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Cellulose in plant cell walls are synthesized as crystalline microfibrils with diameters of 3-4 nm and lengths of around 1-10 μm. These microfibrils are known to be the backbone of cell walls, and their multiscale three-dimensional organization plays a critical role in cell wall functions including plant growth and recalcitrance to degradation. The mesoscale organization of microfibrils over a 1-100 nm range in cell walls is challenging to resolve because most characterization techniques investigating this length scale suffer from low spatial resolution, sample preparation artifacts, or inaccessibility of specific cell types. Here, we report a sum frequency generation (SFG) study determining the mesoscale polarity of cellulose microfibrils in intact plant cell walls. SFG is a nonlinear optical spectroscopy technique sensitive to the molecular-to-mesoscale order of noncentrosymmetric domains in amorphous matrices. However, the quantitative theoretical model to unravel the effect of polarity in packing of noncentrosymmetric domains on SFG spectral features has remained unresolved. In this work, we show how the phase synchronization principle of the SFG process is used to predict the relative intensities of vibrational modes with different polar angles from the noncentrosymmetric domain axis. Applying this model calculation for the first time and employing SFG microscopy, we found that cellulose microfibrils in certain xylem cell walls are deposited unidirectionally (or biased in one direction) instead of the bidirectional polarity which was believed to be dominant in plant cell walls from volume-averaged characterizations of macroscopic samples. With this advancement in SFG analysis, one can now determine the relative polarity of noncentrosymmetric domains such as crystalline biopolymers interspersed in amorphous polymer matrices, which will open opportunities to study new questions that have not been conceived in the past.Reaction intermediates in the green-to-red photoconversion of the photochromic fluorescent protein EosFP have been observed using high-intensity continuous blue illumination. An intermediate was identified through light-induced accumulation that continues to convert the green form in subsequent darkness, putatively containing a tyrosyl radical, albeit with anomalously shifted features in both the electronic and FTIR spectra. Lowering the pH to 5.5 significantly delays the decay of this tyrosyl intermediate, which is accompanied by Stark-shifted features in the electronic spectra of reactants and products. Vibrational mode assignments for the high-frequency and fingerprint FTIR spectral regions of the reaction intermediates support a proposed sequence of events where the newly formed Cα═Cβ ethylenic bond precedes modifications on the His-62 imidazole ring and confirms a C═O(NH2) product group on Phe-61. We propose a reaction mechanism that involves tyrosyl generation via singlet excited-state-mediated oxidation which subsequently triggers the covalent reactions by oxidation of the green chromophore.ConspectusSingle-walled carbon nanotubes (SWCNTs) show promise as light sources for modern fiber optical communications due to their emission wavelengths tunable via chirality and diameter dependency. check details However, the emission quantum yields are relatively low owing to the existence of low-lying dark electronic states and fast excitonic diffusion leading to carrier quenching at defects. Covalent functionalization of SWCNTs addresses this problem by brightening their infrared emission. Namely, introduction of sp3-hybridized defects makes the lowest energy transitions optically active for some defect geometries and enables further control of their optical properties. Such functionalized SWCNTs are currently the only material exhibiting room-temperature single photon emission at telecom relevant infrared wavelengths. While this fluorescence is strong and has the right wavelength, functionalization introduces a variety of emission peaks resulting in spectrally broad inhomogeneous photoluminescence that prohibits the her existing defects. This takes advantage of the changes in π-orbital mismatch enforced by existing defects and the resulting changes in reactivities toward formation of specific defect morphologies. Furthermore, the trends in emissive energies are highly dependent on the value of mod(n-m,3) for an (n,m) tube chirality. These powerful concepts allow for a targeted formation of defects that emit at desired energies based on SWCNT single chirality enriched samples. Finally, the impact of functionalization with specific types of defects that enforce certain defect geometries due to steric constraints in bond lengths and angles to the SWCNT are discussed. We further relate to a similar effect that is present in systems where high density of surface defects is formed due to high reactant concentration. The outlined strategies suggested by simulations are instrumental in guiding experimental efforts toward the generation of functionalized SWCNTs with tunable emission energies.Harnessing the power of graphics processing units (GPUs) to accelerate molecular dynamics (MD) simulations in the context of free-energy calculations has been a longstanding effort toward the development of versatile, high-performance MD engines. We report a new GPU-based implementation in NAMD of free-energy perturbation (FEP), one of the oldest, most popular importance-sampling approaches for the determination of free-energy differences that underlie alchemical transformations. Compared to the CPU implementation available since 2001 in NAMD, our benchmarks indicate that the new implementation of FEP in traditional GPU code is about four times faster, without any noticeable loss of accuracy, thereby paving the way toward more affordable free-energy calculations on large biological objects. Moreover, we have extended this new FEP implementation to a code path highly optimized for a single-GPU node, which proves to be up to nearly 30 times faster than the CPU implementation. Through optimized GPU performance, the present developments provide the community with a cost-effective solution for conducting FEP calculations. The new FEP-enabled code has been released with NAMD 3.0.An in-depth understanding of lithium (Li) diffusion barriers is a crucial factor for enabling Li-ion-based devices such as three-dimensional (3D) thin-film batteries and synaptic redox transistors integrated on silicon substrates. Diffusion of Li ions into silicon can damage the surrounding components, detach the device itself, lead to battery capacity loss, and cause an uncontrolled change of the transistor channel conductance. In this study, we analyze for the first time ultrathin 10 nm titanium nitride (TiN) films as a bifunctional Li-ion diffusion barrier and current collector. Thermal atomic layer deposition (ALD) and pulsed chemical vapor deposition (pCVD) are employed for manufacturing ultrathin films. The 10 nm ALD films demonstrate excellent blocking capability with an insertion of only 0.03 Li per TiN formula unit exceeding 200 galvanostatic cycles at 3 μA/cm2 between 0.05 and 3 V versus Li/Li+. An ultralow electrical resistivity of 115 μΩ cm is obtained. In contrast, a partial barrier breakdown is observed for 10 nm pCVD films. High surface quality with low contamination is identified as a key factor for the excellent performance of ALD TiN. Conformal deposition of 10 nm ALD TiN in 3D structures with high aspect ratios of up to 201 is demonstrated. The measured capacities of the surface area-enhanced samples are in good agreement with the expected values. High-temperature blocking capability is proven for a typical electrode crystallization step. Ultrathin ALD TiN is an ideal candidate for an electrically conducting Li-ion diffusion barrier for Si-integrated devices.Enantiopure aziridin-2-yl methanols 3-7 are used as highly effective sensors for enantiodiscrimination of α-racemic carboxylic acids containing tertiary or quaternary stereogenic centers. A linear correlation between theoretical and observed % ee values for CSA-3 and enantiomerically enriched samples of mandelic acid has been observed, indicating the possible application of these compounds in the ee determination. The free NH and OH groups in 3-7 ensure good recognition.Reducing the amount of organic aerosol (OA) is crucial to mitigation of particulate pollution in China. We present time and air-origin dependent variations of OA markers and source contributions at a regionally urban background site in South China. The continental air contained primary OA markers indicative of source categories, such as levoglucosan, fatty acids, and oleic acid. Secondary OA (SOA) markers derived from isoprene and monoterpenes also exhibited higher concentrations in continental air, due to more emissions of their precursors from terrestrial ecosystems and facilitation of anthropogenic sulfate for monoterpenes SOA. The marine air and continental-marine mixed air had more abundant hydroxyl dicarboxylic acids (OHDCA), with anthropogenic unsaturated organics as potential precursors. However, OHDCA formation in continental air was likely attributable to both biogenic and anthropogenic precursors. The production efficiency of OHDCA was highest in marine air, related to the presence of sulfur dioxide and/or organic precursors in ship emissions. Regional biomass burning (BB) was identified as the largest contributor of OA in continental air, with contributions fluctuating from 8% to 74%. In contrast, anthropogenic SOA accounted for the highest fraction of OA in marine (37 ± 4%) and mixed air (31 ± 3%), overriding the contributions from BB. This study demonstrates the utility of molecular markers for discerning OA pollution sources in the offshore marine atmosphere, where continental and marine air pollutants interact and atmospheric oxidative capacity may be enhanced.The optimization of materials is challenging as it often involves simultaneous manipulation of an assembly of condition parameters, which generates an enormous combinational space. Thus, optimization models and algorithms are widely adopted to accelerate material design and optimization. However, most optimization strategies can poorly handle multiple parameters simultaneously with limited prior knowledge. Herein, we describe a novel systematic optimization strategy, namely, machine-learning-assisted differential evolution, which combines machine learning and the evolutionary algorithm together, for zero-prior-data, rapid, and simultaneous optimization of multiple objectives. The strategy enables the evolutionary algorithm to "learn" so as to accelerate the optimization process, and also to identify quantitative interactions between the condition parameters and functional characteristics of the material. The performance of the strategy is verified by in silico simulations, as well as an application on simultaneously optimizing three characteristics, namely, water contact angle, oil absorption capacity, and mechanical strength, of an electrospun polystyrene/polyacrylonitrile (PS/PAN) material as a potential sorbent for a marine oil spill. With only 50 tests, the optimal fabrication parameters were successfully located from a combinatorial space of 50 000 possibilities. The presented platform technique offers a universal enabling technology to identify the optimal conditions rapidly from a daunting parameter space to synthesize materials with multiple desired functionalities.