This dataset contains example input files, training data sets and potential files related to the publication "First-principles-based Machine Learning Models for Phase Behavior and Transport Properties of CO2." by Mathur et al (2023). In this work, we developed machine learning models for CO2 based on different exchange-correlation DFT functionals. We assessed their performance on liquid densities, vapor-liquid equilibrium and transport properties.
Guo, Xuehui; Pan, Da; Daly, Ryan; Chen, Xi; Walker, John; Tao, Lei; McSpiritt, James; Zondlo, Mark
Abstract:
Gas-phase ammonia (NH3), emitted primarily from agriculture, contributes significantly to reactive nitrogen (Nr) deposition. Excess deposition of Nr to the environment causes acidification, eutrophication, and loss of biodiversity. The exchange of NH3 between land and atmosphere is bidirectional and can be highly heterogenous when underlying vegetation and soil characteristics differ. Direct measurements that assess the spatial heterogeneity of NH3 fluxes are lacking. To this end, we developed and deployed two fast-response, quantum cascade laser-based open-path NH3 sensors to quantify NH3 fluxes at a deciduous forest and an adjacent grassland separated by 700 m in North Carolina, United States from August to November, 2017. The sensors achieved 10 Hz precisions of 0.17 ppbv and 0.23 ppbv in the field, respectively. Eddy covariance calculations showed net deposition of NH3 (-7.3 ng NH3-N m−2 s−1) to the forest canopy and emission (3.2 ng NH3-N m−2 s−1) from the grassland. NH3 fluxes at both locations displayed diurnal patterns with absolute magnitudes largest midday and with smaller peaks in the afternoons. Concurrent biogeochemistry data showed over an order of magnitude higher NH3 emission potentials from green vegetation at the grassland compared to the forest, suggesting a possible explanation for the observed flux differences. Back trajectories originating from the site identified the upwind urban area as the main source region of NH3. Our work highlights the fact that adjacent natural ecosystems sharing the same airshed but different vegetation and biogeochemical conditions may differ remarkably in NH3 exchange. Such heterogeneities should be considered when upscaling point measurements, downscaling modeled fluxes, and evaluating Nr deposition for different natural land use types in the same landscape. Additional in-situ flux measurements accompanied by comprehensive biogeochemical and micrometeorological records over longer periods are needed to fully characterize the temporal variabilities and trends of NH3 fluxes and identify the underlying driving factors.
Numerical data is tabulated for all plots (Figures 2, 3a-b, 4-89, S1, S4a-b,d, S5a-b,d, S6-S156) and included as separate spreadsheets categorized by figure in a .zip file in the Supplementary Material. Error bars in Figure 4 show the spread of data observed for 4 and 5 trials on independent samples for MIL-101 and MOF-235, respectively. Figure 6a shows the average of triplicate filtrate test conversions with error propagated based on this spread. Figures 6b and S165 error bars on rate constants are determined based on propagated conversion uncertainty for independent trials and extracted standard deviations of pseudo-first order rate constants from linearized plots. Error bars on other plots represent propagation of experimental uncertainty on single trials.
These files contain code used to segment D. virilis acoustic duets, quantification of courtship behaviors during acoustic duets, and measurements of duet song features.
