Single-Crystal Elasticity of Phase E at High Pressure and Temperature: Implications for the Low-Velo
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Abstract Molecular dynamics simulation is an important tool in computational materials science and chemistry, and in the past decade it has been revolutionized by machine learning. This rapid progress in machine learning interatomic potentials has produced a number of new architectures in just the past few years. Particularly notable among these are the atomic cluster expansion, which unified many of the earlier ideas around atom-density-based descriptors, and Neural Equivariant Interatomic Potentials (NequIP), a message-passing neural network with equivariant features that exhibited state-of-the-art accuracy at the time. Here we construct a mathematical framework that unifies these models: atomic cluster expansion is extended and recast as one layer of a multi-layer architecture, while the linearized version of NequIP is understood as a particular sparsification of a much larger polynomial model. Our framework also provides a practical tool for systematically probing different choices in this unified design space. An ablation study of NequIP, via a set of experiments looking at in- and out-of-domain accuracy and smooth extrapolation very far from the training data, sheds some light on which design choices are critical to achieving high accuracy. A much-simplified version of NequIP, which we call BOTnet (for body-ordered tensor network), has an interpretable architecture and maintains its accuracy on benchmark datasets.
Three different ex situ alkali degradation protocols were compared on single batches of LDPE-based radiation-grafted anion-exchange membranes (containing trimethylammonium, N -methylpiperidinium, and N -methylpyrrolidinium headgroups).
The photodetachment spectrum of the nitrate anion (NO 3 ₋ ) in the energy range of the NO 3 second excited state is simulated from first principles using quantum wave packet dynamics. The prediction at 10 K and 435 K relies on the use of an accurate full-dimensional fully coupled five state diabatic potential model utilizing an artificial neural network. The ability of this model to reproduce experimental spectra was demonstrated recently for the lower energy range. Analysis of the spectra indicates a weaker Jahn–Teller coupling compared to the first excited state. The detailed non-adiabatic dynamics is studied by computing the population dynamics. An ultra-fast non-statistical radiationless decay is found only among the Jahn–Teller components, which is followed by a slow statistical non-radiative decay among the different state manifolds. The latter is reproduced perfectly by a simple first order kinetics model. The dynamics in the second excited state is not affected by the presence of a conical intersection with the first excited state manifold.
In this paper, we report the measurement of the absolute double differential cross sections (DDCS) of secondary electrons emitted due to the ionization of N2 molecule in collisions with fast electrons having energies between 3 and 5 keV. The emitted electrons with energies from 1-500 eV have been measured for different forward and backward emission angles. The measured DDCS have been compared with the state-of-the-art first Born approximation with correct boundary condition (CB1) model calculations as well as with the classical trajectory Monte Carlo (CTMC) method. From the measured DDCS, the single differential cross sections (SDCS) as a function of the emission energies have been computed and eventually the total ionization cross sections (TCS) have been derived. The TCS values are also compared with a semi-empirical calculation, namely, the CSP-ic (complex scattering potential-ionization contribution) model.
Accelerating cryomodules with superconducting cavities are key components for particle accelerators. The efficiency, energy gain and operating temperature of cavities drive the operating and capital costs; hence, advances in these areas enable future accelerators. While superconducting cavities are currently made from Nb, Nb 3 Sn, with a superconducting transition temperature and superheating field approximately twice that of Nb, is poised to substantially improve the efficiency and energy gain. We present results from the first cryomodule with two five-cell 1.5 GHz superconducting radiofrequency Nb cavities coated with Nb 3 Sn, which attained an accelerating gradient of ⩾10 MV m −1 with low cryogenic loss at 4.4 K.
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Viruses infect, reprogram and kill microbes, leading to profound ecosystem consequences, from elemental cycling in oceans and soils to microbiome-modulated diseases in plants and animals. Although metagenomic datasets are increasingly available, identifying viruses in them is challenging due to poor representation and annotation of viral sequences in databases. Here, we establish efam, an expanded collection of Hidden Markov Model (HMM) profiles that represent viral protein families conservatively identified from the Global Ocean Virome 2.0 dataset. This resulted in 240 311 HMM profiles, each with at least 2 protein sequences, making efam >7-fold larger than the next largest, pan-ecosystem viral HMM profile database. Adjusting the criteria for viral contig confidence from ‘conservative’ to ‘eXtremely Conservative’ resulted in 37 841 HMM profiles in our efam-XC database. To assess the value of this resource, we integrated efam-XC into VirSorter viral discovery software to discover viruses from less-studied, ecologically distinct oxygen minimum zone (OMZ) marine habitats. This expanded database led to an increase in viruses recovered from every tested OMZ virome by ~24% on average (up to ~42%) and especially improved the recovery of often-missed shorter contigs (<5 kb). Additionally, to help elucidate lesser-known viral protein functions, we annotated the profiles using multiple databases from the DRAM pipeline and virion-associated metaproteomic data, which doubled the number of annotations obtainable by standard, single-database annotation approaches. Together, these marine resources (efam and efam-XC) are provided as searchable, compressed HMM databases that will be updated bi-annually to help maximize viral sequence discovery and study from any ecosystem.
Cas9-based genome editing technologies can rapidly generate mutations to probe a diverse array of mutant genotypes. However, aberrant Cas9 nuclease translation and activity can occur despite the use of inducible promoters to control expression, leading to extensive cell death. This background killing caused by promoter leakiness severely limits the application of Cas9 for generating mutant libraries because of the potential for population skew. We demonstrate the utility of temperature sensitive RNA elements as a layer of post-transcriptional regulation to reduce the impact of promoter leak. We observe significant temperature-dependent increases in cell survival when certain RNA thermometers (RNATs) are placed upstream of the cas9 coding sequence. We also show that the most highly repressing RNAT, hsp17rep, significantly reduces population skew with a library of characterized guide RNAs in Escherichia coli. This strategy should be applicable to all bacterial Cas9-based methods and technologies.
Abstract Cell-free systems can expedite the design and implementation of biomanufacturing processes by bypassing troublesome requirements associated with the use of live cells. In particular, the lack of survival objectives and the open nature of cell-free reactions afford engineering approaches that allow purposeful direction of metabolic flux. The use of lysate-based systems to produce desired small molecules can result in competitive titers and productivities when compared to their cell-based counterparts. However, pathway crosstalk within endogenous lysate metabolism can compromise conversion yields by diverting carbon flow away from desired products. Here, the ‘block—push—pull’ concept of conventional cell-based metabolic engineering was adapted to develop a cell-free approach that efficiently directs carbon flow in lysates from glucose and toward endogenous ethanol synthesis. The approach is readily adaptable, is relatively rapid and allows for the manipulation of central metabolism in cell extracts. In implementing this approach, a block strategy is first optimized, enabling selective enzyme removal from the lysate to the point of eliminating by-product-forming activity while channeling flux through the target pathway. This is complemented with cell-free metabolic engineering methods that manipulate the lysate proteome and reaction environment to push through bottlenecks and pull flux toward ethanol. The approach incorporating these block, push and pull strategies maximized the glucose-to-ethanol conversion in an Escherichia coli lysate that initially had low ethanologenic potential. A 10-fold improvement in the percent yield is demonstrated. To our knowledge, this is the first report of successfully rewiring lysate carbon flux without source strain optimization and completely transforming the consumed input substrate to a desired output product in a lysate-based, cell-free system.
Bacteriophages (phages) are critical players in the dynamics and function of microbial communities and drive processes as diverse as global biogeochemical cycles and human health. Phages tend to be predators finely tuned to attack specific hosts, even down to the strain level, which in turn defend themselves using an array of mechanisms. However, to date, efforts to rapidly and comprehensively identify bacterial host factors important in phage infection and resistance have yet to be fully realized. Here, we globally map the host genetic determinants involved in resistance to 14 phylogenetically diverse double-stranded DNA phages using two model Escherichia coli strains (K-12 and BL21) with known sequence divergence to demonstrate strain-specific differences. Using genome-wide loss-of-function and gain-of-function genetic technologies, we are able to confirm previously described phage receptors as well as uncover a number of previously unknown host factors that confer resistance to one or more of these phages. We uncover differences in resistance factors that strongly align with the susceptibility of K-12 and BL21 to specific phage. We also identify both phage specific mechanisms, such as the unexpected role of cyclic-di-GMP in host sensitivity to phage N4, and more generic defenses, such as the overproduction of colanic acid capsular polysaccharide that defends against a wide array of phages. Our results indicate that host responses to phages can occur via diverse cellular mechanisms. Our systematic and high-throughput genetic workflow to characterize phage-host interaction determinants can be extended to diverse bacteria to generate datasets that allow predictive models of how phage-mediated selection will shape bacterial phenotype and evolution. The results of this study and future efforts to map the phage resistance landscape will lead to new insights into the coevolution of hosts and their phage, which can ultimately be used to design better phage therapeutic treatments and tools for precision microbiome engineering.
Passive detection of special nuclear material (SNM) is challenging due to its inherently low rate of spontaneous emission of penetrating radiation, the relative ease of shielding, and the fluctuating and frequently overwhelming background. Active interrogation, the use of external radiation to increase the emission rate of characteristic radiation from SNM, has long been considered to be a promising method to overcome those challenges. Current active-interrogation systems that incorporate radiography tend to use bremsstrahlung beams, which can deliver high radiation doses. Low-energy ion-driven nuclear reactions that produce multiple monoenergetic photons may be used as an alternative. The 12 C ( p , p ' ) 12 C reaction is one such reaction that could produce large yields of highly penetrating 4.4- and 15.1-MeV gamma rays. This reaction does not directly produce neutrons below the approximately 19.7 MeV threshold, and the 15.1-MeV gamma-ray line is well matched to the photofission cross section of 235 U and 238 U . In this article, we report the measurements of thick-target gamma-ray yields at 4.4 and 15.1 MeV from the 12 C ( p , p ' ) 12 C reaction at proton energies of 19.5, 25, and 30 MeV. Measurements are made with two 3 -in. EJ-309 cylindrical liquid scintillation detectors and thermoluminescent dosimeters placed at 0 ° and 90 ° , with an additional 1.5 -in. Na I ( Tl ) cylindrical scintillation detector at 0 ° . We estimate the highest yields of the 4.4- and 15.1-MeV gamma rays of 1.65 × 10 10 and 4.47 × 10 8 sr - 1 μ C - 1 at a proton energy of 30 MeV, respectively. The yields in all experimental configurations are greater than in a comparable deuteron-driven reaction that produces the same gamma-ray energies— 11 B ( d , n γ ) 12 C . However, a significant increase of the neutron radiation dose accompanies the proton energy increase from 19.5 to 30 MeV.
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In the fluctuation regime that precedes the onset of pairing in multi-component superconductors, such as nematic and chiral superconductors, the normal state is generally unstable towards the formation of charge-4e order – an exotic quantum state in which electrons form coherent quartets rather than Cooper pairs. However, charge-4e order is often suppressed by other competing composite orders, such as nematics. Importantly, the formation of nematic domains is unavoidable due to the long-range strains generated, leading to one-dimensional regions where the competing nematic order is suppressed. Here, we employ a real-space variational approach to demonstrate that, in such nematic domain walls, charge-4e order is locally condensed via a vestigial-order mechanism. Here, we explore the experimental manifestations of this effect and discuss materials in which it can be potentially observed.
Growth parameters play a significant role in the crystal quality and physical properties of layered materials. Here we present a case study on a van der Waals magnetic NbFeTe 2 material. Two different types of polymorphic NbFeTe 2 phases, synthesized at different temperatures, display significantly different behaviors in crystal symmetry, electronic structure, electrical transport, and magnetism. While the phase synthesized at low temperature showing behavior consistent with previous reports, the new phase synthesized at high temperature, has completely different physical properties, such as metallic resistivity, long-range ferromagnetic order, anomalous Hall effect, negative magnetoresistance, and distinct electronic structures. Neutron diffraction reveals out-of-plane ferromagnetism below 70 K, consistent with the electrical transport and magnetic susceptibility studies. Finally, our work suggests that simply tuning synthetic parameters in a controlled manner could be an effective route to alter the physical properties of existing materials potentially unlocking new states of matter, or even discovering new materials.