Engineering topics
Li, Jing
Publications and source records attributed to Li, Jing.
Creating Frustrated Lewis Pairs in Defective Boron Carbon Nitride for Electrocatalytic Nitrogen Reduction to Ammonia
Abstract The electrocatalytic nitrogen reduction reaction (NRR) on metal‐free catalysts is an attractive alternative to the industrial Haber–Bosch process. However, the state‐of‐the‐art metal‐free electrocatalysts still suffer from low Faraday efficiencies and low ammonia yields. Herein, we present a molecular design strategy to develop a defective boron carbon nitride (BCN) catalyst with the abundant unsaturated B and N atoms as Lewis acid and base sites, which upgrades the catalyst from a single “Lewis acid catalysis” to “frustrated Lewis pairs (FLPs) catalysis.” 14 N 2 / 15 N 2 exchange experiments and density functional theory (DFT) calculations reveal that FLPs can adsorb an N 2 molecule to form a six‐membered ring intermediate, which enables the cleavage of N 2 via a pull–pull effect, thereby significantly reducing the energy barrier to −0.28 eV. Impressively, BCN achieves a high Faraday efficiency of 18.9 %, an ammonia yield of 20.9 μg h −1 mg −1 cat. , and long‐term durability.
Creating Frustrated Lewis Pairs in Defective Boron Carbon Nitride for Electrocatalytic Nitrogen Reduction to Ammonia
Abstract The electrocatalytic nitrogen reduction reaction (NRR) on metal‐free catalysts is an attractive alternative to the industrial Haber–Bosch process. However, the state‐of‐the‐art metal‐free electrocatalysts still suffer from low Faraday efficiencies and low ammonia yields. Herein, we present a molecular design strategy to develop a defective boron carbon nitride (BCN) catalyst with the abundant unsaturated B and N atoms as Lewis acid and base sites, which upgrades the catalyst from a single “Lewis acid catalysis” to “frustrated Lewis pairs (FLPs) catalysis.” 14 N 2 / 15 N 2 exchange experiments and density functional theory (DFT) calculations reveal that FLPs can adsorb an N 2 molecule to form a six‐membered ring intermediate, which enables the cleavage of N 2 via a pull–pull effect, thereby significantly reducing the energy barrier to −0.28 eV. Impressively, BCN achieves a high Faraday efficiency of 18.9 %, an ammonia yield of 20.9 μg h −1 mg −1 cat. , and long‐term durability.
Solution-processable copper(I) iodide-based inorganic-organic hybrid semiconductors composed of both coordinate and ionic bonds
Three new one-dimensional (1D) All-In-One (AIO) type CuI-based hybrid semiconductors with both dative and ionic bonds between the inorganic and organic components have been successfully designed and synthesized by using the ligands containing both cationic center and coordination available sites. Structural analysis confirms that all compounds share the same formula of Cu 4 I 6 (L) 2 (L = ligand) and are composed of 1D-Cu 4 I 6 2- anionic chains that coordinate to cationic ligands. Additionally, these materials demonstrate high stability towards heat and moisture and excellent solution processability due to their unique bonding nature. They emit low energy light ranging from green to orange color (530-590 nm). The origin and mechanism of their emissions were studied by both experimental and theoretical methods. More importantly, all compounds can be easily fabricated into films by solution process, a desired but rare feature for most of CuI-based hybrids built of extended networks.
Power Converter Circuit Design Automation using Parallel Monte Carlo Tree Search
The tidal waves of modern electronic/electrical devices have led to increasing demands for ubiquitous application-specific power converters. A conventional manual design procedure of such power converters is computation- and labor-intensive, which involves selecting and connecting component devices, tuning component-wise parameters and control schemes, and iteratively evaluating and optimizing the design. To automate and speed up this design process, we propose an automatic framework that designs custom power converters from design specifications using Monte Carlo Tree Search. Specifically, the framework embraces the upper-confidence-bound-tree (UCT), a variant of Monte Carlo Tree Search, to automate topology space exploration with circuit design specification-encoded reward signals. Moreover, our UCT-based approach can exploit small offline data via the specially designed default policy and can run in parallel to accelerate topology space exploration. Further, it utilizes a hybrid circuit evaluation strategy to substantially reduce design evaluation costs. Empirically, we demonstrated that our framework could generate energy-efficient circuit topologies for various target voltage conversion ratios. Compared to existing automatic topology optimization strategies, the proposed method is much more computationally efficient --- the sequential version can generate topologies with the same quality while being up to 67% faster. Here, the parallelization schemes can further achieve high speedups compared to the sequential version.
Discrimination of xylene isomers in a stacked coordination polymer
The separation and purification of xylene isomers is an industrially important but challenging process. Developing highly efficient adsorbents is crucial for the implementation of simulated moving bed technology for industrial separation of these isomers. Herein, we report a stacked one-dimensional coordination polymer {[Mn(dhbq)(H 2 O) 2 ], H 2 dhbq = 2,5-dihydroxy-1,4-benzoquinone} that exhibits an ideal molecular recognition and sieving of xylene isomers. Its distinct temperature-adsorbate–dependent adsorption behavior enables full separation of p -, m -, and o -xylene isomers in both vapor and liquid phases. The delicate stimuli-responsive swelling of the structure imparts this porous material with exceptionally high flexibility and stability, well-balanced adsorption capacity, high selectivity, and fast kinetics at conditions mimicking industrial settings. This study may offer an alternative approach for energy-efficient and adsorption-based industrial xylene separation and purification processes.
CO 2 Capture by Hybrid Ultramicroporous TIFSIX‐3‐Ni under Humid Conditions Using Non‐Equilibrium Cycling
Abstract Although pyrazine‐linked hybrid ultramicroporous materials (HUMs, pore size <7 Å) are benchmark physisorbents for trace carbon dioxide (CO 2 ) capture under dry conditions, their affinity for water (H 2 O) mitigates their carbon capture performance in humid conditions. Herein, we report on the co‐adsorption of H 2 O and CO 2 by TIFSIX‐3‐Ni—a high CO 2 affinity HUM—and find that slow H 2 O sorption kinetics can enable CO 2 uptake and release using shortened adsorption cycles with retention of ca. 90 % of dry CO 2 uptake. Insight into co‐adsorption is provided by in situ infrared spectroscopy and ab initio calculations. The binding sites and sorption mechanisms reveal that both CO 2 and H 2 O molecules occupy the same ultramicropore through favorable interactions between CO 2 and H 2 O at low water loading. An energetically favored water network displaces CO 2 molecules at higher loading. Our results offer bottom‐up design principles and insight into co‐adsorption of CO 2 and H 2 O that is likely to be relevant across the full spectrum of carbon capture sorbents to better understand and address the challenge posed by humidity to gas capture.
CO 2 Capture by Hybrid Ultramicroporous TIFSIX‐3‐Ni under Humid Conditions Using Non‐Equilibrium Cycling
Abstract Although pyrazine‐linked hybrid ultramicroporous materials (HUMs, pore size <7 Å) are benchmark physisorbents for trace carbon dioxide (CO 2 ) capture under dry conditions, their affinity for water (H 2 O) mitigates their carbon capture performance in humid conditions. Herein, we report on the co‐adsorption of H 2 O and CO 2 by TIFSIX‐3‐Ni—a high CO 2 affinity HUM—and find that slow H 2 O sorption kinetics can enable CO 2 uptake and release using shortened adsorption cycles with retention of ca. 90 % of dry CO 2 uptake. Insight into co‐adsorption is provided by in situ infrared spectroscopy and ab initio calculations. The binding sites and sorption mechanisms reveal that both CO 2 and H 2 O molecules occupy the same ultramicropore through favorable interactions between CO 2 and H 2 O at low water loading. An energetically favored water network displaces CO 2 molecules at higher loading. Our results offer bottom‐up design principles and insight into co‐adsorption of CO 2 and H 2 O that is likely to be relevant across the full spectrum of carbon capture sorbents to better understand and address the challenge posed by humidity to gas capture.
Boosted ammonium production by single cobalt atom catalysts with high Faradic efficiencies
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Turbine damper
A turbine damper may be provided that may include an elongated body sized to fit inside a turbine blade, the elongated body elongated along a radial direction of the turbine blade relative to a rotation axis of the turbine blade, and plural dampening masses coupled with the elongated body and disposed at different locations along the radial direction. The plural dampening masses may be one or more of sized to dampen different vibration modes of the turbine blade, or moveable relative to and along the elongated body in the radial direction.
Intrinsic ferroelectricity in Y-doped HfO 2 thin films
Ferroelectric HfO 2 -based materials hold great potential for the widespread integration of ferroelectricity into modern electronics due to their compatibility with existing Si technology. Earlier work indicated that a nanometre grain size was crucial for the stabilization of the ferroelectric phase. This constraint, associated with a high density of structural defects, obscures an insight into the intrinsic ferroelectricity of HfO 2 -based materials. Here we demonstrate that stable and enhanced polarization can be achieved in epitaxial HfO 2 films with a high degree of structural order (crystallinity). In this work, an out-of-plane polarization value of 50 μC cm –2 has been observed at room temperature in Y-doped HfO 2 (111) epitaxial thin films, with an estimated full value of intrinsic polarization of 64 μC cm –2 , which is in close agreement with density functional theory calculations. The crystal structure of films reveals the $Pca2_1$ orthorhombic phase with small rhombohedral distortion, underlining the role of the structural constraint in stabilizing the ferroelectric phase. Our results suggest that it could be possible to exploit the intrinsic ferroelectricity of HfO 2 -based materials, optimizing their performance in device applications.
Wind farm response to mesoscale-driven coastal low level jets: a multiscale large eddy simulation study
Realistic atmospheric turbulence–wind farm interactions during coastal low-level jet (LLJ) events are captured using high-fidelity, mesoscale-driven large eddy simulations (LES) to understand wind turbine loads, wakes and overall performance. The simulation has been carried out using the ExaWind aeroelastic solver, AMR-Wind. The simulations have been compared against a baseline unstable case matching the wind speed, wind direction and TI at hub-height location. Results indicate that the LLJ has negative impacts on the turbine hub and tower loads, and opens up potential avenues for design load mitigation strategies.
Structure of Offshore Low-Level Jet Turbulence and Implications to Mesoscale-to-Microscale Coupling
This paper explores realistic nonstationary atmospheric boundary layer (ABL) turbulence arising from nonstationarity at the mesoscale, particularly within offshore low-level jets with implications to offshore wind farms, using high-fidelity multiscale large-eddy simulations (LES). To this end, we analyzed the single-point turbulence statistical structure of a North-Atlantic offshore LLJ event simulated using high-resolution LES (AMR-Wind). The nonstationary LLJ is simulated using a mesoscale-to-microscale coupled (MMC) simulation procedure involving data assimilation of mesoscale velocity and temperature data from the Weather Research and Forecasting (WRF) model. Unlike the assimilation of mesoscale velocity data into the LES, the direct assimilation of temperature profiles had a strong impact on turbulence stratification, thereby causing erroneous predictions of turbulence both above and within the jet layer. Various approaches to mitigate this effect have resulted in multiple (four) variants of this MMC strategy. Outcomes from this work clearly show that the turbulence within the low-level jet is a strong function of the MMC approach as the turbulence structure within the low-level jet is dependent on the flux of residual turbulence from outside the jet, which in turn depends on the temperature forcing history. Additionally, the turbulence predicted by all these different methods (as well as the observation data) show similar deviations from equilibrium as evidenced by comparisons with idealized atmospheric turbulence structure obtained using the same numerical method. In general, we observe that the predicted LLJ turbulence tends to differ from canonical ABL turbulence with comparable shear. Particularly, the combination of shear and turbulence observed in such nonstationary low-level turbulence cannot be matched using equilibrium settings and therefore, represents a critical use-case for both testing and leveraging meso–micro coupling strategies.
Blade and airfoil damping configurations
The present embodiments set forth a blade including an airfoil, the airfoil including a tip cap, a pressure sidewall and a suction sidewall extending axially between corresponding leading and trailing edges and radially between the base and the tip cap. The blade, including the airfoil and base, being formed in at least two airfoil parts, each of the two airfoil parts including contacting edges engaging each other respective contacting edges, the contacting edges defining a joint for preloading each of the at least two parts with each other and with the base. The at least two airfoil parts forming the airfoil being retained to each other by an interference fit at the joint. The interference fit providing frictional damping of vibrations in the blade during blade operation.
A Water-Resistant Hydrogen-Bonded Organic Framework for Ethane/Ethylene Separation in Humid Environments
The separation of ethane (C 2 H 6 ) and ethylene (C 2 H 4 ) represents a crucial process for the production of polymer-grade C 2 H 4 , and adsorptive separation holds enormous promise for this industrially important but challenging task. Furthermore we report a new hydrogen-bonded organic frameworks (HIAM-102) with suitable channel and superhydrophobicity for preferential adsorption of C 2 H 6 over C 2 H 4 . HIAM-102 shows a C 2 H 6 /C 2 H 4 IAST selectivity of 1.9 and C 2 H 6 uptake of 48.25 cm 3 /g at 1 bar and 298 K. Benefitted from the hydrophobic pore surface, it can well-separate C 2 H 6 and C 2 H 4 under highly humid conditions as confirmed by experimental column breakthrough measurements. Computational calculations provide additional support for the experimental observations that the nonpolar channel of HIAM-102 interact favorably with C 2 H 6 over C 2 H 4 .
Effects of unique band structure of h -BN probed by photocurrent excitation spectroscopy
Here, by employing a photocurrent excitation spectroscopy measurement, a direct bandgap of ~6.46 eV has been resolved for the first time in thick B-10 enriched h-BN films. Together with previous band calculations, an unconventional energy diagram has been constructed to capture the unique features of h-BN: h-BN has a minimum direct bandgap of ~6.5 eV and a bandgap of ~6.1 eV which is indirect with the conduction band minimum (CBM) at M-point and valence band maximum (VBM) at K-point in the Brillouin zone, and the energy levels of the donor and acceptor impurities are measured relative to CBM and VBM, respectively.
Physics-informed Karhunen-Loeve and Neural Network Approximations for Solving Inverse Differential Equation Problems
Here we present the PI-CKL-NN method for parameter estimation in differential equation (DE) models given sparse measurements of the parameters and states. In the proposed approach, the space- or time-dependent parameters are approximated by Karhunen-Loeve (KL) expansions that are conditioned on the parameters’ measurements, and the states are approximated by deep neural networks (DNNs). The unknown weights in the KL expansions and DNNs are found my minimizing the cost function that enforces the measurements of the states the DE constraint. Regularization is achieved by adding the l2 norm of the conditional KL coefficients into the loss function. Our approach assumes that the parameter fields are correlated in space or time and enforces the statistical knowledge (the mean and the covariance function) in addition to the DE constraints and measurements as opposed to the physics-informed neural network (PINN) and other similar physics-informed machine learning methods where only DE constraints and data are used for parameter estimation. We use the PI-CKL-NN method for parameter estimation in an ordinary differential equation with an unknown time-dependent parameter and the one- and two-dimensional partial differential diffusion equations with unknown space-dependent diffusion coefficients. We also demonstrate that PI-CKL-NN is more accurate than the PINN method, especially when the observations of the parameters are very sparse
Decoding the Gate Opening Mechanism of the Flexible Framework RPM3–Zn upon Hydrocarbon Inclusion
Although the existence of a gate-opening phenomenon in the flexible RPM3–Zn is well known, the actual mechanism remains a mystery. Here, we provide a full picture that unambiguously identifies and explains the gate-opening mechanism in RPM3–Zn upon exposure to various hydrocarbons—acetylene, ethylene, ethane, propane, and butane—by combining insights gained from calorimetry, adsorption isotherms, PXRD, in situ infrared spectroscopy, and ab initio simulations. We find that the key to gate opening in this framework is the stretching of a bond between an O and the Zn metal center (COO–Zn), acting as a “stabilizer”, which weakens the necessary support required for the structure to remain intact. Consequently, an increasing concentration of guest molecules exerts sufficient internal pressure to induce strong structural transformations in the unit cell shape and volume, thus triggering the gate opening. Here, our results are critical to understanding the gate opening in several other flexible frameworks and provide an opportunity to fine- tune hydrocarbon separation.