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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Scalability of grid- and subbasin-based land surface modeling approaches for hydrologic simulations

This paper investigates the relative merits of grid- and subbasin-based land surface modeling approaches for hydrologic simulations, with a focus on their scalability (i.e., abilities to perform consistently across a range of spatial resolutions) in simulating runoff generation. Simulations produced by the grid- and subbasin-based configurations of the Community Land Model (CLM) are compared at four spatial resolutions (0.125o, 0.25o, 0.5o and 1o) over the topographically diverse region of the U.S. Pacific Northwest. Using the 0.125o resolution simulation as the “reference”, statistical skill metrics are calculated and compared across simulations at 0.25o, 0.5o and 1o spatial resolutions of each modeling approach at basin and topographic region levels. Results suggest significant scalability advantage for the subbasin-based approach compared to the grid-based approach for runoff generation. Basin level annual average relative errors of surface runoff at 0.25o, 0.5o, and 1o compared to 0.125o are 3%, 4%, and 6% for the subbasin-based configuration and 4%, 7%, and 11% for the grid-based configuration, respectively. The scalability advantages of the subbasin-based approach are more pronounced during winter/spring and over mountainous regions. The source of runoff scalability is found to be related to the scalability of major meteorological and land surface parameters of runoff generation. More specifically, the subbasin-based approach is more consistent across spatial scales than the grid-based approach in snowfall/rainfall partitioning, which is related to air temperature and surface elevation. Scalability of a topographic parameter used in the runoff parameterization also contributes to improved scalability of the rain driven saturated surface runoff component, particularly during winter. Hence this study demonstrates the importance of spatial structure for multi-scale modeling of hydrological processes, with implications to surface heat fluxes in coupled land-atmosphere modeling.

Tesfa, Teklu K.↗
DOE OSTI2025

DAmodel: hierarchical Bayesian modelling of DA white dwarfs for spectrophotometric calibration

We use hierarchical Bayesian modelling to calibrate a network of 32 all-sky faint DA white dwarf (DA WD) spectrophotometric standards (⁠16.5 < V , 19.5⁠) alongside three CALSPEC standards, from 912 Å to 32 μm. The framework is the first of its kind to jointly infer photometric zero points and WD parameters (surface gravity log g⁠, effective temperature T eff ⁠, extinction A V ⁠, dust relation parameter R V ) by simultaneously modelling both photometric and spectroscopic data. We model panchromatic Hubble Space Telescope Wide Field Camera 3 (HST/WFC3) UVIS and IR photometry, HST/STIS UV spectroscopy, and ground-based optical spectroscopy to sub-per cent precision. Photometric residuals for the sample are the lowest yet yielding < 0.004 mag RMS on average from the UV to the NIR, achieved by jointly inferring time-dependent changes in system sensitivity and WFC3/IR count-rate nonlinearity. Our GPU-accelerated implementation enables efficient sampling via Hamiltonian Monte Carlo, critical for exploring the high-dimensional posterior space. The hierarchical nature of the model enables population analysis of intrinsic WD and dust parameters. Inferred spectral energy distributions from this model will be essential for calibrating the James Webb Space Telescope as well as next-generation surveys, including Vera Rubin Observatory’s Legacy Survey of Space and Time and the Nancy Grace Roman Space Telescope.

methods: statistical↗
DOE OSTI2021

Analysis of convection heat transfer on multiscale rough superhydrophobic and liquid infused surfaces

Multiscale rough superhydrophobic or slippery liquid infused porous surfaces have gained much interest in recent years for their improved transport phenomena properties. While there have been several studies on drag reduction and condensation on non-wetting surfaces, convection heat transfer that is important in many thermal and thermochemical applications has not been addressed systematically. Here, this article utilizes a fractal description of rough surface topographies to develop analytical models for the Nusselt number and the thermal hydraulic factor for fluid flow and heat transfer inside a cylinder with non-wetting surfaces. For air-infused superhydrophobic surfaces, the model considers the dynamic stability of the air/fluid interface in the asperities. Using the analytical formulations and the stability criteria, systematic studies are presented on the effects of the fractal surface parameters, cylinder radius and Reynolds number on the convective heat transfer characteristics, from which surface texture design maps are developed for maximizing the convection heat transfer. It is shown that multiscale non-wetting surfaces are most effective in the range of lower Reynolds number and small cylinder radius for achieving the best convective heat transfer and thermal hydraulic performance. Applying the models to actual non-wetting surface topographies fabricated using electrodeposition and chemical etching, it is shown that contrary to prevailing notion, superhydrophobicity, characterized by the highest contact angles, does not always lead to the maximum convective heat transfer performance, and that under certain fluid flow conditions, hydrophobic surfaces may offer a greater thermal performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Multi-scale modelling to relate beryllium surface temperature, deuterium concentration and erosion in fusion reactor environment

Beryllium (Be) has been chosen as the plasma-facing material for the main wall of ITER, the next generation fusion reactor. Identifying the key parameters that determine Be erosion under reactor relevant conditions is vital to predict the ITER plasma-facing component lifetime and viability. To date, a certain prediction of Be erosion, focusing on the effect of two such parameters, surface temperature and D surface content, has not been achieved. In this paper, we develop the first multi-scale KMC-MD modeling approach for Be to provide a more accurate database for its erosion, as well as investigating parameters that affect erosion. First, we calculate the complex relationship between surface temperature and D concentration precisely by simulating the time evolution of the system using an object kinetic Monte Carlo (OKMC) technique. These simulations provide a D surface concentration profile for any surface temperature and incoming D energy. We then describe how this profile can be implemented as a starting configuration in molecular dynamics (MD) simulations. We finally use MD simulations to investigate the effect of temperature (300–800 K) and impact energy (10–200 eV) on the erosion of Be due to D plasma irradiations. The results reveal a strong dependency of the D surface content on temperature. Increasing the surface temperature leads to a lower D concentration at the surface, because of the tendency of D atoms to avoid being accommodated in a vacancy, and de-trapping from impurity sites diffuse fast toward bulk. At the next step, total and molecular Be erosion yields due to D irradiations are analyzed using MD simulations. The results show a strong dependency of erosion yields on surface temperature and incoming ion energy. The total Be erosion yield increases with temperature for impact energies up to 100 eV. However, increasing temperature and impact energy results in a lower fraction of Be atoms being sputtered as BeD molecules due to the lower D surface concentrations at higher temperatures. Finally, these findings correlate well with different experiments performed at JET and PISCES-B devices.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Force field for calcium sulfate minerals to predict structural, hydration, and interfacial properties

Calcium sulfates such as anhydrite, hemihydrate, and gypsum find widespread use in building materials, implants, and tissue healing. We introduce a simple and compatible atomistic force field for all calcium sulfate phases that reproduces a wide range of experimental data including lattice parameters, surface, hydration, mechanical, and thermal properties in 1% to 5% accuracy relative to experiments. The performance is several times better than prior force fields and DFT methods, which lead to errors in structures and energies up to 100%. We explain (hkl) cleavage energies, the dynamics of (hkl) water interfaces, and new insights into molecular origins of crystal-facet specific hydration and solubility. Impressive agreement of computed and experimentally measured hydration energies is shown. The models add to the Interface force field (IFF) and are compatible with multiple force fields (CHARMM, AMBER, GROMOS, CVFF, PCFF, OPLS-AA) for property predictions of sulfate-containing materials from atoms to the large nanometer scale.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multiscale ACI Satellite Database

The SATELLITE_EAGLES_PNNL NetCDF dataset contains a suite of satellite- and reanalysis-derived atmospheric and surface parameters on a regular latitude–longitude grid. The dataset includes core geophysical fields such as land fraction, aerosol optical depth at multiple wavelengths (465, 550, 667, and 865 nm), sea surface temperature, estimated inversion strength, and various thermodynamic and dynamic quantities (e.g., relative humidity, vertical velocity, boundary-layer height, and surface fluxes) from both MERRA and ERA reanalysis products, provided as daily-mean and instantaneous values. A major component of the dataset consists of MODIS-retrieved cloud microphysical properties, including cloud droplet number concentration, cloud effective radius, optical thickness, and liquid water path, provided for three compositing regimes (“All,” “Q06,” and “G18”). Corresponding cloud-top parameters—temperature, height, and pressure—along with total and domain-mean cloud fraction fields are also included. The file further integrates additional satellite data from AMSR-E (for cloud water, rain water, and surface precipitation retrievals) and CERES (for top-of-atmosphere radiative fluxes, cloud fractions, and albedo). This dataset is designed to evaluate aerosol–cloud interactions in warm clouds, emphasizing the use of MODIS for deriving cloud droplet number concentration and liquid water path statistics. The complementary satellite and reanalysis fields are co-located and time-matched to the same instantaneous MODIS observations, enabling consistent comparisons between cloud properties, aerosol loading, and large-scale meteorological conditions. The dataset is recently featured in Christensen et al. (2025), Machine Learning Reveals Strong Grid-Scale Dependence in the Satellite Nd–LWP Relationship, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-3850, 2025.

Christensen, Matthew [Pacific Northwest National L↗
DOE OSTI2025

Multiscale ACI Satellite Database

The SATELLITE_EAGLES_PNNL NetCDF dataset contains a suite of satellite- and reanalysis-derived atmospheric and surface parameters on a regular latitude–longitude grid. The dataset includes core geophysical fields such as land fraction, aerosol optical depth at multiple wavelengths (465, 550, 667, and 865 nm), sea surface temperature, estimated inversion strength, and various thermodynamic and dynamic quantities (e.g., relative humidity, vertical velocity, boundary-layer height, and surface fluxes) from both MERRA and ERA reanalysis products, provided as daily-mean and instantaneous values. A major component of the dataset consists of MODIS-retrieved cloud microphysical properties, including cloud droplet number concentration, cloud effective radius, optical thickness, and liquid water path, provided for three compositing regimes (“All,” “Q06,” and “G18”). Corresponding cloud-top parameters—temperature, height, and pressure—along with total and domain-mean cloud fraction fields are also included. The file further integrates additional satellite data from AMSR-E (for cloud water, rain water, and surface precipitation retrievals) and CERES (for top-of-atmosphere radiative fluxes, cloud fractions, and albedo). This dataset is designed to evaluate aerosol–cloud interactions in warm clouds, emphasizing the use of MODIS for deriving cloud droplet number concentration and liquid water path statistics. The complementary satellite and reanalysis fields are co-located and time-matched to the same instantaneous MODIS observations, enabling consistent comparisons between cloud properties, aerosol loading, and large-scale meteorological conditions. The dataset is recently featured in Christensen et al. (2025), Machine Learning Reveals Strong Grid-Scale Dependence in the Satellite Nd–LWP Relationship, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-3850, 2025.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Uncertainty Analysis of Runoff Simulations and Parameter Identifiability in the Community Land Model – Evidence from MOPEX Basins

With the emergence of earth system models as important tools for understanding and predicting climate change and implications to mitigation and adaptation, it has become increasingly important to assess the fidelity of the land component within earth system models to capture realistic hydrological processes and their response to the changing climate and quantify the associated uncertainties. This study investigates the sensitivity of runoff simulations to major hydrologic parameters in version 4 of the Community Land Model (CLM4) by integrating CLM4 with a stochastic exploratory sensitivity analysis framework at 20 selected watersheds from the Model Parameter Estimation Experiment (MOPEX) spanning a wide range of climate and site conditions. We found that for runoff simulations, the most significant parameters are those related to the subsurface runoff parameterizations. Soil texture related parameters and surface runoff parameters are of secondary significance. Moreover, climate and soil conditions play important roles in the parameter sensitivity. In general, site conditions within water-limited hydrologic regimes and with finer soil texture result in stronger sensitivity of output variables, such as runoff and its surface and subsurface components, to the input parameters in CLM4. This study demonstrated the feasibility of parameter inversion for CLM4 using streamflow observations to improve runoff simulations. By ranking the significance of the input parameters, we showed that the parameter set dimensionality could be reduced for CLM4 parameter calibration under different hydrologic and climatic regimes so that the inverse problem is less ill posed.

analysis↗
DOE OSTI2015

X-ray perspective of the twisted magnetospheres of magnetars

Anomalous X-ray pulsars (AXPs) and soft gamma-ray repeaters (SGRs) are recognized as the most promising magnetar candidates, as indicated by their energetic bursts and rapid spin-downs. It is expected that the strong magnetic field leaves distinctive imprints on the emergent radiation both by affecting the radiative processes in atmospheres of magnetars and by scattering in the upper magnetospheres. We construct a self-consistent physical model that incorporates emission from the magnetar surface and its reprocessing in the three-dimensional (3D) twisted magnetosphere using a Monte Carlo technique. The synthetic spectra are characterized by four parameters: surface temperature kT, surface magnetic field strength B, magnetospheric twist angle Δϕ, and the normalized electron velocity β. We also create a tabular model (STEMS3D) and apply it to a large sample of XMM-Newton spectra of magnetars. The model successfully fits nearly all spectra, and the obtained magnetic field for 7 out of the 11 sources are consistent with the values inferred from the spin-down rates. We conclude that the continuum-fitting by our model is a robust method to measure the magnetic field strength and magnetospheric configuration of AXPs and SGRs. Investigating the multiple observations of variable sources, we also study the mechanism of their spectral evolution. Our results suggest that the magnetospheres in these sources are highly twisted (Δϕ>1), and the behavior of magnetospheric twisting and untwisting is revealed in the 2002 outburst of 1E 2259+586.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

A Polymer-Oriented Self-Assembly Strategy toward Mesoporous Metal Oxides with Ultrahigh Surface Areas

Mesoporous metal oxides (MMOs) have attracted comprehensive attention in many fields, including energy storage, catalysis, and separation. Current synthesis of MMOs mainly involve use of surfactants as templates to generate mesopores and organic reagents as solvents to hinder hydrolysis and condensation of inorganic precursors, which is adverse to adjusting the interactions between surfactants and inorganic precursors. The resulting products have uncontrollable pore structure, crystallinity, and relatively lower surface areas. Here, a facile and general polymer-oriented self-assembly strategy to synthesize a series of MMOs (e.g., TiO 2 , ZrO 2 , NbO 5 , Al 2 O 3 , Ta 2 O 5 , HfO 2 , and SnO 2 ) by using cationic polymers as porogens and metal alkoxides as metal oxide precursors in a robust aqueous synthesis system are reported. Nitrogen adsorption analysis and transmission electron microscopy confirm that the obtained MMOs have ultrahigh specific surface areas and large pore volumes (i.e., 733 m 2 g –1 and 0.485 cm 3 g –1 for mesoporous TiO 2 ). Moreover, the structural parameters (surface area, pore size, and pore volume) and crystallinity can be readily controlled by tuning the interactions between cationic polymers and precursors. The as-synthesized crystalline mesoporous TiO 2 exhibits promising performance in photocatalytic water splitting of hydrogen production and a high hydrogen production rate of 3.68 mol h –1 g –1 .

36 MATERIALS SCIENCE↗
DOE OSTI2024

Shubnikov–de Haas oscillations of biaxial-strain-tuned superconductors in pulsed magnetic field up to 60 T

Two-dimensional (2D) materials have gained increasing prominence not only in fundamental research but also in daily applications. However, to fully harness their potential, it is crucial to optimize their properties with an external parameter and track the electronic structure simultaneously. Magnetotransport over a wide magnetic field range is a powerful method to probe the electronic structure and, for metallic 2D materials, quantum oscillations superimposed on the transport signals encode Fermi surface parameters. In this manuscript, we utilize biaxial strain as an external tuning parameter and investigate the effects of strain on the electronic properties of two quasi-2D superconductors, MoTe 2 and RbV 3 Sb 5 , by measuring their magnetoresistance in pulsed magnetic fields up to 60 T. With a careful selection of insulating substrates, we demonstrate the possibility of both the compressive and tensile biaxial strains imposed on MoTe 2 and RbV 3 Sb 5 , respectively. For both systems, the applied strain has led to superconducting critical temperature enhancement compared to their free-standing counterparts, proving the effectiveness of this biaxial strain method at cryogenic temperatures. Clear quantum oscillations in the magnetoresistance—the Shubnikov–de Haas (SdH) effect—are obtained in both samples. In strained MoTe 2 , the magnetoresistance exhibits a nearly quadratic dependence on the magnetic field and remains non-saturating even at the highest field, whereas in strained RbV 3 Sb 5 , two SdH frequencies showed a substantial enhancement in effective mass values, hinting at a possible enhancement of charge fluctuations. Our results demonstrate that combining biaxial strain and pulsed magnetic field paves the way for studying 2D materials under unprecedented conditions.

2D materials↗
DOE OSTI2024

Shubnikov-de Haas oscillations of biaxial-strain-tuned superconductors in pulsed magnetic field up to 60 T

Two-dimensional (2D) materials have gained increasing prominence not only in fundamental research but also in daily applications. However, to fully harness their potential, it is crucial to optimize their properties with an external parameter and track the electronic structure simultaneously. Magnetotransport over a wide magnetic field range is a powerful method to probe the electronic structure and, for metallic 2D materials, quantum oscillations superimposed on the transport signals encode Fermi surface parameters. In this manuscript, we utilize biaxial strain as an external tuning parameter and investigate the effects of strain on the electronic properties of two quasi-2D superconductors, MoTe 2 and RbV 3 Sb 5 , by measuring their magnetoresistance in pulsed magnetic fields up to 60 T. With a careful selection of insulating substrates, we demonstrate the possibility of both the compressive and tensile biaxial strains imposed on MoTe 2 and RbV 3 Sb 5 , respectively. For both systems, the applied strain has led to superconducting critical temperature enhancement compared to their free-standing counterparts, proving the effectiveness of this biaxial strain method at cryogenic temperatures. Clear quantum oscillations in the magnetoresistance—the Shubnikov–de Haas (SdH) effect—are obtained in both samples. In strained MoTe 2 , the magnetoresistance exhibits a nearly quadratic dependence on the magnetic field and remains non-saturating even at the highest field, whereas in strained RbV 3 Sb 5 , two SdH frequencies showed a substantial enhancement in effective mass values, hinting at a possible enhancement of charge fluctuations. Our results demonstrate that combining biaxial strain and pulsed magnetic field paves the way for studying 2D materials under unprecedented conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Determining the Effects of Environment and Atmospheric Parameters on PV Field Performance

The performance losses due to soiling occurring on any photovoltaic (PV) device are caused by a complex mechanism that involves numerous factors and their interactions. For this reason, the present work analyzes the outputs of reference PV cells installed in various locations, with the aim of contributing to the identification of the most important factors influencing the accumulation of dust on a PV surface. Parameters such as the air-quality indexes, the recurrence and the amount of rainfall and the climate zone are investigated and related to the soiling losses of the PV device.

14 SOLAR ENERGY↗
DOE OSTI2013

A reverse Monte Carlo method for deriving optical constants of solids from reflection electron energy-loss spectroscopy spectra

A reverse Monte Carlo (RMC) method is developed to obtain the energy loss function (ELF) and optical constants from a measured reflection electron energy-loss spectroscopy (REELS) spectrum by an iterative Monte Carlo (MC) simulation procedure. The method combines the simulated annealing method, i.e., a Markov chain Monte Carlo (MCMC) sampling of oscillator parameters, surface and bulk excitation weighting factors, and band gap energy, with a conventional MC simulation of electron interaction with solids, which acts as a single step of MCMC sampling in this RMC method. To examine the reliability of this method, we have verified that the output data of the dielectric function are essentially independent of the initial values of the trial parameters, which is a basic property of a MCMC method. The optical constants derived for SiO{sub 2} in the energy loss range of 8-90 eV are in good agreement with other available data, and relevant bulk ELFs are checked by oscillator strength-sum and perfect-screening-sum rules. Our results show that the dielectric function can be obtained by the RMC method even with a wide range of initial trial parameters. The RMC method is thus a general and effective method for determining the optical properties of solids from REELS measurements.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Parametrically designed surface topography on CAD models of additively manufactured lattice structures for improved design validation

Additively Manufactured (AM) lattice structures of the laser powder bed fusion (LPBF) process generally have different surface geometries depending on the overhang angle and location. This means that the design validation stage is often challenging, considering it is based on an ideal Computer Aided Design (CAD) model that is not truly representative, since the AM part will be different in terms of dimensional accuracy and surface finish. Previous studies have relied on the design of surface textures that are independent of the overhang angle, or techniques based on directly using X-ray Computed Tomography (XCT) data. In this paper, a new technique for designing surface texture on the CAD of lattices has been investigated and correlated with areal surface roughness parameters. After extracting areal surface parameters from the XCT data of the lattice, the method allowed for the design of this surface texture on the part CAD taking in consideration if its up skin or down skin, without using XCT data as the main input. By applying this method, it is possible to obtain a lattice CAD model with a designed surface texture and geometry that is more representative of the actual AM lattice. The mean deviation between the CAD model with the designed surface and the XCT was a third of the one between the XCT and the initial CAD. The proposed method allows for designing and replicating LPBF AM surfaces on the CAD of a lattice, taking into consideration the dimensional deviation caused by AM surfaces, especially on overhangs. Assuming that an LPBF AM process is stable and produces approximately the same AM surface, this method can be used to predict the geometry of a lattice, providing a cost-effective and efficient methodology that minimizes the time needed for design validation.

42 ENGINEERING↗
DOE OSTI2015

Elastic-properties measurement at high temperatures through contact resonance atomic force microscopy

Miniaturization of products and need for further improvement of machines performance introduce new serious challenges in materials characterization. In particular non-destructive mechanical testing in the sub-micrometer scale is needed to better understand and improve micro-manufacturing operations. To this regard, some open issues are of particular interest: low depth of penetration, high lateral resolution and measurements at elevated temperatures. An interesting solution is given by acoustic microscopy techniques, which can be successfully implemented for advanced research in surface elasticity, allowing fast direct and non-destructive measurement of Young’s modulus and related surface parameters. In this work an instrument set up for Contact Resonance Atomic Force Microscopy is proposed, where the sample with is coupled to a heating stage and a piezoelectric transducer directly vibrate the cantilever during scanning, in order to allow exploitation of high resolution measurements at relatively high temperatures. Such instrument set up was undergone a set of calibration experiments in order to allow not only qualitative but also quantitative characterization of surfaces. The work was completed with a feasibility study with mechanical and topography measurements at temperatures as high as 150°C, with lateral resolution lower than 100 nm.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Direct radiative effect by multicomponent aerosol over China

The direct radiative effect (DRE) of multiple aerosol species (sulfate, nitrate, ammonium, black carbon (BC), organic carbon (OC), and mineral aerosol) and their spatiotemporal variations over China were investigated using a fully coupled meteorology–chemistry model (WRF-Chem) for the entire year of 2006. We made modifications to improve model performance, including updating land surface parameters, improving the calculation of transition metal-catalyzed oxidation of SO 2 , and adding in heterogeneous reactions between mineral aerosol and acid gases. The modified model well reproduced the magnitude, seasonal pattern, and spatial distribution of the measured meteorological conditions, concentrations of PM 10 and its components, and aerosol optical depth (AOD). A diagnostic iteration method was used to estimate the overall DRE of aerosols and contributions from different components. At the land surface, all kinds of aerosol species reduced the incident net radiation flux with a total DRE of 10.2 W m -2 over China. Aerosols significantly warm the atmosphere with the national mean DRE of +10.8 W m -2 . BC was the leading radiative-heating component (+8.7 W m -2 ), followed by mineral aerosol (+1.1 W m -2 ). At the top of the atmosphere (TOA), BC introduced the largest radiative perturbation (+4.5 W m -2 ), followed by sulfate (-1.4 W m -2 ). The overall perturbation of aerosols on radiation transfer is quite small over China, demonstrating the counterbalancing effect between scattering and adsorbing aerosols. Aerosol DRE at the TOA had distinct seasonality, generally with a summer maximum and winter minimum, mainly determined by mass loadings, hygroscopic growth, and incident radiation flux.

Huang, Xin↗