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At least 37 records · Page 2

Using Density-Corrected DFT to Understand Density-Driven and Functional-Dependent Errors in Ab Initio Simulations of the Hydrated Electron

The hydrated electron, an excess electron in liquid water, plays a crucial role in a plethora of chemical processes, motivating extensive research efforts to characterize its structure, dynamics, and reactivity in solution. Recent theoretical approaches to understanding this intriguing object have involved ab initio simulations based on density functional theory (DFT). Although DFT allows for the study of hydrated electron reactivity and quantum mechanical behavior, it is well-known that anionic systems can suffer from significant density-driven errors (DDEs). Density-corrected DFT (DC-DFT) provides a framework to mitigate such errors; the method reduces DDEs by replacing the self-consistent (SC) density associated with a given density functional with the Hartree–Fock (HF) density. Since HF densities tend to be more localized than DFT SC densities, the DC-DFT scheme significantly improves errors in calculations where the SC density is spuriously delocalized. Here, we investigate how the use of density correction affects the calculated properties of the DFT-simulated (PBEh) hydrated electron, a particularly challenging diffuse anionic system to simulate. First, we analyze charge delocalization in a system consisting of a model octahedral hydrated electron water cluster (the so-called Kevan structure) along with a spatially separated sulfur atom. We show that the use of density correction indeed reduces DDEs in comparison to a standard DFT global hybrid functional. We then propagate molecular dynamics trajectories of the hydrated electron using DC-DFT, where we find that DC further localizes electron density in the cavity region, a signature of reduced charge delocalization. Unfortunately, the decreased radius of gyration of the spin density and corresponding tightening of the local solvation structure from density correction causes predicted observables to deviate further from experimental measurements than when density correction is not employed. Here, we argue that DC’s worse agreement with experiment results from the removal of a fortuitous cancellation of errors that is intrinsic to the PBEh functional. This indicates that the difficulties with DFT to simulate hydrated electrons are primarily due to the inherent approximations in DFT rather than to density-driven errors.

Density functional theory

Untangling Sources of Error in the Density-Functional Many-Body Expansion

The many-body expansion provides a framework for data-driven applications of electronic structure theory, including parametrization of classical force fields and machine learning. In this article, we demonstrate that its use significantly amplifies quadrature grid errors when modern density-functional approximations are employed. Standard grids that work well in conventional density-functional calculations result in runaway error accumulation when used with the many-body expansion. At the same time, delocalization error is also exacerbated, leading to exaggerated estimates of nonadditive n-body interactions. This is illustrated for anion–water clusters using the SCAN, r2SCAN, ωB97X-V and ωB97M-V functionals. By employing dense quadrature grids, the inherent self-interaction error is exposed, which can then be mitigated using a variety of other strategies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Dehydration of Methyl Lactate on Alkali Cation-Exchanged Faujasite: Effects of Metal Cation Identity and Water Pressure

Turnover rates for the catalytic dehydration of methyl lactate (ML) over ion-exchanged faujasite (FAU) catalysts depend on the identity of alkali metal cations (Na + , K + , Cs + ) and local solvation effects. Analysis of rate measurements and in situ infrared spectroscopy gives evidence that the reaction involves kinetically relevant dissociation of adsorbed methyl lactate upon alkali metal cations. This process involves concerted methyl transfer to the surface and dissociation of the alkali metal from the framework, which occurs at cationic active sites that remain predominantly unoccupied under relevant conditions (0.5–10 kPa ML, 0.5–15 kPa H 2 O, 563–583 K). Despite the mechanistic similarities, apparent activation enthalpies (ΔH app ‡ ) decrease linearly (47 kJ mol –1 from Na + to Cs + ) with ionization energy and cationic radius, and apparent activation entropies (ΔS app ‡ ) decrease 74 J mol –1 K –1 . These trends reflect electrostatic interactions that stabilize the cations to the anionic sites on the zeolite: stronger association between these charges leads to increasingly endothermic processes to displace the alkali metal to form a cationic methoxy and an intrapore metal lactate intermediate. Water physisorption measurements suggest alkali metal ions bind superstoichiometric quantities of water within FAU pores, and in situ infrared spectra suggest the concerted adsorption of ML requires reorganization of this water. Consequently, these processes introduce entropic gains that partially offset entropy losses associated with ML adsorption. Hence, turnover rates differ only by a factor of 2 among Na-, K-, and Cs-FAU at 573 K (ΔΔG app ‡ = 5 kJ mol –1 ). These findings demonstrate the interplay of alkali metal ions with zeolite active sites and intrapore water clusters for ML dehydration, indicating that these interactions can be leveraged to deliver optimal performance under different reaction conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Delocalization error poisons the density-functional many-body expansion

The many-body expansion is a fragment-based approach to large-scale quantum chemistry that partitions a single monolithic calculation into manageable subsystems. This technique is increasingly being used as a basis for fitting classical force fields to electronic structure data, especially for water and aqueous ions, and for machine learning. Here, we show that the many-body expansion based on semilocal density functional theory affords wild oscillations and runaway error accumulation for ion–water interactions, typified by F − (H 2 O) N with N ≳ 15. We attribute these oscillations to self-interaction error in the density-functional approximation. The effect is minor or negligible in small water clusters, explaining why it has not been noticed previously, but grows to catastrophic proportion in clusters that are only moderately larger. This behavior can be counteracted with hybrid functionals but only if the fraction of exact exchange is ≳50%, whereas modern meta-generalized gradient approximations including ωB97X-V, SCAN, and SCAN0 are insufficient to eliminate divergent behavior. Other mitigation strategies including counterpoise correction, density correction (i.e., exchange–correlation functionals evaluated atop Hartree–Fock densities), and dielectric continuum boundary conditions do little to curtail the problematic oscillations. In contrast, energy-based screening to cull unimportant subsystems can successfully forestall divergent behavior. These results suggest that extreme caution is warranted when the many-body expansion is combined with density functional theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Upper atmosphere modifications due to chronic discharges of water vapor from space launch vehicle exhausts

The influences of transport, photodissociation, and frequency of injection on the global redistribution of water deposited in the earth's upper atmosphere by repeated launches of large rockets are investigated. Measurable environmental effects of the injected water are found to occur when the mesospheric water vapor mixing ratio exceeds 100 ppmv, which occurs over areas of order 20,000 sq km in connection with possible future Satellite Power System activities. These effects include (1) a 50% reduction in D-region ionization due to screening of L alpha radiation by water; (2) a 50% reduction of D-region ionization as a result of converting NO(+) to water cluster ions which possess more rapid recombination rates; (3) a doubling of OH concentrations below 100 km; and (4) a global doubling of nighttime E-region ionization due to L alpha and L beta radiations geocoronally scattered by atomic hydrogen released by photolysis of H2O. Mixing ratios of 1,000 ppmv necessary for the maintenance of clouds at the mesopause are reached only over areas of order 200 sq km.

Forbes, J. M.

Analysis of model Titan atmospheric components using ion mobility spectrometry

The Gas Chromatograph-Ion Mobility Spectrometer (GC-IMS) was proposed as an analytical technique for the analysis of Titan's atmosphere during the Cassini Mission. The IMS is an atmospheric pressure, chemical detector that produces an identifying spectrum of each chemical species measured. When the IMS is combined with a GC as a GC-IMS, the GC is used to separate the sample into its individual components, or perhaps small groups of components. The IMS is then used to detect, quantify, and identify each sample component. Conventional IMS detection and identification of sample components depends upon a source of energetic radiation, such as beta radiation, which ionizes the atmospheric pressure host gas. This primary ionization initiates a sequence of ion-molecule reactions leading to the formation of sufficiently energetic positive or negative ions, which in turn ionize most constituents in the sample. In conventional IMS, this reaction sequence is dominated by the water cluster ion. However, many of the light hydrocarbons expected in Titan's atmosphere cannot be analyzed by IMS using this mechanism at the concentrations expected. Research at NASA Ames and PCP Inc., has demonstrated IMS analysis of expected Titan atmospheric components, including saturated aliphatic hydrocarbons, using two alternate sample ionizations mechanisms. The sensitivity of the IMS to hydrocarbons such as propane and butane was increased by several orders of magnitude. Both ultra dry (waterless) IMS sample ionization and metastable ionization were successfully used to analyze a model Titan atmospheric gas mixture.

Kojiro, D. R.

The molecular matching problem

Molecular chemistry contains many difficult optimization problems that have begun to attract the attention of optimizers in the Operations Research community. Problems including protein folding, molecular conformation, molecular similarity, and molecular matching have been addressed. Minimum energy conformations for simple molecular structures such as water clusters, Lennard-Jones microclusters, and short polypeptides have dominated the literature to date. However, a variety of interesting problems exist and we focus here on a molecular structure matching (MSM) problem.

Kincaid, Rex K.

What is the Best Alternative to Diagonalization of the Hamiltonian in Large Scale Semiempirical Calculations?

Recently, several linear scaling approaches have been introduced which replace the time dominating diagonalization step in semiempirical methods, enabling practical calculations to be performed, on very large molecules. This paper compares the accuracy and performance of pseudodiagonalization (PD), conjugate gradient density matrix search (CG-DMS), the Chebyshev polynomial expansion method (CEM), and purification of the density matrix (PDM) as linear scaling substitutions for diagonalization. The scaling, speed, and reliability of these methods are compared for AMI single point energy calculations on polyglycine chains (up to 20,000 atoms), water clusters (up to 12,300 atoms), and nucleic acids (up to 6300 atoms).

Daniels, Andrew D.

Composition Changes After the "Halloween" Solar Proton Event: The High-Energy Particle Precipitation in the Atmosphere (HEPPA) Model Versus MIPAS Data Intercomparison Study

We have compared composition changes of NO, NO2, H2O2,O3, N2O, HNO3 , N2O5, HNO4, ClO, HOCl, and ClONO2 as observed by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on Envisat in the aftermath of the "Halloween" solar proton event (SPE) in October/November 2003 at 25-0.01 hPa in the Northern hemisphere (40-90 N) and simulations performed by the following atmospheric models: the Bremen 2D model (B2dM) and Bremen 3D Chemical Transport Model (B3dCTM), the Central Aerological Observatory (CAO) model, FinROSE, the Hamburg Model of the Neutral and Ionized Atmosphere (HAMMONIA), the Karlsruhe Simulation Model of the Middle Atmosphere (KASIMA), the ECHAM5/MESSY Atmospheric Chemistry (EMAC) model, the modeling tool for SO1ar Climate Ozone Links studies (SOCOL and SOCOLi), and the Whole Atmosphere Community Climate Model (WACCM4). The large number of participating models allowed for an evaluation of the overall ability of atmospheric models to reproduce observed atmospheric perturbations generated by SPEs, particularly with respect to NOS, and ozone changes. We have further assessed the meteorological conditions and their implications on the chemical response to the SPE in both the models and observations by comparing temperature and tracer (CH4 and CO) fields. Simulated SPE-induced ozone losses agree on average within 5% with the observations. Simulated NO(y) enhancements around 1 hPa, however, are typically 30% higher than indicated by the observations which can be partly attributed to an overestimation of simulated electron-induced ionization. The analysis of the observed and modeled NO(y) partitioning in the aftermath of the SPE has demonstrated the need to implement additional ion chemistry (HNO3 formation via ion-ion recombination and water cluster ions) into the chemical schemes. An overestimation of observed H2O2 enhancements by all models hints at an underestimation of the OH/HO2 ratio in the upper polar stratosphere during the SPE. The analysis of chlorine species perturbations has shown that the encountered differences between models and observations, particularly the underestimation of observed ClONO2 enhancements, are related to a smaller availability of ClO in the polar night region already before the SPE. In general, the intercomparison has demonstrated that differences in the meteorology and/or initial state of the atmosphere in the simulations causes a relevant variability of the model results, even on a short timescale of only a few days.

Funke, B.

Editing ERTS-1 data to exclude land aids cluster analysis of water targets

The author has identified the following significant results. It has been determined that an increase in the number of spectrally distinct coastal water types is achieved when data values over the adjacent land areas are excluded from the processing routine. This finding resulted from an automatic clustering analysis of ERTS-1 system corrected MSS scene 1002-18134 of 25 July 1972 over Monterey Bay, California. When the entire study area data set was submitted to the clustering only two distinct water classes were extracted. However, when the land area data points were removed from the data set and resubmitted to the clustering routine, four distinct groupings of water features were identified. Additionally, unlike the previous separation, the four types could be correlated to features observable in the associated ERTS-1 imagery. This exercise demonstrates that by proper selection of data submitted to the processing routine, based upon the specific application of study, additional information may be extracted from the ERTS-1 MSS data.

Erb, R. B.

Modeling the formation of ion clusters by applying classical nucleation theory

Experiments have been conducted to study the clustering of atmospheric trace gases around ion cores (Castleman and Tang, 1972; Searcy and Fenn, 1974; Castleman, 1978). The classical liquid-drop model is used to investigate this ion-induced formation mechanism. Results obtained from models of the distribution of Pb(+)-(H2O)n and H(+)-(H2O)n type clusters under various conditions are compared with experimental results. The distribution of water-ion clusters in the atmosphere as a function of altitude is calculated. In situ measurements of the water-ion cluster distributions in the upper atmosphere are then compared with present predictions. It is concluded that the classical nucleation theory can be used to predict rough estimates for ion cluster sizes under many conditions.

Yue, G. K.

Photoionization in Ultraviolet Processing of Astrophysical Ice Analogs at Cryogenic Temperatures

Two recent experimental studies have demonstrated that amino acids or amino acid precursors are generated when astrophysical ice analogs are subjected to ultraviolet (UV) irradiation at cryogenic temperatures. Understanding the complete phenomenology of photoprocessing is critical to elucidating chemical reaction mechanisms that can function within an ice matrix under very cold conditions. Pushing beyond the much better characterized study of photolytic dissociation of chemical bonds through electronic excitation, this work explored the ability of UV radiation present in the interstellar medium to ionize small molecules embedded in ices. Quantum chemical calculations, including bulk solvation effects, were used to study the ionization of hydrogen (H2), water, and methanol (CH3OH) bound in small clusters of water. Ionization potentials were found to be much smaller in the condensed phase than in the gas phase; even a small cluster can account for large changes in the ionization potentials in ice, as well as the known formation of an OH--H3O+ pair in the case of H2O photoionization. To gauge the impact of photoionization on subsequent grain chemistry, the reaction between OH and CO in the presence of H3O+ was studied and compared with the potential energy surface without hydronium present, which is relevant to chemistry following photolysis. The differences indicate that the reaction is somewhat more likely to proceed to products (H + CO2) in the case of photoionization.

Woon, David E.

Spatial Analysis of Great Lakes Regional Icing Cloud Liquid Water Content

Abstract Clustering of cloud microphysical conditions, such as liquid water content (LWC) and drop size, can affect the rate and shape of ice accretion and the airworthiness of aircraft. Clustering may also degrade the accuracy of cloud LWC measurements from radars and microwave radiometers being developed by the government for remotely mapping icing conditions ahead of aircraft in flight. This paper evaluates spatial clustering of LWC in icing clouds using measurements collected during NASA research flights in the Great Lakes region. We used graphical and analytical approaches to describe clustering. The analytical approach involves determining the average size of clusters and computing a clustering intensity parameter. We analyzed flight data composed of 1-s-frequency LWC measurements for 12 periods ranging from 17.4 minutes (73 km) to 45.3 minutes (190 km) in duration. Graphically some flight segments showed evidence of consistency with regard to clustering patterns. Cluster intensity varied from 0.06, indicating little clustering, to a high of 2.42. Cluster lengths ranged from 0.1 minutes (0.6 km) to 4.1 minutes (17.3 km). Additional analyses will allow us to determine if clustering climatologies can be developed to characterize cluster conditions by region, time period, or weather condition. Introduction

Ryerson, Charles C.

A Transferable Force Field for Predicting Adsorption and Diffusion of Water in Cationic Zeolites with Coupled Cluster Accuracy

We present a transferable force field for water in proton-exchanged, alkali (Li, Na, K, Rb, and Cs) metal-exchanged, and alkaline-earth (Mg, Ca, Sr, and Ba) metal-exchanged zeolites. The fitting methodology is based on adsorbate–adsorbent interaction energies obtained from periodic density functional theory calculations and corrected using the coupled-cluster method applied to small model clusters. To ensure an accurate prediction of both adsorption and diffusion properties of water, sets of configurations that sample both adsorption sites and intracrystalline hopping transition states were used in the fitting. The quality of the force field is assessed for a wide range of zeolites with different topologies and chemical compositions, demonstrating good agreement between theoretical predictions and experimental measurements of water adsorption and diffusion.

Adsorption

Superstructure Optimization for Brine Valorization from Brackish Water Desalination

This poster presents preliminary results from a superstructure optimization framework developed to identify cost-optimal brine valorization configurations for brackish water desalination plants across diverse U.S. regional feed chemistries. The study uses brackish groundwater compositions from Arizona, California, Florida, New Mexico, and Texas. Using Pyomo Generalized Disjunctive Programming (GDP) within the WaterTAP modeling environment, the optimization framework simultaneously evaluates thousands of candidate treatment configurations, spanning nanofiltration, reverse osmosis, and chemical precipitation, to minimize the levelized cost of water (LCOW) while meeting water recovery targets and product recovery constraints. Results across eight representative feed clusters demonstrate water recovery rates of 57–87% and net LCOW values ranging from -$0.032/m³ (net revenue-positive) to $0.80/m. Notably, no single process configuration was optimal across all feed types, underscoring the necessity of feed-specific optimization. Products targeted include calcium carbonate (CaCO₃) at $0.01/kg and sodium chloride (NaCl) at $0.10/kg, both at 95% purity, with product revenues offsetting treatment costs in several scenarios. The work advances NAWI's process systems engineering capabilities for multi-configuration screening.

58 GEOSCIENCES

Nanoscopic Structure of the Interface between Reduced TiO 2– x (110) and Water Vapor

We investigate the interaction between a reduced rutile TiO 2–x (110)-(1×4) surface and water vapor at ambient pressures using atomic force microscopy and X-ray photoelectron spectroscopy (AP-AFM and AP-XPS). Our results reveal that water molecules strongly interact with the reduced surface, leading to hydroxylation and localized clustering of water molecules. In defect-rich regions, AFM tip-induced restructuring causes removal of the topmost surface layer, highlighting the lowered cohesive energy of the surface atoms upon hydroxylation. These findings provide new insights into the water adsorption and restructuring mechanisms on reducible transition metal oxides, relevant for catalytic and environmental applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

An atomic cluster expansion (ACE) potential for water under extreme conditions

We present a machine learning interatomic potential for water designed to capture its complex multiphase behavior, including both molecular and superionic ice phases. The potential is based on the atomic cluster expansion (ACE) formulation and has been parameterized to enable high-fidelity molecular dynamics simulations of water under extreme conditions, for pressures up to 100 GPa and for temperatures between 500 and 6000 K. A diverse range of configurations was generated through ab initio molecular dynamics (AI-MD) simulations, covering insulating and superionic ice phases, liquid water, and dissociated plasma phase. We demonstrate that the H 2 O ACE potential accurately reproduces experimental and DFT predicted isotherms and Hugoniots. Crucially, the potential is able to capture the intricate phase behavior of water, including the transition from molecular fluid to the appropriate solid ice phases, and the superionic ice phases. This work provides a robust interatomic potential that can be used for large-scale, accurate simulations of water under extreme thermodynamic conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND