Template synthesis of dual functional porous MoS2 nanoparticles with photothermal conversion and catalytic properties

Advanced catalysis triggered by photothermal conversion effects has aroused increasing interest due to its huge potential in environmental purification. In this work, we developed a novel approach to the fast degradation of 4 nitrophenol 4 Nip using porous MoS2 nanoparticles as catalysts, which integrate the intrinsic catalytic property of MoS2 with its photothermal conversion capability. Using assembled polystyrene b poly 2 vinylpyridine block copolymers as soft templates, various MoS2 particles were prepared, which exhibited tailored morphologies e.g., pomegranate like, hollow, and open porous structures . The photothermal conversion performance of these featured particles was compared under near infrared NIR light irradiation. Intriguingly, when these porous MoS2 particles were further employed as catalysts for the reduction of 4 Nip, the reaction rate constant was increased by a factor of 1.5 under NIR illumination. We attribute this catalytic enhancement to the open porous architecture and light to heat conversion performance of the MoS2 particles. This contribution offers new opportunities for efficient photothermal assisted catalysis

Poly ionic liquid nanovesicles via polymerization induced self assembly and their stabilization of Cu nanoparticles for tailored CO2 electroreduction

Herein, we report a straightforward, scalable synthetic route towards poly ionic liquid PIL homopolymer nanovesicles NVs with a tunable particle size of 50 to 120 nm and a shell thickness of 15 to 60 nm via one step free radical polymerization induced self assembly. By increasing monomer concentration for polymerization, their nanoscopic morphology can evolve from hollow NVs to dense spheres, and finally to directional worms, in which a multilamellar packing of PIL chains occurred in all samples. The transformation mechanism of NVs internal morphology is studied in detail by coarse grained simulations, revealing a correlation between the PIL chain length and the shell thickness of NVs. To explore their potential applications, PIL NVs with varied shell thickness are in situ functionalized with ultra small 1 amp; 8764; 3 nm in size copper nanoparticles CuNPs and employed as electrocatalysts for CO2 electroreduction. The composite electrocatalysts exhibit a 2.5 fold enhancement in selectivity towards C1 products e.g., CH4 , compared to the pristine CuNPs. This enhancement is attributed to the strong electronic interactions between the CuNPs and the surface functionalities of PIL NVs. This study casts new aspects on using nanostructured PILs as new electrocatalyst supports in CO2 conversion to C1 product

The Role of Structural Flexibility in Plasmon Driven Coupling Reactions Kinetic Limitations in the Dimerization of Nitro Benzenes

Abstract The plasmon-driven dimerization of 4-nitrothiophenol (4NTP) to 4-4′-dimercaptoazobenzene (DMAB) is a testbed for understanding bimolecular photoreactions enhanced by nanoscale metals, in particular, regarding the relevance of electron transfer and heat transfer from the metal to the molecule. By adding a methylene group between the thiol bond and the nitrophenyl, structural flexibility is added to the reactant molecule. Time-resolved surface-enhanced Raman-spectroscopy proves that this (4-nitrobenzyl)mercaptan (4NBM) molecule has a larger dimerization rate and dimerization yield than 4NTP and higher selectivity toward dimerization. X-ray photoelectron spectroscopy and density functional theory calculations show that the electron transfer prefers activation of 4NTP over 4NBM. It is concluded that the rate limiting step of this plasmonic reaction is the dimerization step, which is dramatically enhanced by the additional flexibility of the reactant. This study may serve as an example for using nanoscale metals to simultaneously provide charge carriers for bond activation and localized heat for driving bimolecular reaction steps. The molecular structure of reactants can be tuned to control the reaction kinetics

Monitoring of tool wear and surface roughness in end-milling for intelligent machining

Recently, cutting tool and product quality management in intelligent machining has been implemented by automated tool and quality monitoring and control systems. These systems utilize born features recognized in indirect signals, which reflect, on-line, the tool and quality conditions. In this research work, study was carried out to analyze the dynamic cutting signals of the end-milling process, in order to establish a force based model extracted from these signals, to monitor the end milling tool flank wear and workpiece surface roughness for intelligent machining. Experimental tests in end milling operations are carried out as a case study to verify the results of the proposed force model. The results showed that the proposed force model is an applicable method to predict the tool wear and surface roughness in end milling

Interrelationships between cutting force variation and tool wear in end-milling

Wear of a cutting edge in end-milling is a complicated process that requires a reliable technique for in process monitoring and control of the cutter performance. This paper presents an approach to examine the effect of wear variation on the magnitude of the cutting force harmonics. This approach implies a cutting force based model of end mill wear using computer simulation as function of axial depth of cut, feed rate per tooth, specific cutting pressure of work material and instantaneous angle of rotation. The results were plotted at various cutting conditions in time and frequency domains. Cutting forces in end-milling were measured using highly sensitive strain gauge dynamometer which was calibrated in static and dynamic ranges. The tool wear was measured in an off-line manner and interrelationships of cutting force harmonics and tool wear magnitude were constructed and were found comparable with the computer simulation results. Hence a cutter wear monitoring strategy is constructed

Cutting force-based adaptive neuro-fuzzy approach for accurate surface roughness prediction in end milling operation for intelligent machining

End milling is one of the most common metal removal operations encountered in industrial processes. Product quality is a critical issue as it plays a vital role in how products perform and is also a factor with great influence on manufacturing cost. Surface roughness usually serves as an indicator of product quality. During cutting, surface roughness measurement is impossible as the cutting tool is engaged with the workpiece, chip and cutting fluid. However, cutting force measurement is easier and could be used as an indirect parameter to predict surface roughness. In this research work, a correlation analysis was initially performed to determine the degree of association between cutting parameters (speed, feed rate, and depth of cut) and cutting force and surface roughness using adaptive neuro-fuzzy inference system (ANFIS) modeling. Furthermore, the cutting force values were employed to develop an ANFIS model for accurate surface roughness prediction in CNC end milling. This model provided good prediction accuracy (96.65 average accuracy) of surface roughness, indicating that the ANFIS model can accurately predict surface roughness during cutting using the cutting force signal in the intelligent machining process to achieve the required product quality and productivity

Physicians' circular migration and economic consequence for Jordan

The return of highly skilled migrants has been proofed to be a suitable instrument for reversing brain drain in developing countries. This study examines the relationship between educational attainment represented by migrants physicians' source of board and patients visits. The study focuses on evidence from Jordan since this country has a long history of skilled migration. The study analyses a sample of 267 migrants Jordanian physicians. It shows that migrant's Jordanian physicians source of education, gender, speciality and length of time spent abroad have a significant effect on their average daily income

Surface Functionalized Au Pd Nanorods with Enhanced Photothermal Conversion and Catalytic Performance

Bimetallic nanostructures comprising plasmonic and catalytic components have recently emerged as a promising approach to generate a new type of photo enhanced nanoreactors. Most designs however concentrate on plasmon induced charge separation, leaving photo generated heat as a side product. This work presents a photoreactor based on Au Pd nanorods with an optimized photothermal conversion, which aims to effectively utilize the photo generated heat to increase the rate of Pd catalyzed reactions. Dumbbell shaped Au nanorods were fabricated via a seed mediated growth method using binary surfactants. Pd clusters were selectively grown at the tips of the Au nanorods, using the zeta potential as a new synthetic parameter to indicate the surfactant remaining on the nanorod surface. The photothermal conversion of the Au Pd nanorods was improved with a thin layer of polydopamine PDA or TiO2. As a result, a 60 higher temperature increment of the dispersion compared to that for bare Au rods at the same light intensity and particle density could be achieved. The catalytic performance of the coated particles was then tested using the reduction of 4 nitrophenol as the model reaction. Under light, the PDA coated Au Pd nanorods exhibited an improved catalytic activity, increasing the reaction rate by a factor 3. An analysis of the activation energy confirmed the photoheating effect to be the dominant mechanism accelerating the reaction. Thus, the increased photothermal heating is responsible for the reaction acceleration. Interestingly, the same analysis shows a roughly 10 higher reaction rate for particles under illumination compared to under dark heating, possibly implying a crucial role of localized heat gradients at the particle surface. Finally, the coating thickness was identified as an essential parameter determining the photothermal conversion efficiency and the reaction acceleratio

Multi functionalized carbon nanotubes towards green fabrication of heterogeneous catalyst platforms with enhanced catalytic properties under NIR light irradiation

Metal carbon nanotubes CNTs have been attractive hybrid systems due to their high specific surface area and exceptional catalytic activity, but their challenging synthesis and dispersion impede their extensive applications. Herein, we report a facile and green approach towards the fabrication of metal CNT composites, which utilizes a versatile glycopeptide GP both as a stabilizer for CNTs in water and as a reducing agent for noble metal ions. The abundant hydrogen bonds in GP endow the formed GP CNTs with excellent plasticity, enabling the availability of polymorphic CNT species from dispersion to viscous paste, gel, and even to dough by increasing their concentration. The GP molecules can reduce metal precursors at room temperature without additional reducing agents, enabling the in situ immobilization of metal nanoparticles e.g. Au, Ag, Pt, and Pd on the CNT surface. The combination of the excellent catalytic properties of Pd particles with photothermal conversion capability of CNTs makes the Pd CNT composite a promising catalyst for the fast degradation of organic pollutants, as demonstrated by a model catalytic reaction using 4 nitrophenol 4 NP . The conversion of 4 NP using the Pd CNT composite as the catalyst has increased by 1.6 fold under near infrared light illumination, benefiting from the strong light to heat conversion effect of CNTs. Our proposed strategy opens a new avenue for the synthesis of CNT composites as a sustainable and versatile catalyst platfor