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Chen, Yu

Publications and source records attributed to Chen, Yu.

At least 55 records · Page 3

Surface Regulating of a Double–Perovskite Electrode for Protonic Ceramic Fuel Cells to Enhance Oxygen Reduction Activity and Contaminants Poisoning Tolerance

Protonic ceramic fuel cells (PCFCs) are one of the most efficient energy conversion devices. However, the performance of current PCFCs is greatly limited by the sluggish oxygen reduction reaction (ORR) kinetics and the fast degradation of cathode due to contaminants poisoning (such as Cr species and steam). In this work, we report a surface regulating of a double perovskite PrBa 0.5 Sr 0.5 Co 1.5 Fe 0.5 O 5+δ (PBSCF) cathode by a Pr 0.9 Fe 0.7 Co 0.3 O 3 (PFC) catalyst coating to enhance the ORR activity and stability. When tested in direct contact with Cr in the air with 3% H 2 O at 650 °C, the polarization resistance (Rp) of the PFC-PBSCF electrode increases from $\approx$0.39 to 0.45 Ω cm 2 after 100 h operation; in contrast, the R p of a PBSCF electrode increases from 0.63 to 0.82 Ω cm 2 . Further, a PCFC with the PFC-PBSCF cathode demonstrates an excellent peak power density ($\approx$1.08 W cm -2 at 650 °C) and significantly enhanced durability (degradation rate of 0.03 % h -1 ), much better than those of the cells with a PBSCF cathode ($\approx$0.75 W cm -2 and degradation rate of 0.12 % h -1 ). Raman spectroscopy and density functional theory calculations indicate that the PFC catalyst coating diminishes the formation of Cr species, such as (Ba 1-x Sr x )CrO 4 , on the cathode surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Surface restructuring of a perovskite-type air electrode for reversible protonic ceramic electrochemical cells

Reversible protonic ceramic electrochemical cells (R-PCECs) are ideally suited for efficient energy storage and conversion; however, one of the limiting factors to high performance is the poor stability and insufficient electrocatalytic activity for oxygen reduction and evolution of the air electrode exposed to the high concentration of steam. Here we report our findings in enhancing the electrochemical activity and durability of a perovskite-type air electrode, Ba 0.9 Co 0.7 Fe 0.2 Nb 0.1 O 3-δ (BCFN), via a water-promoted surface restructuring process. Under properly-controlled operating conditions, the BCFN electrode is naturally restructured to an Nb-rich BCFN electrode covered with Nb-deficient BCFN nanoparticles. When used as the air electrode for a fuel-electrode-supported R-PCEC, good performances are demonstrated at 650 °C, achieving a peak power density of 1.70 W cm –2 in the fuel cell mode and a current density of 2.8 A cm –2 at 1.3 V in the electrolysis mode while maintaining reasonable Faradaic efficiencies and promising durability.

30 DIRECT ENERGY CONVERSION↗

Thermodynamically Driven Synthetic Optimization for Cation-Disordered Rock Salt Cathodes

Relating the synthesis conditions of materials to their functional performance has long been an experience-based trial-and-error process. However, this methodology is not always efficient in identifying an appropriate protocol and can lead to overlooked opportunities for the performance optimization of materials through simple modifications of the synthesis process. In this work, we systematically track the structural evolution in the synthesis of a representative disordered rocksalt (a promising next-generation Li-ion cathode material) at the scale of both the long-range crystal structure and the short-range atomic structure using various in situ and ex situ techniques, including transmission electron microscopy, X-ray diffraction, and pair distribution function analysis. Further, an optimization strategy is proposed for the synthesis protocol, leading to a remarkably enhanced capacity (specific energy) of 313 mAh g –1 (987 Wh kg –1 ) at a low rate (20 mA g –1 ), with a capacity of more than 140 mAh g –1 retained even at a very high cycling rate of 2,000 mA g –1 . This strategy is further rationalized using ab initio calculations, and important opportunities for synthetic optimization demonstrated in this study are highlighted.

36 MATERIALS SCIENCE↗

The P132H mutation in the main protease of Omicron SARS-CoV-2 decreases thermal stability without compromising catalysis or small-molecule drug inhibition

The ongoing SARS-CoV-2 pandemic continues to be a significant threat to global health. First reported in November 2021, the Omicron variant (B.1.1.529) is more transmissible and can evade immunity better than previous SARS-CoV-2 variants, fueling an unprecedented surge in cases. To produce functional proteins from its polyprotein, SARS-CoV-2 relies on the cysteine proteases Nsp3/papain-like protease (PL pro ) and Nsp5/main protease (M pro )/3C-like protease to cleave at three and more than 11 sites, respectively. Therefore, M pro and PL pro inhibitors are considered to be one of the most promising SARS-CoV-2 antivirals. On December 22, 2021, the Food and Drug Administration (FDA) issued an Emergency Use Authorization (EUA) for PAXLOVID, a ritonavir-boosted formulation of nirmatrelvir. Nirmatrelvir is a first-in-class orally bioavailable SARS-CoV-2 M pro inhibitor. Thus, the scientific community must vigilantly monitor potential mechanisms of drug resistance, especially because SARS-CoV-2 is naïve to M pro inhibitors. Mutations have been well identified in variants to this point. Notably, Omicron M pro (OM pro ) harbors a single mutation—P132H. Here, we characterized the enzymatic activity, drug inhibition, and structure of OM pro while evaluating the past and future implications of M pro mutations.

59 BASIC BIOLOGICAL SCIENCES↗

Highly Active and Durable Air Electrodes for Reversible Protonic Ceramic Electrochemical Cells Enabled by an Efficient Bifunctional Catalyst

The commercialization of reversible protonic ceramic electrochemical cells is hindered by the lack of highly active and durable air electrodes exposed to high concentration of steam under operating conditions. We report findings that dramatically enhance the electrocatalytic activity and stability of a conventional (La 0.6 Sr 0.4 ) 0.95 Co 0.2 Fe 0.8 O 3-δ (LSCF) air electrode by a multiphase catalyst coating composed of a conformal Pr 1-x Ba x CoO 3-δ thin film and exsolved BaCoO 3-δ nanoparticles, are reported. At 600 °C, the catalyst coating decreases the polarization resistance of the LSCF air electrode by a factor of 25 (from 1.09 to 0.043 Ω cm 2 ) in air and the degradation rate by two orders of magnitude (from 1.0 × 10 -2 to 1.8 × 10 -4 Ω cm2 h -1 in humidified air with 30 vol% H2O). Further, a single cell with the catalyst-coated LSCF air electrode at 600 °C demonstrates a high peak power density of 1.04 W cm -2 in the fuel cell mode and a high current density of 1.82 A cm -2 at 1.3 V in the electrolysis mode. The significantly enhanced performance of the LSCF air electrode is attributed mainly to the high rate of surface oxygen exchange, fast surface proton diffusion, and the rapid H 2 O and O 2 dissociation on the catalysts.

36 MATERIALS SCIENCE↗

A high-performance and durable direct NH 3 tubular protonic ceramic fuel cell integrated with an internal catalyst layer

Nickel-based cermet anode-supported protonic ceramic fuel cells (PCFCs) show great potential for direct utilization of ammonia. However, the insufficient activity of anode and the deterioration of anode activity/durability caused by the undesired interaction between nickel and ammonia greatly limit the application. Here, we report tubular PCFCs embedded with a catalytic iron layer. Such cells show peak power densities of 1.507 W cm -2 and 1.078 W cm -2 at 700 °C when using H 2 and NH 3 as fuel, respectively, which are the highest tubular PCFC performance so far ever reported. In addition, the stability of cells with the catalyst layer has been dramatically enhanced when compared with that of cells without the catalyst layer. As a result, the enhancement of activity and durability is attributed to the catalytic activity of iron for ammonia decomposition, through which the direct contact between nickel and ammonia has been minimized and the anode structure has therefore been protected.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Using Direct Numerical Simulation of Pore-Level Events to Improve Pore-Network Models for Prediction of Residual Trapping of CO2

Direct numerical simulation and pore-network modeling are common approaches to study the physics of two-phase flow through natural rocks. For assessment of the long-term performance of geological sequestration of CO 2 , it is important to model the full drainage-imbibition cycle to provide an accurate estimate of the trapped CO 2 . While direct numerical simulation using pore geometry from micro-CT rock images accurately models two-phase flow physics, it is computationally prohibitive for large rock volumes. On the other hand, pore-network modeling on networks extracted from micro-CT rock images is computationally efficient but utilizes simplified physics in idealized geometric pore elements. This study uses the lattice-Boltzmann method for direct numerical simulation of CO 2 -brine flow in idealized pore elements to develop a new set of pore-level flow models for the pore-body filling and snap-off events in pore-network modeling of imbibition. Lattice-Boltzmann simulations are conducted on typical idealized pore-network configurations, and the interface evolution and local capillary pressure are evaluated to develop modified equations of local threshold capillary pressure of pore elements as a function of shape factor and other geometrical parameters. The modified equations are then incorporated into a quasi-static pore-network flow solver. The modified model is applied on extracted pore-network of sandstone samples, and saturation of residual trapped CO 2 is computed for a drainage-imbibition cycle. The modified model yields different statistics of pore-level events compared with the original model; in particular, the occurrence of snap-off in pore-throats is reduced resulting in a more frontal displacement pattern along the main injection direction. Compared to the original model, the modified model is in closer agreement with the residual trapped CO 2 obtained from core flow experiments and direct numerical simulation.

Kohanpur, Amir H.↗

Surface enhanced performance of La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3-δ cathodes by infiltration Pr-Ni-Mn-O progress

Herein the present study reports the enhancement of electrochemical oxygen reduction activity of porous La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3–δ (LSCF) cathodes by coating a thin film of Pr-Ni-Mn oxide (PNM5) using a multi-step infiltration process. XRD examination reveals that PNM5 mainly contains a multiphase mixture of Pr 6 O 11 , PrNiO 3 , MnO and NiO. SEM morphology shows a thin PNM5 film and small particles are formed on the surface of LSCF backbone particles. Impedance spectrum analysis indicates that PNM5 infiltrated LSCF exhibits dramatically reduced polarization resistance (R p ), reaching R p of 0.244 Ω cm 2 at 973 K, which is one-half of the baseline LSCF cathode. The activation energy of LSCF cathodes infiltrated with PNM5 is 1.45 eV, slightly lower than the baseline LSCF cathode (1.77 eV). Distribution of relaxation time (DRT) function analysis shows PNM5 infiltration layer significantly promotes the oxygen reduction reaction (ORR) of cathode surface. With the increase in firing temperature, the total resistance increases and R p changes from ion transport to oxygen reduction reaction. Degradation rate of the PNM5-infiltrated LSCF is also lower, 0.02168% vs 0.07093% for the baseline LSCF over a 200-h period. A single cell testing indicated that the peak power density of the PNM5-infiltrated cell was increased by 140.66%. Overall, PNM5 could be a potential catalyst for boosting the performance of a commercial LSCF cathode for solid oxide fuel cells (SOFC).

36 MATERIALS SCIENCE↗

Solid-State Calcium-Ion Diffusion in Ca 1.5 Ba 0.5 Si 5 O 3 N 6

Rechargeable batteries based on multivalent working ions are promising candidates for next-generation high-energy-density batteries. Development of these technologies, however, is largely limited by the low diffusion rate of multivalent ions in solid-state materials, thereby necessitating a better understanding of the design principles that control multivalent-ion mobility. We report Ca 1.5 Ba 0.5 Si 5 O 3 N 6 as a potential calcium solid-state conductor and investigate its Ca migration mechanism by means of ab initio computations and neutron diffraction. This compound contains partially occupied Ca sites in close proximity to each other, providing a unique mechanism for Ca migration. Nuclear density maps obtained with the maximum entropy method from neutron powder diffraction data provide strong evidence for low-energy percolating one-dimensional pathways for Ca-ion migration. Ab initio molecular dynamics simulations further support a low Ca-ion migration barrier of ~400 meV when Ca vacancies are present and reveal a unique "vacancy-adjacent"concerted ion migration mechanism. This work provides a new understanding of solid-state Ca-ion diffusion and insights into the future design of novel cation configurations that utilize the interactions between mobile ions to enable fast multivalent-ion conduction in solid-state materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An efficient and durable anode for ammonia protonic ceramic fuel cells

Ammonia protonic ceramic fuel cells (PCFCs) have the potential to be a highly efficient power source with high energy density. However, the inadequate catalytic activity of the existing anodes for utilization of ammonia greatly limits the performance of PCFCs. In this study, we report an Fe-modified state-of-the-art Ni cermet anode with greatly enhanced activity and durability toward utilization of ammonia. Cells with an Fe-decorated Ni-BaZr 0.1 Ce 0.7 Y 0.1 Yb 0.1 O 3 (Ni–BZCYYb) anode demonstrate an excellent performance, achieving peak power densities of 0.360, 0.723, 1.257, and 1.609 W cm –2 at 550, 600, 650, and 700 °C, respectively, which reveal the highest performance of solid oxide fuel cells fueled on ammonia. In addition, the cells show an excellent durability when operated at a constant current density of 0.5 A cm –2 (or a power density of ~0.435 W cm –2 ) at 650 °C. The superior activity and durability of the Fe-modified Ni/BZCYYb anode are attributed to the alternation of NH 3 adsorption strength and N 2 desorption barrier heights, as confirmed by first-principles based mechanistic and microkinetic modeling. Our research provides a valuable guidance for the development of efficient electro-catalysts for ammonia PCFCs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

3D printing of calcined clay-limestone-based cementitious materials

This paper aims to investigate the influences of high Portland cement substitutions (>60 wt%) by low-grade calcined clay (CC) and limestone (LF) on 3D concrete printability, stiffness evolution and early-age hydration. Results show that, with the same dosage of admixtures (superplasticizer and viscosity modifier), increasing LF and CC content reduced the slump, flowability and initial material flow rate, and significantly improved the buildability of fresh mixtures, which can be attributed to the reduced water film thickness (WFT). Furthermore, the stiffness evolution and SSA{sub total} development up to the first 3 h were accelerated by increasing CC content, which can also be linked to the change of WFT, and consumption of superplasticizer for the dispersion induced by hydration products. Additionally, the dilution effect on compressive strength and hydration caused by the high cement replacement was observed.

36 MATERIALS SCIENCE↗

Experimental investigation of the short-term creep recovery of hardened cement paste at micrometre length scale

This paper presents an experimental investigation on the short-term creep recovery of cement paste at micrometre length scale. Micro-cantilever beams were fabricated and tested with 8 different loading series using the nanoindenter. It is found that cement pastes show high recovery ratios (>80%) even subjected to very high stress levels. Relatively lower recovery ratios and non-linear creep were also observed for w/c 0.4 samples under high stress levels. A good agreement is found between the results predicted using the linear superposition principle and the experimental results except for the measured non-linear creep in w/c 0.4 samples. It is suggested that the short-term creep recovery may be associated with the microscale stress redistribution or the reversible internal water movement. The observed non-linear creep under the highest stress level may be due to the higher density of microcracks generated during the loading stage, which may further promote the water transfer.

36 MATERIALS SCIENCE↗

Realizing continuous cation order-to-disorder tuning in a class of high-energy spinel-type Li-ion cathodes

Conventional Li-ion cathode materials are dominated by well-ordered structures, in which Li and transition metals occupy distinct crystallographic sites. Here, we show in this paper that profoundly new degrees of freedom for the optimization of electrochemical properties may be accessed if controllable cation disorder is introduced. In a class of high-capacity spinel-type cathode materials, we identify cation to anion ratio in synthesis as a key parameter for tuning the structure continuously from a well-ordered spinel, through a partially ordered spinel, to rocksalt. We find that the varying degree of cation disorder modifies the voltage profile, rate capability, and charge-compensation mechanism in a rational and predictable way. Our results indicate that spinel-type order is most beneficial for achieving high-rate performance as long as the cooperative 8a to 16c phase transition is suppressed, while more rocksalt-like disorder facilitates O redox, which can increase capacity. Our findings reveal an important tuning handle for achieving high energy and power in the vast space of partially ordered cathode materials.

25 ENERGY STORAGE↗

A physics-informed and hierarchically regularized data-driven model for predicting fluid flow through porous media

This paper presents a new deep learning data-driven model for predicting structure dependent pore-fluid velocity fields in rock. The model is based on a Convolutional Auto-Encoder (CAE) artificial neural network capable of learning from image data generated by direct numerical simulations of fluid flow through pore-structures, such as by Lattice Boltzmann or molecular dynamics methods. The main novelty of the model in comparison to previous CAE-based data-driven approaches consists of three parts. The first is a methodology for decomposing the full-domain of the porous media into sub-regions, or “sub-domains”, in order to reduce the overall size of the CAE, batch process the sub-domains in parallel, and enable the CAE to learn local and generalizable nonlinear mappings of pore-fluid velocities. The second consists of embedding the finite difference solutions of the incompressible Navier-Stokes and continuity equations into convolutional layers prior to the CAE in order to provide the CAE with knowledge of fluid dynamics physics (PhyFlow). The third main novelty is that the training of the CAE is regularized with a hierarchical loss function that encourages the learning of fluid flow patterns (in a way similar to ranked modes in principal component analysis), ranking from most to least important. This is shown to increase the stability in learning, reduce over-fitting, and promote interpretability of the CAE neural network layers (HierCAE). The comprehensive new data-driven model, which we call the PhyFlow-HierCAE model, is shown to exhibit improved accuracy and generalizability of flow field predictions over conventional CAE models, attributable to the embedded physical knowledge and the hierarchical regularization, as well as realize orders of magnitude speed-ups in computation times as a surrogate for the direct numerical simulations. Examples of training and forward predictions on unseen pore-structures are provided and evaluated for data from Lattice Boltzmann and molecular dynamics simulations of pore-fluid flow. The model is shown to be a fast and accurate emulator (or “surrogate”) for predicting effective permeability of unseen pore-structures based on learning from relatively small direct numerical simulation datasets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗