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At least 325 records · Page 18

Harnessing metastability for grain size control in multiprincipal element alloys during additive manufacturing

Abstract Controlling microstructure in fusion-based metal additive manufacturing (AM) remains a significant challenge due to the many parameters that directly impact solidification condition. Multiprincipal element alloys (MPEAs), also known as high entropy alloys, offer a vast compositional space to design for microstructural engineering due to their chemical complexity and exceptional properties. Here, we use the FeMnCoCr system as a model platform for exploring alloy design in MPEAs for AM. By exploiting the decreasing stability of the face-centered cubic phase with increasing Mn content, we achieve notable grain refinement and breakdown of epitaxial columnar grain growth. We employ a multifaceted approach encompassing thermodynamic modeling, operando synchrotron X-ray diffraction, multiscale microstructural characterization, and mechanical testing to gain insight into the solidification physics and its ramifications on the resulting microstructure of FeMnCoCr MPEAs. This work aims toward tailoring desirable grain sizes and morphology through targeted manipulation of phase stability, thereby advancing microstructure control in AM applications.

Wakai, Akane↗

Canted antiferromagnetic phases in the candidate layered Weyl material EuMnSb 2

EuMnSb 2 is a candidate topological material which can be tuned towards a Weyl semimetal, but there are differing reports for its antiferromagnetic (AFM) phases. The coupling of bands dominated by pure Sb layers hosting topological fermions to Mn and Eu magnetic states provides a potential path to tune the topological properties. In this study we present single-crystal neutron diffraction, magnetization, and heat-capacity data as well as polycrystalline 151 Eu Mössbauer data which show that three AFM phases exist as a function of temperature, and we present a detailed analysis of the magnetic structure in each phase. The Mn magnetic sublattice orders into a C-type AFM structure below T N Mn = 323 (1) K with the ordered Mn magnetic moment μ Mn lying perpendicular to the layers. AFM ordering of the Eu sublattice occurs below T N Eu1 = 23 (1) K with the ordered Eu magnetic moment μ Eu canted away from the layer normal and μ Mn retaining its higher temperature order. μ Eu is ferromagnetically aligned within each Eu layer but exhibits a complicated AFM layer stacking. Both of these higher-temperature phases are described by magnetic space group (MSG) $\mathcal{Pn'm'a'}$ with the chemical and magnetic unit cells having the same dimensions. Cooling below T N Eu2 =9 (1) K reveals a third AFM phase where μ Mn remains unchanged but μ Eu develops an additional substantial in-plane canting. This phase has MSG $\mathcal{P11}$ $\frac{2_1}{a′}$. We also find some evidence of short-range magnetic correlations associated with the Eu between 12 K≲ T≲ 30 K . Using the determined magnetic structures, we postulate the signs of nearest-neighbor intralayer and interlayer exchange constants and the magnetic anisotropy within a general Heisenberg model. We then discuss implications of the various AFM states in EuMnSb 2 and their potential for tuning topological properties.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Critical Design Elements for an On-Site Mercury Concentration and Holding Facility - 20175

Administrative changes and funding issues have delayed the Department of Energy (DOE) from establishing and commissioning a National Repository for mercury as required under the Mercury Export Ban Act (MEBA) of 2008. In the interim, a few hazardous waste Treatment, Storage, and Disposal Facilities (TSDFs) have been authorized to accept mercury classified as a hazardous waste as under Subtitle C of the Resource Conservation and Recovery Act (RCRA). Waste generators are charged (either by weight or by volume) for the waste they manifest to these TSDFs. In many cases, mercury and mercury compounds have chemically sorbed to (or physically lodged into) the interstitial spaces of a substrate material. This almost always causes the amount of waste generated to be unnecessarily large, due to the extra volume (or weight) of the accompanying, non-mercury materials. Depending on a multitude of factors, it could be financially beneficial for waste generators to take greater control of their mercury affairs by separating these substrate materials from the mercury and mercury compounds that have become associated with them. Building and operating an on-site mercury Concentration and Holding Facility (CHF) could help relieve a waste generator's overall cost burden. The purpose of such CHFs is not to treat or dispose of mercury, but to recover and concentrate mercury from bulky mercury-laden materials to the extent that the host substrate to which the mercury may have previously been sorbed could pass a Toxicity Characteristic Leaching Procedure (TCLP) test and either be disposed of at a conventional landfill, or be disposed of at a hazardous waste landfill, but absent additional restrictions specifically for mercury. A CHF represents a way for waste generators to save money by separating mercury from common host materials, concentrating it, and then safely storing it until transportation to an authorized TSDF takes place This paper focuses on the critical design elements waste generators should consider when designing and operating a mercury CHF. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

PolyODENet

Kinetics of a reaction network that follows mass-action rate laws can be described with a system of ordinary differential equations (ODEs) with polynomial right-hand side. However, it is challenging to derive such kinetic differential equations from transient kinetic data without knowing the reaction network, especially when the data are incomplete due to experimental limitations. We introduce a program, PolyODENet, toward this goal. Based on the machine-learning method Neural ODE, PolyODENet defines a generative model and predicts concentrations at arbitrary time. As such, it is possible to include unmeasurable intermediate species in the kinetic equations. Importantly, we have implemented various measures to apply physical constraints and chemical knowledge in the training to regularize the solution space.

Wu, Qin [Brookhaven National Lab. (BNL), Upton, NY↗

Reduced diffusion and enhanced retention of multiple radionuclides from pore structure characterization of barrier materials for enhanced repository performance

Fluid flow and chemical transport in porous media are the macroscopic consequences of pore structure, which integrates geometry (e.g., pore size and surface area, pore-size distribution) and topology (e.g., pore connectivity). Low-permeability geological media whose pores are poorly interconnected will exhibit the characteristics of anomalous diffusion and sample size-dependent effective porosity, which will strongly impact long-term net diffusion and retention of radionuclides in geological repository settings involving different host rocks and barrier materials. A suite of innovative and complementary experimental approaches is utilized to study the microscopic pore structure and macroscopic fluid flow & chemical transport for a range of host rocks and barrier materials, in addition to standard clay minerals and reference rocks. With a particular focus on quantifying the presence and magnitude of “isolated” pores for a reduced effective porosity in low-permeability geomedia, the integrated methodologies for basic properties and pore structure characterization of these geomedia include X-ray diffraction, thin section petrography, grain size distribution, water immersion porosimetry after vacuum-pulling for full saturation, mercury intrusion porosimetry, nitrogen physisorption, scanning electron microscopy, X-ray computed tomography, and (ultra-)small angle neutron (X-ray) scattering. In addition, custom-designed gas diffusion, tracer recipe involving a range of anionic and cationic chemicals with subsequent analyses by laser ablation and inductively coupled plasma-mass spectrometry, along with batch sorption, column transport, and imbibition tests were conducted for coupled effects of pore structure and chemical retention/transport. From the perspectives of pore structure in conjunction with multiple and complementary approaches to examining a range of sample sizes under different observational scales, we find that the poor pore connectivity is prevalent in low-permeability media (mudstone and crystalline rock) that is related to geological processes (e.g., compaction, diagenesis and thermal maturation). For example, the deep and organic matter-rich mudstones have a much smaller effective porosity than the total porosity (as a result of poor pore connectivity) and associated diffusion coefficient, and the effective porosity & diffusion coefficients are also dependent upon the sample sizes used in the measurement. Similarly, most of the pore space in the shallow mudstone is also controlled by pore-throat diameters in the 5-50 nm range of intergranular pore types from its fine-grained nature, but with an overall good pore connectivity. However, the nm-sized pore space (physically pore-network architecture) and strong sorption capacities (chemical retention from clay minerals) of both shallow and deep mudstones lead to the synergistic retention of cationic radionuclides and their utilities as effective host rocks and barrier materials. Our unique approaches of studying how the micro-scale pore structure affect macro-scale fluid flow, diffusion & retention, and chemical transport produce improved mechanistic understanding, and realistic quantification, of diffusion and retention of typical radionuclides in a range of generic host rocks and barrier materials (clay/shale, salt, crystalline rock, and tuff), with the overall results leading to scientifically-based understanding of enhanced isolation (from both diffusion and retention) of radionuclides and improved confidence on the long-term performance of geological repository to store high-level radioactive wastes. In addition to the training of 25 undergraduates, graduates, and postdocs of UTA, the scientists (organizations) involved in performing this work (e.g., discussion, sample sharing, and operation of SANS and SAXS instruments) include Ed Matteo, Yifeng Wang, and Kristopher Kuhlman (Sandia National Laboratories), Jens Birkholzer, Liange Zheng, Tim Kneafsey, and Sharon Borglin (Lawrence Berkeley National Laboratory), Mavrik Zavarin (Lawrence Livermore National Laboratory), Yukio Tachi and Yuta Fukatsu (Japan Atomic Energy Agency), Mieke de Craen (Euridice, Belgium), Markus Bleuel (NIST), Wei-Ren Chen, Gergely Nagy, Changwoo Do, William Heller, Larry Anovitz, and Kenneth Littrell (ORNL), as well as Jan Illvsky, Ivan Kuzmenko, Ju-Sang Park and Jon Almers (ANL). Key deliverables include a total of 13 peer-reviewed journal articles (nine published and three under review), 23 presentations at scientific conferences (AAPG, AAPG Southwest Section, AGU, Asian Clay Conference, GSA, GSA South-Central Section, IHLRWM, InterPore, International Conference on Chemistry and Migration Behavior of Actinides and Fission Products in the Geosphere, International Conference on Coupled Processes in Fractured Geological Media: Observation, Modeling and Application), and academic institutions (UTA, New Mexico State University; University of Poitiers, France; University of Helsinki, Finland; Uppsala University, Sweden; Istanbul Technical University, Turkey) and other organizations (Andra, France; Posiva Oy, Finland).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Fully variational incremental CASSCF

We report the complete-active-space self-consistent field (CASSCF) method is a canonical electronic structure theory that holds a central place in conceptualizing and practicing first principles simulations. For application to realistic molecules, however, the CASSCF must be approximated to circumvent its exponentially scaling computational costs. Applying the many-body expansion - also known as the method of increments - to CASSCF (iCASSCF) has been shown to produce a polynomially scaling method that retains much of the accuracy of the parent theory and is capable of treating full valence active spaces. Due to an approximation made in the orbital gradient, the orbital parameters of the original iCASSCF formulation could not be variationally optimized, which limited the accuracy of its nuclear gradient. Herein, a variational iCASSCF is introduced and implemented, where all parameters are fully optimized during energy minimization. This method is able to recover electronic correlations from the full valence space in large systems, produce accurate gradients, and optimize stable geometries as well as transition states. Demonstrations on challenging test cases, such as the oxoMn(salen)Cl complex with 84 electrons in 84 orbitals and the automerization of cyclobutadiene, show that the fully variational iCASSCF is a powerful tool for describing challenging molecular chemistries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chemical Complexity of Phosphorous-bearing Species in Various Regions of the Interstellar Medium

Phosphorus-related species are not known to be as omnipresent in space as hydrogen, carbon, nitrogen, oxygen, and sulfur-bearing species. Astronomers spotted very few P-bearing molecules in the interstellar medium and circumstellar envelopes. Limited discovery of the P-bearing species imposes severe constraints in modeling the P-chemistry. In this paper, we carry out extensive chemical models to follow the fate of P-bearing species in diffuse clouds, photon-dominated or photodissociation regions (PDRs), and hot cores/corinos. We notice a curious correlation between the abundances of PO and PN and atomic nitrogen. Since N atoms are more abundant in diffuse clouds and PDRs than in the hot core/corino region, PO/PN reflects <1 in diffuse clouds, ≪1 in PDRs, and >1 in the late warm-up evolutionary stage of the hot core/corino regions. During the end of the post-warm-up stage, we obtain PO/PN > 1 for hot core and <1 for its low-mass analog. We employ a radiative transfer model to investigate the transitions of some of the P-bearing species in diffuse cloud and hot core regions and estimate the line profiles. Our study estimates the required integration time to observe these transitions with ground-based and space-based telescopes. We also carry out quantum chemical computation of the infrared features of PH{sub 3}, along with various impurities. We notice that SO{sub 2} overlaps with the PH{sub 3} bending-scissoring modes around ∼1000–1100 cm{sup −1}. We also find that the presence of CO{sub 2} can strongly influence the intensity of the stretching modes around ∼2400 cm{sup −1} of PH{sub 3}.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Semiglobal diabatic potential energy matrix for the N–H photodissociation of methylamine

We constructed an analytic diabatic potential energy matrix (DPEM) that describes the N–H photodissociation of methylamine; the electronic state space includes the ground and first excited singlet states. The input for the fit was calculated by extended multi-state complete active space second-order perturbation theory. The data were diabatized using the dipole–quadrupole diabatization method in which we incorporated a coordinate-dependent weighting scheme for the contribution of the quadrupole moments. Therefore, to make the resulting potential energy surfaces semiglobal, we extended the anchor points reactive potential method, a multiscale approach that assigns the internal coordinates to categories with different levels of computational treatment. Key aspects of the adiabatic potential energy surfaces obtained by diagonalizing the DPEM agree with the available experimental and theoretical data at energies relevant for photochemical studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Magnetic structure evolution of LiFe 1- x Co x PO 4 olivines upon delithiation

We present a comprehensive study of the nuclear and magnetic structures of the mixed olivine solid solution series LiFe 1-x Co x PO 4 as well as their delithiated counterparts, for metal concentrations x = 0.2 - 0.6. Through neutron powder diffraction studies, we find that the LiFe 1-x Co x PO 4 series orders in the magnetic space group Pnma', consistent with their Li(Fe/Co)PO 4 parent structures. After chemical delithiation using peracetic acid, however, the removal of over 30% of the lithium from the lattice results in a transition from an A y -type to an A x -type antiferromagnetic structure. The magnetic space group consistent with A x antiferromagnetism was found to be Pn'm'a'. Interestingly, magnetic susceptibility measurements of both series reveal that delithiation increases the magnetic transition temperature, T N , from 50 K to 115 K. We find through analysis of the diffraction data that the unit cell parameters change linearly as a function of x; consequently, the exchange pathways between the Fe/Co magnetic cations are affected by the delithiation. Here, we discuss how exchange pathways, metal oxidation states, and d-orbital occupation all contribute to the observed magnetic symmetries and trends in T N in both series.

Antiferromagnet↗

Hilbert space multireference coupled cluster tailored by matrix product states

In the past decade, the quantum chemical version of the density matrix renormalization group method has established itself as the method of choice for strongly correlated molecular systems. However, despite its favorable scaling, in practice, it is not suitable for computations of dynamic correlation. Several approaches to include that in post-DMRG methods exist; in our group, we focused on the tailored coupled cluster (TCC) approach. This method works well in many situations; however, in exactly degenerate cases (with two or more determinants of equal weight), it exhibits a bias toward the reference determinant representing the Fermi vacuum. Although sometimes it is possible to use a compensation scheme to avoid this bias for energy differences, it is certainly a drawback. In order to overcome this bias of the TCC method, we have developed a Hilbert-space multireference version of tailored CC, which can treat several determinants on an equal footing. We have implemented and compared the performance of three Hilbert-space multireference coupled cluster (MRCC) variants—the state universal one and the Brillouin–Wigner and Mukherjee’s state specific ones. We have assessed these approaches on the cyclobutadiene and tetramethyleneethane molecules, which are both diradicals with exactly degenerate determinants at a certain geometry. We have also investigated the sensitivity of the results on the orbital rotation of the highest occupied and lowest unoccupied molecular orbital (HOMO–LUMO) pair, as it is well known that Hilbert-space MRCC methods are not invariant to such transformations.

Chemistry↗

Covalency of Trivalent Actinide Ions with Different Donor Ligands: Do Density Functional and Multiconfigurational Wavefunction Calculations Corroborate the Observed “Breaks”?

A comprehensive ab initio study of periodic actinide–ligand bonding trends for trivalent actinides is performed. Relativistic density functional theory (DFT) and complete active-space (CAS) self-consistent field wavefunction calculations are used to dissect the chemical bonding in the [AnCl 6 ] 3– , [An(CN) 6 ] 3– , [An(NCS) 6 ] 3– , [An(S 2 PMe 2 ) 3 ], [An(DPA) 3 ] 3– , and [An(HOPO)] – series of actinide (An = U–Es) complexes. Except for some differences for the early actinide complexes with DPA, bond orders and excess 5f-shell populations from donation bonding show qualitatively similar trends in 5f n active-space CAS vs DFT calculations. The influence of spin–orbit coupling on donation bonding is small for the tested systems. Along the actinide series, chemically soft vs chemically harder ligands exhibit clear differences in bonding trends. There are pronounced changes in the 5f populations when moving from Pu to Am or Cm, which correlate with previously noted “breaks” in chemical trends. As a result, bonding involving 5f becomes very weak beyond Cm/Bk. We propose that Cm(III) is a borderline case among the trivalent actinides that can be meaningfully considered to be involved in ground-state 5f covalent bonding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Sonora Substellar Atmosphere Models. II. Cholla: A Grid of Cloud-free, Solar Metallicity Models in Chemical Disequilibrium for the JWST Era

Exoplanet and brown dwarf atmospheres commonly show signs of disequilibrium chemistry. In the James Webb Space Telescope (JWST) era, high-resolution spectra of directly imaged exoplanets will allow the characterization of their atmospheres in more detail, and allow systematic tests for the presence of chemical species that deviate from thermochemical equilibrium in these atmospheres. Constraining the presence of disequilibrium chemistry in these atmospheres as a function of parameters such as their effective temperature and surface gravity will allow us to place better constraints on the physics governing these atmospheres. This paper is part of a series of works presenting the Sonora grid of atmosphere models. In this paper, we present a grid of cloud-free, solar metallicity atmospheres for brown dwarfs and wide-separation giant planets with key molecular species such as CH 4 , H 2 O, CO, and NH 3 in disequilibrium. Our grid covers atmospheres with T eff ∈ [500 K, 1300 K], log g ∈ [3.0, 5.5] (cgs) and an eddy diffusion parameter of logK zz = 2,4 and 7 (cgs). We study the effect of different parameters within the grid on the temperature and composition profiles of our atmospheres. We discuss their effect on the near-infrared colors of our model atmospheres and the detectability of CH 4 , H 2 O, CO, and NH 3 using the JWST. We compare our models against existing MKO and Spitzer observations of brown dwarfs and verify the importance of disequilibrium chemistry for T dwarf atmospheres. Finally, we discuss how our models can help constrain the vertical structure and chemical composition of these atmospheres.

79 ASTRONOMY AND ASTROPHYSICS↗

Turn-key constrained parameter space exploration for particle accelerators using Bayesian active learning

Abstract Particle accelerators are invaluable discovery engines in the chemical, biological and physical sciences. Characterization of the accelerated beam response to accelerator input parameters is often the first step when conducting accelerator-based experiments. Currently used techniques for characterization, such as grid-like parameter sampling scans, become impractical when extended to higher dimensional input spaces, when complicated measurement constraints are present, or prior information known about the beam response is scarce. Here in this work, we describe an adaptation of the popular Bayesian optimization algorithm, which enables a turn-key exploration of input parameter spaces. Our algorithm replaces the need for parameter scans while minimizing prior information needed about the measurement’s behavior and associated measurement constraints. We experimentally demonstrate that our algorithm autonomously conducts an adaptive, multi-parameter exploration of input parameter space, potentially orders of magnitude faster than conventional grid-like parameter scans, while making highly constrained, single-shot beam phase-space measurements and accounts for costs associated with changing input parameters. In addition to applications in accelerator-based scientific experiments, this algorithm addresses challenges shared by many scientific disciplines, and is thus applicable to autonomously conducting experiments over a broad range of research topics.

43 PARTICLE ACCELERATORS↗

Predicting path-dependent diffusion barrier spectra in vast compositional space of multi-principal element alloys via convolutional neural networks

The emergent multi-principal element alloys (MPEAs) provide a vast compositional space to search for novel materials for technological advances. How to screen promising compositions from such an ample design space for targeted properties is a grand challenge. In this report, we demonstrate the state-of-the-art deep learning technology—convolutional neural network (CNN)—in predicting path-dependent vacancy migration energy barrier spectra, which are critical to diffusion behavior and many high-temperature properties, in the hyperdimensional composition space of MPEAs. The developed CNN model, fully capturing local chemical features surrounding each vacancy, accurately and efficiently predicts migration energy barrier of MPEAs with different degrees of chemical short-range order and at any unseen compositions. By varying the size of the local region encapsulating vacancy in the CNN model, we reveal that the length scale influencing vacancy migration is surprisingly extensive, up to its six nearest neighboring shells. The efforts of the CNN model make it promising for developing a database of diffusion barriers for various MPEA systems, which would have profound implications for accelerating alloy screening and discovering new compositions with desirable properties.

36 MATERIALS SCIENCE↗

Machine learning-based discovery of molecular descriptors that control polymer gas permeation

While machine learning has found increasing use in predicting the properties of polymeric materials with only a knowledge of chain architecture, determining the molecular factors underpinning properties (“interpretable AI”) has remained less well explored. We show that encoding chain chemistry in commonly employed formats, e.g., binary-valued fingerprints, leads to uniqueness issues during the hashing process to save storage space. This is because the hashing algorithm can map several chemical moieties into the same bit. These issues carry over into the ML algorithms, especially for “inverse” design and interpretable AI, and cannot be avoided by changing the length of the fingerprint. Using MACCS key featurizations of monomer repeats resolves some of these issues, and we show that a few substructures consistently appear in top features for maximizing permeability across several gases and ML models. These are carbon–carbon double bonds (as in polyacetylenes) especially when they are associated with methyl groups (found in branching architectures). Here these results, derived from the limited data set of ~ 500 polymers with experimental gas permeation data, are in agreement with physical insight and thus provide a robust foundation which could further enable study of these material classes through detailed experiments and simulations.

36 MATERIALS SCIENCE↗

Design and out-of-pile testing of a novel irradiation experiment vehicle to support qualification of nuclear thermal propulsion components

Fission power systems have demonstrated higher thermal energy density per unit mass than chemical systems. High mass specific energy density offers advantages in space thermal propulsion applications. In the 1960s, nuclear thermal propulsion (NTP) development included the ROVER/NERVA program, in which full-scale prototype reactors were tested on the ground using hydrogen as the reactor coolant and propellant. NTP systems are being revisited, with expectations of improved performance resulting from improved fuel materials, allowing propellant temperatures near 2,800 K and over 20 thermal propulsion cycles. An apparatus has been developed to test NTP fuel materials in a research reactor at temperature and in a radiation environment typical of the NTP application. Here, this paper presents the design constraints, preliminary scoping thermal analysis, and basic thermal qualification testing for the out-of-pile experiment set apparatus, or OUTSET.

33 ADVANCED PROPULSION SYSTEMS↗

Chemical Framework to Design Linear-like Relaxors toward Capacitive Energy Storage

ABO 3 -type perovskite relaxor ferroelectrics (RFEs) have emerged as the preferred option for dielectric capacitive energy storage. However, the compositional design of RFEs with high energy density and efficiency poses significant challenges owing to the vast compositional space and the absence of general rules. Here, we present an atomic-level chemical framework that captures inherent characteristics in terms of radius and ferroelectric activity of ions. By categorizing A/B-site ions as host framework, rattling, ferroelectrically active, and blocking ions and assembling these four types of ions with specific criteria, linear-like relaxors with weak locally correlated and highly extendable unit-cell polarization vectors can be constructed. As example, we demonstrate two new compositions of Bi 0.5 K 0.5 TiO 3- based and BaTiO 3- based relaxors, showing extremely high recoverable energy densities of 17.3 and 12.1 J cm –3 , respectively, both with a high efficiency of about 90%. Further, the role of different types of ions in forming heterogeneous polar structures is identified through element-specific local structure analysis using neutron total scattering combined with reverse Monte Carlo modeling. Further, our work not only opens up new avenues toward rational compositional design of high energy storage performance lead-free RFEs but also sheds light on atomic-level manipulation of functional properties in compositionally complex ferroelectrics.

25 ENERGY STORAGE↗

Potential energy surfaces for high-energy N + O 2 collisions

Potential energy surfaces for high-energy collisions between an oxygen molecule and a nitrogen atom are useful for modeling chemical dynamics in shock waves. In the present work, we present doublet, quartet, and sextet potential energy surfaces that are suitable for studying collisions of O 2 ( 3 Σ$^{–}_{g}$) with N( 4 S) in the electronically adiabatic approximation. Two sets of surfaces are developed, one using neural networks (NNs) with permutationally invariant polynomials (PIPs) and one with the least-squares many-body (MB) method, where a two-body part is an accurate diatomic potential and the three-body part is expressed with connected PIPs in mixed-exponential-Gaussian bond order variables (MEGs). We find, using the same dataset for both fits, that the fitting performance of the PIP-NN method is significantly better than that of the MB-PIP-MEG method, even though the MB-PIP-MEG fit uses a higher-order PIP than those used in previous MB-PIP-MEG fits of related systems (such as N 4 and N 2 O 2 ). However, the evaluation of the PIP-NN fit in trajectory calculations requires about 5 times more computer time than is required for the MB-PIP-MEG fit.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗