Beijing Computational Science Research Center

Ammonia decomposition is governed by an intrinsic trade-off between NH3 dehydrogenation and N-N coupling, giving rise to the well-known volcano relationship that has long positioned ruthenium (Ru) near the activity maximum. However, whether this relationship can be reshaped through catalyst design remains an open question. Here we show that metal-oxide interfacial cooperation qualitatively alters the reaction pathway of ammonia decomposition. Using reaction-aware machine learning simulations, we find that on MgO(111)-supported metal nanoparticles, NH3 dehydrogenation, one of the most kinetically demanding steps, occurs predominantly at the metal-MgO(111) interface with substantially reduced activation barriers, while N-N coupling remains governed by the metal surface. This spatial separation of reaction bottlenecks relaxes the classical single-site trade-off and drives a shift of the activity volcano toward weaker nitrogen-binding metals. As a consequence, Ni/MgO(111) and Cu/MgO(111) emerge near the new activity optimum and are predicted to rival or surpass Ru/MgO(111), as supported by density functional theory calculations and microkinetic modeling. Our results establish interfacial cooperation as a general design principle for tuning volcano relationships in heterogeneous catalysis and for activating earth-abundant metals beyond conventional single-site paradigms.

Entanglement and so-called magic states have long been viewed as the key resources for quantum error correction. Now contextuality, a hallmark of quantum theory, joins them as a complementary resource.

596 Background: Glypican‐3 (GPC3) is a membrane proteoglycan expressed in ~80% of hepatocellular carcinomas (HCC). In addition, GPC3 is cleaved by proteases, shedding its N-terminal fragment into the circulation. While GPC3-targeted therapies are under clinical development, the relationship between tumor GPC3 and plasma GPC3 (pGPC3) remains unclear. Here, we investigated the correlation between tumor GPC3 and pGPC3 and their associations with clinical outcomes in HCC patients. Methods: This study included 186 patients with advanced HCC treated at CHA Bundang Medical Center (2017–2023). Tissue GPC3 levels were assessed by immunohistochemistry (IHC) and RNA-seq, while pGPC3 was assessed using ELISA in 166 patients. Clinical outcomes were investigated in 106 patients treated with first-line atezolizumab plus bevacizumab (atezo/bev). H-score groups were defined as: 0 (negative), 1–100 (low), 101–200 (intermediate), and 201–300 (high). Results: The median IHC extent of GPC3 was 80%, reflecting widespread expression in tumor tissue. The median pGPC3 level was 11.4 pg/mL, with 40.7% of patients undetectable. pGPC3 significantly correlated with H-score (R=0.40, p<0.001) and RNA-seq (R=0.28, p=0.006). pGPC3 positivity (>0 pg/mL) increased proportionally across H-score groups (p<0.001); however, even in the high group (201–300), 25.9% of patients had undetectable pGPC3. pGPC3 was higher in patients with BCLC stage C, PVTT, AFP ≥400 ng/mL and no prior local therapy. High pGPC3 (>10 pg/mL) was associated with shorter progression-free survival (PFS) (3.4 vs 9.4 months, p=0.003), overall survival (OS) (12.3 vs 30.6 months, p<0.001), and lower objective response rates (17.9% vs 47.9%, p=0.001). Time-dependent ROC showed that pGPC3 had a higher predictive accuracy than tumor GPC3 for PFS and OS at both 6- and 12-month time points. In multivariable analysis, high pGPC3 was independently associated with worse PFS (Hazard Ratio [HR]=1.68, 95% Confidence Interval [CI]: 1.06–2.66, p=0.03) and OS (HR=1.93, 95% CI: 1.11–3.36, p=0.02). Conclusions: pGPC3 showed positive correlation with tumor tissue GPC3 and high pGPC3 was associated with poor survival outcomes in patients with advanced HCC treated with atezo/bev.

SiC MOSFETs are expected to be exposed to irradiation when applied in harsh environments such as space. Therefore, it is important to understand the ionization radiation effects on the short-circuit (SC) reliability of SiC MOSFETs. In this work, the degradation modes and degradation mechanisms in the atomic scale of Gamma-irradiated SiC MOSFETS under repetitive short-circuit stress are investigated. Compared to single-stress scenarios, the synergistic effect of irradiation and short-circuit stress significantly accelerates the negative shift of threshold voltage of irradiated devices and thus results in the degradations of switching performances. The cyclic SC stress results in the dominate hole trapping in the oxide over the annealing of active oxide defects from the self-heating. The Electro-thermal simulations and Hybrid-functional density functional theory (DFT) calculations are performed and demonstrate that the hole injection into the oxide and the subsequent hole trapping by electrically active oxygen vacancies (VO) are main cause for the enhanced formation of positively charged oxide-trap after irradiation and SC stress, where the irradiation and repetitive SC stress promote the structural transformation of VO and hole trapping of VO by overcoming the thermal barrier, respectively.

• Develop C 1 -conforming and C 0 -nonconforming virtual element methods for Hamilton-Jacobi-Bellman equations in nondivergence form under the Cordes condition. • Introduce a novel stabilization strategy that ensures strong monotonicity and stability without discrete Miranda-Talenti identities. • Establish well-posedness and a priori error estimates with optimal convergence in mesh-broken norms. • The methods are polygonal-mesh flexible, efficiently implementable, and well-suited for low-regularity fully nonlinear PDEs. In this paper, we propose and analyze both conforming and nonconforming virtual element methods (VEMs) for the fully nonlinear second-order elliptic Hamilton-Jacobi-Bellman (HJB) equations with Cordes coefficients. By incorporating stabilization terms, we establish the well-posedness of the proposed methods, thus avoiding the need to construct a discrete Miranda-Talenti estimate. We derive the optimal error estimate in the discrete H 2 norm for both numerical formulations. Furthermore, a semismooth Newton’s method is employed to linearize the discrete problems. Several numerical experiments using the lowest-order VEMs are provided to demonstrate the efficacy of the proposed methods and to validate our theoretical results.

Spin defects in atomically thin two-dimensional (2D) materials are promising for quantum applications, particularly quantum sensing. The long coherence times of the spin defects enable high sensitivity in measurements of the fluctuations of the targeted physical parameters. However, the nuclear-spin bath remains a major source of decoherence. Here, we reveal the presence of optically addressable spin defects in germanium disulfide (β-GeS2) characterized by a wide bandgap and potential nuclear-spin-free lattice. Coherent control of the spin defects has been successfully demonstrated, and the coherence time T2 at 5 K can achieve tens of microseconds, 100 times that of a negatively charged boron vacancy (VB-) in hexagonal boron nitride. An optical-spin defect pair model proposed recently has been used to explain their dynamics. Finally, we use density functional theory calculations to propose possible candidate structures for the spin defects.

ABSTRACT This work presents an improved version of the residual vector correction (RVC) algorithm, designed to address the eigenproblem involved in electronic structure calculations. Instead of directly diagonalizing the entire Hamiltonian matrix, the proposed algorithm iteratively diagonalizes a 2 × 2 submatrix, focusing only on the relevant molecular orbitals. Molecular orbital energies are iteratively minimized along a residual vector, with the step size determined by diagonalizing the 2 × 2 submatrix. To obtain the subsequent eigenvalues, we employ Hotelling deflation, which constructs the necessary auxiliary Fock matrix. Since the size of the diagonalized matrix does not increase with the molecular system, this algorithm eliminates the cubic scaling dependence of computational efficiency on molecule size seen in direct diagonalization. Compared to the earlier version, the implementation within the Hartree–Fock framework shows that the current version is significantly more practical for the calculation of considerably large molecules. As demonstrated, the RVC method consistently surpasses existing iterative approaches in efficiency while maintaining high accuracy.