Dimethyl ether (DME) carbonylation over mordenite (MOR) is a typical spatial confined reaction, but the superior shape selectivity is accompanied by a diffusion limitation of the microporous channel. Thus, enhancing mass transfer to improve the catalytic performance of MOR is important for its application. In this study, an unbiased chemical etching with a NH 4 F solution was employed to introduce secondary porosity into MOR. Through altering the etching temperature, a series of hierarchical MOR with different porosities were successfully prepared. XRD, Ar adsorption, and ICP together with the quantification of acid sites confirmed that the microporous structure and acidity of pristine zeolite were preserved after etching. The Weisz−Prater criterion was used to assess the internal diffusion limitation of DME and methyl acetate (MA). Moreover, toluene was chosen as a representative molecule in zero length column measurements, in order to explore the mass transfer of coke precursors in pristine and modified MOR. Combining the catalytic performance (i.e., TOF MA , selectivity, and deactivation rate constant) and diffusivity of molecules within MOR, we obtain insight into the influence of diffusion on zeolite-catalyzed DME carbonylation.

Precise localization is critical to safety for connected and automated vehicles (CAV). The global navigation satellite system is the most common vehicle positioning method and has been widely studied to improve localization accuracy. In addition to single-vehicle localization, some recently developed CAV applications require accurate measurement of the inter-vehicle distance (IVD). Thus, this paper proposes a cooperative localization framework that shares the absolute position or pseudorange by using V2X communication devices to estimate the IVD. Four IVD estimation methods are presented: Absolute Position Differencing (APD), Pseudorange Differencing (PD), Single Differencing (SD) and Double Differencing (DD). Several static and dynamic experiments are conducted to evaluate and compare their measurement accuracy. The results show that the proposed methods may have different performances under different conditions. The DD shows the superior performance among the four methods if the uncorrelated errors are small or negligible (static experiment or dynamic experiment with open-sky conditions). When multi-path errors emerge due to the blocked GPS signal, the PD method using the original pseudorange is more effective because the uncorrelated errors cannot be eliminated by the differential technique.

As one of the key steps in ethanol production from syngas, dimethyl ether (DME) carbonylation to methyl acetate (MA) catalyzed by zeolite has drawn much attention. H‐mordenite (HMOR) modified with metal has been continuously developed for improving catalytic performance. Here, we investigated the role of Ag species through three series of Ag−HMOR catalysts prepared through altering Ag loading, varying reduction temperature and additional ion exchange. TEM, XPS, CO FTIR and UV‐Vis spectroscopy were employed to identify the nature and the amount of Ag species in xAg−HM with different Ag loading. Taken together with catalytic performance evaluation, 5Ag−HM with the moderate size of Ag0 species (Agnδ+ and Agm clusters) was proved to have greatest promotion effect on DME carbonylation. This was also evidenced by further improved MA formation rate over catalysts via elevating reduction temperature or via additional NH4Cl ion exchange, which contained more Ag0 and fewer Ag+ species respectively. These provide insight into metal‐modified HMOR, inspiring design and fabrication of zeolite catalysts with multi‐active sites.

PurposeTo develop an efficient and economic daily quality research tool (DQRT) for daily check of multiplatform linear accelerators (LINACs) with flattening filter (FF) and flattening filter‐free (FFF) photon beams by using an Electronic Portal Image Device (EPID).Materials and MethodsAfter EPID calibration, the monitored parameters were analyzed from a 10 cm × 10 cm open and 60° wedge portal images measured by the EPID with 100 MU exposure. Next, the repeatability of the EPID position accuracy, long‐term stability, and linearity between image gray value and exposure were verified. Output and beam quality stability of the 6‐MV FF and FFF beams measured by DQRT with the introduced setup errors of EPID were also surveyed. Besides, some test results obtained by DQRT were compared with those measured by FC65‐G and Matrixx. At last, the tool was evaluated on three LINACs (Synergy, VersaHD, TrueBeam) for 2 months with two popular commercial QA tools as references.ResultsThere are no differences between repeatability tests for all monitored parameters. Image grayscale values obtained by EPID and exposure show good linearity. Either 6 MV FF or FFF photon beam shows minimal impact to the results. The differences between FC65‐G, Matrixx and DQRT results are negligible. Monitor results of the two commercial tools are consistent with the DQRT results collected during the 2‐month period.ConclusionWith a shorter time and procedure, the DQRT is useful to daily QA works of LINACs, producing a QA result quality similarly to or more better than the traditional tools and giving richer contents to the QA results. For hospitals with limited QA time window available or lack of funding to purchase commercial QA tools, the proposed DQRT can provide an alternative and economic approach to accomplish the task of daily QA for LINACs.

Autonomous vehicles are expected to completely change the development model of the transportation industry and bring great convenience to our lives. Autonomous vehicles need to constantly obtain the motion status information with on-board sensors in order to formulate reasonable motion control strategies. Therefore, abnormal sensor readings or vehicle sensor failures can cause devastating consequences and can lead to fatal vehicle accidents. Hence, research on the fault tolerant control method is critical for autonomous vehicles. In this paper, we develop a robust fault tolerant path tracking control algorithm through combining the adaptive model predictive control algorithm for lateral path tracking control, improved weight assignment method for multi-sensor data fusion and fault isolation, and novel federal Kalman filtering approach with two states chi-square detector and residual chi-square detector for detection and identification of sensor fault in autonomous vehicles. Our numerical simulation and experiment demonstrate that the developed approach can detect fault signals and identify their sources with high accuracy and sensitivity. In the double line change path tracking control experiment, when the sensors failure occurs, the proposed method shows better robustness and effectiveness than the traditional methods. It is foreseeable that this research will contribute to the development of safer and more intelligent autonomous driving system, which in turn will promote the industrial development of intelligent transportation system.