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Evaluating f-Orbital Participation in the UV═E Multiple Bonds of [U(E)(NR2)3] (E = O, NSiMe3, NAd; R = SiMe3)
The recently developed ab-initio multiple cloning (AIMC) approach based on the multicongurational Ehrenfest (MCE) method provides a powerful and accurate way of describing the excited-state dynamics of molecular systems. The AIMC method is a controlled approximation to non-adiabatic dynamics with a particular strength in the proper description of decoherence effects due to branching of vibrational wavepackets at a level crossing. In this work, we report a new implementation of the AIMC algorithm in the open source NWChem computational chemistry program. The framework combines linear-response time-dependent density functional theory with Ehrenfest mean-eld theory to determine the equations of motion for classical trajectories. The multi-dimensional wave function is decomposed into a superposition of Gaussian coherent states guided by Ehrenfest trajectories (i.e., MCE approach), which can clone with fully quantum mechanical amplitudes and phases. By using an efficient time-derivative based non-adiabatic coupling approach within the AIMC method, all observable are calculated on-the-y in the non-adiabatic molecular dynamics process. As a representative example, we apply our implementation to study the ultrafast photoinduced electronic and vibrational energy transfer in a pyridine molecule. The effects of the cloning procedure on electronic and vibrational coherence, relaxation and unidirectional energy transfer are discussed. This new AIMC implementation provides a high-level non-adiabatic molecular dynamics framework for simulating photoexcited dynamics in complex molecular systems and experimentally relevant ultrafast spectroscopic probes, such as nonlinear coherent optical and X-ray signals.
Over the past decade, there has been a growth of interest in polaritonic chemistry, where the formation of hybrid light–matter states (polaritons) can alter the course of photochemical reactions. These hybrid states are created by strong coupling between molecules and photons in resonant optical cavities and can even occur in the absence of light when the molecule is strongly coupled with the electromagnetic fluctuations of the vacuum field. Here, we present a first-principles model to simulate nonadiabatic dynamics of such polaritonic states inside optical cavities by leveraging graphical processing units (GPUs). Our first implementation of this model is specialized for a single molecule coupled to a single-photon mode confined inside the optical cavity but with any number of excited states computed using complete active space configuration interaction (CASCI) and a Jaynes–Cummings-type Hamiltonian. Using this model, we have simulated the excited-state dynamics of a single salicylideneaniline (SA) molecule strongly coupled to a cavity photon with the ab initio multiple spawning (AIMS) method. We demonstrate how the branching ratios of the photodeactivation pathways for this molecule can be manipulated by coupling to the cavity. We also show how one can stop the photoreaction from happening inside of an optical cavity. Finally, we also investigate cavity-based control of the ordering of two excited states (one optically bright and the other optically dark) inside a cavity for a set of molecules, where the dark and bright states are close in energy.
Products resulting from the sequential activation of one, two, three, and four methane molecules by atomic iridium cations were characterized by gas-phase infrared multiple photon dissociation spectroscopy and density functional theory (DFT) calculations. Iridium cations were generated using a laser ablation source and reacted with methane in a linear radiofrequency ion trap before mass analysis and spectroscopic interrogation in a Fourier transform ion cyclotron resonance mass spectrometer coupled to the free-electron laser for intracavity experiments (FELICE) beamline. Product ions were irradiated using infrared light over the 250–1500 cm –1 range. Comparisons between the experimental and DFT-calculated spectra enabled structural determination of the products formed. The observed products include HIrCH + , Ir(CH 2 ) 2 + , H s Ir(C 3 H 5 ) + , and Ir(CH 3 ) s (C 3 H 5 ) + , where the subscript s denotes a syn orientation of the two ligands. Furthermore, formation of the latter two products provides evidence for efficient C–H bond activation and subsequent C–C coupling on the atomic iridium cation.
The photochemistry of cis-stilbene proceeds through two pathways: cis-trans isomerization and ring closure to 4a,4b-dihydrophenanthrene (DHP). Despite serving for many decades as a model system for photoisomerization, the photodynamics of cis-stilbene is still not fully understood. In this work, we use ab initio multiple spawning on a SA-2-CASSCF(2,2) potential energy surface to simulate the nonadiabatic dynamics of isolated cis-stilbene. We find the cyclization (to DHP and cis-stilbene) and isomerization (to trans- and cis-stilbene) reaction coordinates to be orthogonal; branching between the two pathways is determined on the S1 excited state within 150 fs of photoexcitation. Furthermore ,trajectory basis functions (TBFs) undergoing cyclization decay rapidly to the ground state in 250 fs, while TBFs moving along the isomerization coordinate remain on the excited state longer, with the majority decaying between 300 and 500 fs. We observe three avoided crossing regions in the dynamics: two along the isomerization coordinate (displaying pyramidalization and migration of an ethylenic hydrogen or phenyl group), and one DHP-like conical intersection along the cyclization coordinate. The isomeric form of the vibrationally hot photoproducts (as determined by measurement 2 ps after photoexcitation) is determined within less than 50 fs of decay to the ground state mediated by passage through a conical intersection. Excess vibrational energy of ground state cis- and trans-stilbene is channelled into phenyl torsions (with mostly opposing directionality). Finally, our simulations are validated by direct comparison to experiment for the absorption spectrum, branching ratio of the three photoproducts (44:52:4 cis-stilbene:trans-stilbene:DHP), and excited state lifetime (520 ± 40 fs).
High-ordered multiple-quantum coherences have been used to gauge the size of coupled networks of nuclear spins but are seldom used in modern high-resolution solid-state NMR spectroscopy due to the low resolution of earlier techniques. Herein, we extend this work to the third dimension by designing an MQ spin counting experiment with full chemical resolution of the nuclei involved in the coherences. The technique uses multiplex processing to simultaneously acquire MQ/1Q correlation 2D spectra, with all even-ordered values of M, in the same amount of time it would take to acquire the 2Q/1Q spectrum alone. Further, we apply this multiplexed MQ/1Q correlation method to probe site clustering on functionalized silica surfaces and find the first evidence of clusters involving three or more functionalities. When applied to a supported zirconium metallocene, the observation of a 6Q coherence between six cyclopentadienyl proton nuclei confirms the colocation of two cyclopentadienyl ligands on a single metal center.
An electrolyte transport theory connects its transport properties, evolution of spatiotemporal fields (e.g., concentration), and corresponding macroscopic current and voltage responses. Given this interconnection, the transport properties are typically inferred by analyzing the macroscopic response through the lens of a chosen electrolyte transport theory. Unfortunately, the same macroscopic measurements can be analyzed by using different theories to arrive at seemingly dissimilar properties that are inconsistent with each other. Here, we offer a resolution to this dilemma by analyzing multiple spatiotemporal (i.e., operando) fields for a given electrolyte. We show that predictive transport theory can analyze operando fields to estimate underlying transport properties and subsequently predict another operando field. A theory passing this test identifies meaningful transport properties such that the electrolyte behavior can be accurately predicted over a wide range of excitations, and is critical to property-based electrolyte screening and electrolyte discovery efforts.
We report the ability to insolubilize doped semiconducting polymer layers can help enable the fabrication of efficient multilayer solution-processed electronic and optoelectronic devices. Here, we present a promising approach to simultaneously n-dope and largely insolubilize conjugated polymer films using tetrakis[{4-(1,3-dimethyl-2,3-dihydro-1H-benzo[d]imidazol-2-yl)phenoxy}methyl]methane (tetrakis-O-DMBI-H), which consists of four 2,3-dihydro-1H-benzoimidazole (DMBI-H) n-dopant moieties covalently linked to one another. Doping a thiophene-fused benzodifurandione-based oligo(p-phenylenevinylene)-co-thiophene polymer (TBDOPV-T) with tetrakis-O-DMBI-H results in a highly n-doped film with bulk conductivity of 15 S cm –1 . Optical absorption spectra provide evidence for film retention of ~93% after immersion in o-dichlorobenzene for 5 min. The optical absorption signature of the charge carriers in the n-doped polymer decreases only slightly more than that of the neutral polymer under these conditions, indicating that the exposure to solvent also results in negligible dedoping of the film. Moreover, thermal treatment studies on a tetrakis-O-DMBI-H-doped TBDOPV-T film in contact with another undoped polymer film indicate immobilization of the molecular dopant in TBDOPV-T. This is attributed to the multiple electrostatic interactions between each dopant tetracation and up to four nearby anionic doped polymer segments.
Experimentally determined yields of secondary organic aerosol (SOA) from the photochemical oxidation of isoprene in the absence of aqueous acidic aerosol vary substantially, both within a given experiment and across different environmental chamber conditions. The underlying mechanisms driving this variation remain poorly evaluated, leading to significant uncertainty in how to extrapolate laboratory chamber results to the atmosphere. Herein, we compare SOA predictions from a near-explicit gas-phase chemical mechanism of isoprene oxidation by the hydroxyl radical (OH) in the presence and absence of nitrogen oxide radicals (NOx), to multiple chamber experiments on non-aqueous isoprene photochemical SOA (ipSOA) conducted by different groups in different chambers. SOA is predicted by volatility-driven gas-particle partitioning of hundreds of individual reaction products. The mechanism includes simplified descriptions of particle-phase organic chemistry, including organic hydroperoxide photolysis, and organic nitrate hydrolysis and accretion reactions. The model has good skill (mean normalized bias typically within 25%) at predicting the observed formation and evolution of ipSOA across a range of chambers and conditions at low NOx. The model has much less skill at describing the observed non-linear response of ipSOA to elevated NOx. Organic nitrate hydrolysis is unable to explain significant ipSOA at high NOx, whereas particle-phase accretion reactions of tertiary nitrates may play a role. Uncertainties in the chamber radical environment and fate of key organic peroxy radicals (RO2) remain as or even more important than vapor losses to chamber walls in determining how best to extrapolate chamber-based yields to the atmosphere. Implications for likely atmospheric yields of ipSOA and recommendations for future chamber experiments are discussed.
Processing nuclear waste from sites such as Hanford is a significant environmental cleanup need while being a significant logistical challenge. Integration of process monitoring tools, that can provide in situ and real-time feedback about the process, can significantly alleviate needs to collect grab samples for process control and product characterization. Raman spectroscopy paired with chemometric analysis is one process monitoring tool that can provide chemical composition information on a large number of chemical targets in nuclear waste streams. However, methods to improve limits of detection as well as drop uncertainty in quantification are needed. Optimizing instrument specifications can achieve this, here this is demonstrated by comparing limits of detection for key analytes when using Raman systems with 671 nm, 532 nm, and 405 nm excitation wavelengths. Generally, limits of detection decease (allowing the measurement of lower salt concentrations) with decreasing wavelength. Similarly, data collection times and averaging were optimized. Finally, multiple chemometric modeling approaches were leveraged, including multiblock methods that combined data from all three Raman systems to simultaneously quantify targets with improved sensitivity.
we report over the last few decades, efforts to transition the global production of fuels and chemicals toward renewable carbon feedstocks have accelerated. A large portion of these efforts have focused on valorization of one of the most abundant renewable carbon sources, lignocellulose. Pretreatment of lignocellulose is the first critical step in this process. In this study, novel ionic liquid (IL) systems consisting of multiple ions known to be effective at biomass pretreatment were tested on woody and grassy biomass. Molecular simulations and experimental results established the synergistic advantages of combining specific individual components in these systems. For pine (woody) biomass, pretreatment with the combination of imidazolium, cholinium, acetate, and lysinate ions achieved 80% glucose and 70% xylose yields at high biomass loading. For sorghum biomass, an IL system comprising cholinium, lysinate, and palmitate ions not only enabled a 98% glucose yield but was also found to be biocompatible in a one-pot configuration, producing the biofuel precursor bisabolene using an engineered strain of the yeast Rhodosporidium toruloides.
Due to the abundance of natural gas in our planet, a major goal is to achieve a direct methane to methanol conversion at medium to low temperatures using mixtures of methane and oxygen. Here, we report an efficient catalyst, ZnO/Cu 2 O/Cu(111), for this process investigated using a combination of reactor testing, scanning tunneling microscopy, ambient-pressure x-ray photoemission spectroscopy, density functional calculations, and kinetic Monte Carlo simulations. The catalyst is capable of methane activation at room temperature and transforms mixtures of methane and oxygen to methanol at 450 K with a selectivity of ~30%. This performance is not seen for other heterogenous catalysts which usually require the addition of water to enable a significant conversion of methane to methanol. The unique coarse structure of the ZnO islands supported on a Cu 2 O/Cu(111) substrate provides a collection of multiple centers that display different catalytic activity during the reaction. ZnO-Cu 2 O step sites are active centers for methanol synthesis when exposed to CH 4 and O 2 due to an effective O-O bond dissociation, which enables a methane-to-methanol conversion with a reasonable selectivity. Upon addition of water, the defected O-rich ZnO sites, introduced by Zn vacancies, show superior behavior towards methane conversion and enhance the overall methanol selectivity to over 80%. Thus, in this case, the surface sites involved in a direct CH 4 → to CH 3 OH conversion are different from those engaged in methanol formation without water. Furthermore, the identification of the site-dependent behavior of ZnO/Cu 2 O/Cu(111) opens a design strategy for guiding efficient methane reforming with high methanol selectivity.
Abstract We have developed a new procedure for combining lists of substorm onset times from multiple sources. We apply this procedure to observational data and to magnetohydrodynamic (MHD) model output from 1–31 January 2005. We show that this procedure is capable of rejecting false positive identifications and filling data gaps that appear in individual lists. The resulting combined onset lists produce a waiting time distribution that is comparable to previously published results, and superposed epoch analyses of the solar wind driving conditions and magnetospheric response during the resulting onset times are also comparable to previous results. Comparison of the substorm onset list from the MHD model to that obtained from observational data reveals that the MHD model reproduces many of the characteristic features of the observed substorms, in terms of solar wind driving, magnetospheric response, and waiting time distribution. Heidke skill scores show that the MHD model has statistically significant skill in predicting substorm onset times.
Abstract Understanding spatially correlated floods and modeling joint hazard associated with threshold exceedances across multiple locations is crucial for accurate estimation of continental‐scale portfolio risk. This work uses a non‐parametric copula‐based spatial simulator to analyze peak floods across the United States to derive the first‐of‐its‐kind continental portfolio risk estimates at the 10‐ and 100‐year return levels. We find significant interdependence in floods across the nation, revealing the recurring pattern of extreme events affecting the Northeast, Central, West, and Northwest United States in the same year. The stochastic simulator effectively manages high‐dimensional data and offers reliable uncertainty estimates for both spatially dependent floods and the aggregated flood losses at the continental level. El Niño‐Southern Oscillation and Atlantic Multidecadal Oscillation are identified as statistically significant tele‐connectors of aggregate loss. This research aims to advance the understanding of compound continental flood hazard and the potential large‐scale climate teleconnections that lead to such compound floods.
Ambient fine particulate matter (PM 2.5 ) is the world’s leading environmental health risk factor. Reducing the PM 2.5 disease burden requires specific strategies that target dominant sources across multiple spatial scales. We provide a contemporary and comprehensive evaluation of sector- and fuel-specific contributions to this disease burden across 21 regions, 204 countries, and 200 sub-national areas by integrating 24 global atmospheric chemistry-transport model sensitivity simulations, high-resolution satellite-derived PM 2.5 exposure estimates, and disease-specific concentration response relationships. Globally, 1.05 (95% Confidence Interval: 0.74–1.36) million deaths were avoidable in 2017 by eliminating fossil-fuel combustion (27.3% of the total PM 2.5 burden), with coal contributing to over half. Other dominant global sources included residential (0.74 [0.52–0.95] million deaths; 19.2%), industrial (0.45 [0.32–0.58] million deaths; 11.7%), and energy (0.39 [0.28–0.51] million deaths; 10.2%) sectors. Our results show that regions with large anthropogenic contributions generally had the highest attributable deaths, suggesting substantial health benefits from replacing traditional energy sources.
Aquatic ecosystems are globally significant sources of the greenhouse gas methane to the atmosphere. Until recently, methane production was thought to be a strictly anaerobic process confined primarily to anoxic sediments. However, supersaturation of methane in oxygenated waters has been consistently observed in lakes and the ocean (termed the ‘methane paradox’), indicating that methane can be produced under oxic conditions through unclear mechanisms. Here we show aerobic methane production from multiple sources in freshwater incubation experiments under different treatments and based on biogeochemical, metagenomic, and metatranscriptomic data. We find that aerobic methane production appears to be associated with (bacterio)chlorophyll metabolism and photosynthesis, as well as with Proteobacterial degradation of methylphosphonate. Genes encoding pathways for putative photosynthetic- and methylphosphonate-based methane production also co-occur in Proteobacterial metagenome-assembled genomes. Our findings provide insight into known mechanisms of aerobic methane production, and suggest a potential co-occurring mechanism associated with bacterial photosynthesis in aquatic ecosystems.
Understanding the interaction of intense, femtosecond X-ray pulses with heavy atoms is crucial for gaining insights into the structure and dynamics of matter. One key aspect of nonlinear light–matter interaction was, so far, not studied systematically at free-electron lasers—its dependence on the photon energy. Here, we use resonant ion spectroscopy to map out the transient electronic structures occurring during the complex charge-up pathways of xenon. Massively hollow atoms featuring up to six simultaneous core holes determine the spectra at specific photon energies and charge states. We also illustrate how different X-ray pulse parameters, which are usually intertwined, can be partially disentangled. The extraction of resonance spectra is facilitated by the possibility of working with a constant number of photons per X-ray pulse at all photon energies and the fact that the ion yields become independent of the peak fluence beyond a saturation point. Our study lays the groundwork for spectroscopic investigations of transient atomic species in exotic, multiple-core-hole states that have not been explored previously.
Acute gastroenteritis caused by human noroviruses (HuNoVs) is a significant global health and economic burden and is without licensed vaccines or antiviral drugs. The GII.4 HuNoV causes most epidemics worldwide. This virus undergoes epochal evolution with periodic emergence of variants with new antigenic profiles and altered specificity for histo-blood group antigens (HBGA), the determinants of cell attachment and susceptibility, hampering the development of immunotherapeutics. Here, we show that a llama-derived nanobody M4 neutralizes multiple GII.4 variants with high potency in human intestinal enteroids. The crystal structure of M4 complexed with the protruding domain of the GII.4 capsid protein VP1 revealed a conserved epitope, away from the HBGA binding site, fully accessible only when VP1 transitions to a “raised” conformation in the capsid. Together with dynamic light scattering and electron microscopy of the GII.4 VLPs, our studies suggest a mechanism in which M4 accesses the epitope by altering the conformational dynamics of the capsid and triggering its disassembly to neutralize GII.4 infection.