Bond-Order Time Series Analysis for Detecting Reaction Events in Ab Initio Molecular Dynamics Simulations.

Ab initio molecular dynamics is able to predict novel reaction mechanisms by directly observing the individual reaction events that occur in simulation trajectories. In this article, we describe an approach for detecting reaction events from simulation trajectories using a physically motivated model based on time series analysis of ab initio bond orders. We found that applying a threshold to the bond order was insufficient for accurate detection, whereas peak finding on the first time derivative resulted in significantly improved accuracy. The model is trained on a reference set of reaction events representing the ideal result given unlimited computing resources. Our study includes two model systems: a heptanylium carbocation that undergoes hydride shifts and an unsaturated iron carbonyl cluster that features CO ligand migration and bridging behavior. The results indicate a high level of promise for this analysis approach to be used in mechanistic analysis of reactive AIMD simulations more generally

Quantum chemical studies of redox properties and conformational changes of a four-center iron CO2 reduction electrocatalyst.

The CO2 reduction electrocatalyst [Fe4N(CO)12]- (abbrev. 1-) reduces CO2 to HCO2- in a two-electron, one-proton catalytic cycle. Here, we employ ab initio calculations to estimate the first two redox potentials of 1- and explore the pathway of a side reaction involving CO dissociation from 13-. Using the BP86 density functional approximation, the redox potentials were computed with a root mean squared error of 0.15 V with respect to experimental data. High temperature Born-Oppenheimer molecular dynamics was employed to discover a reaction pathway of CO dissociation from 13- with a reaction energy of +10.6 kcal mol-1 and an activation energy of 18.8 kcal mol-1; including harmonic free energy terms, this yields ΔGsep = 1.4 kcal mol-1 for fully separated species and ΔG‡ = +17.4 kcal mol-1, indicating CO dissociation is energetically accessible at ambient conditions. The analogous dissociation pathway from 12- has a reaction energy of 22.1 kcal mol-1 and an activation energy of 22.4 kcal mol-1 (ΔGsep = 12.8 kcal mol-1, ΔG‡ = +18.1 kcal mol-1). Our computed harmonic vibrational analysis of [Fe4N(CO)11]3- or 23- reveals a distinct CO-stretching peak red-shifted from the main CO-stretching band, pointing to a possible vibrational signature of dissociation. Multi-reference CASSCF calculations are used to check the assumptions of the density functional approximations that were used to obtain the majority of the results

Pathways for the OH + Cl<inf>2</inf> → HOCl + Cl and HOCl + Cl → HCl + ClO Reactions

High level coupled-cluster theory, with spin-orbit coupling evaluated via the Breit-Pauli operator in the interacting-states approach, is used to investigate the OH radical reaction with Cl2 and the subsequent reaction HOCl + Cl. The entrance complex, transition state, and exit complex for both reactions have been determined using the CCSD(T) method with correlation consistent basis sets up to cc-pV6Z. Also reported are CCSDT computations. The OH + Cl2 reaction is predicted to be endothermic by 2.2 kcal/mol, compared to the best experiments, 2.0 kcal/mol. The above theoretical results include zero-point vibrational energy corrections and spin-orbit contributions. The activation energy (Ea) of the OH + Cl2 reaction predicted here, 2.3 kcal/mol, could be as much as 1 kcal/mol too high, but it falls among the four experimental Ea values, which span the range 1.1-2.5 kcal/mol. The exothermicity of the second reaction HOCl + Cl → HCl + ClO is 8.4 kcal/mol, compared to experiment 8.7 kcal/mol. The activation energy for latter reaction is unknown experimentally, but predicted here to be large, 11.5 kcal/mol. There are currently no experiments relevant to the theoretical entrance and exit complexes predicted here. © 2015 American Chemical Society

A New Tool for CME Arrival Time Prediction using Machine Learning Algorithms: CAT-PUMA

Coronal mass ejections (CMEs) are arguably the most violent eruptions in the solar system. CMEs can cause severe disturbances in interplanetary space and can even affect human activities in many aspects, causing damage to infrastructure and loss of revenue. Fast and accurate prediction of CME arrival time is vital to minimize the disruption that CMEs may cause when interacting with geospace. In this paper, we propose a new approach for partial-/full halo CME Arrival Time Prediction Using Machine learning Algorithms (CAT-PUMA). Via detailed analysis of the CME features and solar-wind parameters, we build a prediction engine taking advantage of 182 previously observed geo-effective partial-/full halo CMEs and using algorithms of the Support Vector Machine. We demonstrate that CAT-PUMA is accurate and fast. In particular, predictions made after applying CAT-PUMA to a test set unknown to the engine show a mean absolute prediction error of ∼5.9 hr within the CME arrival time, with 54% of the predictions having absolute errors less than 5.9 hr. Comparisons with other models reveal that CAT-PUMA has a more accurate prediction for 77% of the events investigated that can be carried out very quickly, i.e., within minutes of providing the necessary input parameters of a CME. A practical guide containing the CAT-PUMA engine and the source code of two examples are available in the Appendix, allowing the community to perform their own applications for prediction using CAT-PUMA

Boosting with an aerosolized Ad5-nCoV elicited robust immune responses in inactivated COVID-19 vaccines recipients

IntroductionThe SARS-CoV-2 Omicron variant has become the dominant SARS-CoV-2 variant and exhibits immune escape to current COVID-19 vaccines, the further boosting strategies are required.MethodsWe have conducted a non-randomized, open-label and parallel-controlled phase 4 trial to evaluate the magnitude and longevity of immune responses to booster vaccination with intramuscular adenovirus vectored vaccine (Ad5-nCoV), aerosolized Ad5-nCoV, a recombinant protein subunit vaccine (ZF2001) or homologous inactivated vaccine (CoronaVac) in those who received two doses of inactivated COVID-19 vaccines. ResultsThe aerosolized Ad5-nCoV induced the most robust and long-lasting neutralizing activity against Omicron variant and IFNg T-cell response among all the boosters, with a distinct mucosal immune response. SARS-CoV-2-specific mucosal IgA response was substantially generated in subjects boosted with the aerosolized Ad5-nCoV at day 14 post-vaccination. At month 6, participants boosted with the aerosolized Ad5-nCoV had remarkably higher median titer and seroconversion of the Omicron BA.4/5-specific neutralizing antibody than those who received other boosters. DiscussionOur findings suggest that aerosolized Ad5-nCoV may provide an efficient alternative in response to the spread of the Omicron BA.4/5 variant.Clinical trial registrationhttps://www.chictr.org.cn/showproj.html?proj=152729, identifier ChiCTR2200057278

Research on the energy balance algorithm of WSN based on topology control

Abstract Topology control is a key energy-saving technology in the wireless-sensor networking. In this paper, networking-associated algorithm named local minimum spanning tree (LMST) employed while compromising on energy balance issues, leading to the short lifetime of the network, and proposes an energy balance algorithm. The algorithm fully investigates the energy utilization to link the data communication and the remaining energy of the communication node, to achieve the balanced energy, and to avoid the complexities associated with excessive consumption of energy when the intermediate node acts as a data forwarding task, thus extending the network life cycle. The simulated experimental outcomes showed a great potential of the proposed algorithm that can efficiently prolong the network lifetime and guarantee the long-term reliable operation of the network while ensuring other network performance indicators, such as throughput and delivery rate