Search

One promising method for mitigating low-temperature and low-concentration NO2 pollution is selective adsorption using porous solid materials. However, the corrosive nature of NO2 renders the development of an adsorbent with high and cyclable NO2 uptake a formidable challenge. Herein, we attempted to address this challenge by developing a microporous covalent triazine framework (CTF) as effective adsorbents for NO2 capture, achieving unprecedented high cyclable capacity enabled by simultaneous high adsorbent stability and moderate adsorption affinity via tuning specific binding sites. Using dynamic column breakthrough experiments, we demonstrated that the pristine CTF exhibited a high NO2 adsorption capacity (dry: 3.83 mmol/g; wet: 5.26 mmol/g) overtaking most reported solid adsorbents, thanks to abundant active sites (e.g., nitrogen/carbon/triazine rings). Post-synthesis converted the surface nitrogen to protonated nitrogen site and further to transition metal site affording more effective binding sites that allows for moderately strong adsorption, resulting in elevated NO2 adsorption capacity (dry: 6.11 mmol/g; wet: 8.97 mmol/g) and a highest reversible NO2 adsorption (retaining 91 % and 64 % at dry and wet conditions after five cycles, respectively), as illustrated by our mechanistic study using in situ DRIFTS and DFT calculations. This work affords not only promising adsorbents for real-world applications in mitigating NO2 pollution, but also a strategy of developing robust adsorbents with desired affinity generally applicable to adsorptive capture of corrosive and toxic gases.

We consider a hybrid manufacturing/remanufacturing system where the returned products (cores) are classified into different quality grades. Each grade requires different remanufacturing operations and thus lead times. We examine the implications of the quality-grading scheme on the dynamic behavior of closed-loop supply chains, benchmarking this against a typical system where all the returns undergo the same remanufacturing process. Through control engineering techniques, we evaluate the Bullwhip and inventory performance of the supply chain by observing the step response of the orders and net stocks (the shock lens), analyzing the frequency behavior of these signals (the filter lens), and measuring their dynamics due to stochastic demand (the variance lens). Subsequently, we discuss the operational savings and additional costs derived from quality grading. We find that the pre-sorting mechanism allows for smoothing the supply chain operations; however, its impact on customer satisfaction is ambivalent. Indeed, we observe that the documented ‘lead-time paradox’ of the remanufacturing process in hybrid systems results here in a ‘quality paradox’: lower quality returns may increase the performance of inventories. This affects particularly low-frequency demands. Importantly, we analytically derive the optimal setting of the closed-loop pipeline estimation in order-up-to policies for avoiding long-term inventory drifts. This analysis reveals key potential benefits of information transparency for improving the operational performance, and thus the environmental and economic sustainability, of closed-loop supply chains.

We consider a hybrid manufacturing/remanufacturing system where the returned products (cores) are classified into different quality grades. Each grade requires different remanufacturing operations and thus lead times. We examine the implications of the quality-grading scheme on the dynamic behavior of closed-loop supply chains, benchmarking this against a typical system where all the returns undergo the same remanufacturing process. Through control engineering techniques, we evaluate the Bullwhip and inventory performance of the supply chain by observing the step response of the orders and net stocks (the shock lens), analyzing the frequency behavior of these signals (the filter lens), and measuring their dynamics due to stochastic demand (the variance lens). Subsequently, we discuss the operational savings and additional costs derived from quality grading. We find that the pre-sorting mechanism allows for smoothing the supply chain operations; however, its impact on customer satisfaction is ambivalent. Indeed, we observe that the documented ‘lead-time paradox’ of the remanufacturing process in hybrid systems results here in a ‘quality paradox’: lower quality returns may increase the performance of inventories. This affects particularly low-frequency demands. Importantly, we analytically derive the optimal setting of the closed-loop pipeline estimation in order-up-to policies for avoiding long-term inventory drifts. This analysis reveals key potential benefits of information transparency for improving the operational performance, and thus the environmental and economic sustainability, of closed-loop supply chains.

We consider a hybrid manufacturing/remanufacturing system where the returned products (cores) are classified into different quality grades. Each grade requires different remanufacturing operations and thus lead times. We examine the implications of the quality-grading scheme on the dynamic behavior of closed-loop supply chains, benchmarking this against a typical system where all the returns undergo the same remanufacturing process. Through control engineering techniques, we evaluate the Bullwhip and inventory performance of the supply chain by observing the step response of the orders and net stocks (the shock lens), analyzing the frequency behavior of these signals (the filter lens), and measuring their dynamics due to stochastic demand (the variance lens). Subsequently, we discuss the operational savings and additional costs derived from quality grading. We find that the pre-sorting mechanism allows for smoothing the supply chain operations; however, its impact on customer satisfaction is ambivalent. Indeed, we observe that the documented ‘lead-time paradox’ of the remanufacturing process in hybrid systems results here in a ‘quality paradox’: lower quality returns may increase the performance of inventories. This affects particularly low-frequency demands. Importantly, we analytically derive the optimal setting of the closed-loop pipeline estimation in order-up-to policies for avoiding long-term inventory drifts. This analysis reveals key potential benefits of information transparency for improving the operational performance, and thus the environmental and economic sustainability, of closed-loop supply chains.

We present a detailed description of the electromagnetic filter for the PTOLEMY project to directly detect the Cosmic Neutrino Background (CNB). Starting with an initial estimate for the orbital magnetic moment, the higher-order drift process of E×B is configured to balance the gradient-B drift motion of the electron in such a way as to guide the trajectory into the standing voltage potential along the mid-plane of the filter. As a function of drift distance along the length of the filter, the filter zooms in with exponentially increasing precision on the transverse velocity component of the electron kinetic energy. This yields a linear dimension for the total filter length that is exceptionally compact compared to previous techniques for electromagnetic filtering. The parallel velocity component of the electron kinetic energy oscillates in an electrostatic harmonic trap as the electron drifts along the length of the filter. An analysis of the phase-space volume conservation validates the expected behavior of the filter from the adiabatic invariance of the orbital magnetic moment and energy conservation following Liouville's theorem for Hamiltonian systems.

Supported Co3O4 nanoparticles on SBA-15 aluminosilicates (Al-SBA-15) with different cobalt loadings (0.5, 1, 5, 10 wt %) were synthesized by ball-milling. The synthesized materials were characterized by different techniques including, N2 adsorption measurements, XRD, TEM, EDX, ICP-MS, DRIFTs of pyridine among others. The catalysts were studied in the microwave assisted benzyl alcohol oxidation as well as in the akylation of toluene with benzyl chloride. Co3O4 catalysts exhibited moderate conversions in the selective oxidation of benzyl alcohol, with a high selectivity towards benzaldehyde. Lewis acidity increases upon the incorporation of cobalt nanoparticles onto the surface of the support which was found to significantly influence the materials in the alkylation of toluene with benzyl chloride. The high active sites accessibility of ball-milling prepared materials leads to high conversions to alkylated derivatives in short periods of time (>99 mol %, 30 min). A direct correlation acidity/activity could not be obtained in the systems, for which nanoparticle sizes and distribution could influence the observed activities. © 2018