Engineering topics
Wang, Di
Publications and source records attributed to Wang, Di.
O 2 dosage as a descriptor of TWC performance under lean/rich dithering in stoichiometric natural gas engines
The effects of oscillations in gas composition, known as lean/rich dithering, on the performance of a commercial Pd-based three-way catalyst (TWC) for stoichiometric natural gas (NG) engines were evaluated using synthetic exhaust flow reactor experiments. Under simulated NG exhaust conditions, NO conversion was intimately correlated to CH 4 conversion at slightly fuel-rich operating conditions. CH 4 conversion significantly varied with lambda (or O 2 concentration) and depended on the direction of the lambda change. The dynamic CH 4 conversion is likely related to the change of catalyst oxidation state and structures of Pd active sites. The CH 4 -NO cross-over point was found at a rich-biased lambda rather than stoichiometry. Compared to static operation, catalyst performance was much higher under a realistic dithering condition. The impacts of dithering parameters including amplitude and frequency on CH 4 and NO conversions were explored. O 2 dosage is proposed as an effective descriptor of the TWC dithering performance. In the O 2 -dosage space, the performance of distinct dithering parameters collapse, helping to elucidate the fundamental influence of dithering parameters on TWC performance. With the help of O2 dosage, an optimal operating window leading to high CH 4 and NO conversions was identified. A higher dithering amplitude is required to keep the catalyst in a reduced state for higher CH 4 and NO conversions, while an appropriate O 2 dosage that does not exceed the breakthrough OSC is necessary to avoid excess O 2 that results in NO slip. The dithering amplitude and O 2 -dosage-metric maps provide a new method for studying dynamic TWC performance and identifying optimum operation strategies.
Covalent surface modifications and superconductivity of two-dimensional metal carbide MXenes
Versatile chemical transformations of surface functional groups in two-dimensional transition-metal carbides (MXenes) open up a previously unexplored design space for this broad class of functional materials. We introduce a general strategy to install and remove surface groups by performing substitution and elimination reactions in molten inorganic salts. Successful synthesis of MXenes with oxygen, imido, sulfur, chlorine, selenium, bromine, and tellurium surface terminations, as well as bare MXenes (no surface termination), was demonstrated. These MXenes show distinctive structural and electronic properties. For example, the surface groups control interatomic distances in the MXene lattice, and Ti n +1 C n ( n = 1, 2) MXenes terminated with telluride (Te 2− ) ligands show a giant (>18%) in-plane lattice expansion compared with the unstrained titanium carbide lattice. The surface groups also control superconductivity of niobium carbide MXenes.
A Chip-Scale Oscillation-Mode Optomechanical Inertial Sensor Near the Thermodynamical Limits
Modern navigation systems integrate the global positioning system (GPS) with an inertial navigation system (INS), which complement each other for correct attitude and velocity determination. Here, the core of the INS integrates accelerometers and gyroscopes used to measure forces and angular rate in the vehicular inertial reference frame. With the help of gyroscopes and by integrating the acceleration to compute velocity and distance, precision and compact accelerometers with sufficient accuracy can provide small–error location determination. Solid–state implementations, through coherent readout, can provide a platform for high performance acceleration detection. In contrast to prior accelerometers using piezoelectric or capacitive readout techniques, optical readout provides narrow–linewidth high–sensitivity laser detection along with low–noise resonant optomechanical transduction near the thermodynamical limits. Here an optomechanical inertial sensor with an 8.2 µg Hz –1/2 velocity random walk (VRW) at an acquisition rate of 100 Hz and 50.9 µg bias instability is demonstrated, suitable for applications, such as, inertial navigation, inclination sensing, platform stabilization, and/or wearable device motion detection. Driven into optomechanical sustained–oscillation, the slot photonic crystal cavity provides radio–frequency readout of the optically–driven transduction with an enhanced 625 µg Hz –1 sensitivity. Measuring the optomechanically–stiffened oscillation shift, instead of the optical transmission shift, provides a 220× VRW enhancement over pre–oscillation mode detection.
X Fe 4 Ge 2 ( X = Y , Lu ) and Mn 3 Pt : Filling-enforced magnetic topological metals
Magnetism, coupled with nontrivial band topology, can bring about many interesting and exotic phenomena, so that magnetic topological materials have attracted persistent research interest. However, compared with nonmagnetic topological materials (TMs), the magnetic TMs are less studied, since their magnetic structures and topological phase transitions are usually complex and the first-principles predictions are usually sensitive on the effect of Coulomb interaction. Here we present a comprehensive investigation of XFe 4 Ge 2 (X = Y, Lu) and Mn 3 Pt, and find these materials to be filling-enforced magnetic topological metals. Our first-principles calculations show that XFe 4 Ge 2 (X = Y, Lu) host Dirac points near the Fermi level at high symmetry point S. These Dirac points are protected by $\text{P}\mathcal{T}$ symmetry ($\text{P}$ and $\mathcal{T}$ are inversion and time-reversal transformations, respectively) and a twofold screw rotation symmetry. Moreover, through breaking $\text{P}\mathcal{T}$ symmetry, the Dirac points would split into Weyl nodes. Mn 3 Pt is found to host fourfold degenerate band crossings in the whole high symmetry path of A – Z . We also utilize the GGA + U scheme to take into account the effect of Coulomb repulsion and find that the filling-enforced topological properties are naturally insensitive on U .
Enhanced Selective Oxidation of Ammonia in a Pt/Al 2 O 3 @Cu/ZSM-5 Core–Shell Catalyst
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Two-dimensional topological materials discovery by symmetry-indicator method
Two-dimensional (2D) topological materials (TMs) have attracted tremendous attention due to the promise of revolutionary devices with nondissipative electric or spin currents. Unfortunately, the scarcity of 2D TMs holds back the experimental realization of such devices. In this work, based on our recently developed, highly efficient TM discovery algorithm using symmetry indicators, we explore the possible 2D TMs in all nonmagnetic compounds in four recently proposed materials databases for possible 2D materials. We identify hundreds of 2D TM candidates, including 205 topological (crystalline) insulators and 299 topological semimetals. In particular, we highlight MoS, with a mirror Chern number of –4, as a possible experimental platform for studying the interaction-induced modification to the topological classification of materials. Here, our results winnow out the topologically interesting 2D materials from these databases and provide a TM gene pool for further experimental studies.
Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications
With the rapid adoption of machine learning techniques for large-scale applications in science and engineering comes the convergence of two grand challenges in visualization. First, the utilization of black box models (e.g., deep neural networks) calls for advanced techniques in exploring and interpreting model behaviors. Second, the rapid growth in computing has produced enormous datasets that require techniques that can handle millions or more samples. Although some solutions to these interpretability challenges have been proposed, they typically do not scale beyond thousands of samples, nor do they provide the high-level intuition scientists are looking for. Here, we present the first scalable solution to explore and analyze high-dimensional functions often encountered in the scientific data analysis pipeline. By combining a new streaming neighborhood graph construction, the corresponding topology computation, and a novel data aggregation scheme, namely topology aware datacubes, we enable interactive exploration of both the topological and the geometric aspect of high-dimensional data. Following two use cases from high-energy-density (HED) physics and computational biology, we demonstrate how these capabilities have led to crucial new insights in both applications.
Effect of a Zinc Interlayer on a Cu/Al Lap Joint in Ultrasound-Assisted Friction Stir Welding
This study proposes a welding process, ultrasound-assisted friction stir welding of dissimilar Al/Cu metals. Zinc foil is melted using the heat generated by a pinless stirring tool, and the molten intermediate layer is stirred by ultrasonic cavitation to achieve an effective connection. The metallurgical reaction behavior of the joint under the action of the sound field was studied, and the effects of different microstructures on the joint performance were analyzed. Specifically, the following observations were reported in this study: (1) When ultrasound assistance was used, the cavitation effect changed the brittle intermetallic compounds of Al{sub 2}Cu from a continuous distribution to a block distribution, and the mechanical properties of the joint were greatly improved; (2) the effects of the thickness of the zinc were also determined. The results showed that the highest shear tensile force was obtained when the thickness of the zinc foil was 0.2 mm. When the thickness was 0.3 mm, the ultrasound effect was weakened. The copper-side interface generated a zigzag-shaped Al{sub 4.2}Cu{sub 3.2}Zn{sub 0.7} layer with a thickness of 3.4 μm and had a continuous distribution. Increasing the thickness of the zinc to 0.5 mm, however, drastically decreased the mechanical properties of the joint due to incomplete melting of the zinc layer.
Nickel@Siloxene catalytic nanosheets for high-performance CO 2 methanation
Two-dimensional (2D) materials are of considerable interest for catalyzing the heterogeneous conversion of CO 2 to synthetic fuels. In this regard, 2D siloxene nanosheets, have escaped thorough exploration, despite being composed of earth-abundant elements. Herein we demonstrate the remarkable catalytic activity, selectivity, and stability of a nickel@siloxene nanocomposite; it is found that this promising catalytic performance is highly sensitive to the location of the nickel component, being on either the interior or the exterior of adjacent siloxene nanosheets. Control over the location of nickel is achieved by employing the terminal groups of siloxene and varying the solvent used during its nucleation and growth, which ultimately determines the distinct reaction intermediates and pathways for the catalytic CO 2 methanation. Significantly, a CO 2 methanation rate of 100 mmol gNi –1 h –1 is achieved with over 90% selectivity when nickel resides specifically between the sheets of siloxene.