Recent advances in heterogeneous catalytic conversion of glucose to 5-hydroxymethylfurfural via green routes

With concerns of diminishing fossil fuel reserves and environmental deterioration, great efforts have been made to explore novel approaches of efficiently utilizing bio-renewable feedstocks to produce chemicals and fuels. 5-Hydroxymethylfurfural(HMF),generated from dehydration of six-carbon ketose, is regarded as a primary and versatile renewable building block to realize the goal of production of these high valued products from renewable biomass resources transformation. In this review, we summarize the recent advances via green routes in the heterogeneous reaction system for the catalytic production of HMF from glucose conversion, and emphasize reaction pathways of these reaction approaches based on the fundamental mechanistic chemistry as well as highlight the challenges(such as separation and purification of products, reusing and regeneration of catalyst, recycling solvent) in this field.

New Hybrid Algorithm Based on BicriterionAnt for Solving Multiobjective Green Vehicle Routing Problem

The main objective of this paper is to propose a new hybrid algorithm for solving the Bi objective green vehicle routing problem (BGVRP) from the BicriterionAnt metaheuristic. The methodology used is subdivided as follows: first, we introduce data from the GVRP or instances from the literature. Second, we use the first cluster route second technique using the k-means algorithm, then we apply the BicriterionAntAPE (BicriterionAnt Adjacent Pairwise Exchange) algorithm to each cluster obtained. And finally, we make a comparative analysis of the results obtained by the case study as well as instances from the literature with some existing metaheuristics NSGA, SPEA, BicriterionAnt in order to see the performance of the new hybrid algorithm. The results show that the routes which minimize the total distance traveled by the vehicles are different from those which minimize the CO2 pollution, which can be understood by the fact that the objectives are conflicting. In this study, we also find that the optimal route reduces product CO2 by almost 7.2% compared to the worst route.

G-MER： Green Mobility Estimation- Based Routing Protocol in Wireless Sensor Network

As a core technology of Intemet of Things （loT）, Wireless Sensor Network （WSN） has become a research hotspot recently. More and more WSNs are being deployed in highly mobile environments. The fast moving sensor nodes bring significant challenges for the routing decision. In this paper, we propose an efficient logical location method, and designe a mobility estimating metric and derive a novel Green Mobility Estirmtion- based Routing protocol （G-MER） for WSNs. We also set up a full framework to evaluate its per- formance. Simulation results illustrate that G-MER achieves a fairly better perforrmnce in terrm of broadcast times and link failures than AODV. What＇s more, it decreases the mean hops by about 0.25 and reduces energy consumption by about 10% during the whole experiment. All the results show that G-MER can be effectively used in fast- moving and limited resource scenarios.

Enhanced Property of Thin Cuprous Oxide Film Prepared through Green Synthetic Route

Thin cuprous oxide films have been prepared by chemical vapor deposition(pulsed spray evaporation-chemical vapor deposition)method without post-treatment.The synthesis of cuprous oxide was produced by applying a water strategy effect.Then,the effect of water on the morphology,topology,structure,optical properties and surface composition of the obtained films has been comprehensively investigated.The results reveal that a pure phase of Cu2O was obtained.The introduction of a small quantity of water in the liquid feedstock lowers the band gap energy from 2.16 eV to 2.04 eV.This finding was mainly related to the decrease of crystallite size due to the effect of water.The topology analyses,by using atomic force microscope,also revealed that surface roughness decreases with water addition,namely more uniform covered surface.Moreover,theoretical calculations based on density functional theory method were performed to understand the adsorption and reaction behaviors of water and ethanol on the Cu2O thin film surface.Formation mechanism of the Cu2O thin film was also suggested and discussed.

A Bi-Objective Green Vehicle Routing Problem: A New Hybrid Optimization Algorithm Applied to a Newspaper Distribution

The purpose of this work is to present a methodology to provide a solution to a Bi-objective Green Vehicle Routing Problem (BGVRP). The methodology, illustrated using a case study (newspaper distribution problem) and literature Instances, was divided into three stages: Stage 1, data treatment;Stage 2, “metaheuristic approaches” (hybrid or non-hybrid), used comparatively, more specifically: NSGA-II (Non-dominated Sorting Genetic Algorithm II), MOPSO (Multi-Objective Particle Swarm Optimization), which were compared with the new approaches proposed by the authors, CWNSGA-II (Clarke and Wright’s Savings with the Non-dominated Sorting Genetic Algorithm II) and CWTSNSGA-II (Clarke and Wright’s Savings, Tabu Search and Non-dominated Sorting Genetic Algorithm II);Stage 3, analysis of the results, with a comparison of the algorithms. An optimization of 19.9% was achieved for Objective Function 1 (OF1;minimization of CO2 emissions) and consequently the same percentage for the minimization of total distance, and 87.5% for Objective Function 2 (OF2;minimization of the difference in demand). Metaheuristic approaches hybrid achieved superior results for case study and instances. In this way, the procedure presented here can bring benefits to society as it considers environmental issues and also balancing work between the routes, ensuring savings and satisfaction for the users.

Connectivity-Enhanced Route Selection and Adaptive Control for the Chevrolet Volt

The National Renewable Energy Laboratory and General Motors evaluated connectivity-enabled efficiency enhancements for the Chevrolet Volt. A high-level model was developed to predict vehicle fuel and electricity consumption based on driving characteristics and vehicle state inputs. These techniques were leveraged to optimize energy efficiency via green routing and intelligent control mode scheduling, which were evaluated using prospective driving routes between tens of thousands of real-world origin/destination pairs. The overall energy savings potential of green routing and intelligent mode scheduling was estimated at 5% and 3%, respectively. These represent substantial opportunities considering that they only require software adjustments to implement.

MoC nanocrystals confined in N-doped carbon nanosheets toward highly selective electrocatalytic nitric oxide reduction to ammonia

Electrochemical nitric oxide reduction reaction(NORR)to produce ammonia(NH3)under ambient conditions is a promising alternative to the energy and carbon-intensive Haber–Bosch approach,but its performance is still improved.Herein,molybdenum carbides(MoC)nanocrystals confined by nitrogen-doped carbon nanosheets are first designed as an efficient and durable electrocatalyst for catalyzing the reduction of NO to NH3 with maximal Faradaic efficiency of 89%±2%and a yield rate of 1,350±15μg·h^(−1)·cm^(−2) at the applied potential of−0.8 V vs.reversible hydrogen electrode(RHE)as well as high stable activity with negligible current density and NH3 yield rate decays over a 30 h continue the test.Moreover,as a proof-of-concept of Zn–NO battery,it achieves a peak power density of 1.8 mW·cm^(−2) and a large NH3 yield rate of 782±10μg·h^(−1)·cm^(−2),which are comparable to the best-reported results.Theoretical calculations reveal that the MoC(111)has a strong electronic interaction with NO molecules and thus lowering the energy barrier of the potential-determining step and suppressing hydrogen evolution kinetics.This work suggests that Mo-based materials are a powerful platform providing great opportunities to explore highly selective and active catalysts for NH3 production.

High-efficiency electrocatalytic NO reduction to NH_(3) by nanoporous VN

Electrocatalytic NO reduction reaction to generate NH_(3)under ambient conditions offers an attractive alternative to the energy-extensive Haber-Bosch route;however,the challenge still lies in the development of cost-effective and high-performance electrocatalysts.Herein,nanoporous VN film is first designed as a highly selective and stable electrocatalyst for catalyzing reduction of NO to NH_(3)with a maximal Faradaic efficiency of 85%and a peak yield rate of 1.05×10^(-7)mol·cm^(-2)·s^(-1)(corresponding to 5,140.8mg·h^(-1)·mg_(cat).^(-1))at-0.6 V vs.reversible hydrogen electrode in acid medium.Meanwhile,this catalyst maintains an excellent activity with negligible current density and NH_(3)yield rate decays over 40 h.Moreover,as a proof-of-concept of Zn-NO battery,it delivers a high power density of 2.0 mW·cm^(-2)and a large NH_(3)yield rate of 0.22×10^(-7)mol·cm^(-2)·s^(-1)(corresponding to 1,077.1mg·h^(-1)·mg_(cat).^(-1)),both of which are comparable to the best-reported results.Theoretical analyses confirm that the VN surface favors the activation and hydrogenation of NO by suppressing the hydrogen evolution.This work highlights that the electrochemical NO reduction is an eco-friendly and energy-efficient strategy to produce NH_(3).