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Zhang, Hong

Publications and source records attributed to Zhang, Hong.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Thermally Stable Co@C3N4 Single-Atom Catalysts for CO Oxidation: Atomic-Level Insights into Structure and Activity

Single Co atoms supported on C3N4 (Co@C3N4) have demonstrated high activity and selectivity in photocatalysis. However, the investigation of structure–function relationships and reaction mechanisms under photocatalytic conditions is very challenging due to the complex conditions of light absorption, charge transfer, and catalysis. In this study, we employed thermal CO oxidation as a prototypical probe reaction to benchmark the intrinsic catalytic performance and track the active-site evolution of Co@C3N4. Single Co atoms were identified and shown to be the catalytically active sites for CO oxidation based on control experiments and isotope-labeling experiments. The Co sites remained atomically dispersed before, during, and after the reaction with temperatures up to 400 °C, as established by in situ X-ray absorption fine structure (XAFS) combined with density functional theory (DFT), FDMNES simulations, and dynamic-time-warping (DTW)-assisted X-ray absorption near edge structure (XANES) matching. Together with theoretical calculations, the integrated analysis reveals a stable coordination environment under reaction conditions, which correlates with sustained activity, establishing Co@C3N4 single-atom catalysts as thermally stable CO oxidation catalysts. Beyond these findings, the current study provides a workflow for unambiguously assigning active sites in Co@C3N4 for thermal CO oxidation. This workflow will aid the understanding of their behavior in photocatalysis in the future, where light-driven dynamics obscure direct structure–function links. Notably, this study provides fundamental insights for the rational design of robust single-atom catalysts and a foundation for the broader application of Co@C3N4 catalysts in oxidation reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Fine-tuning catalytic selectivity by modulating catalyst-environment interactions: CO 2 hydrogenation over Pd-based catalysts

Capturing catalytic behaviors under operational conditions is pivotal to gaining a mechanistic understanding and promoting the design of robust catalysts. The challenge lies in the difficulty of monitoring real-time surface dynamics driven by catalyst-environment interactions. Here, in this work, we introduce a framework based on density functional calculations and kinetic modeling. This framework significantly improves the accuracy of theoretical models’ descriptions of experimental observations by quantifying environmental impacts on surface phases and active sites. CO 2 hydrogenation over Pd-based catalysts is taken as a showcase. The observed selectivity variations of Pd and Pd-M bimetallic catalysts strongly correlate with hydrogen coverage maintained under typical CO 2 hydrogenation conditions. By reducing the amount of surface hydrogen, the selectivity tuned effectively from formic acid toward CO and methanol. This study not only deepens the comprehension of dynamics of active sites under active chemical conditions but also introduces an alternative opportunity for catalytic tuning by modulating catalyst-environment interactions.

03 NATURAL GAS↗
DOE OSTI2023

Revealing Intermetallic Active Sites of PtNi Nanocatalysts for Reverse Water Gas Shift Reaction

Bimetallic nanoparticles have gained great interest due to their potential applications in catalysis. By combining Lattice Boltzmann Modeling (LBM), Density Functional Theory (DFT) calculations, and kinetic Monte Carlo (KMC) simulation, here we rationalize the superior performance of supported Pt-Ni alloy nanostructures over Pt and Ni alone during the reverse Water Gas Shift (rWGS) reaction, which was observed previously. The LBM simulation including the diffusion and flow of the reacting gas molecules within the supporting nanoporous channels in SBA-15 indicates that the simple combination of contributions from Ni and Pt alone is not enough to result in the observed promotion in rWGS activity and selectivity of the Pt-Ni alloy. Instead, the synergy between Pt and Ni via a unique intermetallic motif is responsible according to the DFT and KMC simulation. In conclusion, compared to the monometallic counterparts, the intermetallic-introduced ensemble effect at the low-coordinated Pt-Ni hybrid site of Pt-Ni alloy nanocatalysts enables the enhanced activation of CO 2 and promoted removal of CO/H 2 O as gas phase product.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

On fast simulation of dynamical system with neural vector enhanced numerical solver

The large-scale simulation of dynamical systems is critical in numerous scientific and engineering disciplines. However, traditional numerical solvers are limited by the choice of step sizes when estimating integration, resulting in a trade-off between accuracy and computational efficiency. To address this challenge, we introduce a deep learning-based corrector called Neural Vector (NeurVec), which can compensate for integration errors and enable larger time step sizes in simulations. Our extensive experiments on a variety of complex dynamical system benchmarks demonstrate that NeurVec exhibits remarkable generalization capability on a continuous phase space, even when trained using limited and discrete data. NeurVec significantly accelerates traditional solvers, achieving speeds tens to hundreds of times faster while maintaining high levels of accuracy and stability. Moreover, NeurVec’s simple-yet-effective design, combined with its ease of implementation, has the potential to establish a new paradigm for fast-solving differential equations based on deep learning.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Multirate partitioned Runge–Kutta methods for coupled Navier–Stokes equations

Earth system models are complex integrated models of atmosphere, ocean, sea ice, and land surface. Coupling the components can be a significant challenge due to the difference in physics, temporal, and spatial scales. Further, this study explores multirate partitioned Runge-Kutta methods for the fluid-fluid interaction problem and demonstrates its parallel performance by using the PETSc library. We consider compressible Navier-Stokes equations with gravity coupled through a rigid-lid interface. Our large-scale numerical experiments reveal that multirate partitioned Runge-Kutta coupling schemes (1) can conserve total mass; (2) have second-order accuracy in time; and (3) provide favorable strong- and weak-scaling performance on modern computing architectures. We also show that the speedup factors of multirate partitioned Runge-Kutta methods match theoretical expectations over their base (single-rate) method.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Amino-tethering synthesis strategy toward highly accessible sub-3-nm L1 0 -PtM catalysts for high-power fuel cells

Because of the poor accessibility of embedded active sites, platinum (Pt)-based electrocatalysts suffer from insufficient Pt utilization and mass transport in membrane electrode assemblies (MEAs), limiting their performance in polymer electrolyte membrane fuel cells. Here, we report a simple and universal approach to depositing sub-3-nm L1 0 -PtM nanoparticles over external surfaces of carbon supports through pore-tailored amino (NH 2 )-modification, which enables not only excellent activity for the oxygen reduction reaction, but also enhanced Pt utilization and mass transport in MEAs. Using a low loading of 0.10 mg Pt ∙cm -2 , the MEA of PtCo/KB-NH 2 delivered an excellent mass activity of 0.691 A∙mgPt -1 , a record-high power density of 0.96 W∙cm -2 at 0.67 V, and only a 30-mV drop at 0.80 A∙cm -2 after 30,000 voltage cycles, which meets nearly all targets set by the Department of Energy. Finally, this work provides an efficient strategy for designing advanced Pt-based electrocatalysts and realizing high-power fuel cells.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Optimal checkpointing for adjoint multistage time-stepping schemes

Here, we consider checkpointing strategies that minimize the number of recomputations needed when performing discrete adjoint computations using multistage time-stepping schemes that require computing several substeps within one complete time step. Specifically, we propose two algorithms that can generate optimal checkpoint-ing schedules under weak assumptions. The first is an extension of the seminal Revolve algorithm adapted to multistage schemes. The second algorithm, named CAMS, is developed based on dynamic programming, and it requires the least number of recomputations when compared with other algorithms. The CAMS algorithm is made publicly available in a library with bindings to C and Python. Numerical results show that the proposed algorithms can deliver up to two times the speedup compared with that of classical Revolve. Moreover, we discuss the utilization of the CAMS library in mature scientific computing libraries and demonstrate the ease of using it in an adjoint workflow. The proposed algorithms have been adopted by the PETSc TSAdjoint library. Their performance has been demonstrated with a large-scale PDE-constrained optimization problem on a leadership-class supercomputer. This work is a significant extension of the authors' conference paper.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Stability Analysis of Coupled Advection-Diffusion Models with Bulk Interface Condition

Numerical stability is of critical importance in general circulation models because it affects the design of algorithms, time to solution, and computational costs associated with the simulations, which are very expensive in practice. In this paper we extend the stability analysis for ocean-atmosphere coupling proposed in [Zhang et al., J. Sci. Comput. 84, 44(2020)] to a more realistic model that includes horizontal advection. We analyze various time-stepping strategies. We find that advection has a stabilizing effect in scenarios common to climate models when bulk interface condition and explicit flux coupling are used. We also show that our method can be used to study the stability impact of advection for other interface conditions such as Dirichlet-Neumann conditions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Investigating the Elusive Nature of Atomic O from CO 2 Dissociation on Pd(111): The Role of Surface Hydrogen

CO 2 dissociation is a key step in CO 2 conversion reactions to produce value-added chemicals typically through hydrogenation. In many cases, the atomic O produced from CO 2 dissociation can potentially block adsorption sites or change the oxidation state of the catalyst. Here, we used ambient pressure X-ray photoelectron spectroscopy (AP-XPS) and density functional theory (DFT) calculations to investigate the presence of surface species from the dissociation of CO 2 on Pd(111). AP-XPS results show that CO 2 was dissociated to produce adsorbed CO, but dissociated atomic O was not observed at room temperature. We were only able to observe atomic O when CO 2 was introduced at 500 K. Further investigations of O-covered Pd(111) revealed that chemisorbed O could be easily removed by low pressures of CO and H 2 . Notably, the effect of H 2 is quite prominent since it could react with chemisorbed O at a pressure as low as 2 × 10 -9 Torr, and the presence of H2 at ambient pressure prevented CO 2 dissociation. DFT calculations showed that in the presence of background H 2 , facile CO 2 dissociation took place via the reverse water–gas shift (rWGS) reaction, which resulted in the formation of adsorbed CO and removal of O by H 2 . DFT also identified the possible variation of surface species on simultaneous exposure of CO 2 and H 2 over Pd(111) depending on temperature and pressure, which opens alternative opportunities to tune the CO 2 hydrogenation catalysis by controlling the reaction conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

mTOR regulates aerobic glycolysis through NEAT1 and nuclear paraspeckle-mediated mechanism in hepatocellular carcinoma

Hepatocellular Carcinoma (HCC) is a major form of liver cancer and a leading cause of cancer-related death worldwide. New insights into HCC pathobiology and mechanism of drug actions are urgently needed to improve patient outcomes. HCC undergoes metabolic reprogramming of glucose metabolism from respiration to aerobic glycolysis, a phenomenon known as the ‘Warburg Effect’ that supports rapid cancer cell growth, survival, and invasion. mTOR is known to promote Warburg Effect, but the underlying mechanism(s) remains poorly defined. The aim of this study is to understand the mechanism(s) and significance of mTOR regulation of aerobic glycolysis in HCC. We profiled mTORC1-dependent long non-coding RNAs (lncRNAs) by RNA-seq of HCC cells treated with rapamycin. Chromatin immunoprecipitation (ChIP) and luciferase reporter assays were used to explore the transcriptional regulation of NEAT1 by mTORC1. [U- 13 C]-glucose labeling and metabolomic analysis, extracellular acidification Rate (ECAR) by Seahorse XF Analyzer, and glucose uptake assay were used to investigate the role of mTOR-NEAT1-NONO signaling in the regulation of aerobic glycolysis. RNA immunoprecipitation (RIP) and NONO-binding motif scanning were performed to identify the regulatory mechanism of pre-mRNA splicing by mTOR-NEAT1. Myristoylated AKT1 (mAKT1)/NRASV 12 -driven HCC model developed by hydrodynamic transfection (HDT) was employed to explore the significance of mTOR-NEAT1 signaling in HCC tumorigenesis and mTOR-targeted therapy. mTOR regulates lncRNA transcriptome in HCC and that NEAT1 is a major mTOR transcriptional target. Interestingly, although both NEAT1_1 and NEAT1_2 are down-regulated in HCC, only NEAT1_2 is significantly correlated with poor overall survival of HCC patients. NEAT1_2 is the organizer of nuclear paraspeckles that sequester the RNA-binding proteins NONO and SFPQ. We show that upon oncogenic activation, mTORC1 suppresses NEAT1_2 expression and paraspeckle biogenesis, liberating NONO/SFPQ, which in turn, binds to U5 within the spliceosome, stimulating mRNA splicing and expression of key glycolytic enzymes. This series of actions lead to enhanced glucose transport, aerobic glycolytic flux, lactate production, and HCC growth both in vitro and in vivo. Furthermore, the paraspeckle-mediated mechanism is important for the anticancer action of US FDA-approved drugs rapamycin/temsirolimus. These findings reveal a molecular mechanism by which mTOR promotes the ‘Warburg Effect’, which is important for the metabolism and development of HCC, and anticancer response of mTOR-targeted therapy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

An anti-PD-1–GITR-L bispecific agonist induces GITR clustering-mediated T cell activation for cancer immunotherapy

Costimulatory receptors such as glucocorticoid-induced tumor necrosis factor receptor–related protein (GITR) play key roles in regulating the effector functions of T cells. In human clinical trials, however, GITR agonist antibodies have shown limited therapeutic effect, which may be due to suboptimal receptor clustering-mediated signaling. To overcome this potential limitation, a rational protein engineering approach is needed to optimize GITR agonist-based immunotherapies. Here we show a bispecific molecule consisting of an anti-PD-1 antibody fused with a multimeric GITR ligand (GITR-L) that induces PD-1-dependent and FcγR-independent GITR clustering, resulting in enhanced activation, proliferation and memory differentiation of primed antigen-specific GITR + PD-1 + T cells. The anti-PD-1–GITR-L bispecific is a PD-1-directed GITR-L construct that demonstrated dose-dependent, immunologically driven tumor growth inhibition in syngeneic, genetically engineered and xenograft humanized mouse tumor models, with a dose-dependent correlation between target saturation and Ki67 and TIGIT upregulation on memory T cells. Anti-PD-1–GITR-L thus represents a bispecific approach to directing GITR agonism for cancer immunotherapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

PETSc TSAdjoint: A Discrete Adjoint ODE Solver for First-Order and Second-Order Sensitivity Analysis

Here, we present a new software system PETSc TSAdjoint for first-order and second order adjoint sensitivity analysis of time-dependent nonlinear differential equations. The derivative calculation in PETSc TSAdjoint is essentially a high-level algorithmic differentiation process. The adjoint models are derived by differentiating the timestepping algorithms and implementing them based on the parallel infrastructure in PETSc. Full differentiation of the library code, including MPI routines, is avoided, and users do not need to derive their own adjoint models for their specific applications. PETSc TSAdjoint can compute the first-order derivative, that is, the gradient of a scalar functional, and the Hessian-vector product, which carries second-order derivative information, while requiring minimal input (a few callbacks) from the users. The adjoint model employs optimal checkpointing schemes in a manner that is transparent to users. Finally, usability, efficiency, and scalability are demonstrated through examples from a variety of applications.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Trust-Region Approximation of Extreme Trajectories in Power System Dynamics

In this work we present a novel technique, based on a trust-region optimization algorithm and second-order trajectory sensitivities, to compute the extreme trajectories of power system dynamic simulations given a bounded set that represents parametric uncertainty. Furthermore, we show how this method, while remaining computationally efficient compared with sampling-based techniques, overcomes the limitations of previous sensitivity-based techniques to approximate the bounds of the trajectories when the local approximation loses validity because of the nonlinearity. We present several numerical experiments that showcase the accuracy and scalability of the technique, including a demonstration on the IEEE New England test system.

42 ENGINEERING↗
DOE OSTI2022

A universal co-solvent dilution strategy enables facile and cost-effective fabrication of perovskite photovoltaics

Cost management and toxic waste generation are two key issues that must be addressed before the commercialization of perovskite optoelectronic devices. We report a groundbreaking strategy for eco-friendly and cost-effective fabrication of highly efficient perovskite solar cells. This strategy involves the usage of a high volatility co-solvent, which dilutes perovskite precursors to a lower concentration (<0.5 M) while retaining similar film quality and device performance as a high concentration (>1.4 M) solution. More than 70% of toxic waste and material cost can be reduced. Mechanistic insights reveal ultra-rapid evaporation of the co-solvent together with beneficial alteration of the precursor colloidal chemistry upon dilution with co-solvent, which in-situ studies and theoretical simulations confirm. The co-solvent tuned precursor colloidal properties also contribute to the enhancement of the stability of precursor solution, which extends its processing window thus minimizing the waste. This strategy is universally successful across different perovskite compositions, and scales from small devices to large-scale modules using industrial spin-coating, potentially easing the lab-to-fab translation of perovskite technologies.

36 MATERIALS SCIENCE↗