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The formation of molecular clusters and secondary aerosols in the atmosphere has a significant impact on the climate. Studies typically focus on the new particle formation (NPF) of sulfuric acid (SA) with a single base molecule (e.g., dimethylamine or ammonia). In this work, we examine the combinations and synergy of several bases. Specifically, we used computational quantum chemistry to perform configurational sampling (CS) of (SA)0-4(base)0-4 clusters with five different types of bases: ammonia (AM), methylamine (MA), dimethylamine (DMA), trimethylamine (TMA), and ethylenediamine (EDA). Overall, we studied 316 different clusters. We used a traditional multilevel funnelling sampling approach augmented by a machine-learning (ML) step. The ML made the CS of these clusters possible by significantly enhancing the speed and quality of the search for the lowest free energy configurations. Subsequently, the cluster thermodynamics properties were evaluated at the DLPNO-CCSD(T0)/aug-cc-pVTZ//ωB97X-D/6-31++G(d,p) level of theory. The calculated binding free energies were used to evaluate the cluster stabilities for population dynamics simulations. The resultant SA-driven NPF rates and synergies of the studied bases are presented to show that DMA and EDA act as nucleators (although EDA becomes weak in large clusters), TMA acts as a catalyzer, and AM/MA is often overshadowed by strong bases.

Adequate representation of new-particle formation from vapors in aerosol microphysics and atmospheric transport models is essential for providing reliable predictions of ambient particle numbers and for interpretation of observations. Atmospheric particle formation processes involve multiple species, which complicates the derivation and implementation of data and parameterizations to describe the processes. Ideally, the representation of multi-compound mechanisms should be reduced, but remain accurate. Here, we evaluate common approaches to simplify the description of representative multi-compound acid-base chemistries by applying different theoretical molecular cluster data sets, focusing on simplifications (1) in formation rates that are used as input in aerosol process models and large-scale models, and (2) in cluster models that are applied to assess particle formation dynamics and survival to larger sizes. We test the following approaches: assuming non-interactive additive formation pathways, lumping of similar species, and application of quasi-unary approximations. We assess the possible biases of the simplifications for different types of chemistries and propose best practices for reducing the chemical complexity. We demonstrate that simplifications in formation rates are most often justifiable, but the choice of the preferred simplification method depends on the types of species and their similarity. Simplifications in cluster growth dynamics by quasi-unary approaches, on the other hand, are reasonable mainly for strong cluster formation involving very low-evaporating species and at excess concentration of the implicitly treated stabilizing compound.

Kinetics of collision-sticking processes between vapor molecules and clusters of low-volatility compounds govern the initial steps of atmospheric new particle formation. Conventional non-interacting hard-sphere models underestimate the collision rate by neglecting long-range attractive forces, and the commonly adopted assumption that every collision leads to the formation of a stable cluster (unit mass accommodation coefficient) is questionable for small clusters, especially at elevated temperatures. Here, we present a generally applicable analytical interacting hard-sphere model for evaluating collision rates between molecules and clusters, accounting for long-range attractive forces. In the model, the collision cross section is calculated based on an effective molecule–cluster potential, derived using Hamaker's approach. Applied to collisions of sulfuric acid or dimethylamine with neutral bisulfate–dimethylammonium clusters composed of 1–32 dimers, our new model predicts collision rates 2–3 times higher than the non-interacting model for small clusters, while decaying asymptotically to the non-interacting limit as cluster size increases, in excellent agreement with a collision-rate-theory atomistic molecular dynamics simulation approach. Additionally, we calculated sticking rates and mass accommodation coefficients (MACs) using atomistic molecular dynamics collision simulations. For sulfuric acid, a MAC ≈1 is observed for collisions with all cluster sizes at temperatures between 200 and 400 K. For dimethylamine, we find that MACs decrease with increasing temperature and decreasing cluster size. At low temperatures, the MAC ≈1 assumption is generally valid, but at elevated temperatures MACs can drop below 0.2 for small clusters.

Water and butanol are used as working fluids in condensation particle counters, and condensation of a single vapor onto an ion can be used as a simple model system for the study of ion-induced nucleation in the atmosphere. Motivated by this, we examine heterogeneous nucleation of water (H2O) and n-butanol (BuOH) vapors onto three positively (Li+, Na+, K+) and three negatively charged (F-, Cl-, Br-) ions using classical nucleation theory and computational quantum chemistry methods. We study phenomena that cannot be captured by Kelvin-Thomson equation for small nucleation ion cores. Our quantum chemistry calculations reveal the molecular mechanism behind ion-induced nucleation for each studied system. Typically, ions become solvated from all sides after several vapor molecules condense onto the ion. However, we show that the clusters of water and large negatively charged ions (Cl- and Br-) thermodynamically prefer the ion being migrated to the cluster surface. Although our methods generally do not show clear sign-preference for ion-water nucleation, we identified positive sign-preference for ion-butanol nucleation caused by the possibility to form stabilizing hydrogen bonds between butanol molecules condensed onto a positively charged ion. These bonds cannot form when butanol condenses onto a negatively charged ion. Therefore, we show that ion charge, its sign, as well as vapor properties have effects on the prenucleation and critical cluster/droplet sizes and also on the molecular mechanism of ion-induced nucleation.

Quantum chemical studies of the formation and growth of atmospheric molecular clusters are important for understanding aerosol particle formation. However, the search for the lowest free-energy cluster configuration is extremely time consuming. This makes high-level benchmark data sets extremely valuable in the quest for the global minimum as it allows the identification of cost-efficient computational methodologies, as well as the development of high-level machine learning (ML) models. Herein, we present a highly versatile quantum chemical data set comprising a total of 11 749 (acid)1-2(base)1-2cluster configurations, containing up to 44 atoms. Utilizing the LUMI supercomputer, we calculated highly accurate PNO-CCSD(F12*)(T)/cc-pVDZ-F12 binding energies of the full set of cluster configurations leading to an unprecedented data set both in regard to sheer size and with respect to the level of theory. We employ the constructed benchmark set to assess the performance of various semiempirical and density functional theory methods. In particular, we find that the r2-SCAN-3c method shows excellent performance across the data set related to both accuracy and CPU time, making it a promising method to employ during cluster configurational sampling. Furthermore, applying the data sets, we construct ML models based on Δ-learning and provide recommendations for future application of ML in cluster configurational sampling.

Because of the lack of long-term measurements, new particle formation (NPF) in the marine atmosphere remains puzzling. Using quantum chemical methods, this study elucidates the cluster formation and further growth of sulfuric acid-methanesulfonic acid-dimethylamine (SA-MSA-DMA) clusters, relevant to NPF in the marine atmosphere. The cluster structures and thermochemical parameters of (SA) n(MSA) m(DMA) l(n + m ≤ 4 and l ≤ 4) systems are calculated using density functional theory at the ωB97X-D/6-31++G(d,p) level of theory, and the single-point energies are calculated using high-level DLPNO-CCSD(T 0)/aug-cc-pVTZ calculations. The calculated thermochemistry is used as input to the Atmospheric Cluster Dynamics Code (ACDC) to gain insight into the cluster dynamics. At ambient conditions (298.15 K, 1 atm), we find that the distribution of outgrowing clusters primarily consists of SA and DMA, with a minor contribution from the mixed SA-MSA-DMA clusters. At lower temperature (278.15 K, 1 atm) the distribution broadens, and clusters containing one or more MSA molecules emerge. These findings show that in the cold marine atmosphere MSA likely participates in atmospheric NPF.

Using a combination of quantum chemistry and cluster size distribution dynamics, we study the heterogeneous nucleation of n-butanol and water onto sodium chloride (NaCl)(10) seeds at different butanol saturation ratios and relative humidities. We also investigate how the heterogeneous nucleation of butanol is affected by the seed size through comparing (NaCl)(5), (NaCl)(10), and ( NaCl)(25) seeds and by seed electrical charge through comparing (Na10Cl9)(+), (NaCl)(10), and (Na9Cl10)(-) seeds. Butanol is a common working fluid for condensation particle counters used in atmospheric aerosol studies, and NaCl seeds are frequently used for calibration purposes and as model systems, for example, sea spray aerosol. In general, our simulations reproduce the experimentally observed trends for the NaCl-BuOH-H2O system, such as the increase of nucleation rate with relative humidity and with temperature (at constant supersaturation of butanol). Our results also provide molecular-level insights into the vapor-seed interactions driving the first steps of the heterogeneous nucleation process. The main purpose of this work is to show that theoretical studies can provide molecular understanding of initial steps of heterogeneous nucleation and that it is possible to find cost-effective yet accurate-enough combinations of methods for configurational sampling and energy evaluation to successfully model heterogeneous nucleation of multicomponent systems. In the future, we anticipate that such simulations can also be extended to chemically more complex seeds.

Sampling the shallow free energy surface of hydrated atmospheric molecular clusters is a significant challenge. Using computational methods, we present an efficient approach to obtain minimum free energy structures for large hydrated clusters of atmospheric relevance. We study clusters consisting of two to four sulfuric acid (sa) molecules and hydrate them with up to five water (w) molecules. The structures of the "dry" clusters are obtained using the ABCluster program to yield a large pool of low-lying conformer minima with respect to free energy. The conformers (up to ten) lowest in free energy are then hydrated using our recently developed systematic hydrate sampling technique. Using this approach, we identify a total of 1145 unique (sa)(2-4)(w)(1-5) cluster structures. The cluster geometries and thermochemical parameters are calculated at the omega B97X-D/6-31++G(d,p) level of theory, at 298.15 K and 1 atm. The single-point energy of the most stable clusters is calculated using a high-level DLPNO-CCSD(T-0)/aug-cc-pVTZ method. Using the thermochemical data, we calculate the equilibrium hydrate distribution of the clusters under atmospheric conditions and find that the larger (sa)(3) and (sa)(4) clusters are significantly more hydrated than the smaller (sa)(2) cluster or the sulfuric acid (sa)(1) molecule. These findings indicate that more than five water molecules might be required to fully saturate the sulfuric acid clusters with water under atmospheric conditions. The presented methodology gives modelers a tool to take the effect of water explicitly into account in atmospheric particle formation models based on quantum chemistry.

Quantum chemical (QC) calculations can yield direct insight into an atmospheric cluster formation mechanism and cluster formation rates. However, such calculations are extremely computationally demanding as more than millions of cluster configurations might exist and need to be computed. We present an efficient approach to produce high quality QC data sets for applications in cluster formation studies and how to train an accurate quantum machine learning model on the generated data. Using the two-component sulfuric acid-water system as a proof of concept, we demonstrate that a kernel ridge regression machine learning model with Δ-learning can be trained to accurately predict the binding energies of cluster equilibrium configurations with mean absolute errors below 0.5 kcal mol-1. Additionally, we enlarge the training data set with nonequilibrium configurations and show the possibility of predicting the binding energies of new structures of clusters several molecules larger than those in the training set. Applying the trained machine learning model leads to a drastic reduction in the number of relevant clusters that need to be explicitly evaluated by QC methods. The presented approach is directly transferable to clusters of arbitrary composition and will lead to faster and more efficient exploration of the configurational space of new cluster systems.

We discuss a fragment-based QM:QM scheme as a practical way to access the energetics of vertical electronic processes in the condensed phase. In the QM:QM scheme, we decompose the large molecular system into small fragments, which interact solely electrostatically. The energies of the fragments are calculated in a self-consistent field generated by the other fragments and the total energy of the system is calculated as a sum of the fragment energies. We show on two test cases (cytosine and a sodium cation) that the method allows one to accurately simulate the shift of vertical ionization energies (VIE) while going from the gas phase to the bulk. For both examples, the predicted solvent shifts and peak widths estimated at the DFT level agree well with the experimental observations. We argue that the QM:QM approach is more suitable than either an electrostatic embedding based QM/MM approach, a full quantum description at the DFT level with a generally used functional or a combination of both. We also discuss the potential scope of the applicability for other electronic processes such as Auger decay.

We studied the configurational sampling of noncovalently bonded molecular clusters relevant to the atmosphere. In this article, we discuss possible approaches to searching for optimal configurations and present one alternative based on systematic configurational sampling, which seems able to overcome the typical problems associated with searching for global minima on multidimensional potential energy surfaces. Since atmospheric molecular clusters are usually held together by intermolecular bonds, we also present a cost-effective strategy for treating hydrogen bonding and proton transferring by using rigid molecules and ions in different protonation states and illustrate its performance on clusters containing guanidine and sulfuric acid.

Sulfuric acid and dimethylamine vapours in the atmosphere can form molecular clusters, which participate in new particle formation events. In this work, we have produced, measured and identified clusters of sulfuric acid and dimethylamine using an electrospray ionizer coupled with a planar differential mobility analyser, connected to an atmospheric pressure interface time-of-flight mass spectrometer (ESI–DMA–APi-TOF MS). This set-up is suitable for evaluating the extent of fragmentation of the charged clusters inside the instrument. We evaluated the fragmentation of 11 negatively charged clusters both experimentally and using a statistical model based on quantum chemical data. The results allowed us to quantify the fragmentation of the studied clusters and to reconstruct the mass spectrum removing the artifacts due to the fragmentation.

Studies of vapor phase nucleation have largely been restricted to one of two limiting cases—nucleation controlled by a substantial free energy barrier or the collisional limit where the barrier is negligible. For weakly bound systems, exploring the transition between these regimes has been an experimental challenge, and how nucleation evolves in this transition remains an open question. We overcome these limitations by combining complementary Laval expansion experiments, providing new particle formation data for carbon dioxide over a uniquely broad range of conditions. Our experimental data together with a kinetic model using rate constants from high-level quantum chemical calculations provide a comprehensive picture of new particle formation as nucleation transitions from a barrier-dominated process to the collisional limit.

Molecular clusters are ubiquitous constituents of the ambient atmosphere, that can grow into larger sizes forming new aerosol particles. The formation and growth of small clusters into aerosol particles remain one of the largest uncertainties in global climate predictions. This has made the modeling of atmospheric molecular clustering into an active field of research, yielding direct molecular level information about the formation mechanism. We review the present state-of-the-art quantum chemical methods and cluster distribution dynamics models that are applied to study the formation and growth of atmospheric molecular clusters. We outline the current challenges in applying theoretical methods and the future directions to move the field forward.

Organic peroxy radicals (RO

We tested the influence of various parameters on the new particle formation rate predicted for the sulfuric acid–ammonia system using quantum chemistry and cluster distribution dynamics simulations, in our case, Atmospheric Cluster Dynamics Code (ACDC). We found that consistent consideration of the rotational symmetry number of monomers (sulfuric acid and ammonia molecules, and bisulfate and ammonium ions) leads to a significant rise in the predicted particle formation rate, whereas inclusion of the rotational symmetry number of the clusters only changes the results slightly, and only in conditions where charged clusters dominate the particle formation rate. This is because most of the clusters stable enough to participate in new particle formation have a rotational symmetry number of 1, and few exceptions to this rule are positively charged clusters. In contrast, the application of the quasi-harmonic correction for low-frequency vibrational modes tends to generally decrease predicted new particle formation rates and also significantly alters the slope of the formation rate curve plotted against the sulfuric acid concentration, which is a typical convention in atmospheric aerosol science. The impact of the maximum size of the clusters explicitly included in the simulations depends on the simulated conditions. The errors arising from a limited set of clusters are higher for higher evaporation rates, and thus tend to increase with temperature. Similarly, the errors tend to be higher for lower vapor concentrations. The boundary conditions for outgrowing clusters (that are counted as formed particles) have only a small influence on the results, provided that the definition is chemically reasonable and that the set of simulated clusters is sufficiently large. A comparison with data from the Cosmics Leaving OUtdoor Droplets (CLOUD) chamber and a cluster distribution dynamics model using older quantum chemistry input data shows improved agreement when using our new input data and the proposed combination of symmetry and quasi-harmonic corrections.

The bulk of aerosol particles in the atmosphere are formed by gas-to-particle nucleation (Merikanto et al., 2009). However, the exact process of single molecules forming cluster, which subsequently can grow into particles, remains largely unknown. Recently, sulfuric acid has been identified to play a key role in this new particle formation enhanced by other compounds such as organic acids (Zhang, 2010) or ammonia (Anttila et al., 2005). To identify the characteristics of cluster formation and nucleation involving sulfuric acid and ammonia in neutral, positive and negative modes, we conducted a computational study. We used a layered approach for configurational sampling of the molecular clusters starting from utilizing a genetic algorithm in order to explore the whole potential energy surface (PES) with all plausible geometrical minima, however, with very unreliable energies. The structures were further optimized with a semi-empirical method and, then, at the ωB97X-D DFT level of theory. After each step, the optimized geometries were filtered to obtain the global minimum configuration. Further, a high level of theory (DLPNO-CCSD(T)) was used for obtaining the electronic energies, in addition to performing DFT frequency analysis, to calculate the Gibbs free energies of formation. These were passed to the Atmospheric Cluster Dynamics Code (ACDC) (McGrath et al., 2012) for studying the evolution of cluster populations. We determined the global minima for the following sulfuric acid - ammonia clusters: (H2SO4)m(NH3)n with m=n, m=n+1 and n=m+1 for neutral clusters, (H2SO4)m(HSO4)−(NH3)n with m=n and n=m+1 for positively charged clusters, and (H2SO4)m(NH4)+(NH3)n with m=n and m=n+1 for negatively charged clusters. Further, we present the formation rates, steady state concentrations and fluxes of these clusters calculated using ACDC and discuss how a new configurational sampling procedure, more precise quantum chemistry methods and parameters, such as symmetry and a quasiharmonic approach, impact these ACDC results in comparison to previous studies. References:J. Merikanto, D. V. Spracklen, G. W. Mann, S. J. Pickering, and K. S. Carslaw (2009). Atmos. Chem. Phys., 9, 8601-8616. R. Zhang (2010). Science, 328, 1366-1367. T. Anttila, H. Vehkamäki, I. Napari, M. Kulmala (2005). Boreal Env. Res., 10, 523. M.J. McGrath, T. Olenius, I.K. Ortega, V. Loukonen, P. Paasonen, T. Kurten, M. Kulmala (2012). Atmos. Chem. Phys., 12, 2355.

Recent technological developments have made it possible to detect the elemental composition of even the smallest airborne clusters at low ambient concentrations through chemical ionization atmospheric pressure interface time-of-flight mass spectrometry (CI-APi-TOF-MS). The charging process and collisions inside the instrument will however affect the molecular composition of the original sample clusters. A process model is therefore needed to connect the mass spectra to the original molecular clusters in the measured sample. Our research has been focused on developing this process model for clusters involving highly oxygenated organic molecules (HOM) with molecular formula C10H16O8. This elemental composition corresponds to one of the most common mass peaks observed in experiments on ozone-initiated autoxidation of α-pinene. For the model, two situations inside the mass spectrometer have to be taken into account: the chemical ionization and collisions with carrier gas inside the atmospheric pressure interface. Recently, a model predicting the fragmentation of clusters as a result of collisions in APi has been developed by Zapadinsky et al. (2018). We used this model to perform numerical simulations of fragmentation in the APi on our selected clusters. The results show that fragmentation is highly unlikely for the considered clusters, provided their bonding energy is large enough to allow formation in the atmosphere in the first place. Current research is focused on developing a model for the charging process inside CI-APi-TOF MS. Configurational sampling is combined with high quality quantum chemistry calculations to derive the binding energies and evaporation rates of the studied clusters. This model should eventually connect the ionized clusters after charging to the original distribution of neutral clusters in the measured sample.

Recent developments in mass spectrometry have brought huge advancements to the field of atmospheric science. For example, mass spectrometers are now able to detect ppq-level (10-15) concentrations of both clusters and precursor vapours in atmospheric samples (Junninen et al., 2010; Jokinen et al., 2012), as well as directly explore the chemistry of new particle formation (NPF) in the atmosphere (Kulmala et al., 2014; Bianchi et al., 2016; Ehn et al., 2014). One of the most common mass spectrometers used to measure online cluster composition and concentration in the atmosphere is the Atmospheric Pressure interface Time Of Flight Mass Spectrometer (APi-TOF MS).Identification of atmospheric molecular clusters and measurement of their concentrations by APi-TOF may be affected by systematic error due to possible decomposition of clusters inside the instrument. Indeed, the detection process in the APi-TOF involves energetic interactions between the carrier gas and the clusters, possibly leading to their decomposition, and thus altering the measurement results.Here we use a theoretical model to study in detail the decomposition of clusters involving so-called Highly-Oxygenated organic Molecules (HOM), which have recently been identified as a key contributor to NPF (Bianchi et al., 2019). HOM are molecules formed in the atmosphere from Volatile Organic Compounds (VOC). Some VOC with suitable functional groups can undergo an autoxidation process involving peroxy radicals, generating polyfunctional low-volatility vapors (i.e. HOM) that subsequently condense onto pre-existing particles. Our study involves a specific kind of representative HOM (C10H16O8) in the APi. This elemental composition corresponds to one of the most common mass peaks observed in experiments on ozone-initiated autoxidation of α-pinene, which also fulfills the “HOM” definition of Bianchi et al. (2019). The precise molecular structure was adopted from Kurtén et al. (2016), and corresponds to the lowest-volatility structural isomer of the three C10H16O8 compounds investigated in that study.The main scope of this work is to determine to what extent we are able to perform measurements of atmospheric cluster concentrations using APi-TOF mass spectrometers. More specifically, we want to determine whether decomposition can possibly be responsible for the lack of observations of some HOM-containing clusters in an APi-TOF. Here, we predict both an upper bound for decomposition energy necessary for decomposition in the APi-TOF, and a lower bound for new-particle formation in the atmosphere given realistic vapor concentrations.Our results show that decomposition is highly unlikely for the considered clusters, provided their bonding energy is large enough to allow formation in the atmosphere in the first place.

Ions enhance the formation rate of atmospheric aerosol particles, which play an important role in Earth’s radiative balance. Ion-induced nucleation involves the stepwise accretion of neutral monomers onto a molecular cluster containing an ion, which helps to stabilize the cluster against evaporation. Although theoretical frameworks exist to calculate the collision rate coefficients between neutral molecules and ions, they need to be experimentally confirmed, ideally under atmospherically relevant conditions of around 1000 ion pairs cm−3. Here, in experiments performed under atmospheric conditions in the CERN CLOUD chamber, we have measured the collision rate coefficients between neutral iodic acid (HIO3) monomers and charged iodic acid molecular clusters containing up to 11 iodine atoms. Three methods were analytically derived to calculate ion-polar molecule collision rate coefficients. After evaluation with a kinetic model, the 50% appearance time method is found to be the most robust. The measured collision rate coefficient, averaged over all iodine clusters, is (2.4 ± 0.8)×10−9 cm3 s−1, which is close to the expectation from the surface charge capture theory.

Identification of atmospheric molecular clusters and measurement of their concentrations by atmospheric pressure interface time-of-flight (APi-TOF) mass spectrometers may be affected by systematic error due to possible decomposition of clusters inside the instrument. Here, we perform numerical simulations of decomposition in an APi-TOF mass spectrometers and formation in the atmosphere of a set of clusters which involve a representative kind of highly oxygenated organic molecule (HOM), with the molecular formula C10H16O8. This elemental composition corresponds to one of the most common mass peaks observed in experiments on ozone-initiated autoxidation of α-pinene. Our results show that decomposition is highly unlikely for the considered clusters, provided their bonding energy is large enough to allow formation in the atmosphere in the first place.

In atmospheric sulfuric-acid-driven particle formation, bases are able to stabilize the initial molecular clusters and thus enhance particle formation. The enhancing potential of a stabilizing base is affected by different factors, such as the basicity and abundance. Here we use weak (ammonia), medium strong (dimethylamine) and very strong (guanidine) bases as representative atmospheric base compounds, and we systematically investigate their ability to stabilize sulfuric acid clusters. Using quantum chemistry, we study proton transfer as well as intermolecular interactions and symmetry in clusters, of which the former is directly related to the base strength and the latter to the structural effects. Based on the theoretical cluster stabilities and cluster population kinetics modeling, we provide molecular-level mechanisms of cluster growth and show that in electrically neutral particle formation, guanidine can dominate formation events even at relatively low concentrations. However, when ions are involved, charge effects can also stabilize small clusters for weaker bases. In this case the atmospheric abundance of the bases becomes more important, and thus ammonia is likely to play a key role. The theoretical findings are validated by cluster distribution experiments, as well as comparisons to previously reported particle formation rates, showing a good agreement.

High molecular weight "ROOR" dimers, likely formed in the gas phase through self- and cross-reactions of complex peroxy radicals (RO2), have been suggested to play a key role in forming ultrafine aerosol particles in the atmosphere. However, the molecular-level reaction mechanism producing these dimers remains unknown. Using multireference quantum chemical methods, we explore one potentially competitive pathway for ROOR' production, involving the initial formation of triplet alkoxy radical (RO) pairs, followed by extremely rapid intersystem crossings (ISC) to the singlet surface, permitting subsequent recombination to ROOR'. Using CH3OO + CH3OO as a model system, we show that the initial steps of this reaction mechanism are likely to be very fast, as the transition states for both the formation and the decomposition of the CH3O4CH3 tetroxide intermediate are far below the reactants in energy. Next, we compute ISC rates for seven different atmospherically relevant (3)(RO center dot center dot center dot R'O) complexes. The ISC rates vary significantly depending on the conformation of the complex and also exhibit strong stereoselectivity. Furthermore, the fastest ISC process is usually not between the lowest-energy triplet and singlet states but between the triplet ground state and an exited singlet state. For each studied (RO center dot center dot center dot R'O) system, at least one low-energy conformer with an ISC rate above 10(8) s(-1) can be found. This demonstrates that gas-phase dimer formation in the atmosphere very likely involves ISCs originating in relativistic quantum mechanics.

In atmospheric sulfuric acid-driven particle formation, bases are able to stabilize the initial molecular clusters, and thus enhance particle formation. The enhancing potential of a stabilizing base is affected by different factors, such as the basicity and abundance. Here we use weak (ammonia), medium strong (dimethylamine) and very strong (guanidine) bases as representative atmospheric base compounds, and systematically investigate their ability to stabilize sulfuric acid clusters. Using quantum chemistry, we study proton transfer as well as intermolecular interactions and symmetry in clusters, of which the former is directly related to the base strength and the latter to the structural effects. Based on the theoretical cluster stabilities and cluster population kinetics modeling, we provide molecular-level mechanisms of cluster growth and show that in electrically neutral particle formation, guanidine can dominate formation events even at relatively low concentrations. However, when ions are involved, charge effects can stabilize small clusters also for weaker bases. In this case the atmospheric abundance of the bases becomes more important, and thus ammonia is likely to play a key role. The theoretical findings are validated by cluster distribution experiments, as well as comparisons to previously reported particle formation rates, showing a good agreement.

We investigate both experimentally and theoretically the structure and photodynamics of nitrophenol molecules and clusters, addressing the question how the molecular photodynamics can be controlled by specific inter- and intramolecular interactions. Using quantum chemical calculations, we demonstrate the structural and energetic differences between clusters of 2-nitrophenol and 4-nitrophenol, using phenol as a reference system. The calculated structures are supported by mass spectrometry. The mass spectra of 2-nitrophenol clusters provide an evidence for a stacked structure compared to a strong O-H···O hydrogen bonding for 4-nitrophenol aggregates. We further investigate the photodynamics of nitrophenol molecules and clusters by means of velocity map imaging of the H-fragment generated upon 243 nm photodissociation. The experiments are complemented by ab initio calculations which demonstrate distinct photophysics of phenol, 2-nitrophenol, 4-nitrophenol. The measured H-fragment kinetic energy distributions (KEDs) from 2-nitrophenol molecules are compared to the KEDs from phenol. The comparison points to the intramolecular O-H···O hydrogen bond in 2-nitrophenol, stimulating fast internal conversion into the ground electronic state. This reaction channel is marked by exclusive appearance of slow statistical hydrogen fragments in 2-nitrophenol, which contrasts with fast hydrogen atoms observed for phenol. The photodissociation of 2-nitrophenol clusters yields a fraction of H-fragments with higher kinetic energies than the isolated molecules. These fragments originate from the caging effect in the clusters leading to multiphoton dissociation of molecules excited by the previous photons. We also propose a new ab initio based value for the O-H bond dissociation enthalpy in 2-nitrophenol (4.25 eV), which is in excellent agreement with the maximum measured H-fragment kinetic energy.

Under certain conditions, the mean squared displacement (MSD) can be retrieved from fluorescence correlation spectroscopy (FCS) measurements. However, in the general case this procedure is not valid, and the apparent MSD obtained from FCS data may substantially differ from the true one. In this work we discuss under which conditions this procedure can be applied. Furthermore, we use computer simulations to obtain the MSD and the apparent MSD for the diffusion of a single polymer chain under various approximations. Based on the simulation results we discuss the reliability of the apparent MSD obtained from FCS, showing that it systematically deviates from the true MSD. We also propose a general procedure to verify the reliability of the apparent MSD by measurements at various focal spot sizes.

A suspension of fine solid particles and liquid droplets in the air is called an aerosol. Atmospheric aerosols play an important role in climate and also affect human health. Some of these aerosols are formed in the atmosphere by collisions of gas molecules with favorable interactions. The agglomerations of molecules formed in this process are referred to as molecular clusters. Unstable molecular clusters usually break apart quickly. In contrast, stable molecular clusters may become the nuclei of subsequent growth by condensation of other vapor molecules, and eventually form new atmospheric fine particles (this process is called new particle formation = NPF). This process is typically accompanied by a nucleation barrier, which has to be surmounted to form the new particle. It is essential to understand and accurately describe the molecular mechanism behind this process as our current understand- ing of NPF is incomplete, leading to significant uncertainties when it comes to forecasting NPF-related phenomena (e.g., mists, clouds). I utilize computational quantum chemistry (QC) to evaluate the stability of molecular clusters, which determines their decomposition rates. The surmounting of the (free) energy nucleation barrier is about a probabilistic competition between cluster evaporation and cluster growth due to the collision with other condensable molecules in the air. The collision rate can be approximately calculated from kinetic gas theory. The evaporation rate can then be calculated using the detailed balance equation, which, however, requires thermodynamic calculations using computationally demanding QC methods. Moreover, to calculate thermodynamic properties of a molecular cluster, the cluster structure has to be known beforehand. The main focus of this thesis is studying molecular cluster structures/configurations and searching for those configurations that can be most probably found in the atmospheric air. The process of searching for various configurations is known as configurational sampling. I discuss methods of configurational sampling and suggest an approach for configurational sampling of atmospherically relevant molecular clusters. The core of the research results shown in this work are applications of the configurational sampling protocol, and the Jammy Key for Configurational Sampling (JKCS) program, which was developed over the course of my Ph.D. studies. Aerosoli on hienojen kiinteiden hiukkasten tai nestemäisten pisaroiden sekä ilman muodostama seos. Ilmakehän aerosoleilla on tärkeä rooli ilmastolle, minkä lisäksi ne vaikuttavat myös ihmisten terveyteen. Osa näistä aerosoleista muodostuu ilmakehässä toistensa kanssa suotuisalla tavalla vuorovaikuttavien kaasumolekyylien törmäilyjen seurauksena. Tämän prosessin aikana muodostuvat molekyyliryppäät eli molekylaariset klusterit. Epästabiilit molekylaariset klusterit hajoavat yleensä nopeasti. Sen sijaan stabiileista klustereista voi tulla ytimiä tiivistyville höyrymolekyyleille, mikä lopulta johtaa uusien hiukkasten muodostumiseen ilmakehässä. Tätä prosessia kutsutaan hiukkasmuodostumiseksi (New Particle Formation, NPF). Jotta uusi hiukkanen voi muodostua, täytyy prosessiin yleensä liittyvä vapaaenergiavalli ylittää. Prosessin vaiheiden ymmärtäminen ja kuvaaminen yksittäisten molekyylien tarkkuudella on välttämätöntä, sillä sen nykyinen ymmärrys on vajavaista, minkä vuoksi hiukkasmuodostumiseen liittyvien ilmiöiden (kuten sumun ja pilvien muodostuminen) ennustamiseen liittyy paljon epävarmuutta. Hyödynnän kvanttikemiaa (Quantum Chemistry, QC) arvioidakseni molekulaaristen klusterien stabiiliutta, joka määrittää klusterin hajoamisnopeudet. Vapaaenergiavallin ylittäminen on stokastinen prosessi, jonka aikana klusterin haihtumis- ja kasvuprosessit kilpailevat keskenään klusterin törmäillessä muiden tiivistyvien höyrymolekyylien kanssa ilmassa. Törmäysnopeus voidaan laskea likimääräisesti kineettisen kaasuteorian avulla. Tämän jälkeen haihtumisnopeus voidaan laskea käyttäen tasapainoyhtälöä, mikä kuitenkin vaatii termodynaamisia laskelmia, jotka saadaan suoritettua laskennallisesti vaativien kvanttikemiallisten menetelmien avulla. Tämän lisäksi molekylaaristen klusterien termodynaamisten ominaisuuksien onnistunut laskeminen vaatii sen, että klusterin rakenne tiedetään ennen laskujen suorittamista. Tämän työn päätarkoitus on tutkia molekylaaristen klusterien rakenteita/konfiguraatioita ja etsiä ne rakenteet, jotka esiintyvät todennäköisimmin ilmakehässä. Useiden rakenteiden etsimisprosessia kutsutaan konformeerien näytteistykseksi. Selitän konformeerien näytteistykseen liittyvät metodit ja esitän uuden lähestymistavan ilmakehärelevanttien molekylaaristen klusterien konformeerien näytteistykseen. Tämän työn ydintuloksia ovat konformeerien näytteistykseen liittyvät sovellukset sekä tohtoriopintojeni aikana kehitetty tietokoneohjelma Jammy Key for Configurational Sampling (JKCS).