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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Investigation into Sizing Photovoltaic with Energy Storage for Off-Grid Transactive Scenarios

In this study, a novel sizing methodology was developed for centralized and interconnected operating strategies of transactive microgrids and several variables were investigated including starting month, initial charge of battery, load variability, unit cost of solar panels and energy storage, number of systems, climate, and required reliability to determine their effect on total cost. The centralized strategy improved cost by seven to ten percent compared to the isolated strategy in every case. The interconnected strategy saved an incremental amount of money consistently compared to the isolated standard. The number of connected systems was not a strong effect. It was thought that increasing the number of systems would increase the benefit of energy sharing. Climate zones studied (“Cold”; “Hot-Dry/Mixed Dry”; “Mixed Humid”; and “Cold but with lower solar irradiation”) showed a large variation on cost with the Hot-Dry/Mixed Dry being the least expensive and Cold, with lower solar irradiation being the most expensive. Cost sensitivity analysis was performed showing that the unit cost of solar has a greater effect on the total cost. Required reliability of power, measured in outage hours, exhibited an inverse relation with cost.

14 SOLAR ENERGY↗
DOE OSTI2023

Risk Ratio and Risk Difference Estimation in Case-cohort Studies

Background: In case-cohort studies with binary outcomes, ordinary logistic regression analyses have been widely used because of their computational simplicity. However, the resultant odds ratio estimates cannot be interpreted as relative risk measures unless the event rate is low. The risk ratio and risk difference are more favorable outcome measures that are directly interpreted as effect measures without the rare disease assumption. Methods: We provide pseudo-Poisson and pseudo-normal linear regression methods for estimating risk ratios and risk differences in analyses of case-cohort studies. These multivariate regression models are fitted by weighting the inverses of sampling probabilities. Also, the precisions of the risk ratio and risk difference estimators can be improved using auxiliary variable information, specifically by adapting the calibrated or estimated weights, which are readily measured on all samples from the whole cohort. Finally, we provide computational code in R (R Foundation for Statistical Computing, Vienna, Austria) that can easily perform these methods. Results: Through numerical analyses of artificially simulated data and the National Wilms Tumor Study data, accurate risk ratio and risk difference estimates were obtained using the pseudo-Poisson and pseudo-normal linear regression methods. Also, using the auxiliary variable information from the whole cohort, precisions of these estimators were markedly improved. Conclusion: The ordinary logistic regression analyses may provide uninterpretable effect measure estimates, and the risk ratio and risk difference estimation methods are effective alternative approaches for case-cohort studies. These methods are especially recommended under situations in which the event rate is not low.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Integrability technique for fluid flow induced deformation of a boundary hair

The deformation of a dense carpet of hair due to Stokes flow in a channel can be described by a nonlinear integrodifferential equation for the shape of a single hair, which possesses several solutions for a given choice of parameters. Although it was posed in a previous study and it bears a resemblance to the pendulum problem from mechanics, this equation has not been analytically solved until now. Despite the presence on an integral with a nonlinear functional dependence on the dependent variable, the system is integrable. We compare the analytically obtained solution to a finite-difference numerical approach, identify the physically realizable solution branch, and briefly study the solution structure through a conserved energylike quantity. Time-dependent fluid-structure interactions are a rich and complex subject to investigate, and we argue that the solution discussed herein can be used as a basis for understanding these systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

How will United States commercial building energy use be impacted by IPCC climate scenarios?

Climate change and anthropogenically-forced shift of weather in the future will impact energy use and resilience of both the built environment and the electric grid. The aim of this analysis is to understand how future climate scenarios will impact electricity and natural gas use of commercial buildings in the United States. Here, this study analyzes this impact for 2030, 2045, and 2100 using Representative Concentration Pathways (RCP) scenarios defined in Intergovernmental Panel on Climate Change (IPCC) Assessment Report 5. The large, gridded simulation of meteorological variables for RCPs 2.6, 4.5, 6.0, and 8.5 are selected and downscaled to make available hourly Future Meteorological Year (FMY) weather files for use and improvement in subsequent studies. High performance computing resources use these FMYs to simulate commercial prototype buildings in every American Society of Heating, Refrigeration, and Air Conditioning Engineers (ASHRAE) climate zone of the United States (US), and results are scaled to nation-wide energy use using conditioned floor area multipliers. The analysis is conducted without speculating the physical and performance traits of future buildings or the grid characteristics. This analysis quantifies the impact of climate change on source electrical and natural gas usage for commercial buildings in the United States over the next 80 years. If US commercial floorspace remained constant, total energy use by 2100 is predicted between an 1.75% decrease under the greatest emission scenario (8.5) and a 1.76% increase under the lowest emission scenario (2.6). When adjusted for anticipated urban growth by 2100, the predicted range is 65% increase (8.5) and 71% increase (2.6). Under a global temperature rise climate scenario, the warmest US climate zones will see a large increases in electricity use derived from space cooling while the coldest US climate zones will see significant decreases in natural gas use caused by the decrease in heating necessary. While climate change may ultimately require adaptations of the built environment to withstand its effects and because the United States is a country that requires more heating than cooling, from a building energy perspective, climate change (average temperature rise) is a net energy saver for the United States.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

On the Emergence of Human Influence on Surface Air Temperature Changes Over India

Human activities in terms of greenhouse gas (GHG) emissions and aerosols resulting from the combustion of fossil fuels have been shown to have affected the temperature of the Earth on global and continental scales. The surface air temperature (TAS) over India has also been observed to be increasing over the last 100 years. Understanding the underlying causes of regional climate change over India can help in developing appropriate mitigation and adaptation strategies. Differentiating signals of externally forced climate changes from the noise of natural internal variability generally becomes more difficult as spatial scale reduces. Therefore detecting and attributing the influence of external forcings such as GHGs and aerosols is harder at local and regional scales. In this study, we applied a detection and attribution (D&A) method to study annual and seasonal mean TAS over the Indian region. We found that the observed warming over India from 1906 to 2005 cannot be explained by natural climate variability alone. We found that the warming is largely driven by the increase in GHGs, and partially offset by regional anthropogenic emissions of aerosols. These results were confirmed for the shorter 1956–2005 period, but results were sensitive to the choice of observational data set. Furthermore, the changes cannot be explained by internal climate variability or natural external forcings alone, but are compatible with the responses to combined anthropogenic GHG and aerosol forcings.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

H α emission in local galaxies: star formation, time variability, and the diffuse ionized gas

ABSTRACT The nebular recombination line H α is widely used as a star formation rate (SFR) indicator in the local and high-redshift Universe. We present a detailed H α radiative transfer study of high-resolution isolated Milky-Way and Large Magellanic Cloud simulations that include radiative transfer, non-equilibrium thermochemistry, and dust evolution. We focus on the spatial morphology and temporal variability of the H α emission, and its connection to the underlying gas and star formation properties. The H α and H β radial and vertical surface brightness profiles are in excellent agreement with observations of nearby galaxies. We find that the fraction of H α emission from collisional excitation amounts to fcol ∼ 5–$10{{\ \rm per\ cent}}$, only weakly dependent on radius and vertical height, and that scattering boosts the H α luminosity by $\sim 40{{\ \rm per\ cent}}$. The dust correction via the Balmer decrement works well (intrinsic H α emission recoverable within 25 per cent), though the dust attenuation law depends on the amount of attenuation itself both on spatially resolved and integrated scales. Important for the understanding of the H α–SFR connection is the dust and helium absorption of ionizing radiation (Lyman continuum [LyC] photons), which are about $f_{\rm abs}\approx 28{{\ \rm per\ cent}}$ and $f_{\rm He}\approx 9{{\ \rm per\ cent}}$, respectively. Together with an escape fraction of $f_{\rm esc}\approx 6{{\ \rm per\ cent}}$, this reduces the available budget for hydrogen line emission by nearly half ($f_{\rm H}\approx 57{{\ \rm per\ cent}}$). We discuss the impact of the diffuse ionized gas, showing – among other things – that the extraplanar H α emission is powered by LyC photons escaping the disc. Future applications of this framework to cosmological (zoom-in) simulations will assist in the interpretation of spectroscopy of high-redshift galaxies with the upcoming James Webb Space Telescope.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Describing the Mechanism of Instability Suppression Using a Central Pilot Flame With Coupled Experiments and Simulations

Pilot flames are commonly used to extend combustor operability limits and suppress combustion oscillations in low-emissions gas turbines. Combustion oscillations, a coupling between heat release rate oscillations and combustor acoustics, can arise at the operability limits of low-emissions combustors where the flame is more susceptible to perturbations. While the use of pilot flames is common in land-based gas turbine combustors, the mechanism by which they suppress instability is still unclear. In this study, we consider the impact of a central jet pilot on the stability of a swirl-stabilized flame in a variable-length, single-nozzle combustor. Previously, the pilot flame was found to suppress the instability for a range of equivalence ratios and combustor lengths. We hypothesize that combustion oscillation suppression by the pilot occurs because the pilot provides hot gases to the vortex breakdown region of the flow that recirculate and improve the static, and hence dynamic, stability of the main flame. This hypothesis is based on a series of experimental results that show that pilot efficacy is a strong function of pilot equivalence ratio but not pilot flow rate, which would indicate that the temperature of the pilot products as well as the combustion intensity of the pilot flame play more of a role in oscillation stabilization than the length of the pilot flame relative to the main flame. Further, the pilot-flame efficacy increases with pilot-flame equivalence ratio until it matches the main-flame equivalence ratio; at pilot equivalence ratios greater than the main equivalence ratio, the pilot-flame efficacy does not change significantly with pilot equivalence ratio. To understand these results, we use large-eddy simulation (LES) to provide a detailed analysis of the flow in the region of the pilot flame and the transport of radical species in the region between the main flame and pilot flame. Furthermore, the simulation, using a flamelet/progress variable-based chemistry tabulation approach and standard eddy viscosity/diffusivity turbulence closure models, provides detailed information that is inaccessible through experimental measurements.

42 ENGINEERING↗
DOE OSTI2026

Deep Learning enabled spectral energy conversion for in situ exposure measurements

A detector-specific deep learning (DL) approach is presented for spectra-to-exposure conversion using large-format sodium iodide (NaI(Tl)) detectors deployed for in situ environmental radiation measurements in emergency response scenarios. Accurate determination of exposure from NaI spectra is challenging due to poor energy resolution, partial energy absorption, and the strong sensitivity of traditionally deployed analytical conversion methods to calibrated source geometry and pre-deployment assumptions. Here, to address these limitations, a multi-layer perceptron model was trained on a hybrid in situ /Monte Carlo dataset constructed to span a broad range of photon energies, spatial extents, and realistic deployment variability, representative of general in situ emergency response conditions. The DL model was evaluated against commonly fielded analytical approaches under matched simulation conditions, including a single-factor method, a G-function method, and a modeled pressurized ion chamber (PIC) baseline. This study was intentionally computational in scope to enable controlled, like-for-like comparisons between conversion techniques while minimizing confounding real-world variability. Comparison to the modeled PIC provides contextual benchmarking and is not intended as a field inter-comparison with deployed instruments. Across the evaluated 20 keV to 3 MeV energy range, the DL approach consistently exhibited higher accuracy and reduced variance relative to the analytical methods against a deterministically calculated exposure. This may indicate improved robustness to spectral complexity without reliance on source-, geometric-, or spectral region-specific optimization. While results do not represent real-world validation, the presented work demonstrates that deep learning may effectively learn the nonlinear detector response-to-exposure relationship for asymmetric NaI(Tl) detectors and offers a promising pathway for improving in situ exposure estimation using spectroscopic systems already integrated into initial real-time emergency response operations.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2024

Exploring the role of biotic factors in regulating the spatial variability in land surface phenology across four temperate forest sites

Here, land surface phenology (LSP), the characterization of plant phenology with satellite data, is essential for understanding the effects of climate change on ecosystem functions. Considerable LSP variation is observed within local landscapes, and the role of biotic factors in regulating such variation remains underexplored. In this study, we selected four National Ecological Observatory Network terrestrial sites with minor topographic relief to investigate how biotic factors regulate intra-site LSP variability. We utilized plant functional type (PFT) maps, functional traits, and LSP data to assess the explanatory power of biotic factors for the start and end of season (SOS and EOS) variability. Our results indicate that PFTs alone explain only 0.8–23.4% of intra-site SOS and EOS variation, whereas including functional traits significantly improves explanatory power, with cross-validation correlations ranging from 0.50 to 0.85. While functional traits exhibited diverse effects on SOS and EOS across different sites, traits related to competitive ability and productivity were important for explaining both SOS and EOS variation at these sites. These findings reveal that plants exhibit diverse phenological responses to comparable environmental conditions, and functional traits significantly contribute to intra-site LSP variability, highlighting the importance of intrinsic biotic properties in regulating plant phenology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

A surrogate-model-based approach for estimating the first and second-order moments of offshore wind power

Power curve, the functional relationship that governs the process of converting a set of weather variables experienced by a wind turbine into electric power, is widely used in the wind industry to estimate power output for planning and operational purposes. Existing methods for power curve estimation have three main limitations: (i) they mostly rely on wind speed as the sole input, thus ignoring the secondary, yet possibly significant effects of other environmental factors, (ii) they largely overlook the complex marine environment in which offshore turbines operate, potentially compromising their value in offshore wind energy applications, and (ii) they solely focus on the first-order properties of wind power, with little (or null) information about the variation around the mean behavior, which is important for ensuring reliable grid integration, asset health monitoring, and energy storage, among others. In light of that, this study investigates the impact of several wind-and wave-related factors on offshore wind power variability, with the ultimate goal of accurately predicting its first two moments. Further, our approach couples OpenFAST—a multi-physics wind turbine simulator—with Gaussian Process (GP) regression to reveal the underlying relationships governing offshore weather-to-power conversion. We first find that a multi-input power curve which captures the combined impact of wind speed, direction, and air density, can provide double-digit improvements, in terms of prediction accuracy, relative to univariate methods which rely on wind speed as the sole explanatory variable (e.g. the standard method of bins). Wave-related variables are found not important for predicting the average power output, but interestingly, appear to be extremely relevant in describing the fluctuation of the offshore power around its mean. Tested on real-world data collected at the New York/New Jersey bight, our proposed multi-input models demonstrate a high explanatory power in predicting the first two moments of offshore wind generation, testifying their potential value to the offshore wind industry.

17 WIND ENERGY↗
DOE OSTI2025

Impact of U-10Mo HALEU fuel element tolerances on the Massachusetts Institute of Technology reactor safety and operational performance – Thermal hydraulics

The U.S. is coordinating efforts for the conversion of six U.S. High Performance Research Reactors (USHPRR) including one critical facility from highly enriched uranium (HEU) to low-enriched uranium (LEU). In order to continue the mission of these reactors, including the Massachusetts of Institute of Technology Reactor (MITR), and achieve similar performance, high-assay low-enriched uranium (HALEU) with a high-density metallic alloy of uranium with 10 wt% molybdenum (U-10Mo) is being evaluated. The impact of the fabrication specification and tolerances was assessed following the preliminary design of the MITR LEU fuel elements using the U-10Mo monolithic alloy. This research focuses on the analysis of fabrication specification impact on thermal hydraulics (TH) characteristic of the MITR LEU core as a function of the variation of the relevant fuel specification parameters (e.g., coolant channel gap thickness, fuel plate thickness, etc.). The analyses are performed based on an all-fresh LEU fuel conversion plan identified in a preliminary safety analysis report submitted to the Nuclear Regulatory Commission. The reactor power margin to the onset of nucleate boiling (ONB) is assessed under the limiting safety system settings (LSSS), where a scram occurs, to ensure there is sufficient margin to the reactor safety limit, which is defined by the onset of flow instability that occurs after the ONB. The best estimate plus uncertainty approach is employed to analyze this TH characteristic, which yields realistic results while maintaining adequate conservatism, utilizing a statistical uncertainty propagation method with the STAT7 code. The TH characteristic is analyzed as a function of the variability of the specification parameters resulting from the fabrication process. The main findings of this study show that the MITR core can meet the TH safety and operational requirements at the all-LEU initial core startup (cycle 1), selected transition cycles (most reactive cycle and most limiting cycle: cycle 3 and 5, respectively) and equilibrium (cycle 14) cores under all limiting fabrication parameter combinations considered. In addition, the analyses show that the dependency of the core power margin to ONB on those specification parameters that have the most direct impact on TH performance is non-linear but monotonically decreasing within the specification tolerances. The third order polynomial fit curves are reported in detail for selected limiting cases and can serve as a powerful tool for future MITR fuel management in cases such as when HALEU supply is established that may allow additional cycle length or other operational benefits.

Conversion↗
DOE OSTI2020

High temperature air oxidation behavior of Hastelloy X processed by Electron Beam Melting (EBM) and Selective Laser Melting (SLM)

The microstructure and oxidation behavior of Laser Beam Melted, Electron Beam Melted and wrought Hastelloy X were studied at 950 °C in dry air, 50 h cycles, up to 1000 h. The variability of processing parameters and powder compositions strongly impacted the oxidation and spallation behavior. Finally, the alloys with high Mn and Si were associated with higher oxidation rates, finer Cr 2 O 3 grain microstructure and increased spallation was observed for the alloys with large elongated grain microstructures (aspect ratio of 10 ± 3).

36 MATERIALS SCIENCE↗
DOE OSTI2021

Quantifying the hierarchy of structural and mechanical length scales in granular systems

Continuum modeling of granular media is made possible by the existence of a length scale at and above which grain-resolved properties can be meaningfully homogenized. Progress has been made in identifying such length scales relevant to local structural properties such as porosity. However, a systematic analysis of scales above which different mechanical properties can be homogenized has yet to emerge. Here, X-ray tomography and 3D X-ray diffraction data are examined to identify such length scales. The data was obtained in-situ in compressed granular materials with rigid and flexible confinement. The experimental data are supplemented with validated discrete element simulations which examine different system sizes and different boundary conditions. Overall, our study reveals a hierarchy in the length scales of granular solids, with lengths governing structural variables being the shortest, lengths of stress variables being intermediate, and lengths of energy dissipation being the longest. All structural and mechanical length scales obey a power law based on the theory of Geostatistics, implying that the length scales can be found by analyzing samples significantly smaller than the length scales themselves. The length scales are also found to be sensitive to boundary conditions, implying that they are extrinsic features of granular media.

36 MATERIALS SCIENCE↗
DOE OSTI2024

CatTestHub: A benchmarking database of experimental heterogeneous catalysis for evaluating advanced materials

The ability to quantitatively compare newly evolving catalytic materials and technologies is hindered by the widespread availability of catalytic data collected in a consistent manner. While certain catalytic chemistries have been widely studied across decades of scientific research, quantitative comparisons based on literature information is hindered by variability in reaction conditions, types of reported data, and reporting procedures. Here, we present CatTestHub, an open-access database dedicated to benchmarking experimental heterogeneous catalysis data. Combining systematically reported catalytic activity data for selected probe chemistries, with relevant material characterization and reactor configuration information, the database provides a collection of catalytic benchmarks for distinct classes of active site functionality. Through key choices in data access, availability, and traceability, CatTestHub seeks to balance the fundamental information needs of chemical catalysis and the FAIR data design principles. Details of the database architecture and the means through which to navigate it are presented, highlighting examples of catalytic insights readily drawn from the available benchmarking data. In its current iteration, CatTestHub spans over 250 unique experimental data points, collected over 24 solid catalysts, that facilitated the turnover of 3 distinct catalytic chemistries. Here, a roadmap is presented through which to expand the open-access platform that serves as a community wide benchmark, primarily through continuous addition of kinetic information on select catalytic systems by members of the heterogeneous catalysis community at large.

Benchmark↗
DOE OSTI2024

Enriching OpenStreetMap network data for transportation applications: Insights into the impact of urban congestion on accessibility

OpenStreetMap (OSM) data is a valuable open-source resource for various transportation, traffic, and planning applications. However, OSM network data lack operating traffic speed information, which is critical for transport planning and operations. Addressing this shortcoming, this study leverages commercial vendor data (to serve as ground truth) with exogenous, open-source variables characterizing local transport infrastructure, land use, and demographic information to predict average congested traffic speeds on OSM networks. Three machine-learning models were tested and estimated for OSM links with and without speed limit information in the Denver metropolitan region. Among these, XGBoost performed best, with mean absolute errors of 3.27 and 3.62 mph for links with and without speed limits, respectively. The developed models accurately predicted traffic speeds for different hours and days of the week compared to ground truth data. Using these predicted speeds, drive accessibility scores were computed for the Denver region for different time periods using the Mobility Energy Productivity (MEP) metric to understand the impact of congestion on energy-efficient accessibility. Results show that congestion-adjusted drive accessibility can be significantly lower compared to accessibility calculated using free flow speeds. Specifically, weekday evening hours saw a 42 % drop in accessibility due to reduced speeds, particularly around downtown Denver. Across the Denver metro region, approximately half as many opportunities and jobs are accessible in under 20 min by car during the evening peak period relative to free flow conditions. These findings underscore the importance of using congestion-adjusted operating speeds rather than speed limits in accessibility calculations, as reliance on speed limits can substantially overestimate energy-efficient drive accessibility in large, car-centric cities susceptible to significant congestion. In conclusion, the methodology presented here could further enrich OSM network data, making them useful for an even broader range of transportation applications.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Tunable mechanical behavior of graphene nanoribbon-metal composites fabricated through an electrocharge-assisted process

This work investigates the role of a carbon nanophase on the local mechanical behavior of nanocarbon metal matrix composites (NCMCs) produced through an electrocharge-assisted process. Nanoindentation experiments on single crystal Al, Al 1350 parent alloys, and Al 1350 NCMCs revealed variable mechanical properties, caused by an interplay between microstructure and graphitic reinforcements. TEM and AFM studies also reveal nanoscale structural changes based on the incorporation of a carbon nanophase. In order to decouple the effects of the aforementioned mechanical behaviors, molecular dynamics nanoindentation simulations were performed on the (111) surface of Al and Al NCMC samples containing semi-infinite graphene nanoribbons to examine the evolution of plasticity over time. Findings indicate that the arrangement of a finite graphene nanophase within a host matrix can alter plasticity mechanisms and therefore yield strength in near-surface mechanical behavior with little effect on elastic properties. Here, this understanding enables further study into tunable bulk properties of Al-based NCMCs while isolating microstructural effects and reinforcement effects of the carbon phase. Such an understanding will lead to application-specific material geometries ranging from highperforming vehicle structures to next-generation electrical devices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Exploring Afro-Asian water fluxes in CMIP5 and CMIP6 models: Present-day evaluation and future projections

Accurate representation and projection of water fluxes are vital, particularly in monsoon regions where seasonal variability and changes significantly impact water resources, agriculture, hydroelectric power generation, and the economy. This study uses both CMIP5 and CMIP6 models to investigate the present-day representation of key water flux components (including precipitation, evaporation, water vapor, and moisture advection) over the Afro-Asian region during the summer monsoon (JJAS). We also examine future changes under two emission scenarios and assess the underlying physical mechanisms driving these changes while identifying sources of projection uncertainty. Our results show that both models reasonably capture the present-day characteristics of water flux components, although with noticeable biases. Across most regions, we find that CMIP6 models demonstrate slight improvements over CMIP5 in the representation of these components. In a warmer future, a robust intensification of JJAS precipitation (exceeding 0.25 mm/day) is projected across the Afro-Asian region. This increase is largely driven by the vertical thermodynamic term associated with increasing temperature. We find that model uncertainty is the primary source of uncertainty in water flux projections, accounting for over 50 % of the total variance.

Climate change↗
DOE OSTI2025

Unraveling the Nature of Vibrational Dynamics in CsPbI 3 by Inelastic Neutron Scattering and Molecular Dynamics Simulations

Cesium lead iodide, CsPbI 3 , is an optoelectronic material of large interest for various technological applications; however, fundamental questions surrounding the vibrational dynamics of this material, especially regarding its role in structural phase transitions, remain to be elucidated. Here, in a combined variable temperature inelastic neutron scattering (INS) and machine-learning based molecular dynamics (MD) simulation study, we show that the stable phase at room temperature, i.e., the nonperovskite δ-phase, exhibits phonon modes with weak anharmonicity with only a weak temperature dependence from 10 K all the way up to the transition to the cubic perovskite α-phase at approximately 600 K. In contrast, the α-phase features anharmonic and damped vibrational dynamics, mainly associated with overdamped tilting motions of the PbI 6 octahedra. Crucially, these overdamped tilting modes, which relate to the tetragonal and orthorhombic distorted perovskite phases (β- and γ-phase, respectively) formed at lower temperatures, stay overdamped by more than 100 K above the respective phase transition. This suggests a flat energy landscape of octahedral tilting motions in α-CsPbI3 and with structural fluctuations on the picosecond time scale with tilting patterns that locally resemble the structure of the β- and γ-phases. The vibrational dynamics of α-CsPbI 3 are also characterized by pronounced anharmonic motions with large thermal displacements of the Cs + ions, but these modes remain underdamped at 600 K.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗