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At least 739 records · Page 41

The Remarkable I 2 O 3 Molecule: A New View from Theory

Atmospheric iodine chemistry has garnered increasing attention as a result of increased iodine emissions. A key subset of this chemistry involves iodine oxides (I 2 O 2–5 ), which serve as precursors to particle formation. Among these, I 2 O 3 is the simplest iodine oxide involved in particle formation, but it has remained undetected in the atmosphere. Previous theoretical studies have characterized this peculiar molecule, primarily using energies to refine geometries obtained at low levels of theory. Due to the reemerging interest in I 2 O 3 , this study presents geometries optimized at the CCSD(T)/aug-cc-pwCVTZ-PP level of theory─marking the first instance, to the best of our knowledge, where this system has been studied exclusively with CCSD(T). Harmonic vibrational frequencies were computed at the same level of theory. Final energetics were obtained using the very high level CCSDT(Q) method with basis sets up to quintuple-zeta cardinality (aug-cc-pwCV5Z-PP) and extrapolated to the CBS limit to yield CCSDT(Q)/CBS//CCSD(T)/aug-cc-pwCVTZ-PP energies. These energies include harmonic zero-point vibrational energy corrections and scalar relativistic energy corrections. Additionally, this study discovers new isomers along the I 2 O 3 potential energy surface, a novel contribution to the field. The performance of different computational methods and DFT functionals commonly used in atmospheric chemistry is also assessed relative to high-level theoretical methods.

basis sets↗

Summer Convective Precipitation Changes Over the Great Lakes Region Under a Warming Scenario

To understand future summer precipitation changes over the Great Lakes Region (GLR), we performed an ensemble of regional climate simulations through the Pseudo-Global Warming (PGW) approach. We found that different types of convective precipitation respond differently to the PGW signal. Isolated deep convection (IDC), usually concentrated in the southern domain, shows an increase in precipitation to the north of the GLR. Mesoscale convective systems (MCSs), usually concentrated upwind of the GLR, shift to the downwind region with increased precipitation. Thermodynamic variables such as convective available potential energy (CAPE) and convective inhibition energy (CIN) are found to increase across almost the entire studied domain, creating a potential environment more favorable for stronger convection systems and less favorable for weaker ones. Meanwhile, changes in the lifting condensation level (LCL) and level of free convection (LFC) show a strong correlation with variations in convective precipitation, highlighting the significance of these thermodynamic factors in controlling precipitation over the domain. Our results indicate that the decrease in LCL and LCF in areas with increased convective precipitation is mainly due to increased atmospheric moisture. In response to the prescribed warming perturbation, MCSs occur more frequently downwind, while localized IDCs exhibit more intense rain rates, longer durations, and larger rainfall area.

54 ENVIRONMENTAL SCIENCES↗

A Look Inside the Black Box: Using graph-theoretical descriptors to interpret a Continuous-Filter Convolutional Neural Network (CF-CNN) trained on the global and local minimum energy structures of neutral water clusters

A Continuous Filter Convolutional Neural Network (CF-CNN) was trained to predict the potential energy of water cluster networks \ce{(H2O)_{\textit{N}}}, \textit{N}=10--30, corresponding to local minima lying within 5 kcal/mol from the putative minima taken from a newly published database containing over 5 million unique networks. The chemical sampling space of the database was characterized using chemical descriptors derived from graph theory, which led to the identification of important trends in the topology, connectivity, polygon structures associated with the various networks as a function of cluster size. The resulting graphs are available alongside the original database at \url{https://sites.uw.edu/wdbase/}. The CF-CNN trained on a subset of 500,000 networks for (\textit{N}=10, 30) yielded a mean absolute error of 0.002$\pm$0.002 kcal/mol per water molecule, giving the trained CF-CNN the highest accuracy of any neural network-based surrogate model to date. In addition, clusters of sizes not included in the training set exhibited errors of the same magnitude, indicating that the CF-CNN ptotocol is general enough to accurately predict energies of networks for both smaller and larger sizes than those used during training. The graph-theoretical descriptors were developed in order to analyze the properties of the full database and interpret the predictive power of the CF-CNN. Using topology measures, such as the Wiener index and the average shortest path length along with two similarity measures, we showed that all networks from the test set were within the range of the ones from the training set, suggesting that the training set covered the chemical space of interest quite well. Our graph analysis suggests that the mean degree and number of polygons for networks with larger errors tend to lie further from the mean than those with lower errors. The generality of the used CF-CNN was thus demonstrated, while the use of the graph-theoretical descriptors assisted in interpreting the predicted results.

Bilbrey, Jenna A.↗

Ultrafast dynamics of 2-thiouracil investigated by time-resolved Auger spectroscopy

In this paper, we present time-resolved ultraviolet-pump x-ray probe Auger spectra of 2-thiouracil. An ultraviolet induced shift towards higher kinetic energies is observed in the sulfur 2p Auger decay. The difference Auger spectra of pumped and unpumped molecules exhibit ultrafast dynamics in the shift amplitude, in which three phases can be recognized. In the first 100 fs, a shift towards higher kinetic energies is observed, followed by a 400 fs shift back to lower kinetic energies and a 1 ps shift again to higher kinetic energies. We use a simple Coulomb-model, aided by quantum chemical calculations of potential energy states, to deduce a C-S bond expansion within the first 100 fs. The bond elongation triggers internal conversion from the photoexcited S 2 to the S 1 state. Based on timescales, the subsequent dynamics can be interpreted in terms of S 1 nuclear relaxation and S 1 -triplet internal conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optimization-based algorithms for nonlinear mechanics and frictional contact

An optimization-based strategy for solving nonlinear mechanics problems is proposed. In contrast to typical nonlinear equation solver algorithms that aim to find zeros in the residual force function, we minimize an energy (or energy-like) function to encourage solutions which are locally stable equilibria. These smooth and potentially non-convex objective functions are minimized using a preconditioned conjugate-gradient trust-region algorithm. Contact is formulated as an inequality constrained minimization problem, and is solved with an augmented Lagrangian algorithm. Friction is included in the approach via a regularized quasi-potential energy, and other dissipative behavior is included through the use of variational constitutive updates. Finally, to accelerate convergence rates for the Lagrange multipliers, we propose a novel multiplier update algorithm utilizing the Fischer-Burmeister function, and demonstrate super-linear solver convergence for some applications.

42 ENGINEERING↗

Extending the Air and Moisture Leakage Calculator to add Residential Buildings and Additional Commercial Buildings

The DOE Windows and Building Envelope Research and Development Roadmap for Emerging Technologies shows that in 2010, infiltration was responsible for 4 quads of space conditioning primary energy use in the residential and commercial sectors. The relative contribution of air leakage in building heating and cooling load is increasing with improvement in the thermal resistance of building envelopes. Advanced air barrier technologies and construction practices have been developed to reduce air leakage in buildings. However, limited information on the impact of air barrier technologies on energy consumption and the durability of buildings has hindered their adoption. In the past Oak Ridge National Laboratory (ORNL), the National Institute of Standards and Technology (NIST), Air Barrier Association of America (ABBA), and U.S.-China Clean Energy Research Center for Building Energy Efficiency (CERC-BEE) collaborated to develop an online calculator that estimates the potential energy and cost savings in major U.S., Canadian and Chinese cities from improvement in air tightness in commercial buildings. In 2018–2019, the calculator was expanded to add moisture transfer calculations given that air leakage through the building envelope can have a significant impact on moisture transfer and associated impacts. In this study, the calculator is expanded further by adding data for two additional commercial buildings (strip mall and primary school) and a residential building. The team investigated the impact of airtightness on energy consumption and moisture transfer of the added buildings. The study includes the analysis of air tightness in 52 major cities in the U.S. and 5 cities in Canada.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Translational and extensional energy release rates (the J- and M-integrals) for a crack layer in thermoelasticity

A number of papers have been presented on the evaluation of energy release rate for thermoelasticity and corresponding J integral. Two main approaches were developed to treat energy release rate in elasticity. The first is based on direct calculation of the potential energy rate with respect to crack length. The second makes use of Lagrangian formalism. The translational and expansional energy release rates in thermoelasticity are studied by employing the formalism of irreversible thermodynamics and the Crack Layer Approach.

Chudnovsky, A.↗

Comparison of calculated and experimental thermal attachment rate constants for SF6 in the temperature range 200-600 K

Electron-attachment cross sections are calcualted for the process e(-) + SF6 yields SF6(-) in the energy range 1-200 meV. An electron scattering approximation is used in which diatomiclike potential energy curves near the equilibrium SF6 ground state are constructed from recent spectroscopic data. Excellent agreement is found over the entire energy range with experimental attachment cross sections at a temperature of 300 K for s-wave (l = 0) scattering. The same calculation, with appropriate adjustment of the thermal populations, is used to calculate attachment rate constants in the range 50-600 K for both s- and p-wave scattering.

Orient, O. J.↗

An economic analysis of space solar power and its cost competitiveness as a supplemental source of energy for space and ground markets

Economic Growth has been historically associated with nations that first made use of each new energy source. There is no doubt that Solar Power Satellites is high as a potential energy system for the future. A conceptual cost model of the economics value of space solar power (SSP) as a source of complementary power for in-space and ground applications will be discussed. Several financial analysis will be offered based on present and new technological innovations that may compete with or be complementary to present energy market suppliers depending on various institutional arrangements for government and the private sector in a Global Economy. Any of the systems based on fossil fuels such as coal, oil, natural gas, and synthetic fuels share the problem of being finite resources and are subject to ever-increasing cost as they grow ever more scarce with drastic increase in world population. Increasing world population and requirements from emerging underdeveloped countries will also increase overall demand. This paper would compare the future value of SSP with that of other terrestrial renewable energy in distinct geographic markets within the US, in developing countries, Europe, Asia, and Eastern Europe.

electric power inter-regional electricity trading↗

Investigation of Condensing Ice Heat Exchangers for MTSA Technology Development

Metabolic heat regenerated Temperature Swing Adsorption (MTSA) technology is being developed for thermal, carbon dioxide (CO2) and humidity control for a Portable Life Support Subsystem (PLSS). Metabolically-produced CO2 present in the ventilation gas of a PLSS is collected using a CO2selective adsorbent via temperature swing adsorption. The temperature swing is initiated through cooling to well below metabolic temperatures. Cooling is achieved with a sublimation heat exchanger using water or liquid carbon dioxide (LCO2) expanded below sublimation temperature when exposed to low pressure or vacuum. Subsequent super heated vapor, as well as additional coolant, is used to further cool the astronaut. The temperature swing on the adsorbent is then completed by warming the adsorbent with a separate condensing ice heat exchanger (CIHX) using metabolic heat from moist ventilation gas. The condensed humidity in the ventilation gas is recycled at the habitat. The water condensation from the ventilation gas is a significant heat transfer mechanism for the warming of the adsorbent bed because it represents as much as half of the energy potential in the moist ventilation gas. Designing a heat exchanger to efficiently transfer this energy to the adsorbent bed and allow the collection of the water is a challenge since the CIHX will operate in a temperature range from 210K to 280K. The ventilation gas moisture will first freeze and then thaw, sometimes existing in three phases simultaneously. A NASA Small Business Innovative Research (SBIR) Phase 1 contract was performed to investigate condensing and icing as applied to MTSA to enable higher fidelity modeling and assess the impact of geometry variables on CIHX performance for future CIHX design optimization. Specifically, a design tool was created using analytical relations to explore the complex, interdependent design space of a condensing ice heat exchanger. Numerous variables were identified as having nontrivial contributions to performance such as hydraulic diameter, heat exchanger effectiveness, ventilation gas mass flow rate and surface roughness. Using this tool, four test articles were designed and manufactured to map to a full MTSA subassembly (the adsorbent bed, the sublimation heat exchanger for cooling and the condensing ice heat exchanger for warming). The design mapping considered impacts due to CIHX geometry as well as subassembly impacts such as thermal mass and thermal resistance through the adsorbent bed. The test articles were tested at simulated PLSS ventilation loop temperature, moisture content and subambient pressure. Ice accumulation and melting were observed. Data and test observations were analyzed to identify drivers of the condensing ice heat exchanger performance. This paper will discuss the analytical models, the test article designs, and testing procedures. Testing issues will be discussed to better describe data and share lessons learned. Data analysis and subsequent conclusions will be presented.

Padilla, Sebastian↗

A Framework for Identifying Building Energy Models of Localized Utility Service Areas Using Smart Meter Data

Bottom-up load modeling of buildings offers a versatile approach to simulating baseline demand and scenarios of future technology evolution and adoption at the individual building level. This capability is essential to understanding how future load shapes may change with the adoption of electric equipment and vehicles, particularly as it relates to grid planning and infrastructure investments. Traditionally, grid planning techniques have used historical load data to predict future load and infrastructure needs. However, with the anticipated rise in adoption of electrification technologies such as heat pumps and electric vehicles, historical data become less reliable predictors of the future. By employing ResStock, a high-fidelity building stock modeling tool, we can fine-tune electrification scenarios and aggregate models to represent varying geographic resolutions of the grid system, while considering the underlying features of homes. This may enable a more accurate and responsive approach to anticipate and plan for the evolving landscape of energy demands. We present a new framework that leverages building stock energy modeling to identify building models that align with the load shapes and housing attributes of buildings with AMI data. This approach applies two model layers: (1) a classification step that identifies the presence of air conditioning, electric heating, and electric water heating, and (2) an optimization routine that identifies building energy models aligning with load profile data from advanced metering infrastructure meters. This report demonstrates one approach to deploying this framework, and presents results for three test cases that use both modeled and AMI data to assess performance. For a test case using AMI data in Fort Collins, Colorado, we observed a median monthly electricity load CV-RMSE of 16.6%, and a top ten daily heating and cooling median absolute percent error of 7.7% and 8.3%, respectively. For each AMI meter, we identify a set of potential energy models so that downstream use-cases can account for uncertainty driven by variability of baseline technologies and occupant behavior, which impact the response to electrification and energy efficiency scenarios. Our results indicate that ResStock has potential as a scalable solution for modeling residential energy demand at local grid resolutions. Its performance depends on location-specific factors, underlying building characteristics, and the level of aggregation, offering a path towards more precise and adaptive distribution grid planning for the evolving energy landscape.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Maximizing machine learning interatomic potential transferability for the discovery of the novel stellated octadecagon Bi18-Pt24 cage structure

Achieving true transferability remains the central challenge for Machine Learning Interatomic Potentials (ML-IAPs) in modeling complex bimetallic nanoclusters across their vast potential energy surfaces. We systematically investigate data selection strategies to optimize the Chebyshev Interaction Model for Efficient Simulation (ChIMES) potential for the Bi-Pt nanoclusters by comparing three innovative sampling methods: Principal Component Analysis (PCA)/k-means (structural diversity), t-distributedStochasticNeighborEmbedding (t-SNE)/k-means (force-space diversity), and hierarchical clustering. Quantitatively, the PCA/k-means strategy proved most effective for global accuracy, yielding the lowest force errors and achieving energy root mean square errors (RMSE) values competitive with Density Functional Theory (DFT), demonstrating excellent accuracy (19.16meV/atom). Structural validation on 34 unique DFT-optimized isomers further confirmed the potential’s high fidelity, with the best model PCA/k-means reproducing structures with an average root mean square deviation (RMSD) of 0.10 Å. However, the t-SNE methods, by maximizing diversity in the force space, demonstrated superior extrapolative power, leading to the more precise prediction of a novel stellated octadecagon Bi18⁢Pt24 cage structure, demonstrating the potential for exploring previously unseen morphologies. Our results establish a clear methodology for strategic data sampling that successfully maximizes ML-IAP transferability, providing an accurate and computationally efficient tool that accelerates the theoretical discovery of complex bimetallic architectures.

Vangheluwe, Raphaël [Université Paris-Saclay, CNRS↗

Resonant two-photon photoelectron imaging and adiabatic detachment processes from bound vibrational levels of dipole-bound states

Anions cannot have Rydberg states, but anions with polar neutral cores can support highly diffuse dipole-bound states (DBSs) as a class of interesting electronically excited states below the electron detachment threshold. The binding energies of DBSs are extremely small, ranging from a few to few hundred wavenumbers and generally cannot support bound vibrational levels below the detachment threshold. Thus, vibrational excitations in the DBS are usually above the electron detachment threshold and they have been used to conduct resonant photoelectron spectroscopy, which is dominated by state-specific autodetachment. Here we report an investigation of a cryogenically-cooled complex anion, the enantiopure (R)-(–)-1-(9-anthryl)-2,2,2-trifluoroethanolate (R-TFAE–). The neutral R-TFAE radical is relatively complex and highly polar with a non-planar structure (C 1 symmetry). Photodetachment spectroscopy reveals a DBS 209 cm–1 below the detachment threshold of R-TFAE– and seven bound and eight above-threshold vibrational levels of the DBS. Resonant two-photon detachment (R2PD) via the bound vibrational levels of the DBS exhibits strictly adiabatic photodetachment behaviors by the second photon, in which the vibrational energies in the DBS are carried to the neutral final states, because of the parallel potential energy surfaces of the DBS and the corresponding neutral ground electronic state. Relaxation processes from the bound DBS levels to the ground and low-lying electronically excited states of R-TFAE– are also observed in the R2PD photoelectron spectra. Finally, the combination of photodetachment and resonant photoelectron spectroscopy yields frequencies for eight vibrational modes of the R-TFAE radical.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

How Well Can Quantum Embedding Method Predict the Reaction Profiles for Hydrogenation of Small Li Clusters?

Quantum computing leverages the principles of quantum mechanics in novel ways to tackle complex chemistry problems that cannot be accurately addressed using traditional quantum chemistry methods. However, the high computational cost and available number of physical qubits with high fidelity limit its application to small chemical systems. This work employed a quantum-classical framework which features a quantum active space-embedding approach to perform simulations of chemical reactions that require up to 14 qubits. This framework was applied to prototypical example metal hydrogenation reactions: the coupling between hydrogen and Li 2 , Li 3 , and Li 4 clusters. Particular attention was paid to the computation of barriers and reaction energies. The predicted reaction profiles compare well with advanced classical quantum chemistry methods, demonstrating the potential of the quantum embedding algorithm to map out reaction profiles of realistic gas-phase chemical reactions to ascertain qualitative energetic trends. Additionally, the predicted potential energy curves provide a benchmark to compare against both current and future quantum embedding approaches.

36 MATERIALS SCIENCE↗

Energy distribution functions of kilovolt ions in a modified Penning discharge

The distribution function of ion energy parallel to the magnetic field of a Penning discharge was measured with a retarding potential energy analyzer. Simultaneous measurements of the ion energy distribution function perpendicular to the magnetic field were made with a charge-exchange neutral detector. The ion energy distribution functions are approximately Maxwellian, and their kinetic temperatures are equal within experimental error. This suggests that turbulent processes previously observed Maxwellianize the velocity distribution along a radius in velocity space, and result in an isotropic energy distribution. The kinetic temperatures are on the order of kilovolts, and the tails of the ion energy distribution functions are Maxwellian up to a factor of 7 e-folds in energy. When the distributions depart from Maxwellian, they are enhanced above the Maxwellian tail. Above densities of about 10 to the 10th power particles/cc, this enhancement appears to be the result of a second, higher temperature Maxwellian distribution. At these high particle energies, only the ions perpendicular to the magnetic field lines were investigated.

Roth, J. R.↗

Kinetics of homogeneous nucleation in many component systems

Reiss's classical treatment of the kinetics of homogeneous nucleation in a system containing two chemical components is extended to many-component systems. The formulation is analogous to the pseudo-stationary state theory of chemical reaction rates with the free energy as a function of the composition of the embryo taking the place of the potential energy as a function of interatomic distances.

Hirschfelder, J. O.↗

Kinetics of homogeneous nucleation on many-component systems

Reiss's (1950) classical treatment of the kinetics of homogeneous nucleation in a system containing two chemical components is extended to many-component systems. The formulation is analogous to the pseudostationary-state theory of chemical reaction rates, with the free energy as a function of the composition of the embryo taking the place of the potential energy as a function of interatomic distances.

Hirschfelder, J. O.↗