Mechanistic photophysics of tellurium-substituted cytosine: Electronic structure calculations and nonadiabatic dynamics simulations.

Previously, the MS-CASPT2 method was performed to study the static and qualitative photophysics of tellurium-substituted cytosine (TeC). To get quantitative information, we used our recently developed QTMF-FSSH dynamics method to simulate the excited-state decay of TeC. The CASSCF method was adopted to reduce the calculation costs, which was confirmed to provide reliable structures and energies as those of MS-CASPT2. A detailed structural analysis showed that only 5% trajectories will hop to the lower triplet or singlet state via the twisted (S2 /S1 /T2 )T intersection, while 67% trajectories will choose the planar intersections of (S2 /S1 /T3 /T2 /T1 )P and (S2 /S1 /T2 /T1 )P but subsequently become twisted in other electronic states. By contrast, ~28% trajectories will maintain in a plane throughout dynamics. Electronic population revealed that the S2 population will ultrafast transfer to the lower triplet or singlet state. Later, the TeC system will populate in the spin-mixed electronic states composed of S1 , T1 and T2 . At the end of 300 fs, most trajectories (~74%) will decay to the ground state and only 17.4% will survive in the triplet states. Our dynamics simulation verified that tellurium substitution will enhance the intersystem crossings, but the very short triplet lifetime (ca. 125 fs) will make TeC a less effective photosensitizer.

Improved Interfacial Ion Migration and Deposition through the Chain-Liquid Synergistic Effect by a Carboxylated Hydrogel Electrolyte for Stable Zinc Metal Anodes.

The large-scale applicability of Zn-metal anodes is severely impeded by the issues such as the dendrite growth, complicated hydrogen evolution, and uncontrollable passivation reaction. Herein, a negatively charged carboxylated double-network hydrogel electrolyte (Gelatin/Sodium alginate-acetate, denoted as Gel/SA-acetate) has been developed to stabilize the interfacial electrochemistry, which restructures a type of Zn2+ ion solvent sheath optimized via a chain-liquid synergistic effect. New hydrogen bonds are reconstructed with water molecules by the zincophilic functional groups, and directional migration of hydrated Zn2+ ions is therefore induced. Concomitantly, the robust chemical bonding of such hydrogel layers to the Zn slab exhibits a desirable anti-catalytic effect, thereby greatly diminishing the water activity and eliminating side reactions. Subsequently, a symmetric cell using the Gel/SA-acetate electrolyte demonstrates a reversible plating/stripping performance for 1580 h, and an asymmetric cell reaches a state-of-the-art runtime of 5600 h with a high average Coulombic efficiency of 99.9 %. The resultant zinc ion hybrid capacitors deliver exceptional properties including the capacity retention of 98.5 % over 15000 cycles, energy density of 236.8 Wh kg-1 , and high mechanical adaptability. This work is expected to pave a new avenue for the development of novel hydrogel electrolytes towards safe and stable Zn anodes.

α-Synuclein Aggregation Is Triggered by Oligomeric Amyloid-ß 42 via Heterogeneous Primary Nucleation.

An increasing number of cases where amyloids of different proteins are found in the same patient are being reported. This observation complicates diagnosis and clinical intervention. Amyloids of the amyloid-ß peptide or the protein α-synuclein are traditionally considered hallmarks of Alzheimer's and Parkinson's diseases, respectively. However, the co-occurrence of amyloids of these proteins has also been reported in patients diagnosed with either disease. Here, we show that soluble species containing amyloid-ß can induce the aggregation of α-synuclein. Fibrils formed under these conditions are solely composed of α-synuclein to which amyloid-ß can be found associated but not as part of the core of the fibrils. Importantly, by global kinetic analysis, we found that the aggregation of α-synuclein under these conditions occurs via heterogeneous primary nucleation, triggered by soluble aggregates containing amyloid-ß.

Understanding the Excited-State Relaxation Mechanisms of Xanthophyll Lutein by Multi-configurational Electronic Structure Calculations.

The contradictory behaviors in light harvesting and non-photochemical quenching make xanthophyll lutein the most attractive functional molecule in photosynthesis. Despite several theoretical simulations on the spectral properties and excited-state dynamics, the atomic-level photophysical mechanisms need to be further studied and established, especially for an accurate description of geometric and electronic structures of conical intersections for the lowest several electronic states of lutein. In the present work, semiempirical OM2/MRCI and multi-configurational restricted active space self-consistent field methods were performed to optimize the minima and conical intersections in and between the 1Ag-, 2Ag-, 1Bu+, and 1Bu- states. Meanwhile, the relative energies were refined by MS-CASPT2(10,8)/6-31G*, which can reproduce correct electronic state properties as those in the spectroscopic experiments. Based on the above calculation results, we proposed a possible excited-state relaxation mechanism for lutein from its initially populated 1Bu+ state. Once excited to the optically bright 1Bu+ state, the system will propagate along the key reaction coordinate, i.e., the stretching vibration of the conjugated carbon chain. During this period of time, the 1Bu- state will participate in and forms a resonance state between the 1Bu- and 1Bu+ states. Later, the system will rapidly hop to the 2Ag- state via the 1Bu+/2Ag- conical intersection. Finally, the lutein molecule will survive in the 2Ag- state for a relatively long time before it internally converts to the ground state directly or via a twisted S1/S0 conical intersection. Notably, though the photophysical picture may be very different in solvents and proteins, the current theoretical study proposed a promising calculation protocol and also provided many valuable mechanistic insights for lutein and similar carotenoids.

Lightweight Deep Neural Networks for Ship Target Detection in SAR Imagery.

In recent years, deep convolutional neural networks (DCNNs) have been widely used in the task of ship target detection in synthetic aperture radar (SAR) imagery. However, the vast storage and computational cost of DCNN limits its application to spaceborne or airborne onboard devices with limited resources. In this paper, a set of lightweight detection networks for SAR ship target detection are proposed. To obtain these lightweight networks, this paper designs a network structure optimization algorithm based on the multi-objective firefly algorithm (termed NOFA). In our design, the NOFA algorithm encodes the filters of a well-performing ship target detection network into a list of probabilities, which will determine whether the lightweight network will inherit the corresponding filter structure and parameters. After that, the multi-objective firefly optimization algorithm (MFA) continuously optimizes the probability list and finally outputs a set of lightweight network encodings that can meet the different needs of the trade-off between detection network precision and size. Finally, the network pruning technology transforms the encoding that meets the task requirements into a lightweight ship target detection network. The experiments on SSDD and SDCD datasets prove that the method proposed in this paper can provide more flexible and lighter detection networks than traditional detection networks.