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Register a new userMetavalent bonding in crystalline solids: how does it collapse?
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The chemical bond is one of the most powerful, yet controversial concepts in chemistry, explaining property trends in solids. Recently, a novel type of chemical bonding has been identified in several higher chalcogenides, characterized by a unique property portfolio, unconventional bond breaking and sharing of about one electron between adjacent atoms. Metavalent bonding is a fundamental type of bonding besides covalent, ionic and metallic bonding, raising the pertinent question, if there is a well-defined transition between metavalent and covalent bonding. For three different pseudo-binary lines, namely GeTe1-xSex, Sb2Te3(1-x)Se3x and Bi2-2xSb2xSe3, a sudden drop in several properties, including the optical dielectric constant, the Born effective charge, the electrical conductivity as well as the bond breaking is observed once a critical Se or Sb concentration is reached. This finding provides a blueprint to explore the impact of metavalent bonding on attractive properties utilized in phase change materials and thermoelectrics.
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Third-generation photovoltaic (PV) materials combine many advantageous properties, including a high optical absorption together with a large charge carrier mobility, facilitated by small effective masses. Halide perovskites (ABX3, where X is I, Br or Cl) appear to be the most promising third-generation PV materials at present. Their opto-electronic properties are governed by the B-X bond. A quantum-chemical bond analysis reveals that this bond differs significantly from ionic, metallic or covalent bonds. Instead, it is better regarded as metavalent, since it shares approximately one p-electron between adjacent atoms. The resulting sigma-bond is half-filled, which causes pronounced optical absorption. Electron transfer and lattice distortions open a moderate band gap, resulting in charge carriers with small effective masses. Hence metavalent bonding explains the favorable PV properties of halide perovskites. This is summarized in a map for different bond types, which provides a blueprint to design third-generation PV materials.
In order to stabilize the behavior of noisy systems, confining it around a desirable state, an effort is required to suppress the intrinsic noise. This noise suppression task entails a cost. For the important case of thermal noise in an overdamped system, we show that the minimum cost is achieved when the system control parameters are held constant: any additional deterministic or random modulation produces an increase of the cost. We discuss the implications of this phenomenon for those overdamped systems whose control parameters are intrinsically noisy, presenting a case study based on the example of a Brownian particle optically trapped in an oscillating potential.
There is a longstanding discrepancy between the observed Galactic classical nova rate of $sim 10$ yr$^{-1}$ and the predicted rate from Galactic models of $sim 30$--50 yr$^{-1}$. One explanation for this discrepancy is that many novae are hidden by interstellar extinction, but the degree to which dust can obscure novae is poorly constrained. We use newly available all-sky three-dimensional dust maps to compare the brightness and spatial distribution of known novae to that predicted from relatively simple models in which novae trace Galactic stellar mass. We find that only half ($sim 48$%) of novae are expected to be easily detectable ($g lesssim 15$) with current all-sky optical surveys such as the All-Sky Automated Survey for Supernovae (ASAS-SN). This fraction is much lower than previously estimated, showing that dust does substantially affect nova detection in the optical. By comparing complementary survey results from ASAS-SN, OGLE-IV, and the Palomar Gattini IR-survey in the context of our modeling, we find a tentative Galactic nova rate of $sim 40$ yr$^{-1}$, though this could decrease to as low as $sim 30$ yr$^{-1}$ depending on the assumed distribution of novae within the Galaxy. These preliminary estimates will be improved in future work through more sophisticated modeling of nova detection in ASAS-SN and other surveys.
Nanophotonic chiral sensing has recently attracted a lot of attention. The idea is to exploit the strong light-matter interaction in nanophotonic resonators to determine the concentration of chiral molecules at ultra-low thresholds, which is highly attractive for numerous applications in life science and chemistry. However, a thorough understanding of the underlying interactions is still missing. The theoretical description relies on either simple approximations or on purely numerical approaches. We close this gap and present a general theory of chiral light-matter interactions in arbitrary resonators. Our theory describes the chiral interaction as a perturbation of the resonator modes, also known as resonant states or quasi-normal modes. We observe two dominant contributions: A chirality-induced resonance shift and changes in the modes excitation and emission efficiencies. Our theory brings new and deep insights for tailoring and enhancing chiral light-matter interactions. Furthermore, it allows to predict spectra much more efficiently in comparison to conventional approaches. This is particularly true as chiral interactions are inherently weak and therefore perturbation theory fits extremely well for this problem.
We explore whether the topology of energy landscapes in chemical systems obeys any rules and what these rules are. To answer this and related questions we use several tools: (i)Reduced energy surface and its density of states, (ii) descriptor of structure called fingerprint function, which can be represented as a one-dimensional function or a vector in abstract multidimensional space, (iii) definition of a distance between two structures enabling quantification of energy landscapes, (iv) definition of a degree of order of a structure, and (v) definitions of the quasi-entropy quantifying structural diversity. Our approach can be used for rationalizing large databases of crystal structures and for tuning computational algorithms for structure prediction. It enables quantitative and intuitive representations of energy landscapes and reappraisal of some of the traditional chemical notions and rules. Our analysis confirms the expectations that low-energy minima are clustered in compact regions of configuration space (funnels) and that chemical systems tend to have very few funnels, sometimes only one. This analysis can be applied to the physical properties of solids, opening new ways of discovering structure-property relations. We quantitatively demonstrate that crystals tend to adopt one of the few simplest structures consistent with their chemistry, providing a thermodynamic justification of Paulings fifth rule.
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