Abstract

Lead sulfide quantum dots solar cells (PbS QDSCs) have recently received substantial attention due to their
unparalleled photoelectric properties that can lead to a new record theoretical efficiency in thin film photovoltaic devices. However, the high voltage losses of PbS QDSCs induced by non-radiative recombination
losses bring about the low device performance. In this study, a real planar heterojunction PbS QD-based solar cell structure of FTO/PbS-EMII/PbS-EDT/Au is successfully simulated and then theoretically analyzed
the effects of these determining factors on device performance via drift-diffusion modeling. After modulating these factors, a new device is finalized with defect density (Nt) of 10^15 cm^-3
in absorber layer and acceptor density (NA) of 10^18 cm^-3 in hole transport material (HTM) as well as surface recombination velocity of 10 cms^-1 at absorber/HTM interface, which can deliver a power conversion efficiency (PCE) of 17.08%, with a 27.21% improvement in open-circuit voltage (VOC). This method used in this study can provide access guidelines and accelerate the efficiency improvements in PbS QDSCs.

Abstract

As a clean energy carrier, hydrogen has attracted extensive international attention. Hydrogen liquefaction is the key solution of large-scale utilization of hydrogen energy. How to realize the high-efficiency and low-cost liquefaction of hydrogen is one of the key technologies that need to be solved urgently. In the current mainstream hydrogen liquefaction technology, the high-speed rotating turbine may have an adverse impact on the stable operation of the bearing. Therefore, the supersonic two-phase expander in liquid hydrogen temperature zone is innovatively employed for the first time to complete expansion refrigeration, condensation phase change, gas-liquid separation and pressure recovery in a compact space. It has the advantages of gas-liquid two-phase operation, direct liquefaction, easy high power, simple structure and low processing cost. In the hydrogen supersonic two-phase expander, Laval nozzle is the key component. The main research contents in this paper include: (1) Establish the design criteria of hydrogen Laval nozzles. (2) The design law of hydrogen Laval nozzles under different working conditions. (3) The cooling characteristics of hydrogen Laval nozzles under different operating conditions. This paper preliminarily investigates the liquefaction possibility of supersonic two-phase expansion refrigeration technology in liquid hydrogen temperature region, and supports the development of new hydrogen liquefaction technology. It has important strategic value for promoting the realization of carbon neutralization goal in clean energy industry.

Abstract

This paper employs the robot application data from the International Federation of Robotics and China’s micro firm-level data to empirically investigate the impact of artificial intelligence on the energy efficiency of firms. Artificial intelligence has a positive and significant impact on improving Chinese firms’ energy efficiency. Controlling the endogeneity issues, the results show robust. Artificial intelligence affects the energy consumption of enterprises through scale, structural, and efficiency effects. Structural and efficiency effects are greater than the impact of scale effects. Therefore, artificial intelligence saves energy consumption and improves energy efficiency.

Abstract

The salient question addressed in this work is whether and how photovoltaic-biased photoelectro-catalysis(PV-PEC) can fairly and practically beat photovoltaic-powered electrocatalysis (PV-EC) for solar-driven carbon dioxide reduction (CO2RR). First, it was argued that to fairly evaluate PV-PEC and PV-EC CO2RR approaches in terms of techno-economy, the two devices should be driven by the same PV cell and produce the same group of products for the same series of Faradaic efficiency for each product. For this condition, PV-PEC CO2RR was shown to surprisingly have higher solar-to-chemical conversion efficiency, and thereby more competitive, than PV-EC. This non-trivial performance was achieved by leveraging novel design of light management presented in this work and careful choice of PV and PEC cells achievable in literature. Furthermore, the framework generalized in this work is also applicable to other solar-driven catalytic processes with various different products such as productions of H2O2 by water oxidation and ammonia by nitrogen fixation.

Abstract

Plasmonic photocatalysts provide means to efficient solar water splitting. Recently, researchers proposed that high-energy hot carriers generated by plasmon resonance can be transferred directly to the adsorbates, driving photochemistry, which differs from the previous indirect charge transfer forming electron-hole pairs. This study analysed underlying mechanism of charge transition channel in plasmon-driven photochemistry at the atomic scale, and evidence was provided for distinguishing between different modes of charge transfer. A specific example, where a cluster of six gold atoms interacts with one water molecule, was investigated. Based on combined density functional theory (DFT), Linear-Response time-dependent density functional (LR-TDDFT) and Ehrenfest dynamics simulations, the results revealed that hot electrons selectively transfer to high-energy unoccupied orbitals through indirect single-particle excitations or direct plasmon decay excitations. Direct transition was more conducive to photochemical reactions due to its higher energy.

Abstract

Reducing water flooding and enhancing oxygen transport in the gas diffusion layer (GDL) of proton exchange membrane fuel cells are of great importance for optimizing cell performance. In this study, a pore-scale model based on the lattice Boltzmann method is proposed, which considers two-phase flow, oxygen diffusion and electrochemical reaction. The pore-scale model is then adopted to explore multiphase reactive transport processes in the GDL. Effects of compression on the liquid water saturation and current density are explored. It is found that, by increasing the compression ratio from 0.2 to 0.4, the current density increases by 4.7%, with obvious relieve of the water flooding under the rib and increment of the number of reaction sites under the gas channel. Besides, the results demonstrate that while reducing the total saturation in the GDL is important, decreasing the local saturation near the interface of the microporous layer/GDL is also crucial for enhancing cell performance. The coupled method can directly reveal the effects of GDL compression on water flooding and oxygen reactive transport, which provides a new insight for optimizing cell performance.

Abstract

The influence of clay minerals in marine sediments – strong interactions between clay particles, water and CO2 hydrate – on hydrate-based carbon sequestration has long been a controversial topic, hampered in part by a lack of experimental evidence. In this study, we investigated experimentally and morphologically the effect of clay minerals on the nucleation and growth kinetics of CO2 hydrate in sodium montmorillonite (Na-MMT) suspensions with mass fractions ranging from 0 wt% – 10.0 wt%. The results indicated that Na-MMT greatly reduced the induction time tind by ~77%. While, the average growth rate (NR20) of CO2 hydrate was reduced by ~70% in high Na-MMT mass fraction systems (>5.0 wt%). Furthermore, significant morphological changes were identified, which were in accordance with the growth kinetics. The flakes-corolla lobes-like hydrate rapidly rises up toward spreading growth across the gas-liquid interface to the gas phase space and then extends down into bulk suspension. The clay induces significant changes in hydrate morphology, which results in the upward water migration, hydrate-clay stratification and the growth of densely packed hydrate particles.

Abstract

Lithium metal is a promising negative electrode material that has received extensive attention owing to its ultrahigh theoretical specific capacity (3860 mAh g−1) and extremely low standard electrode potential (−3.04 V vs standard hydrogen electrode). However, the formation of lithium dendrite and the unstable interface between solid electrolyte and lithium metal have hindered the application of lithium metal in sulfide-based all-solid-state batteries. In this work, a LiAlO2 interface layer is coated on the surface of lithium metal through magnetic sputtering method. As LiAlO2 can function as a good Li-ion conductor but an electronic insulator, the LiAlO2 interface layer can effectively suppress the severe interface reaction between lithium metal and the Li10GeP2S12 solid electrolyte. The Li@LiAlO2/Li10GeP2S12/Li@LiAlO2 symmetric cell was stably cycled for 3000 h with a low overpotential of 200 mV at 0.1 mA cm−2 and 0.1 mAh cm−2. Moreover, unlike the rapid capacity decay of the Li/Li10GeP2S12/LiCoO2@LiNbO3 full cell, the Li@LiAlO2/Li10GeP2S12/LiCoO2@LiNbO3 full cell remained stable for 96 cycles with a high reversible capacity of 115 mAh g−1.

Abstract

The power sector plays a pivotal role in China’s carbon peak and carbon neutrality targets. To build a low-carbon power system, it is important to develop wind and solar. This study aims to evaluate the economic impacts of the newly launched renewable portfolio standard in 2030 in China using a cost minimization model and an input-output model. The results show that to accomplish the renewable electricity portfolio standard in 2030, the installed wind and solar capacity will have to reach 1451.9 gigawatts (GW) in 2030. The Northeast, Northwest, and North regions will deploy the most installed capacity, and Inner Mongolia will take on the most renewable energy generation tasks. The annual cost of wind and solar development is expected to be 506.6 billion yuan in 2030, 94.7% of which are new construction costs and storage costs. Renewable energy growth will result in a 5.4-cent (RMB) per kWh rise in the national average electricity price compared to 2019, and Heilongjiang, Gansu, and Shanxi are the most affected. The rapid development of renewable electricity in the next decade will increase the Consumer Price Index (CPI) by 0.4%, Producer Price Index (PPI) by 0.9%, and Gross Domestic Product (GDP) deflator by 0.5% in 2030. Based on the results, we propose to improve the electricity market mechanisms, enhance the electricity transmission stability, and develop policies appropriate to local conditions.

Abstract

With the continuous promotion of the carbon peak emissions and carbon neutralization strategies, higher demands are placed on engine economic performance. Virtual sensors as an online information collection technology can be used to control various performance indicators of engines. Here is an example of ISFC to represent the engine performance prediction. In this paper, the feasibility of three machine learning methods, Artificial Neural Network (ANN), Random Forest (RF), and Support Vector Regression (SVR), for predicting fuel consumption applications are explored. Firstly, a calibrated engine one-dimensional (1D) model is constructed. Then, the 1D model generates a dataset with engine load, engine speed and spark time, and indicative specific fuel consumption (ISFC) as an output, for the training of machine learning methods. The performance of different algorithms was compared using the coefficient of determination (R2), the root-mean-square error (RMSE), and the mean absolute percentage error (MAPE) as evaluation metrics. By comparing test dataset prediction and map prediction, RF has a large prediction error at boundary operation conditions and ANN sometimes has a relative error of more than 10%. SVR performs well in each statistical index and map prediction, and therefore it is an algorithm that can be used by virtual sensors.