Detection of low levels of trichloroethylene vapor with Raman spectrometry

The response of a novel fiber-optic Raman probe to low levels of trichloroethylene (TCE) vapors is characterized. The detection limit of the current probe for TCE vapor is 34 mg/L, and the probe exhibits a fully reversible response. The probe uses an organic-polymer, low-density polyethylene to concentrate TCE vapors in the optical path of the fiber-optic Raman spectrometer. The relative standard deviation for measurement of 677 mg/L of TCE in the vapor is 0.3%.     

Characterization of laser hardened steels by laser induced ultrasonic surface waves

Ultrasonic surface waves are suitable for the characterization of surface hardened materials. This is shown on laser hardened turbine blades. The martensitic microstructure within the surface layer of surface hardened steels has a lower surface wave propagation velocity than the annealed or normalized substrate material. Because the propagation velocity depends on the ratio of layer thickness to wavelengthd/, its measurement allows the determination of the hardening depth. If the surface wave frequency is high enough, the surface wave propagates mainly within the hardened layer. A correlation of the surface wave velocity to the surface hardness has been found. Because the variation of the surface velocity in hardened steels is small, a high measurement accuracy is necessary to obtain the interesting hardening parameters with sufficient certainty. Therefore, a measuring arrangement has been developed where laser pulses, guided by optical fibers to the surface hardened structure, generate simultaneously surface wave pulses at two different positions. The two ultrasonic pulses are received by a piezoelectric transducer. The surface wave velocity is obtained from the time delay between these pulses which is determined by the cross-correlation method. To evaluate simultaneously surface waves with different penetration depths from the same signal acquisition, digital filtering has been used in connection with the cross-correlation.     

Advanced Characterization and Optimization of NiOx:Cu-SAM Hole-Transporting Bi-Layer for 23.4% Efficient Monolithic Cu(In,Ga)Se2-Perovskite Tandem Solar Cells

The performance of five hole-transporting layers (HTLs) is investigated in both single-junction perovskite and Cu(In, Ga)Se₂ (CIGSe)-perovskite tandem solar cells: nickel oxide (NiO_x,), copper-doped nickel oxide (NiO_x:Cu), NiO_x+SAM, NiO_x:Cu+SAM, and SAM, where SAM is the [2-(3,-6Dimethoxy-9H-carbazol-9yl)ethyl]phosphonic acid (MeO-2PACz) self-assembled monolayer. The performance of the devices is correlated to the charge-carrier dynamics at the HTL/perovskite interface and the limiting factors of these HTLs are analyzed by performing time-resolved and absolute photoluminescence ((Tr)PL), transient surface photovoltage (tr-SPV), and X-ray/UV photoemission spectroscopy (XPS/UPS) measurements on indium tin oxide (ITO)/HTL/perovskite and CIGSe/HTL/perovskite stacks. A high quasi-Fermi level splitting to open-circuit (QFLS-V_oc) deficit is detected for the NiO_x-based devices, attributed to electron trapping and poor hole extraction at the NiO_x-perovskite interface and a low carrier effective lifetime in the bulk of the perovskite. Simultaneously, doping the NiO_x with 2% Cu and passivating its surface with MeO-2PACz suppresses the electron trapping, enhances the holes extraction, reduces the non-radiative interfacial recombination, and improves the band alignment. Due to this superior interfacial charge-carrier dynamics, NiO_x:Cu+SAM is found to be the most suitable HTL for the monolithic CIGSe-perovskite tandem devices, enabling a power-conversion efficiency (PCE) of 23.4%, V_oc of 1.72V, and a fill factor (FF) of 71%, while the remaining four HTLs suffer from prominent V_oc and FF losses.     

A framework for implementing robotic process automation projects

Robotic process automation is a disruptive technology to automate already digital yet manual tasks and subprocesses as well as whole business processes rapidly. In contrast to other process automation technologies, robotic process automation is lightweight and only accesses the presentation layer of IT systems to mimic human behavior. Due to the novelty of robotic process automation and the varying approaches when implementing the technology, there are reports that up to 50% of robotic process automation projects fail. To tackle this issue, we use a design science research approach to develop a framework for the implementation of robotic process automation projects. We analyzed 35 reports on real-life projects to derive a preliminary sequential model. Then, we performed multiple expert interviews and workshops to validate and refine our model. The result is a framework with variable stages that offers guidelines with enough flexibility to be applicable in complex and heterogeneous corporate environments as well as for small and medium-sized companies. It is structured by the three phases of initialization, implementation, and scaling. They comprise eleven stages relevant during a project and as a continuous cycle spanning individual projects. Together they structure how to manage knowledge and support processes for the execution of robotic process automation implementation projects.

     

Laser pyrolysis in papers and patents

Journal of Intelligent Manufacturing - This paper presents a critical review of laser pyrolysis. Although this technology is almost 60 years old, in literature many researchers, both from...     

Structure and Magnetic Property Control of Copper Hydroxide Acetate by Non‐Classical Crystallization

Copper hydroxide acetate (CHA), one layered hydroxide compound with tunable magnetism, attracts great interest because of its potential applications in memory devices. However, ferromagnetism for CHA is only demonstrated by means of GPa pressure. Herein, a new method is reported, involving the combination of different crystallization pathways to control crystallization of amorphous CHA toward the formation of CHA/polymer composites with tunable magnetic properties and even a tunability that can be tested at room temperature. By using poly[(ethylene glycol)₆ methyl ether methacrylate]‐block‐poly[2‐(acetoacetoxy) ethyl methacrylate] (PEGMA‐b‐PAEMA) diblock copolymers as additives in combination with a post‐treatment process by ultracentrifugation, it is demonstrated that CHA and PEGMA‐b‐PAEMA form composites exhibiting different magnetic properties, depending on CHA in‐plane nanostructures. Analytical characterization reveals that crystallization of CHA is induced by ultracentrifugation, during which CHA nanostructures can be well controlled by changing the degrees of polymerization of the PEGMA and PAEMA blocks and their block length ratios. These findings not only present the first example of using crystallization from polymer stabilized amorphous precursors toward the generation of magnetic nanomaterials with tunable magnetism but also pave the way for the future design of functional composite materials.     

On the simulation,economic analysis,and life cycle assessment of batch-mode organic solvent recovery alternatives for the pharmaceutical industry

This study explores design alternatives for the purification and possible reuse of low-volume organic solvents waste streams in pharmaceutical manufacturing. Solvent use has a large impact on the life cycle of pharmaceutical processes, as typically 80–90% of the total mass used in the production of an active pharmaceutical ingredient is attributed to solvent use. Solvents are not consumed in pharmaceutical processes so they exit the process as waste. These waste streams are usually disposed of using incineration; therefore, generating significant life cycle emissions from disposal and replacement of virgin solvent. Solvent recovery efforts are generally limited to large-volume waste streams. However, results show that solvents in low-volume streams can also be economically recovered using a versatile multi-campaign solvent recovery skid. Three different solvent waste streams were evaluated, and 85.3% reduction in total emissions and 86.3% reduction in operating costs were achieved. Investment in the solvent recovery system was determined to have a payback period of 4.5 years and a 28% IRR over 10 years. A life cycle impact assessment shows impacts on the human health, ecosystems, and resources categories have been reduced by 82.4, 85.1, and 87.1%, respectively.     

Real‐time updating of structural mechanics models using Kalman filtering,modified constitutive relation error,and proper generalized decomposition

The paper aims at proposing a new strategy for real‐time identification or updating of structural mechanics models defined as dynamical systems. The main idea is to introduce the modified constitutive relation error concept, which is a practical tool that enables to efficiently solve identification problems with highly corrupted data, into the Kalman filtering, which is a classical framework for data assimilation. Furthermore, a PGD‐based model reduction method is performed in order to optimize capabilities of the online updating strategy. Performances of the proposed approach, in terms of robustness gain and computational cost reduction, are illustrated on several unsteady thermal applications. Copyright © 2015 John Wiley & Sons, Ltd.