Investigating extreme ultraviolet radiation chemistry with first-principles quantum chemistry calculations
Not Available
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Engineering topics
Wang, Han
Publications and source records attributed to Wang, Han.
Organizing principles for vegetation dynamics
Understanding vegetation dynamics is very challenging because of the multitude of contributing processes at 64widely different spatial and temporal scales. In this Perspective we propose that understanding of vegetation dynamics can be improved, permitting better predictions, based on organizing principles that constrain plant and ecosystem be haviour: natural selection, self-organization, and entropy maximization. Although these ideas are increasingly used,a limited common understanding of their theoretical basis has prevented their full potential to be realized. We explain the power of natural selection-based optimality to predict photosynthesis and carbon allocation responses to multiple environmental drivers, and how individual plasticity leads to the predictable self-organization of forest canopies. We show how models of natural selection acting on a few key traits can generate realistic plant communities, and how entropy maximization can distinguish between stochastic and deterministic drivers of vegetation patterns. In combination with empirical exploration of patterns in plant functional variation, these principles can accelerate the development of dynamic vegetation models as well as trait-based ecology resting on strengthened theoretical and empirical foundations.
Geosciences↗
Raman spectrum and polarizability of liquid water from deep neural networks
We introduce a scheme based on machine learning and deep neural networks to model the environmental dependence of the electronic polarizability in insulating materials. Application to liquid water shows that training the network with a relatively small number of molecular configurations is sufficient to predict the polarizability of arbitrary liquid configurations in close agreement with ab initio density functional theory calculations. In combination with a neural network representation of the interatomic potential energy surface, the scheme allows us to calculate the Raman spectra along 2-nanosecond classical trajectories at different temperatures for H 2 O and D 2 O. The vast gains in efficiency provided by the machine learning approach enable longer trajectories and larger system sizes relative to ab initio methods, reducing the statistical error and improving the resolution of the low-frequency Raman spectra. Decomposing the spectra into intramolecular and intermolecular contributions elucidates the mechanisms behind the temperature dependence of the low-frequency and stretch modes.
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Room-Temperature Ferroelectric LiNb 6 Ba 5 Ti 4 O 30 Spinel Phase in a Nanocomposite Thin Film Form for Nonlinear Photonics
Tetragonal tungsten bronze (TTB) materials are one of the most promising classes of materials for ferroelectric and nonlinear optical devices, owing to their very unique noncentrosymmetric crystal structure. In this work, a new TTB phase of LiNb 6 Ba 5 Ti 4 O 30 (LNBTO) has been discovered and studied. A small amount of a secondary phase, LiTiO 2 (LTO), has been incorporated as nanopillars that are vertically embedded in the LNBTO matrix. The new multifunctional nanocomposite thin film presents exotic highly anisotropic microstructure and properties, e.g., strong ferroelectricity, high optical transparency, anisotropic dielectric function, and strong optical nonlinearity evidenced by the second harmonic generation results. An optical waveguide structure based on the stacks of α-Si on SiO 2 /LNBTO–LTO has been fabricated, exhibiting low optical dispersion with an optimized evanescent field staying in the LNBTO–LTO active layer. Lastly, this work highlights the combination of new TTB material designs and vertically aligned nanocomposite structures for further enhanced anisotropic and nonlinear properties.
36 MATERIALS SCIENCE↗
P-model v1.0: an optimality-based light use efficiency model for simulating ecosystem gross primary production
Terrestrial photosynthesis is the basis for vegetation growth and drives the land carbon cycle. Accurately simulating gross primary production (GPP, ecosystem-level apparent photosynthesis) is key for satellite monitoring and Earth system model predictions under climate change. While robust models exist for describing leaf-level photosynthesis, predictions diverge due to uncertain photosynthetic traits and parameters which vary on multiple spatial and temporal scales. Here, we describe and evaluate a GPP (photosynthesis per unit ground area) model, the P-model, that combines the Farquhar–von Caemmerer–Berry model for C 3 photosynthesis with an optimality principle for the carbon assimilation–transpiration trade-off, and predicts a multi-day average light use efficiency (LUE) for any climate and C 3 vegetation type. The model builds on the theory developed in Prentice et al. (2014) and Wang et al. (2017a) and is extended to include low temperature effects on the intrinsic quantum yield and an empirical soil moisture stress factor. The model is forced with site-level data of the fraction of absorbed photosynthetically active radiation (fAPAR) and meteorological data and is evaluated against GPP estimates from a globally distributed network of ecosystem flux measurements. Although the P-model requires relatively few inputs, the R 2 for predicted versus observed GPP based on the full model setup is 0.75 (8 d mean, 126 sites) – similar to comparable satellite-data-driven GPP models but without predefined vegetation-type-specific parameters. The R 2 is reduced to 0.70 when not accounting for the reduction in quantum yield at low temperatures and effects of low soil moisture on LUE. The R 2 for the P-model-predicted LUE is 0.32 (means by site) and 0.48 (means by vegetation type). Applying this model for global-scale simulations yields a total global GPP of 106–122 Pg C yr –1 (mean of 2001–2011), depending on the fAPAR forcing data. The P-model provides a simple but powerful method for predicting – rather than prescribing – light use efficiency and simulating terrestrial photosynthesis across a wide range of conditions. The model is available as an R package (rpmodel).
54 ENVIRONMENTAL SCIENCES↗
Electronic colloidal nanocrystal devices
Colloidal nanocrystal electronic devices including multiple types of nanocrystal device elements including nanocrystal metallic electrodes, nanocrystal insulators, and nanocrystal insulators. Colloidal nanocrystal electronic devices may be produced by forming multiple nanocrystal electronic device elements on a substrate.
36 MATERIALS SCIENCE↗
Emergence of Nontrivial Low-Energy Dirac Fermions in Antiferromagnetic EuCd 2 As 2
Not provided.
Chemistry↗
Acclimation of leaf respiration consistent with optimal photosynthetic capacity
Abstract Plant respiration is an important contributor to the proposed positive global carbon‐cycle feedback to climate change. However, as a major component, leaf mitochondrial (‘dark’) respiration ( R d ) differs among species adapted to contrasting environments and is known to acclimate to sustained changes in temperature. No accepted theory explains these phenomena or predicts its magnitude. Here we propose that the acclimation of R d follows an optimal behaviour related to the need to maintain long‐term average photosynthetic capacity ( V cmax ) so that available environmental resources can be most efficiently used for photosynthesis. To test this hypothesis, we extend photosynthetic co‐ordination theory to predict the acclimation of R d to growth temperature via a link to V cmax , and compare predictions to a global set of measurements from 112 sites spanning all terrestrial biomes. This extended co‐ordination theory predicts that field‐measured R d and V cmax accessed at growth temperature ( R d,tg and V cmax,tg ) should increase by 3.7% and 5.5% per degree increase in growth temperature. These acclimated responses to growth temperature are less steep than the corresponding instantaneous responses, which increase 8.1% and 9.9% per degree of measurement temperature for R d and V cmax respectively. Data‐fitted responses proof indistinguishable from the values predicted by our theory, and smaller than the instantaneous responses. Theory and data are also shown to agree that the basal rates of both R d and V cmax assessed at 25°C ( R d,25 and V cmax,25 ) decline by ~4.4% per degree increase in growth temperature. These results provide a parsimonious general theory for R d acclimation to temperature that is simpler—and potentially more reliable—than the plant functional type‐based leaf respiration schemes currently employed in most ecosystem and land‐surface models.
Wang, Han↗
Fluidic Flow Assisted Deterministic Folding of Van der Waals Materials
Origami offers a distinct approach for designing and engineering new material structures and properties. The folding and stacking of atomically thin van der Waals (vdW) materials, for example, can lead to intriguing new physical properties including bandgap tuning, Van Hove singularity, and superconductivity. On the other hand, achieving well-controlled folding of vdW materials with high spatial precision has been extremely challenging and difficult to scale toward large areas. In this paper, a deterministic technique is reported to fold vdW materials at a defined position and direction using microfluidic forces. Electron beam lithography (EBL) is utilized to define the folding area, which allows precise control of the folding geometry, direction, and position beyond 100 nm resolution. Using this technique, single-atomic-layer vdW materials or their heterostructures can be folded without the need for any external supporting layers in the final folded structure. In addition, arrays of patterns can be folded across a large area using this technique and electronic devices that can reconfigure device functionalities through folding are also demonstrated. Such scalable formation of folded vdW material structures with high precision can lead to the creation of new atomic-scale materials and superlattices as well as opening the door to realizing foldable and reconfigurable electronics.
2D materials↗
Tellurene Photodetector with High Gain and Wide Bandwidth
Two-dimensional (2D) semiconductors have been extensively explored as a new class of materials with great potential. In particular, black phosphorus (BP) has been considered to be a strong candidate for applications such as high-performance infrared photodetectors. However, the scalability of BP thin film is still a challenge, and its poor stability in the air has hampered the progress of the commercialization of BP devices. Herein, we report the use of hydrothermal-synthesized and air-stable 2D tellurene nanoflakes for broadband and ultrasensitive photodetection. The tellurene nanoflakes show high hole mobilities up to 458 cm 2 /V·s at ambient conditions, and the tellurene photodetector presents peak extrinsic responsivity of 383 A/W, 19.2 mA/W, and 18.9 mA/W at 520 nm, 1.55 μm, and 3.39 μm light wavelength, respectively. Because of the photogating effect, high gains up to 1.9 × 10 3 and 3.15 × 10 4 are obtained at 520 nm and 3.39 μm wavelength, respectively. At the communication wavelength of 1.55 μm, the tellurene photodetector exhibits an exceptionally high anisotropic behavior, and a large bandwidth of 37 MHz is obtained. The photodetection performance at different wavelength is further supported by the corresponding quantum molecular dynamics (QMD) simulations. Our approach has demonstrated the air-stable tellurene photodetectors that fully cover the short-wave infrared band with ultrafast photoresponse.
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