A System-Level Dynamic Binary Translator using Automatically-Learned Translation Rules

System-level emulators have been used extensively for system design, debugging and evaluation. They work by providing a system-level virtual machine to support a guest operating system (OS) running on a platform with the same or different native OS that uses the same or different instruction-set architecture. For such system-level emulation, dynamic binary translation (DBT) is one of the core technologies. A recently proposed learning-based DBT approach has shown a significantly improved performance with a higher quality of translated code using automatically learned translation rules. However, it has only been applied to user-level emulation, and not yet to system-level emulation. In this paper, we explore the feasibility of applying this approach to improve system-level emulation, and use QEMU to build a prototype. ... To achieve better performance, we leverage several optimizations that include coordination overhead reduction to reduce the overhead of each coordination, and coordination elimination and code scheduling to reduce the coordination frequency. Experimental results show that it can achieve an average of 1.36X speedup over QEMU 6.1 with negligible coordination overhead in the system emulation mode using SPEC CINT2006 as application benchmarks and 1.15X on real-world applications.Comment: 10 pages, 19 figures, to be published in International Symposium on Code Generation and Optimization (CGO) 202

Rational approach to guest confinement inside MOF cavities for low-temperature catalysis.

Geometric or electronic confinement of guests inside nanoporous hosts promises to deliver unusual catalytic or opto-electronic functionality from existing materials but is challenging to obtain particularly using metastable hosts, such as metal-organic frameworks (MOFs). Reagents (e.g. precursor) may be too large for impregnation and synthesis conditions may also destroy the hosts. Here we use thermodynamic Pourbaix diagrams (favorable redox and pH conditions) to describe a general method for metal-compound guest synthesis by rationally selecting reaction agents and conditions. Specifically we demonstrate a MOF-confined RuO2 catalyst (RuO2@MOF-808-P) with exceptionally high catalytic CO oxidation below 150 °C as compared to the conventionally made SiO2-supported RuO2 (RuO2/SiO2). This can be caused by weaker interactions between CO/O and the MOF-encapsulated RuO2 surface thus avoiding adsorption-induced catalytic surface passivation. We further describe applications of the Pourbaix-enabled guest synthesis (PEGS) strategy with tutorial examples for the general synthesis of arbitrary guests (e.g. metals, oxides, hydroxides, sulfides).EPSRC Centre for Doctoral Training in Sensor Technologies and Applications (EP/L015889/1)； EPSRC Centre for Doctoral Training in Sensor Technologies and Applications (1566990)； EPSRC grants (EP/L011700/1); EPSRC grants (EP/N004272/1); Isaac Newton Trust [Minute 13.38(k)]; European Research Council (ERC) EMATTER (# 280078)； National Natural Science Foundation of China (No. 21688102); National Natural Science Foundation of China (No. 21825203); Ministry of Science and Technology of China (No. 2016YFA0200200); Strategic Priority Research Program of the Chinese Academy of Sciences (No. XDB17020000); Ras Al Khaimah Center for Advanced Materials (RAK-CAM); China Scholarship Council (CSC)

Towards Experimental Handbooks in Catalysis

The “Seven Pillars” of oxidation catalysis proposed by Robert K. Grasselli represent an early example of phenomenological descriptors in the field of heterogeneous catalysis. Major advances in the theoretical description of catalytic reactions have been achieved in recent years and new catalysts are predicted today by using computational methods. To tackle the immense complexity of high-performance systems in reactions where selectivity is a major issue, analysis of scientific data by artificial intelligence and data science provides new opportunities for achieving improved understanding. Modern data analytics require data of highest quality and sufficient diversity. Existing data, however, frequently do not comply with these constraints. Therefore, new concepts of data generation and management are needed. Herein we present a basic approach in defining best practice procedures of measuring consistent data sets in heterogeneous catalysis using “handbooks”. Selective oxidation of short-chain alkanes over mixed metal oxide catalysts was selected as an example.DFG, 390540038, EXC 2008: Unifying Systems in Catalysis "UniSysCat

Carbide-Supported Au Catalysts for Water-Gas Shift Reactions: A New Territory for the Strong Metal-Support Interaction Effect

Strong metal-support interaction (SMSI) has been regarded as one of the most important concepts in heterogeneous catalysis, which has been almost exclusively discussed in metal/oxide catalysts. Here, we show that gold/molybdenum carbide (Au/MoCx) catalysts feature highly dispersed Au overlayers, strong interfacial charge transfer between metal and support, and excellent activity in the low-temperature water-gas shift reaction (LT-WGSR), demonstrating the active SMSI state. Subsequent oxidation treatment results in strong aggregation of Au nanoparticles, weak interfacial electronic interaction, and poor LT-WGSR activity. The two interface states can be transformed into each other by alternative carbonization and oxidation treatments. This work reveals the active SMSI effect in metal/carbide catalysts induced by carbonization, which opens a new territory for this important concept