Study of Residual Stress and Surface Morphology Changes in Al2O3 Induced by Nd:YAG Laser Irradiation

In this study, the residual stress and surface morphology changes in alumina plates by the irradiation of a Q-switched Nd:YAG laser were investigated. The results of x-ray diffraction using the sin²ψ technique show that laser irradiation induces tensile residual stresses on the surface of the plates, which increase with the increasing energy density of the laser beam. Residual stress and surface morphology are sensitive to the irradiation conditions. The surface morphology of the plates systematically changed with the laser energy density and the presence of an aluminum foil or water on the plates. The physical reasons for these changes are discussed in this article.     

An optimization approach to estimate and calibrate column water vapour for hyperspectral airborne data

The article describes a novel approach to estimate and calibrate column water vapour (CWV), a key parameter for atmospheric correction of remote-sensing data. CWV is spatially and temporally variable, and image-based methods are used for its inference. This inference, however, is affected by methodological and numeric limitations, which likely propagate to reflectance estimates. In this article, a method is proposed to estimate CWV iteratively from target surface reflectances. The method is free from assumptions for at sensor radiance-based CWV estimation methods. We consider two cases: (a) CWV is incorrectly estimated in a processing chain and (b) CWV is not estimated in a processing chain. To solve (a) we use the incorrect estimations as initial values to the proposed method during calibration. In (b), CWV is estimated without initial information. Next, we combined the two scenarios, resulting in a generic method to calibrate and estimate CWV. We utilized the hyperspectral mapper (HyMap) and airborne prism experiment (APEX) instruments for the synthetic and real data experiments, respectively. Noise levels were added to the synthetic data to simulate real imaging conditions. The real data used in this research are cloud-free scenes acquired from the airborne campaigns. For performance assessment, we compared the proposed method with two state-of-the-art methods. Our method performed better as it minimizes the absolute error close to zero, only within 8–10 iterations. It thus suits existing operational chains where the number of iterations is considerable. Finally, the method is simple to implement and can be extended to address other atmospheric trace gases.     

Energy dissipation in laser-based free form heading: a numerical approach

Cold forming generally allows the fast generation of parts with very low tolerances. In addition, mechanical properties are improved, if work hardening materials are used. Transferring the cold forming process to micro range leads to a decrease in the maximum achievable upset ratio so that the forming process becomes inefficient. Therefore, a laser-based free form heading process has been developed to generate preforms which can be calibrated in a secondary cold forming step. The achievable upset ratios reach values of several hundreds instead of 2.1 which is common for single step mechanical upsetting. In this article, heat losses arising in the material accumulation process using laser-based free form heading are analyzed and discussed. For this purpose, the process is modeled within the framework of continuum mechanics and simulated by a finite element method. By using a numerical approach, a systematic study on heat losses is performed in order to identify the influence of radiation, heat transfer due to convection and thermal conduction during laser irradiation time. The simulation results, which are validated with experimental data, show that the radiation is the most important mechanism reducing the efficiency of the accumulation process.     

Large scale fabrication of asymmetric 2D and 3D micro/nano array pattern structures using multi-beam interference lithography technique for Solar cell texturing application

Microsystem Technologies - A method for the large scale fabrication of nano/micro array patterned structure for solar Photovoltaics (PV) is demonstrated by the use of laser interference lithography...     

Overview of the potent cyanobacterial neurotoxin β-methylamino-L-alanine (BMAA) and its analytical determination

Blue-green algae are responsible for the production of different types of toxins which can be neurotoxic, hepatotoxic, cytotoxic and dermatotoxic and that can affect both aquatic and terrestrial life. Since its discovery the neurotoxin β-methylamino-L-alanine (BMAA) has been a cause for concern, being associated with the neurodegenerative disease amyotrophic lateral sclerosis/Parkinsonism–dementia complex (ALS/PDC). The initial focus was on Guam where it was observed that a high number of people were affected by the ALS/PDC complex. Subsequently, researchers were surprised to find levels of BMAA in post mortem brains from Canadian patients who also suffered from ALS/PDC. Recent research demonstrates that BMAA has been found at different levels in the aquatic food web in the brackish waters of the Baltic Sea. There is emerging evidence to suggest that sand-borne algae from Qatar can also contain BMAA. Furthermore, there is now concern because BMAA has been found not only in warmer regions of the world but also in temperate regions like Europe. The aim of this review is to focus on the methods of extraction and analysis of the neurotoxic non-protein amino acid BMAA. We also consider the neurotoxicity, aetiology, and diverse sources and routes of exposure to BMAA. In recent years, different methods have been developed for the analysis of BMAA. Some of these use HPLC-FD, UPLC-UV, UPLC-MS and LC-MS/MS using samples that have been derivatised or underivatised. To date the LC-MS/MS approach is the most widely used analytical technique as it is the most selective and sensitive method for BMAA determination.     

A network prototype for integrated production-distribution planning with non-multi-functional plants

This paper proposes a two-echelon network prototype for integrated production and distribution planning where non-multi-functional plants supply multiple types of products with limited quantities to the customers via capacitated warehouses. Four variations of the prototype, formulated as individual mixed integer programming models, are solved using the branch and bound algorithms by numerical experiments to examine the cost implications of production-distribution strategies involving single-sourcing constraints on different levels of the supply chain. Further discussions on the practicality and versatility of the proposed prototype (i.e. its ability to consider different facility locations, specialised capabilities of individual plants, safety stock levels and demand characteristics) illustrate the usefulness of the prototype to industry practitioners when making strategic and/or tactical decisions.     

Aktuelle Aktivitäten zu den europäischen Rohstoff-Initiativen

The European Initiatives manifested in the Communications of the European Commission on Raw Materials, in the Strategic Implementation Plan of the European Innovation Partnership on Raw Materials and in the 2014 Call of the European Institute for Innovation & Technology (EIT) for a Knowledge and Innovation Community (KIC) on Raw Materials lead to manifold Austrian activities on Government level and on level of the Montanuniversitaet Leoben. The ESEE Region, thus East- and Southeast Europe has a special role.     

Nanosensors for Continuous and Noninvasive Monitoring of Mesenchymal Stem Cell Osteogenic Differentiation

Assessing mesenchymal stem cell (MSC) differentiation status is crucial to verify therapeutic efficacy and optimize treatment procedures. Currently, this involves destructive methods including antibody‐based protein detection and polymerase chain reaction gene analysis, or laborious and technically challenging genetic reporters. Development of noninvasive methods for real‐time differentiation status assessment can greatly benefit MSC‐based therapies. This report introduces a nanoparticle‐based sensing platform that encapsulates two molecular beacon (MB) probes within the same biodegradable polymeric nanoparticles. One MB targets housekeeping gene glyceraldehyde‐3‐phosphate dehydrogenase (GAPDH) as an internal reference, while another detects alkaline phosphatase (ALP), a functional biomarker. Following internalization, MBs are gradually released as the nanoparticle degrades. GAPDH MBs provide a stable reference signal throughout the monitoring period (18 days) regardless of differentiation induction. Meanwhile, ALP mRNA undergoes well‐defined dynamics with peak expression observed during early stages of osteogenic differentiation. By normalizing ALP‐MB signal with GAPDH‐MB, changes in ALP expression can be monitored, to noninvasively validate osteogenic differentiation. As proof‐of‐concept, a dual‐colored nanosensor is applied to validate MSC osteogenesis on 2D culture and polycaprolactone films containing osteo‐inductive tricalcium phospate.