DFT Benchmark Studies on Representative Species and Poisons of Methane Steam Reforming on Ni(111)

Ni catalysts used in Methane Steam Reforming (MSR) are highly susceptible to poisoning by carbon-based species, which poses a major impediment to the productivity of industrial operations. These graphitic carbon-like formations are typically modelled from first principles as graphene. Although numerous experimental investigations have been carried out, a conclusive mechanistic molecular-level understanding of graphene formation on Ni during the MSR reaction is still elusive. First principles-based approaches, such as Density Functional Theory (DFT) calculations, can provide valuable insight into the mechanism of graphene growth in the MSR reaction. It is, however, critical that a DFT model of this reaction can accurately describe the interactions of Ni(111) with the MSR intermediates as well as graphene. Crucially, these interactions include van der Waals forces, making the choice of a proper DFT functional a subject of debate, as there are several dispersion-inclusive functionals available in the literature. In this work, a systematic benchmark study has been carried out to identify a suitable DFT functional for the graphene and MSR system. The binding energies of graphene and important MSR species were computed on Ni(111) using GGA functionals, DFT-D3 and van der Waals density functionals (vdW-DF). Comparisons of these binding energies with published experimental data reveal that the GGA functionals are inadequate for the graphene-Ni(111) system. Among the vdW-DF, optB88-vdW predicts the binding energy of graphene with high accuracy; however, its predictions significantly deviate from the experimental binding energies of CO and O. Among DFT-D3 functionals, PBE-D3 was found to have a reasonable predictive accuracy for most MSR species (excluding the CO adsorbate). Overall, no single DFT functional could estimate the binding energies of all the species with equally high accuracy. Our benchmarks guide the selection of DFT functionals for simulations of MSR and could aid in the future development of predictive quality functionals

Silicon Atomic Quantum Dots Enable Beyond-CMOS Electronics

We review our recent efforts in building atom-scale quantum-dot cellular automata circuits on a silicon surface. Our building block consists of silicon dangling bond on a H-Si(001) surface, which has been shown to act as a quantum dot. First the fabrication, experimental imaging, and charging character of the dangling bond are discussed. We then show how precise assemblies of such dots can be created to form artificial molecules. Such complex structures can be used as systems with custom optical properties, circuit elements for quantum-dot cellular automata, and quantum computing. Considerations on macro-to-atom connections are discussed.Comment: 28 pages, 19 figure

The RAG1 N-terminal region regulates the efficiency and pathways of synapsis for V(D)J recombination

Immunoglobulin and T cell receptor gene assembly depends on V(D)J recombination initiated by the RAG1-RAG2 recombinase. The RAG1 N-terminal region (NTR; aa 1-383) has been implicated in regulatory functions whose influence on V(D)J recombination and lymphocyte development in vivo is poorly understood. We generated mice in which RAG1 lacks ubiquitin ligase activity (P326G), the major site of autoubiquitination (K233R), or its first 215 residues (Δ215). While few abnormalities were detected in R1.K233R mice, R1.P326G mice exhibit multiple features indicative of reduced recombination efficiency, including an increased Igκ+:Igλ+ B cell ratio and decreased recombination of Igh, Igκ, Igλ, and Tcrb loci. Previous studies indicate that synapsis of recombining partners during Igh recombination occurs through two pathways: long-range scanning and short-range collision. We find that R1Δ215 mice exhibit reduced short-range Igh and Tcrb D-to-J recombination. Our findings indicate that the RAG1 NTR regulates V(D)J recombination and lymphocyte development by multiple pathways, including control of the balance between short- and long-range recombination

Systematic Improvements in Transmon Qubit Coherence Enabled by Niobium Surface Encapsulation

We present a novel transmon qubit fabrication technique that yields systematic improvements in T$_1$ coherence times. We fabricate devices using an encapsulation strategy that involves passivating the surface of niobium and thereby preventing the formation of its lossy surface oxide. By maintaining the same superconducting metal and only varying the surface structure, this comparative investigation examining different capping materials and film substrates across different qubit foundries definitively demonstrates the detrimental impact that niobium oxides have on the coherence times of superconducting qubits, compared to native oxides of tantalum, aluminum or titanium nitride. Our surface-encapsulated niobium qubit devices exhibit T$_1$ coherence times 2 to 5 times longer than baseline niobium qubit devices with native niobium oxides. When capping niobium with tantalum, we obtain median qubit lifetimes above 200 microseconds. Our comparative structural and chemical analysis suggests that amorphous niobium suboxides may induce higher losses. These results are in line with high-accuracy measurements of the niobium oxide loss tangent obtained with ultra-high Q superconducting radiofrequency (SRF) cavities. This new surface encapsulation strategy enables further reduction of dielectric losses via passivation with ambient-stable materials, while preserving fabrication and scalable manufacturability thanks to the compatibility with silicon processes

Protease-Resistant Prions Selectively Decrease Shadoo Protein

The central event in prion diseases is the conformational conversion of the cellular prion protein (PrPC) into PrPSc, a partially protease-resistant and infectious conformer. However, the mechanism by which PrPSc causes neuronal dysfunction remains poorly understood. Levels of Shadoo (Sho), a protein that resembles the flexibly disordered N-terminal domain of PrPC, were found to be reduced in the brains of mice infected with the RML strain of prions [1], implying that Sho levels may reflect the presence of PrPSc in the brain. To test this hypothesis, we examined levels of Sho during prion infection using a variety of experimental systems. Sho protein levels were decreased in the brains of mice, hamsters, voles, and sheep infected with different natural and experimental prion strains. Furthermore, Sho levels were decreased in the brains of prion-infected, transgenic mice overexpressing Sho and in infected neuroblastoma cells. Time-course experiments revealed that Sho levels were inversely proportional to levels of protease-resistant PrPSc. Membrane anchoring and the N-terminal domain of PrP both influenced the inverse relationship between Sho and PrPSc. Although increased Sho levels had no discernible effect on prion replication in mice, we conclude that Sho is the first non-PrP marker specific for prion disease. Additional studies using this paradigm may provide insight into the cellular pathways and systems subverted by PrPSc during prion disease

Inventory system with renewal demands at service facilities

Inventory systems where customers join waiting line to receive their demanded items are recently considered by many researchers, as these models allow the study of both queue length and size of the inventory. This article considers a continuous review inventory system at a service facility, wherein an item demanded by a customer is issued to him/her only after performing service of random duration on the item. The service facility is assumed to have waiting hall of infinite size. The arrival time points of customers form a renewal process. The service times are assumed to be distributed as negative exponential. The operating policy is (s,S) policy with instantaneous supply of ordered items. We consider two models which differ in the way that ordered items, when received, is brought into the stock. In the first model, the ordered items are brought into the stock immediately. In the second model, the supplied items are brought into the stock only at the next demand epoch. The stationary distribution of the underlying Markov chain is obtained in matrix-geometric form. The joint probability distribution of the number of customers in the system and the inventory level is obtained in the steady-state case.