In nature one can associate to each particle an antiparticle with equal mass and opposite charge: to the electron there is the positron, to the proton there is an anti-proton, etc. Majorana fermions ...are particles with an identity crisis: they are their own antiparticles and hence they self-annihilate. In this Colloquium the nature of Majorana particles and their presence in several different branches of physics is discussed from nuclear to condensed matter. Ettore Majorana (1906-1938) disappeared while traveling by ship from Palermo to Naples in 1938. Most notably the process of neutrino-less double beta decay can exist only if neutrinos are massive Majorana particles. Hence, many efforts to search for this process are underway. The equations he derived also arise in solid-state physics where they describe electronic states in materials with super-conducting order. This Colloquium first summarizes the basics of Majorana's theory and its implications. It then provides an overview of the rich experimental programs trying to find a fermion that is its own antiparticle in nuclear, particle, and solid-state physics.
The precise nature of chemical‐bonding interactions in amorphous, and crystalline, chalcogenides is still unclear due to the complexity arising from the delocalization of bonding, and nonbonding, ...electrons. Although an increasing degree of electron delocalization for elements down a column of the periodic table is widely recognized, its influence on chemical‐bonding interactions, and on consequent material properties, of chalcogenides has not previously been comprehensively understood from an atomistic point of view. Here, a chemical‐bonding framework is provided for understanding the behavior of chalcogenides (and, in principle, other lone‐pair materials) by studying prototypical telluride nonvolatile‐memory, “phase‐change” materials (PCMs), and related chalcogenide compounds, via density‐functional‐theory molecular‐dynamics (DFT‐MD) simulations. Identification of the presence of previously unconsidered multicenter “hyperbonding” (lone‐pair–antibonding‐orbital) interactions elucidates not only the origin of various material properties, and their contrast in magnitude between amorphous and crystalline phases, but also the very similar chemical‐bonding nature between crystalline PCMs and one of the bonding subgroups (with the same bond length) found in amorphous PCMs, in marked contrast to existing viewpoints. The structure–property relationship established from this new bonding‐interaction perspective will help in designing improved chalcogenide materials for diverse applications, based on a fundamental chemical‐bonding point of view.
The concept of multicenter (three‐center/four‐electron) hyperbonding is introduced to elucidate the unique properties of (telluride‐based) chalcogenides, in particular, used for phase‐change memory applications. The characteristic features of hyperbonding, induced by the stabilization interaction of a lone pair with an adjacent antibonding orbital, establish a structure/property relationship from which a diversity of the material properties can be comprehensively understood.
We quantify the impact of the Wuhan Covid-19 lockdown on concentrations of four air pollutants using a two-step approach. First, we use machine learning to remove the confounding effects of weather ...conditions on pollution concentrations. Second, we use a new augmented synthetic control method (Ben-Michael et al. in The augmented synthetic control method. University of California Berkeley, Mimeo,
2019
.
https://arxiv.org/pdf/1811.04170.pdf
) to estimate the impact of the lockdown on weather normalised pollution relative to a control group of cities that were not in lockdown. We find NO
2
concentrations fell by as much as 24
μ
g/m
3
during the lockdown (a reduction of 63% from the pre-lockdown level), while PM10 concentrations fell by a similar amount but for a shorter period. The lockdown had no discernible impact on concentrations of SO
2
or CO. We calculate that the reduction of NO
2
concentrations could have prevented as many as 496 deaths in Wuhan city, 3368 deaths in Hubei province and 10,822 deaths in China as a whole.
The typically poor outcomes of schizophrenia could be improved through interventions that reduce cardiometabolic risk, negative symptoms and cognitive deficits; aspects of the illness which often go ...untreated. The present review and meta-analysis aimed to establish the effectiveness of exercise for improving both physical and mental health outcomes in schizophrenia patients.
We conducted a systematic literature search to identify all studies that examined the physical or mental effects of exercise interventions in non-affective psychotic disorders. Of 1581 references, 20 eligible studies were identified. Data on study design, sample characteristics, outcomes and feasibility were extracted from all studies and systematically reviewed. Meta-analyses were also conducted on the physical and mental health outcomes of randomized controlled trials.
Exercise interventions had no significant effect on body mass index, but can improve physical fitness and other cardiometabolic risk factors. Psychiatric symptoms were significantly reduced by interventions using around 90 min of moderate-to-vigorous exercise per week (standardized mean difference: 0.72, 95% confidence interval -1.14 to -0.29). This amount of exercise was also reported to significantly improve functioning, co-morbid disorders and neurocognition.
Interventions that implement a sufficient dose of exercise, in supervised or group settings, can be feasible and effective interventions for schizophrenia.
Since the pioneering work of Elie Metchnikoff and the discovery of cellular immunity, the phagocytic clearance of cellular debris has been considered an integral component of resolving inflammation ...and restoring function of damaged and infected tissues. We now know that the phagocytic clearance of dying cells (efferocytosis), particularly by macrophages and other immune phagocytes, has profound consequences on innate and adaptive immune responses in inflamed tissues. These immunomodulatory effects result from an array of molecular signaling events between macrophages, dying cells, and other tissue-resident cells. In recent years, many of these molecular pathways have been identified and studied in the context of tissue inflammation, helping us better understand the relationship between efferocytosis and inflammation. We review specific types of efferocytosis-related signals that can impact macrophage immune responses and discuss their relevance to inflammation-related diseases.
Breaking the Speed Limits of Phase-Change Memory Loke, D.; Lee, T. H.; Wang, W. J. ...
Science (American Association for the Advancement of Science),
06/2012, Letnik:
336, Številka:
6088
Journal Article
Recenzirano
Phase-change random-access memory (PCRAM) is one of the leading candidates for next-generation data-storage devices, but the trade-off between crystallization (writing) speed and amorphous-phase ...stability (data retention) presents a key challenge. We control the crystallization kinetics of a phase-change material by applying a constant low voltage via prestructural ordering (incubation) effects. A crystallization speed of 500 picoseconds was achieved, as well as high-speed reversible switching using 500-picosecond pulses. Ab initio molecular dynamics simulations reveal the phase-change kinetics in PCRAM devices and the structural origin of the incubation-assisted increase in crystallization speed. This paves the way for achieving a broadly applicable memory device, capable of nonvolatile operations beyond gigahertz data-transfer rates.
The phagocytic clearance of dying cells in a tissue is a highly orchestrated series of intercellular events coordinated by a complex signaling network. Recent data from genetic, biochemical, and ...live-imaging approaches have greatly enhanced our understanding of the dynamics of cell clearance and how the process is orchestrated at the cellular and tissue levels. We discuss how networks regulating apoptotic cell clearance are integrated to enable a rapid, efficient, and high-capacity clearance system within tissues.
Recent studies have greatly enhanced our understanding of the dynamics of cell clearance by phagocytes and how the process is orchestrated at the cellular and tissue levels. In this review, Elliott and Ravichandran discuss how networks regulating apoptotic cell clearance are integrated to enable rapid and efficient clearance within tissues.
Ge-Sb-Te materials are used in optical DVDs and non-volatile electronic memories (phase-change random-access memory). In both, data storage is effected by fast, reversible phase changes between ...crystalline and amorphous states. Despite much experimental and theoretical effort to understand the phase-change mechanism, the detailed atomistic changes involved are still unknown. Here, we describe for the first time how the entire write/erase cycle for the Ge(2)Sb(2)Te(5) composition can be reproduced using ab initio molecular-dynamics simulations. Deep insight is gained into the phase-change process; very high densities of connected square rings, characteristic of the metastable rocksalt structure, form during melt cooling and are also quenched into the amorphous phase. Their presence strongly facilitates the homogeneous crystal nucleation of Ge(2)Sb(2)Te(5). As this simulation procedure is general, the microscopic insight provided on crystal nucleation should open up new ways to develop superior phase-change memory materials, for example, faster nucleation, different compositions, doping levels and so on.
Structurally disordered materials pose fundamental questions
, including how different disordered phases ('polyamorphs') can coexist and transform from one phase to another
. Amorphous silicon has ...been extensively studied; it forms a fourfold-coordinated, covalent network at ambient conditions and much-higher-coordinated, metallic phases under pressure
. However, a detailed mechanistic understanding of the structural transitions in disordered silicon has been lacking, owing to the intrinsic limitations of even the most advanced experimental and computational techniques, for example, in terms of the system sizes accessible via simulation. Here we show how atomistic machine learning models trained on accurate quantum mechanical computations can help to describe liquid-amorphous and amorphous-amorphous transitions for a system of 100,000 atoms (ten-nanometre length scale), predicting structure, stability and electronic properties. Our simulations reveal a three-step transformation sequence for amorphous silicon under increasing external pressure. First, polyamorphic low- and high-density amorphous regions are found to coexist, rather than appearing sequentially. Then, we observe a structural collapse into a distinct very-high-density amorphous (VHDA) phase. Finally, our simulations indicate the transient nature of this VHDA phase: it rapidly nucleates crystallites, ultimately leading to the formation of a polycrystalline structure, consistent with experiments
but not seen in earlier simulations
. A machine learning model for the electronic density of states confirms the onset of metallicity during VHDA formation and the subsequent crystallization. These results shed light on the liquid and amorphous states of silicon, and, in a wider context, they exemplify a machine learning-driven approach to predictive materials modelling.
PDF
