Browsing by Subject "LIQUID WATER"

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  • Daub, Christopher D.; Halonen, Lauri (2019)
    The deprotonation of formic acid is investigated using metadynamics in tandem with Born-Oppenheimer molecular dynamics simulations. We compare our findings for formic acid in pure water with previous studies before examining formic acid in aqueous solutions of lithium bromide. We carefully consider different definitions for the collective variable(s) used to drive the metadynamics, emphasizing that the variables used must include all of the possible reactive atoms in the system, in this case carboxylate oxygens and water hydrogens. This ensures that all the various possible proton exchange events can be accommodated and the collective variable(s) can distinguish the protonated and deprotonated states, even over rather long ab initio simulation runs (ca. 200-300 ps). Our findings show that the formic acid deprotonation barrier and the free energy of the deprotonated state are higher in concentrated lithium bromide, in agreement with the available experimental data for acids in salt solution. We show that the presence of Br- in proximity to the formic acid hydroxyl group effectively inhibits deprotonation. Our study extends previous work on acid deprotonation in pure water and at air-water interfaces to more complex multicomponent systems of importance in atmospheric and marine chemistry.
  • Roet, Sander; Daub, Christopher; Riccardi, Enrico (2021)
    We propose to analyze molecular dynamics (MD) output via a supervised machine learning (ML) algorithm, the decision tree. The approach aims to identify the predominant geometric features which correlate with trajectories that transition between two arbitrarily defined states. The data-driven algorithm aims to identify these features without the bias of human “chemical intuition”. We demonstrate the method by analyzing the proton exchange reactions in formic acid solvated in small water clusters. The simulations were performed with ab initio MD combined with a method to efficiently sample the rare event, path sampling. Our ML analysis identified relevant geometric variables involved in the proton transfer reaction and how they may change as the number of solvating water molecules changes.
  • Pathak, Harshad; Spah, Alexander; Kim, Kyung Hwan; Tsironi, Ifigeneia; Mariedahl, Daniel; Blanco, Maria; Huotari, Simo; Honkimäki, Veijo; Nilsson, Anders (2019)
    Wide angle x-ray scattering of supercooled water down to 234.8 K was studied using high energy x rays at the European Synchrotron Radiation Facility. The oxygen-oxygen pair distribution function (PDF) was calculated from the scattering pattern out to the 5th peak at an intermolecular distance, r approximate to 11 angstrom. We observe that the 4th peak and the 5th peak in the PDF increase in height upon supercooling. We also observe that the 4th peak position (r(4)) shifts to shorter distances upon supercooling consistent with previous studies, but we see a more rapid change at the lowest temperature. The running oxygen-oxygen coordination number is calculated for 5 different temperatures, and an isosbestic point at r(iso) = 3.31 +/- 0.05 angstrom was found corresponding to a coordination number of 4.39 +/- 0.15. The comparison of the PDF of the coldest water with that of amorphous ice shows distinct differences. We propose that there are 5-member pentamer rings in low density liquid-like structures giving rise to the sharp correlations at r approximate to 9 angstrom and r approximate to 11 angstrom.
  • Lehmkuehler, Felix; Forov, Yury; Buening, Thomas; Sahle, Christoph J.; Steinke, Ingo; Julius, Karin; Buslaps, Thomas; Tolan, Metin; Hakala, Mikko; Sternemann, Christian (2016)
    We studied the structure and energetics of supercooled water by means of X-ray Raman and Compton scattering. Under supercooled conditions down to 255 K, the oxygen K-edge measured by X-ray Raman scattering suggests an increase of tetrahedral order similar to the conventional temperature effect observed in non-supercooled water. Compton profile differences indicate contributions beyond the theoretically predicted temperature effect and provide a deeper insight into local structural changes. These contributions suggest a decrease of the electron mean kinetic energy by 3.3 +/- 0.7 kJ (mol K)(-1) that cannot be modeled within established water models. Our surprising results emphasize the need for water models that capture in detail the intramolecular structural changes and quantum effects to explain this complex liquid.
  • Junttila, Samuli; Kaasalainen, Sanna; Vastaranta, Mikko; Hakala, Teemu; Nevalainen, Olli; Holopainen, Markus (2015)
    Global warming is posing a threat to the health and condition of forests as the amount and length of biotic and abiotic disturbances increase. Most methods for detecting disturbances and measuring forest health are based on multi- and hyperspectral imaging. We conducted a test with spruce and pine trees using a hyperspectral Lidar instrument in a laboratory to determine the capability of combined range and reflectance measurements to investigate forest health. A simple drought treatment was conducted by leaving the harvested trees outdoors without a water supply for 12 days. The results showed statistically significant variation in reflectance after the drought treatment for both species. However, the changes differed between the species, indicating that drought-induced alterations in spectral characteristics may be species-dependent. Based on our results, hyperspectral Lidar has the potential to detect drought in spruce and pine trees.
  • Mason, S. L.; Chiu, C. J.; Hogan, R. J.; Moisseev, D.; Kneifel, S. (2018)
    Retrievals of ice and snow are made from Ka- and W-band zenith-pointing Doppler radars at Hyytiala, Finland, during the snow experiment component of the Biogenic Aerosols: Effects on Clouds and Climate (2014) field campaign. In a novel optimal estimation retrieval, mean Doppler velocity is exploited to retrieve a density factor parameter, which modulates the mass, shape, terminal velocity, and backscatter cross sections of ice particles. In a case study including aggregate snow and graupel we find that snow rate and ensemble mean ice density can be retrieved to within 50% of in situ measurements at the surface using dual-frequency Doppler radar retrievals. While Doppler measurements are essential to the retrieval of particle density, the dual-frequency ratio provides a strong constraint on particle size. The retrieved density factor is strongly correlated with liquid water path, indicating that riming is the primary process by which the density factor is modulated. Using liquid water path as a proxy for riming, profiles classified as unrimed snow, rimed snow, and graupel exhibit distinct features characteristic of aggregation and riming processes, suggesting the potential to make estimates of process rates from these retrievals. We discuss the potential application of the technique to future satellite missions. Plain Language Summary Ground-based radar measurements of ice clouds and snow are used to estimate the size, number, and density of snowflakes. Doppler velocity measurements of particle fall speeds are used to estimate the mass and shape of the snow particles. The properties of snow estimated using radar compare well against measurements of particles at the surface and estimates of the amount of liquid water in the atmosphere; the presence of liquid water relates to the potential for riming, in which snowflakes increase in density and fall speed by collecting and freezing liquid droplets. More accurate estimates of snow density from ground-based and satellite radars help to improve global estimates of precipitation and snow accumulation and the representation of clouds and snow in weather and climate models.