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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Resolving the Heat Generated from ZrO 2 Atomic Layer Deposition Surface Reactions

Abstract In situ pyroelectric calorimetry and spectroscopic ellipsometry were used to investigate surface reactions in atomic layer deposition (ALD) of zirconium oxide (ZrO 2 ). Calibrated and time‐resolved in situ ALD calorimetry provides new insights into the thermodynamics and kinetics of saturating surface reactions for tetrakis(dimethylamino)zirconium(IV) (TDMAZr) and water. The net ALD reaction heat ranged from 0.197 mJ cm −2 at 76 °C to 0.155 mJ cm −2 at 158 °C, corresponding to an average of 4.0 eV/Zr at all temperatures. A temperature dependence for reaction kinetics was not resolved over the range investigated. The temperature dependence of net reaction heat and distribution among metalorganic and oxygen source exposure is attributed to factors including growth rate, equilibrium surface hydroxylation, and the extent of the reaction. ZrO 2 ‐forming surface reactions were investigated computationally using DFT methods to better understand the influence of surface hydration on reaction thermodynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Medium controlled aggregative growth as a key step in mesoporous silica nanoparticle formation

Near monodisperse mesoporous silica nanoparticles (MSN) represent a promising and rapidly developing type of mesoporous silica materials; however, the vast data on their synthesis remains unorganized and ill-understood. We systematically studied the formation of MSN under basic and neutral conditions using various temperatures, CTAB concentrations, hydrolyzing agents (triethanolamine, ammonia, phosphate buffers), and media with different colloidal stabilization properties (with ethanol as a cosolvent and monovalent salts). In the typical conditions for the preparation of stable MSN colloids, the particle size was controlled by colloidal stabilization by the medium (solvent type, ionic strength, and surfactant concentration) in agreement with the “aggregative growth” mechanism, rather than by solely the hydrolysis and condensation rates conventionally used for data interpretation in the classical nucleation theory. Medium properties (pH, ion types and concentration, polarity) also defined the efficiency of silica-surfactant cooperative self-assembly, which directly affected the porosity, mesopore size and pore wall thickness. Interestingly, this traditional silica-surfactant route showed a limited effect on the particle size, emphasizing the dominating role of colloidal stabilization in the studied reaction conditions. In situ pH measurements showed that every reaction medium has unique pH evolution profiles depending on the buffer capacity, hydrolysis and condensation rates. Reaction systems that fail to maintain the working pH can lead to non-porous products or undesired particle morphology and size distribution. The established particle formation mechanism allowed us to formulate comprehensive guidelines for preparing relatively concentrated colloids of near monodisperse (PDI 5–15%) mesoporous 30–700 nm silica spheres with variable porosity and mesopore size. Here, these findings will be particularly useful in designing new mesoporous silica-containing materials for biomedical applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Gas generation and intramolecular isotope study in laboratory pyrolysis of the Springfield coal from the Illinois Basin

Position-specific (PS) isotopes of propane have been proposed as a potential geochemical tool to decipher various geological processes (e.g., thermal cracking, biodegradation, H exchange) in natural reservoirs. The limited studies have been conducted on the PS isotopes of propane from the pyrolysis gases from marine shales, and natural gases sourced from lacustrine and marine kerogens, but little is known on gases produced from the humic kerogen. Here, this study investigated the PS δ 13 C of propane in the closed-system pyrolysis of the Springfield coal, Illinois Basin, Indiana, at 310 to 470 °C (Easy %Ro: 0.76 to 3.07). The C kinetic isotope effect (KIE) of CH 4 produced in both this study and previous low-temperature pyrolysis of the same coal indicates the cleavage of C—O bonds is the main generation pathway at the early kerogen cracking stage, followed by the breakdown of alkyl groups. At the wet-gas cracking stage, C 3 H 8 production from thermally stable compounds has a significant influence on the bulk and position-specific C KIE in the pyrolysis of marine Woodford kerogen and Springfield coal. According to the PS δ 13 C of propane, the central site is likely more enriched in 13 C and the δ 13 C of the terminal site is relatively heterogeneous within the propyl group attached to different functional groups of the gas-prone kerogen. Our findings based on the pyrolysis experiments and natural gas samples indicate thermal cracking and biodegradation appear to alter the δ 13 C cen values more significantly than the δ 13 C ter values of propane. The larger magnitude of ΔC c-t in the kMC simulations (Peterson et al., 2018) compared with those from the marine shale and coal possibly implies the non-random distributions of 13 C of propane precursors in the kerogens. As a new dimension of intramolecular isotopic information of propane, the PS δ 13 C values can contribute to fingerprinting the gas origins and identifying the various geological processes (e.g., kerogen cracking, wet-gas cracking, microbial activities) in sedimentary basins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Computational study of the adsorption of bimetallic clusters on alumina substrate

We performed computational investigation of the adsorption of bimetallic Pd 3 M 2 (where M changes from Ag, Au, Co, Cu, Mn, Ni, Pt, and Ru) cluster on the hydroxylated alumina surface. Previously, it was shown that small silver cluster can control the rate of discharge at the cathode of lithium-oxygen battery. The gap near the fermi energy was shown to control the oxygen reduction, an important reaction for LiO 2 formation. Controlling the gap would ultimately control the rate of LiO 2 formation. One can vary the size of the cluster to vary the gap, however, this "knob" provides limited variance in the gap. Alloying, in combination with size variation offer a much wider control of the gap, hence the LiO 2 formation. Using Density Functional Theory (DFT), we determined the most stable geometry of the bimetallic clusters Pd 3 M 2 and calculated the binding energies of these clusters on the alumina substrate which ranges from 0.2 eV to 0.25 eV depending upon the composition of the alloy-cluster, its orientation and the adsorption site. We also find that Pd atoms bind strongly with the substrate oxygen atoms with an average short bond-length of about 2.2 angstrom. We explored how the gap at the Fermi level of the system varies as a function of elemental composition and the calculated gap ranges from 0 meV to 90 meV. Charges distribution using Bader analysis was also performed to probe how charges are transferred between the cluster and the substrate. These preliminary results will open the door for more systematic studies of alloy clusters of different size and stoichiometry for Li-O 2 battery cathode design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Graph characterization of higher-order structure in atmospheric chemical reaction mechanisms

Atmospheric chemical reactions play an important role in air quality and climate change. While the structure and dynamics of individual chemical reactions are fairly well understood, the emergent properties of the entire atmospheric chemical system, which can involve many different species that participate in many different reactions, are not well described. In this work, we leverage graph-theoretic techniques to characterize patterns of interaction (“motifs”) in three different representations of gas-phase atmospheric chemistry, termed “chemical mechanisms.” These widely used mechanisms, the master chemical mechanism, the GEOS-Chem mechanism, and the Super-Fast mechanism, vary dramatically in scale and application, but they all generally aim to simulate the abundance and variability of chemical species in the atmosphere. This motif analysis quantifies the fundamental patterns of interaction within the mechanisms, which are directly related to their construction. For example, the gas-phase chemistry in the very small Super-Fast mechanism is entirely composed of bimolecular reactions, and its motif distribution matches that of an individual bimolecular reaction well. The larger and more complex mechanisms show emergent motif distributions that differ strongly from any specific reaction type, consistent with their complexity. The proposed motif analysis demonstrates that while these mechanisms all have a similar design goal, their higher-order structure of interactions differs strongly and thus provides a novel set of tools for exploring differences across chemical mechanisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Description of global EGAM in the maximum of local frequency during current ramp-up discharges in DIII-D

Energetic-particle-induced geodesic acoustic modes, EGAMs (Fu, Phys. Rev. Let., vol. 101, 2008, pp. 185002), driven by neutral beam injection (NBI), have been observed in many DIII-D tokamak experiments (Nazikian et al., Phys. Rev. Lett., vol. 101, 2008, pp. 185001). This mechanism has been theoretically investigated in (Qiu et al., Plasma Phys. Control. Fusion, vol. 52, 2010, pp. 095003), using a sharp energetic particle distribution function, and in (Qu et al., Plasma Phys. Control. Fusion, vol. 59, 2017, pp. 055018), where the dispersion relation and eigenmode behaviour were obtained for the situation of early beam scenario, that is, for times smaller than the beam slowing down time. In this work, we extend these studies determining the eigenmode for beyond the slowing down time, in a scenario with reverse safety factor q profile, where a small concentration of energetic ions can produce an off-axis maximum in the GAM dispersion relation. Here, the characteristics of EGAM are analytically studied with the drift kinetic equation together with the MHD code NOVA. The toroidal energetic ion transit frequency, coupled with the GAM frequency, produces the maximum in the dispersion relation where the eigenmode can be found. The quantitative correspondence of experimental results with the predictions of the proposed model is analysed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Role of Dynamic Polarization Interactions in the Electrical Double Layer at Calcite (104) Interfaces with Aqueous Solutions

Reactions at mineral interfaces with aqueous solutions control many geochemical and biogeochemical processes in the Earth’s critical zone. At the molecular level, insights into important properties such as the structure of the electrical double layer (EDL) at specific mineral interfaces continue to improve due to the increasing fidelity of laboratory instrumentation and computational approaches. However, molecular simulation approaches suffer from limited reach into relevant scales of time, length, and system complexity. To span this gap, a novel hybrid approach that couples first principle plane-wave density functional theory (DFT) with classical DFT (cDFT) is demonstrated and applied to calcite (104) interfaces with various electrolytes. In this approach, a region of interest described using DFT interacts with the surrounding medium described using cDFT to arrive at a self-consistent ground state. Benchmarking against experimental observations and entirely first principle DFT simulations demonstrates that this hybrid model efficiently encompasses the key short-range and collective interactions in the EDL. Simulations of calcite (104)/solution interfaces reveal the key static and dynamic polarization interactions that give rise to structuring of ions and water. Ion hydration interactions have the strongest effect on the depth of the first minimum in the density distribution of counterions at the surface, and the position and width of the first density peak is largely determined by the strength of ion-correlation forces. Finer details of ion distributions are controlled by mutual polarization of the calcite surface and interfacial electrolyte. Finally, this new ability to efficiently and rigorously predict EDL structure at mineral surfaces in contact with complex solutions paves the way to accurately modeling sorption, nucleation, dissolution, and growth in realistic systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Direct Identification of Mixed-Metal Centers in Metal–Organic Frameworks: Cu 3 (BTC) 2 Transmetalated with Rh 2+ Ions

Raman spectroscopy was used to establish direct evidence of heterometallic metal centers in a metal–organic framework (MOF). The Cu 3 (BTC) 2 MOF HKUST-1 (BTC 3– = benzenetricarboxylate) was transmetalated by heating it in a solution of RhCl 3 to substitute Rh 2+ ions for Cu 2+ ions in the dinuclear paddlewheel nodes of the framework. In addition to the Cu–Cu and Rh–Rh stretching modes, Raman spectra of (Cu x Rh 1– x ) 3 (BTC) 2 show the Cu–Rh stretching mode, indicating that mixed-metal Cu–Rh nodes are formed after transmetalation. Density functional theory studies confirmed the assignment of a Raman peak at 285 cm –1 to the Cu–Rh stretching vibration. Electron paramagnetic resonance spectroscopy experiments further supported the conclusion that Rh 2+ ions are substituted into the paddlewheel nodes of Cu 3 (BTC) 2 to form an isostructural heterometallic MOF, and electron microscopy studies showed that Rh and Cu are homogeneously distributed in (Cu x Rh 1– x ) 3 (BTC) 2 on the nanoscale.

02 PETROLEUM↗
DOE OSTI2022

Unimolecular dissociation dynamics of electronically excited HCO(Ã 2 A"): rotational control of nonadiabatic decay

The photoinduced unimolecular decay of the electronically excited HCO(Ã 2 A") is investigated in a combined experimental–theoretical study. The molecule is excited to the (1, n 2 , 0) combination bands, which decay via Renner–Teller coupling to the ground electronic state. The rovibrational state distribution of the CO fragment was measured via the high-n Rydberg H-atom time-of-flight method and calculated using a wave packet method on an accurate set of potential energy surfaces. It is shown that the non-adiabatic decay rate is strongly modulated by the HCO rotational angular momentum, which leaves unique signatures in the product state distribution. Finally, the experimentally observed bimodal rotational distribution of the dominant CO(v = 0) fragment is likely due to decay of different vibronic states populated by the excitation and modulated by the excited state lifetime, which is in turn controlled by the parent rotational quantum number.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Stochastic Kinetics of Nanocatalytic Systems

Catalytic reaction events occurring on the surface of a nanoparticle constitute a complex stochastic process. Although advances in modern single-molecule experiments enable direct measurements of individual catalytic turnover events occurring on a segment of a single nanoparticle, we do not yet know how to measure the number of catalytic sites in each segment or how the catalytic turnover counting statistics and the catalytic turnover time distribution are related to the microscopic dynamics of catalytic reactions. Here, we address these issues by presenting a stochastic kinetics for nanoparticle catalytic systems. We propose a new experimental measure of the number of catalytic sites in terms of the mean and variance of the catalytic event count. By considering three types of nanocatalytic systems, we investigate how the mean, the variance, and the distribution of the catalytic turnover time depend on the catalytic reaction dynamics, the heterogeneity of catalytic activity, and communication among catalytic sites. This work enables accurate quantitative analyses of single-molecule experiments for nanocatalytic systems and enzymes with multiple catalytic sites.

Statistical Physics↗
DOE OSTI2026

Bayesian Physics Informed Spatio-Temporal Network for Streamflow Data Imputation

Reliable reconstruction of incomplete streamflow records is critical for improving hydrological forecasting, flood preparedness, and water resource management. However, large observational gaps and uncertainties in governing physical parameters limit the accuracy of traditional statistical and machinelearning imputation frameworks. To address these challenges, we develop a Bayesian Physics-Informed Spatio-Temporal Network (BPI-STNet) that jointly captures spatial and temporal dependencies while enforcing hydrologic consistency through embedded physical constraints. The framework integrates a GraphSAGE-LSTM architecture to model spatial connectivity across gauges and temporal flow dynamics, coupled with a Bayesian update mechanism to estimate uncertain parameters in a simplified water-balance framework. Unlike conventional physics-informed networks that rely on sampling-based posterior estimation, BPI-STNet derives an analytic solution to the inverse problem, allowing closed-form Bayesian updates of uncertain parameters Λ={α,β,k} using Gaussian priors and likelihoods. Applied to daily observations from the Susquehanna River Basin (1980-2022), BPI-STNet achieves substantial improvements over a purely data-driven RGNN baseline, which reduced RMSE by 23 % and MAE by 9 %, and achieving an average NSE values up to 0.96. The results demonstrate that coupling Bayesian inference with physics-informed learning yields physically consistent, uncertainty-aware reconstructions that preserve the temporal persistence and statistical distribution of observed flows. The proposed framework establishes a generalizable paradigm for data-sparse hydrologic systems where both data fidelity and physical interpretability are essential.

Krishnan Kutty Ambika, Anukesh [ORNL] (ORCID:00000↗
DOE OSTI2022

T-odd leading-twist quark TMDs at small x

We study the small-x asymptotics of the flavor non-singlet T-odd leading-twist quark transverse momentum dependent parton distributions (TMDs), the Sivers and Boer-Mulders functions. While the leading eikonal small-x asymptotics of the quark Sivers function is given by the spin-dependent odderon [1, 2], we are interested in revisiting the sub-eikonal correction considered by us earlier in [3]. We first simplify the expressions for both TMDs at small Bjorken x and then construct small-x evolution equations for the resulting operators in the large-N c limit, with N c the number of quark colors. For both TMDs, the evolution equations resum all powers of the double-logarithmic parameter α s ln 2 (1/x), where α s is the strong coupling constant, which is assumed to be small. Solving these evolution equations numerically (for the Sivers function) and analytically (for the Boer-Mulders function) we arrive at the following leading small-x asymptotics of these TMDs at large N c :$$ {\displaystyle \begin{array}{l}{f}_{1T}^{\perp NS}\left(x\ll 1,{k}_T^2\right)={C}_O\left(x,{k}_T^2\right)\frac{1}{x}+{C}_1\left(x,{k}_T^2\right){\left(\frac{1}{x}\right)}^{3.4\sqrt{\frac{\alpha_s{N}_c}{4\pi }}}\\ {}{h}_1^{\perp \textrm{NS}}\left(x\ll 1,{k}_T^2\right)=C\left(x,{k}_T^2\right){\left(\frac{1}{x}\right)}^{-1}.\end{array}} $$ The functions C O (x,$ {k}_T^2 $), C 1 (x,$ {k}_T^2 $), and C(x,$ {k}_T^2 $) can be readily obtained in our formalism: they are mildly x-dependent and do not strongly affect the power-of-x asymptotics shown above. The function C O , along with the 1/x factor, arises from the odderon exchange. For the sub-eikonal contribution to the quark Sivers function (the term with C 1 ), our result shown above supersedes the one obtained in [3] due to the new contributions identified recently in [4].

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Ground Heat Flux Reconstruction Using Bayesian Uncertainty Quantification Machinery and Surrogate Modeling

Ground heat flux (G 0 ) is a key component of the land-surface energy balance of high-latitude regions. Despite its crucial role in controlling permafrost degradation due to global warming, G 0 is sparsely measured and not well represented in the outputs of global scale model simulation. In this study, an analytical heat transfer model is tested to reconstruct G 0 across seasons using soil temperature series from field measurements, Global Climate Model, and climate reanalysis outputs. The probability density functions of ground heat flux and of model parameters are inferred using available G 0 data (measured or modeled) for snow-free period as a reference. When observed G 0 is not available, a numerical model is applied using estimates of surface heat flux (dependent on parameters) as the top boundary condition. These estimates (and thus the corresponding parameters) are verified by comparing the distributions of simulated and measured soil temperature at several depths. Aided by state-of-the-art uncertainty quantification methods, the developed G 0 reconstruction approach provides novel means for assessing the probabilistic structure of the ground heat flux for regional permafrost change studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Microwave-assisted conversion of methane over H-(Fe)-ZSM-5: Evidence for formation of hot metal sites

We report microwave-assisted catalysis offers great promise as an “intensified” technology for chemical processing. The present study investigates microwave-assisted direct conversion of methane with focus on the design and evaluation of microwave-sensitive H-(Fe)ZSM-5 catalysts for the existence of hotspot formation. Isomorphous substituted H-(Fe)ZSM-5 catalysts are tuned to identify key design parameters that control their microwave sensitivity. Increasing the amount of Al and Fe substitution in the zeolite lattice is found to result in higher microwave sensitivity due to improved dielectric properties and hence facilitated microwave heating of the catalyst bed. Comparison between the performance of these catalysts in a conventional thermally-heated (CH) fixed-bed and a microwave (MW) reactor allows identification of the effect of microwave irradiation on the catalyst activity. Methane conversion is drastically enhanced at MW conditions (from 3% at CH conditions to 40% at MW conditions), indicating accelerated methane activation over the metal site and hence suggesting a hot metal site despite much lower catalyst bulk temperature measured in the microwave reactor. The existence of metal hotspot formation is further supported by the reaction product distribution and spent catalyst analysis. At MW conditions, C 2 (ethane and ethylene) and coke (mainly carbon nanotubes and nanofibers) selectivity are much higher at the cost of aromatics make compared to CH conditions. This can be explained by reduced aromatization activity at the Brønsted acid sites of the zeolite due to its lower relative temperature of the zeolite. The much-enhanced metal aggregation observed in the spent catalyst from the MW reactor along with the distribution of coke species further confirms the existence of selective heating (i.e. hotspot formation) occurring at the active metal site in the catalyst at MW conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Comparison of chromium poisoning between lanthanum strontium manganite and lanthanum strontium ferrite composite cathodes in solid oxide fuel cells

Degradation mechanisms of chromium poisoning have been extensively investigated for last two decades on various cathode materials for solid oxide fuel cells. While most researchers used half-cell experiments to investigate the effects of chromium impurities, this paper compares the degradation phenomena of LSM-YSZ and LSF-GDC cathodes in full cells under different operating conditions, namely polarized current density and humidity over the cathode. Under cathodic load, performance degradation of LSF-GDC cathode is significantly less than that of LSM-YSZ cathode. Most interestingly, under humidified air condition, LSF-based cell hardly experiences performance degradation while LSM-based cell shows a catastrophic degradation. Cr deposition in LSM-based cells occurs mainly near the electrolyte under both dry and humidified air conditions. In contrast, Cr deposition in LSF-based cell concentrates at the cathode surface under dry air condition, but concentrates both at cathode surface and near electrolyte under humidified air condition. Microstructure analysis reveals Mn-associated Cr deposits in LSM-based cathode, and Sr- and Fe-associated Cr deposits in LSF-based cathode. With the help of distribution of relaxation time analysis, the different electrochemical behaviors of LSM- and LSF-based cells are carefully interpreted. The effects of electrochemical deposition, Sr surface segregation, and humidity on LSM- and LSF-based cathodes are discussed.

25 ENERGY STORAGE↗
DOE OSTI2024

Electrophoretic deposition for improved trace element homogeneity in silica reference materials

Spatially-resolved analysis requires homogeneous reference materials (RMs) to make reliable quantitative measurements. Here we previously developed an electrophoretic deposition (EPD) method for fabrication of glassy microanalytical RMs with superior platinum-group element homogeneity **[1], and now include further dopants. For 39 trace elements, we analyzed dopant homogeneity in sintered silica (SiO 2 ) samples consolidated either mechanically by die-pressing (DP) or by EPD. A set of EPD and DP samples was made from each of two nanoparticle feedstocks produced by variations of the Stöber process **[2]. Spatially-resolved dopant distribution was characterized in all samples by laser-ablation inductively-coupled plasma mass spectrometry (LA-ICP-MS). In both sample sets, homogeneity of most trace elements was substantially improved by EPD relative to their DP counterpart.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Interfacial Response and Structural Adaptation of Structured Polyelectrolyte Thin Films

Ionizable block copolymers with distinctive block characteristics display the diversity crucial for the design of macromolecules for targeted applications. In contrast to van der Waals copolymers, their interfaces, which are critical to their function, consist of nanodomains, each of a different nature and thus unique interfacial behavior. Here, the interfacial response of a symmetric block copolymer with a sulfonated polystyrene polyelectrolyte center, tethered to polyethylene-r-propylene and terminated by poly(t-butyl styrene) is probed as polymer films are exposed to three polar solvents, water, propanol, and tetrahydrofuran (THF), using molecular dynamics simulations. Each of the solvents captures a distinctive interaction with the individual blocks. We find that at the film boundary, the interfacial response is initially dominated by that of the hydrophobic blocks to all solvents. At later times, the solvent distribution among the blocks, where water molecules associate predominantly with the sulfonated groups and propanol and THF reside at multiple different sites, determines the chemical composition and the polymer conformation at the interface. Altogether, these simulations provide the first direct molecular insight into the interfacial response of ionizable copolymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Uncertainty quantification for molecular property predictions with graph neural architecture search

Graph Neural Networks (GNNs) have emerged as a prominent class of data-driven methods for molecular property prediction. However, a key limitation of typical GNN models is their inability to quantify uncertainties in the predictions. This capability is crucial for ensuring the trustworthy use and deployment of models in downstream tasks. To that end, we introduce AutoGNNUQ, an automated uncertainty quantification (UQ) approach for molecular property prediction. AutoGNNUQ leverages architecture search to generate an ensemble of high-performing GNNs, enabling the estimation of predictive uncertainties. Our approach employs variance decomposition to separate data (aleatoric) and model (epistemic) uncertainties, providing valuable insights for reducing them. In our computational experiments, we demonstrate that AutoGNNUQ outperforms existing UQ methods in terms of both prediction accuracy and UQ performance on multiple benchmark datasets, and generalizes well to out-of-distribution datasets. Additionally, we utilize t-SNE visualization to explore correlations between molecular features and uncertainty, offering insight for dataset improvement. AutoGNNUQ has broad applicability in domains such as drug discovery and materials science, where accurate uncertainty quantification is crucial for decision-making.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗