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Register a new userThe role of water in host-guest interaction
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One of the main applications of atomistic computer simulations is the calculation of ligand binding energies. The accuracy of these calculations depends on the force field quality and on the thoroughness of configuration sampling. Sampling is an obstacle in modern simulations due to the frequent appearance of kinetic bottlenecks in the free energy landscape. Very often this difficulty is circumvented by enhanced sampling techniques. Typically, these techniques depend on the introduction of appropriate collective variables that are meant to capture the systems degrees of freedom. In ligand binding, water has long been known to play a key role, but its complex behaviour has proven difficult to fully capture. In this paper we combine machine learning with physical intuition to build a non-local and highly efficient water-describing collective variable. We use it to study a set of of host-guest systems from the SAMPL5 challenge. We obtain highly accurate binding energies and good agreement with experiments. The role of water during the binding process is then analysed in some detail.
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In this work, we study the rotating magnetic field driven domain wall (DW) motion in antiferromagnetic nanowires, using the micromagnetic simulations of the classical Heisenberg spin model. We show that in low frequency region, the rotating field alone could efficiently drive the DW motion even in the absence of Dzyaloshinskii-Moriya interaction (DMI). In this case, the DW rotates synchronously with the magnetic field, and a stable precession torque is available and drives the DW motion with a steady velocity. In large frequency region, the DW only oscillates around its equilibrium position and cannot propagate. The dependences of the velocity and critical frequency differentiating the two motion modes on several parameters are investigated in details, and the direction of the DW motion can be controlled by modulating the initial phase of the field. Interestingly, a unidirectional DW motion is predicted attributing to the bulk DMI, and the nonzero velocity for high frequency is well explained. Thus, this work does provide useful information for further antiferromagnetic spintronics applications.
Carbene-metal-amide type photoemitters based on CF$_3$-substituted carbazolate ligands show sky-blue to deep-blue photoluminescence from charge-transfer excited states. They are suitable for incorporation into organic light-emitting diodes (OLEDs) by thermal vapour deposition techniques, either embedded within a high-triplet-energy host, or used host-free. We report high-efficiency OLEDs with emission ranging from yellow to blue (Commission Internationale de lEclairage (CIE) coordinates from [0.35, 0.53] to [0.17, 0.17]). The latter show a peak electroluminescence external quantum efficiency (EQE) of 20.9 $%$ in a polar host. We observe that the relative energies of CT and $^{3}$LE states influence the performance of deep-blue emission from carbene-metal-amide materials. We report prototype host-free blue devices with peak external quantum efficiency of 17.3 $%$, which maintain high performance at brightness levels of 100 cd m$^{-2}$.
We report the results of our participation in the SAMPL8 GDCC Blind Challenge for host-guest binding affinity predictions. Absolute binding affinity prediction is of central importance to the biophysics of molecular association and pharmaceutical discovery. The blinded SAMPL series have provided an important forum for assessing the reliability of binding free energy methods in an objective way. In this blinded challenge, we employed two binding free energy methods, the newly developed alchemical transfer method (ATM) and the well-established potential of mean force (PMF) physical pathway method, using the same setup and force field model. The calculated binding free energies from the two methods are in excellent quantitative agreement. Importantly, the results from the two methods were also found to agree well with the experimental binding affinities released subsequently, with an $R^2$ of 0.89 (ATM) and 0.83 (PMF). Given that the two free energy methods are based on entirely different thermodynamic pathways, the close agreement between the results from the two methods and their general agreement with the experimental binding free energies are a testament to the high quality achieved by theory and methods. The study provides further validation of the novel ATM binding free energy estimation protocol and it paves the way to further extensions of the method to more complex systems.
Identifying key players in collective dynamics remains a challenge in several research fields, from the efficient dissemination of ideas to drug target discovery in biomedical problems. The difficulty lies at several levels: how to single out the role of individual elements in such intermingled systems, or which is the best way to quantify their importance. Centrality measures describe a nodes importance by its position in a network. The key issue obviated is that the contribution of a node to the collective behavior is not uniquely determined by the structure of the system but it is a result of the interplay between dynamics and network structure. We show that dynamical influence measures explicitly how strongly a nodes dynamical state affects collective behavior. For critical spreading, dynamical influence targets nodes according to their spreading capabilities. For diffusive processes it quantifies how efficiently real systems may be controlled by manipulating a single node.
We report on the successful synthesis and hyperpolarization of N unprotected {alpha} amino acid ethyl acrylate esters and extensively, on an alanine derivative hyperpolarized by PHIP (4.4$pm$1% $^{13}$C-polarization), meeting required levels for in vivo detection. Using water as solvent increases biocompatibility and the absence of N-protection is expected to maintain biological activity.
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