The direct growth of single-walled carbon nanotubes (SWCNTs) with a narrow distribution of diameter or chirality remains elusive despite significant benefits in properties and applications. Nanoparticle catalysts are vital for SWCNT synthesis, but how to precisely manipulate their chemistry, size, concentration, and deposition remains difficult, especially within a continuous production process from the gas-phase. Here, we demonstrate the preparation of W₆Co₇ alloyed nanoparticle catalysts with precisely tunable stoichiometry using electrospray, which remain solid state during SWCNT growth. We also demonstrate continuous production of liquid iron nanoparticles with in-line size selection. With the precise size manipulation of catalysts in the range of 1-5 nm, and a nearly monodisperse distribution (σ_g < 1.2), an excellent size selection of SWCNT can be achieved. All of the presented techniques show great potential to facilitate the realization of single-chirality SWCNT production.

Exposure to malachite green (MG) may pose great health risks to humans, thus it is of prime importance to develop fast and robust methods to quantitatively screen the presence malachite green in environment. Herein application of extractive electrospray ionization mass spectrometry (EESI-MS) has been extended to the trace detection of MG within lake water and aquiculture water, due to the intensive use of MG as biocide in fisheries. This method has the advantage of obviating offline liquid-liquid extraction or tedious matrix separation prior to the measurement of malachite green in native aqueous medium. The experimental results indicate that the extrapolated detection limit for MG was ~3.8 ug L-1 (S/N=3) in lake water samples and ~ 0.5 ug L-1 in ultrapure water under optimized experimental conditions. The signal intensity of MG showed good linearity over the concentration range of 10–5000 ug L-1. Measurement of practical water samples fortified with MG at 0.01 and 0.1 mg L-1 gave a good validation of the established calibration curve. The average recoveries of malachite green in lake water and Carassius carassius fish farm effluent water were 114.9% (6.6% RSD) and 85.4% (9.2% RSD), respectively. Overall, the established EESI-MS/MS method has been demonstrated suitable for sensitive and rapid (<2 min per sample) quantitative detection of malachite green in various aqueous media, indicating its potential for online real-time monitoring of real life samples.

One of the research priorities in atmospheric chemistry is to advance our understanding of heterogeneous reactions and their effect on the composition of the troposphere. Chemistry on aqueous surfaces is particularly important in this regard because of their ubiquity and expanse. They range from the surfaces of oceans (360 million km²), cloud and aerosol drops (~10 trillion km²) to the fluids lining the human lung (~200 m²). Typically, ambient air contains reactive gases that may affect human health, influence climate and participate in biogeochemical cycles. Despite their importance, reactions between gases and solutes at air-aqueous interfaces are not well understood. New, surface-specific techniques are required that detect and identify the intermediates and products of such reactions as they happen on liquids. This is a tall order because genuine interfacial reactions are faster than mass diffusion into bulk liquids, and may produce novel species at low concentrations. Herein, we review evidence that validates online pneumatic ionization mass spectrometry of liquid microjets dosed by reactive gases as a technique meeting such requirements. Next, we call attention to results obtained by this approach on reactions of ozone, nitrogen dioxide and hydroxyl radicals with various solutes on aqueous surfaces. The overarching conclusion is that the outermost layers of aqueous solutions are unique media, where equilibria shift and reactions proceed faster than, in some cases along different pathways from the bulk liquids. The fact that the rates and mechanisms of reactions at air-aqueous interfaces may not be deduced from experiments in bulk liquids opens new conceptual frameworks and lines of research, and adds an overlooked dimension to atmospheric chemistry.

The ‘inverse problem’ of mass spectrometric molecular identification (‘given a mass spectrum, calculate/predict the 2D structure of the molecule whence it came’) is largely unsolved, and is especially acute in metabolomics where many small molecules remain unidentified. This is largely because the number of experimentally available electrospray mass spectra of small molecules is quite limited. However, the forward problem (‘calculate a small molecule’s likely fragmentation and hence at least some of its mass spectrum from its structure alone’) is much more tractable, because the strengths of different chemical bonds are roughly known. This kind of molecular identification problem may be cast as a language translation problem in which the source language is a list of high-resolution mass spectral peaks and the ‘translation’ a representation (for instance in SMILES) of the molecule. It is thus suitable for attack using the deep neural networks known as transformers. We here present MassGenie, a method that uses a transformer-based deep neural network, trained on ~6 million chemical structures with augmented SMILES encoding and their paired molecular fragments as generated in silico, explicitly including the protonated molecular ion. This architecture (containing some 400 million elements) is used to predict the structure of a molecule from the various fragments that may be expected to be observed when some of its bonds are broken. Despite being given essentially no detailed nor explicit rules about molecular fragmentation methods, isotope patterns, rearrangements, neutral losses, and the like, MassGenie learns the effective properties of the mass spectral fragment and valency space, and can generate candidate molecular structures that are very close or identical to those of the ‘true’ molecules. We also use VAE-Sim, a previously published variational autoencoder, to generate candidate molecules that are ‘similar’ to the top hit. In addition to using the ‘top hits’ directly, we can produce a rank order of these by ‘round-tripping’ candidate molecules and comparing them with the true molecules, where known. As a proof of principle, we confine ourselves to positive electrospray mass spectra from molecules with a molecular mass of 500Da or lower, including those in the last CASMI challenge (for which the results are known), getting 49/93 (53%) precisely correct. The transformer method, applied here for the first time to mass spectral interpretation, works extremely effectively both for mass spectra generated in silico and on experimentally obtained mass spectra from pure compounds. It seems to act as a Las Vegas algorithm, in that it either gives the correct answer or simply states that it cannot find one. The ability to create and to ‘learn’ millions of fragmentation patterns in silico, and therefrom generate candidate structures (that do not have to be in existing libraries) directly, thus opens up entirely the field of de novo small molecule structure prediction from experimental mass spectra.

Production and transport of reactive species through plasma-liquid interactions plays a significant role in multiple applications in biomedicine, environment, and agriculture. We experimentally investigated the transport mechanisms of hydrogen peroxide H2O2 and ozone O3, as the typical plasma species, into water. We measured the solvation of gaseous H2O2 and O3 in airflow into water bulk vs. electrosprayed microdroplets while changing the gas and water flow rates, applied voltage that determines the gas-liquid interface area, and treatment time. The solvation rate of H2O2 and O3 increased with the treatment time and the gas-liquid interface area. The total surface area of the electrosprayed microdroplets was larger than that of the bulk, but their lifetime was much shorter. We estimated that only microdroplets with diameters below ~ 40 µm could achieve the saturation by O3 during their lifetime, while the saturation by H2O2 was impossible due to its depletion from air. Besides the short-lived flying microdroplets, the longer-lived bottom microdroplets substantially contributed to H2O2 and O3 solvation in water electrospray. This study contributes to a better understanding of the gaseous H2O2 and O3 transport into water as a function of different parameters and will lead to design optimization of the plasma-liquid interaction systems.