Plasmonic enhancement of molecular hydrogen dissociation on metallic magnesium nanoclusters

Light-driven plasmonic enhancement of chemical reactions on metal catalysts is a promising strategy to achieve highly selective and efficient chemical transformations. The study of plasmonic catalyst materials has traditionally focused on late transition metals such as Au, Ag, and Cu. In recent years, there has been increasing interest in the plasmonic properties of a set of earth-abundant elements such as Mg, which exhibit interesting hydrogenation chemistry with potential applications in hydrogen storage. This work explores the optical, electronic, and catalytic properties of a set of metallic Mg nanoclusters with up to 2057 atoms using time-dependent density functional tight-binding and density functional theory calculations. Our results show that Mg nanoclusters are able to produce highly energetic hot electrons with energies of up to 4 eV. By electronic structure analysis, we find that these hot electrons energetically align with electronic states of physisorbed molecular hydrogen, occupation of which by hot electrons can promote the hydrogen dissociation reaction. We also find that the reverse reaction, hydrogen evolution on metallic Mg, can potentially be promoted by hot electrons, but following a different mechanism. Thus, from a theoretical perspective, Mg nanoclusters display very promising behaviour for their use in light promoted storage and release of hydrogen

Importance of equivariant features in machine-learning interatomic potentials for reactive chemistry at metal surfaces

Reactive chemistry of molecular hydrogen at surfaces, notably dissociative sticking and hydrogen evolution, play a crucial role in energy storage, fuel cells, and chemical synthesis. Copper is a particularly interesting metal for studying these processes due to its widespread use as both a catalyst in industry and a model catalyst in fundamental research. Theoretical studies can help to decipher underlying mechanisms and reaction design, but studying these systems computationally is challenging due to the complex electronic structure of metal surfaces and the high sensitivity towards reaction barriers. In addition, ab initio molecular dynamics, based on density functional theory, is too computationally demanding to explicitly simulate reactive sticking or desorption probabilities. A promising solution to such problems can be provided through high-dimensional machine learning-based interatomic potentials (MLIPs). Despite the remarkable accuracy and fidelity of MLIPs, particularly in molecular and bulk inorganic materials simulations, their application to different facets of hybrid systems and the selection of appropriate representations remain largely unexplored. This paper addresses these issues and investigates how feature equivariance in MLIPs impacts adaptive sampling workflows and data efficiency. Specifically, we develop high-dimensional MLIPs to investigate reactive hydrogen scattering on copper surfaces and compare the performance of various MLIPs that use equivariant features for atomic representation (PaiNN) with those that use invariant representations (SchNet). Our findings demonstrate that using equivariant features can greatly enhance the accuracy and reliability of MLIPs for gas surface dynamics and that this approach should become the standard in this field

Overcoming the bottleneck to widespread testing: a rapid review of nucleic acid testing approaches for COVID-19 detection

The current COVID-19 pandemic presents a serious public health crisis, and a better understanding of the scope and spread of the virus would be aided by more widespread testing. Nucleic-acid-based tests currently offer the most sensitive and early detection of COVID-19. However, the “gold standard” test pioneered by the U.S. Centers for Disease Control and Prevention takes several hours to complete and requires extensive human labor, materials such as RNA extraction kits that could become in short supply, and relatively scarce qPCR machines. It is clear that a huge effort needs to be made to scale up current COVID-19 testing by orders of magnitude. There is thus a pressing need to evaluate alternative protocols, reagents, and approaches to allow nucleic-acid testing to continue in the face of these potential shortages. There has been a tremendous explosion in the number of papers written within the first weeks of the pandemic evaluating potential advances, comparable reagents, and alternatives to the “gold-standard” CDC RT-PCR test. Here we present a collection of these recent advances in COVID-19 nucleic acid testing, including both peer-reviewed and preprint articles. Due to the rapid developments during this crisis, we have included as many publications as possible, but many of the cited sources have not yet been peer-reviewed, so we urge researchers to further validate results in their own laboratories. We hope that this review can urgently consolidate and disseminate information to aid researchers in designing and implementing optimized COVID-19 testing protocols to increase the availability, accuracy, and speed of widespread COVID-19 testing

NQCDynamics.jl : a Julia package for nonadiabatic quantum classical molecular dynamics in the condensed phase

Accurate and efficient methods to simulate nonadiabatic and quantum nuclear effects in high-dimensional and dissipative systems are crucial for the prediction of chemical dynamics in condensed phase. To facilitate effective development, code sharing and uptake of newly developed dynamics methods, it is important that software implementations can be easily accessed and built upon.Using the Julia programming language, we have developed the \pkgname ~ package which provides a framework for established and emerging methods for performing semiclassical and mixed quantum-classical dynamics in condensed phase. The code provides several interfaces to existing atomistic simulation frameworks, electronic structure codes, and machine learning representations. In addition to the existing methods, the package provides infrastructure for developing and deploying new dynamics methods which we hope will benefit reproducibility and code sharing in the field of condensed phase quantum dynamics. Herein, we present our code design choices and the specific Julia programming features from which they benefit.We further demonstrate the capabilities of the package on two examples of chemical dynamics in condensed phase: the population dynamics of the spin-boson model as described by a wide variety of semi-classical and mixed quantum-classical nonadiabatic methods and the reactive scattering of H2 on Ag(111) using the Molecular Dynamics with Electronic Friction method. Together, they exemplify the broad scope of the package to study effective model Hamiltonians and realistic atomistic systems

Prefacing unexplored archives from Central Andean surface-to-bedrock ice cores through a multifaceted investigation of regional firn and ice core glaciochemistry.

Shallow firn cores, in addition to a near-basal ice core, were recovered in 2018 from the Quelccaya ice cap (5470 m a.s.l) in the Cordillera Vilcanota, Peru, and in 2017 from the Nevado Illimani glacier (6350 m a.s.l) in the Cordillera Real, Bolivia. The two sites are ~450 km apart. Despite meltwater percolation resulting from warming, particle-based trace element records (e.g. Fe, Mg, K) in the Quelccaya and Illimani shallow cores retain well-preserved signals. The firn core chronologies, established independently by annual layer counting, show a convincing overlap indicating the two records contain comparable signals and therefore capture similar regional scale climatology. Trace element records at a ~1?4 cm resolution provide past records of anthropogenic emissions, dust sources, volcanic emissions, evaporite salts and marine-sourced air masses. Using novel ultra-high-resolution (120 ?m) laser technology, we identify annual layer thicknesses ranging from 0.3 to 0.8 cm in a section of 2000-year-old radiocarbon-dated near-basal ice which compared to the previous annual layer estimates suggests that Quelccaya ice cores drilled to bedrock may be older than previously suggested by depth-age models. With the information collected from this study in combination with past studies, we emphasize the importance of collecting new surface-to-bedrock ice cores from at least the Quelccaya ice cap, in particular, due to its projected disappearance as soon as the 2050s

The Victorian Newsletter (Fall 1959)

The Victorian Newsletter is edited for the English X Group of the Modern Language Association by William E. Buckler, 737 East Building, New York University, New York 3, New York.Some pages are missing from this record

The Victorian Newsletter (Spring 1960)

The Victorian Newsletter is edited for the English X Group of the Modern Language Association by William E. Buckler, 737 East Building, New York University, New York 3, New York

An Extensive Quality Control and Quality Assurance (QC/QA) Program Significantly Improves Inter-Laboratory Concordance Rates of Flow-Cytometric Minimal Residual Disease Assessment in Acute Lymphoblastic Leukemia: An I-BFM-FLOW-Network Report

Monitoring of minimal residual disease (MRD) by flow cytometry (FCM) is a powerful prognostic tool for predicting outcomes in acute lymphoblastic leukemia (ALL). To apply FCM-MRD in large, collaborative trials, dedicated laboratory staff must be educated to concordantly high levels of expertise and their performance quality should be continuously monitored. We sought to install a unique and comprehensive training and quality control (QC) program involving a large number of reference laboratories within the international Berlin-Frankfurt-Münster (I-BFM) consortium, in order to complement the standardization of the methodology with an educational component and persistent quality control measures. Our QC and quality assurance (QA) program is based on four major cornerstones: (i) a twinning maturation program, (ii) obligatory participation in external QA programs (spiked sample send around, United Kingdom National External Quality Assessment Service (UK NEQAS)), (iii) regular participation in list-mode-data (LMD) file ring trials (FCM data file send arounds), and (iv) surveys of independent data derived from trial results. We demonstrate that the training of laboratories using experienced twinning partners, along with continuous educational feedback significantly improves the performance of laboratories in detecting and quantifying MRD in pediatric ALL patients. Overall, our extensive education and quality control program improved inter-laboratory concordance rates of FCM-MRD assessments and ultimately led to a very high conformity of risk estimates in independent patient cohorts