Showing papers by "Stevens Institute of Technology published in 2022"

Inclusive wealth index measuring sustainable development potentials for Chinese cities

Abstract: The UN Sustainable Development Goals (SDGs) are the blueprint to achieve a better and more sustainable future. To achieve the goal, tracking progress — not just on a national level, but locally — is crucial to guide future policy development. While sustainability assessment at the national evel is quite advanced in China, similar assessments focusing at the regional or even at the city-level are currently lacking. Here, we advanced the Inclusive Wealth Index (IWI) framework, which is firstly proposed by the United Nations Development Programme, through taking water wealth into account and adjusting the variable based on data availability. Then we investigate the sustainability performance of 210 cities in China in 2016 via the advanced version of the IWI framework. The analysis makes a holistic assessment based on produced, human, and natural capital, as well as considering heterogeneities in economy, social, and environmental conditions across these cities. We find that cities clustered in the eastern parts of China are characterized by high levels of sustainability performance and increasing capacities for sustainability, largely driven by their high quality and quantity of human capital. In comparison, the western cities have a large amount of low-skilled human capital and low levels of produced capital, which determines their low sustainability performance. Cities clustered in the north are heavily dependent on low value-added products and resource-intensive industries. Furthermore, we make projections of the IWI and its three components for different cities from 2020 to 2030, referring to the index systems presented in city planning which describe the development speed of income, education, fixed asset investment, forests etc. In the future, cities in central and western clusters show considerable potential for increasing IWI per capita, whereas cities with a dominant energy sector in the north would face declining capacity for sustainability due to the exhaustion of fossil fuels and raw materials. By fully taking account of and adapting to local circumstances, we tailor-design pathways for different types of cities to grow their sustainability potentials. Those resources-dependent cities in the north could avoid the impending decline by gradually developing their human and produced capital while abandoning their resource dependency. Our study contributes to city-level sustainable development in China through the lens of per capita IWI and the potential future dynamics of changing compositions in their capital.

Electromagnetic interference shielding epoxy composites with satisfactory thermal conductivity and electrical insulation performance enabled by low-melting-point alloy layered structure

Abstract: Nowadays, electronic packaging materials requires electrical insulation, heat conduction and electromagnetic interference (EMI) shielding performance. With the inspiration raised by Janus materials, introducing low-melting-point alloy (LMPA) layered structure in epoxy resin is potential method to acquiring satisfying properties. The layered structure is originated from LMPA particles self-sedimentation and closely stacking. Meanwhile, LMPA particles are coated by epoxy resin that could remain the overall electrical insulation. When loading of 20 vol% LMPA, composite obtained thermal conductivity 1.23 W/mK (the LMPA side), total EMI shielding value of 35.56 dB at 30 GHz, and electrical conductivity of 5.00 × 10−8 S/cm. Further, the introduction of boron nitride nanosheet (BNNS) into the composites could promote isotropic heat conduction and improve the electrical insulation. This paper has provided novel LMPA layered structure, showing great promise for applications of electronic packaging materials with heat conduction, electrical insulation and EMI shielding properties.

The role of carbon capture, utilization and storage in realizing China's carbon neutrality: A source-sink matching analysis for existing coal-fired power plants

Abstract: China's carbon neutrality target before 2060 requires a significant CO2 emissions reduction for the power industry. The application of carbon capture, utilization and storage (CCUS) technology in coal-fired power plants (CFPPs) can significantly reduce the CO2 emissions while avoiding stranded assets loss; however, its contribution to carbon neutrality remains unclear. Based on a CCUS source-sink matching analysis, this paper investigates the role of CO2 emissions reduction of existing CFPPs in realizing China's carbon neutrality. This research yielded several important findings. (1) During 2020–2060, China's existing 584 CFPPs (670 GW) will totally lock in associated CO2 emissions of 60.87 Gt CO2, and have the CCUS retrofitting potential of 136–560 GW, contributing to the cumulative CO2 emissions reduction of 5.46–38.48 Gt depending on different deployment time (2025, 2030, and 2035) and maximum transport distance (100 km, 250 km, and 800 km); (2) The best window for retrofitting China's existing CFPPs is quite short and will soon be closed, because the cumulative mitigation potential will drop by 3.76–17.14 Gt (over 40%) if the deployment time is delayed by 10 years from 2025; (3) The geographical consistency of matched CFPPs and storage sites provides great opportunities for the development of CCUS clusters in Bohai Bay Basin, South Huabei Basin, Subei Basin, Songliao Basin, and Junggar Basin; (4) Jiangsu, Henan, Anhui, Hebei, Xinjiang, Heilongjiang, and Tianjin are identified as the highest priority for large-scale CCUS deployment considering that they have low-cost opportunities for CO2 transportation; (5) CFPPs in Heilongjiang, Shanxi and Jilin are more sensitive to the injection rate capacity of nearby storage sites; (6) 300 km are highly suggested to be the upper limit of transport distance especially for those CFPPs targeting deep saline aquifers (DSA) sites. This study provides low-cost CCUS opportunities for provinces and even power plants, as well as support government policymaking, especially in the appropriate length of onshore pipelines and the locations of CCUS hubs.

The role of carbon capture, utilization and storage in realizing China's carbon neutrality: A source-sink matching analysis for existing coal-fired power plants

Abstract: China's carbon neutrality target before 2060 requires a significant CO2 emissions reduction for the power industry. The application of carbon capture, utilization and storage (CCUS) technology in coal-fired power plants (CFPPs) can significantly reduce the CO2 emissions while avoiding stranded assets loss; however, its contribution to carbon neutrality remains unclear. Based on a CCUS source-sink matching analysis, this paper investigates the role of CO2 emissions reduction of existing CFPPs in realizing China's carbon neutrality. This research yielded several important findings. (1) During 2020–2060, China's existing 584 CFPPs (670 GW) will totally lock in associated CO2 emissions of 60.87 Gt CO2, and have the CCUS retrofitting potential of 136–560 GW, contributing to the cumulative CO2 emissions reduction of 5.46–38.48 Gt depending on different deployment time (2025, 2030, and 2035) and maximum transport distance (100 km, 250 km, and 800 km); (2) The best window for retrofitting China's existing CFPPs is quite short and will soon be closed, because the cumulative mitigation potential will drop by 3.76–17.14 Gt (over 40%) if the deployment time is delayed by 10 years from 2025; (3) The geographical consistency of matched CFPPs and storage sites provides great opportunities for the development of CCUS clusters in Bohai Bay Basin, South Huabei Basin, Subei Basin, Songliao Basin, and Junggar Basin; (4) Jiangsu, Henan, Anhui, Hebei, Xinjiang, Heilongjiang, and Tianjin are identified as the highest priority for large-scale CCUS deployment considering that they have low-cost opportunities for CO2 transportation; (5) CFPPs in Heilongjiang, Shanxi and Jilin are more sensitive to the injection rate capacity of nearby storage sites; (6) 300 km are highly suggested to be the upper limit of transport distance especially for those CFPPs targeting deep saline aquifers (DSA) sites. This study provides low-cost CCUS opportunities for provinces and even power plants, as well as support government policymaking, especially in the appropriate length of onshore pipelines and the locations of CCUS hubs.

MDA + RRT: A general approach for resolving the problem of angle constraint for hyper-redundant manipulator

Abstract: • The MDA + RRT algorithms guarantee that planned path satisfies the constraint of angle. • Compared with other algorithms, this algorithm does not increase the computation amount. • The feasibility and optimization of MDA + RRT are preferable to the corresponding RRT. • This method is a universal method that can be associated with any kind of RRT algorithm. In this paper, a cable-driven hyper-redundant manipulator with 17 degrees of freedom is presented for narrow and complex environments firstly. Based on the mechanical structure, the MDA + RRT algorithms is proposed for path planning considering the maximum deflection angle of joint. First, the transformation relationship between the path parameters and manipulator parameters is obtained through the theorem of sine of triangles and two extreme points, which can convert limitation of the deflection angle of the joint to the limitation of the deflection angle of the path. Then, three corresponding improved algorithms are proposed: MDA-RRT, MDA-RRT*, MDA-QRRT* on the basis of the traditional RRT, RRT* and Q-RRT* algorithms. Finally, six algorithms are applied to plan the path of avoiding three different obstacles respectively by simulation. The results demonstrate that, three improved algorithms can guarantee that the planned path satisfies the constraint of deflection angle of joint without increasing the computational amount compared with the three traditional algorithms, only by limiting the selection range of the next random vertex. Among the six algorithms, the feasibility and optimization of the MDA-QRRT* algorithm are the best and the feasibility and optimization of the three improved algorithms are also better than the corresponding traditional algorithms.

Propane Dehydrogenation to Propylene and Propylene Adsorption on Ni and Ni‐Sn Catalysts

Abstract: Temperature programmed reaction (TPR) measurements with propane over silica-supported Ni, Ni−Sn and Sn catalysts show that the reaction products change significantly from mostly methane, hydrogen and surface carbon over Ni to propylene and hydrogen over Ni−Sn. Propylene formation over Ni−Sn starts at a moderate temperature of 630 K. Since the activity of Sn by itself is low, Sn serves as a promoter for Ni. The promoter effects are attributed to a lower adsorption energy of molecularly adsorbed propylene and suppression of propylidyne formation on Ni−Sn based on temperature programmed desorption (TPD) and infrared reflection absorption spectroscopy (IRAS) measurements as well as density functional theory (DFT) calculations for propylene adsorption on Ni(110) and c(2×2)-Sn/Ni(110) single-crystal surfaces. On Ni, propylene forms a π-bonded structure with ν(C=C) at 1500 cm−1, which desorbs at 170 K, and a di-σ-bonded structure with ν(C=C) at 1416 cm−1, which desorbs at 245 K. The di-σ-bonded structure is asymmetric, with the methylene C atom being in the middle of the Ni−Ni bridge site, and the methylidyne C atom being above one of these Ni atoms. Therefore, this structure can also be characterized as a hybrid between di-σ- and π-bonded structures. Only a fraction of propylene desorbs from Ni because propylene can convert into propylidyne, which decomposes further. In contrast, propylene forms only a π-bonded structure on Ni−Sn with ν(C=C) at 1506 cm−1, which desorbs at 125 K. The low stability of this structure enables propylene to desorb fully, resulting in high reaction selectivity in propane dehydrogenation to propylene over the Ni−Sn catalyst.

Effective prediction of soil organic matter by deep SVD concatenation using FT-NIR spectroscopy

Abstract: Soil organic matters (SOM), specifically carbon and nitrogen, bring numerous benefits to soil’s physical and chemical properties. In this paper, we employ spectral data obtained by Fourier transform near-infrared (FT-NIR) spectroscopy to predict the content of organic carbon (OC) and total nitrogen (TN) in mineral soils. To address the limitation generated by massive hyperparameters on convolution neural network (CNN), we substitute using a technique named SVD concatenation to learn features. The proposed model combines the layers of fully connected and regression to complete the prediction task. We abbreviate it as SVD-CNN, which is capable provide a multi-tasks output simultaneously. In experiments, we study the prediction performances of SVD-CNN on two datasets of FT-NIR and LUCAS 2009 topsoil. Based on different situations, the highest performance of R2 achieves 0.8891 for OC and 0.9048 for TN on the FT-NIR dataset. Similarly, the most prominent results on the LUCAS 2009 topsoil dataset are R2 = 0.9304, RMSE = 3.6014 for OC and R2 = 0.9319, RMSE = 0.2733 for TN. Furthermore, we also evaluate the results obtained by solely using SVD concatenation, which reveals SVD-CNN performs a better generalization ability.