. Together these studies motivate the further development of higher-potential iron complexes that employ motifs beyond the equatorial ligation plane to enhance ORR catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A near-explicit mechanistic evaluation of Isoprene photochemical seecondary organic aerosol formation and evolution: simulations of multiple chamber experiments with and without added NOx

Experimentally determined yields of secondary organic aerosol (SOA) from the photochemical oxidation of isoprene in the absence of aqueous acidic aerosol vary substantially, both within a given experiment and across different environmental chamber conditions. The underlying mechanisms driving this variation remain poorly evaluated, leading to significant uncertainty in how to extrapolate laboratory chamber results to the atmosphere. Herein, we compare SOA predictions from a near-explicit gas-phase chemical mechanism of isoprene oxidation by the hydroxyl radical (OH) in the presence and absence of nitrogen oxide radicals (NOx), to multiple chamber experiments on non-aqueous isoprene photochemical SOA (ipSOA) conducted by different groups in different chambers. SOA is predicted by volatility-driven gas-particle partitioning of hundreds of individual reaction products. The mechanism includes simplified descriptions of particle-phase organic chemistry, including organic hydroperoxide photolysis, and organic nitrate hydrolysis and accretion reactions. The model has good skill (mean normalized bias typically within 25%) at predicting the observed formation and evolution of ipSOA across a range of chambers and conditions at low NOx. The model has much less skill at describing the observed non-linear response of ipSOA to elevated NOx. Organic nitrate hydrolysis is unable to explain significant ipSOA at high NOx, whereas particle-phase accretion reactions of tertiary nitrates may play a role. Uncertainties in the chamber radical environment and fate of key organic peroxy radicals (RO2) remain as or even more important than vapor losses to chamber walls in determining how best to extrapolate chamber-based yields to the atmosphere. Implications for likely atmospheric yields of ipSOA and recommendations for future chamber experiments are discussed.

Thornton, Joel A.↗

Low-Temperature Plasticity in Olivine: Grain Size, Strain Hardening, and the Strength of the Lithosphere

Plastic deformation of olivine at relatively low temperatures (i.e., low-temperature plasticity) likely controls the strength of the lithospheric mantle in a variety of geodynamic contexts. Unfortunately, laboratory estimates of the strength of olivine deforming by low-temperature plasticity vary considerably from study to study, limiting confidence in extrapolation to geological conditions. Here we present the results of deformation experiments on olivine single crystals and aggregates conducted in a deformation-DIA at confining pressures of 5 to 9 GPa and temperatures of 298 to 1473 K. These results demonstrate that, under conditions in which low-temperature plasticity is the dominant deformation mechanism, fine-grained samples are stronger at yield than coarse-grained samples, and the yield stress decreases with increasing temperature. All samples exhibited significant strain hardening until an approximately constant flow stress was reached. The magnitude of the increase in stress from the yield stress to the flow stress was independent of grain size and temperature. Cyclical loading experiments revealed a Bauschinger effect, wherein the initial yield strength is higher than the yield strength during subsequent cycles. Both strain hardening and the Bauschinger effect are interpreted to result from the development of back stresses associated with long-range dislocation interactions. We calibrated a constitutive model based on these observations, and extrapolation of the model to geological conditions predicts that the strength of the lithosphere at yield is low compared to previous experimental predictions but increases significantly with increasing strain. Our results resolve apparent discrepancies in recent observational estimates of the strength of the oceanic lithosphere.

58 GEOSCIENCES↗