Microstructure and thermal properties of dissimilar M300–CuCr1Zr alloys by multi-material laser-based powder bed fusion

Multi-material laser-based powder bed fusion (PBF-LB) allows manufacturing of parts with 3-dimensional gradient and additional functionality in a single step. This research focuses on the combination of thermally-conductive CuCr1Zr with hard M300 tool steel.Two interface configurations of M300 on CuCr1Zr and CuCr1Zr on M300 were investigated. Ultra-fine grains form at the interface due to the low mutual solubility of Cu and steel. The material mixing zone size is dependent on the configurations and tunable in the range of0.1–0.3 mm by introducing a separate set of parameters for the interface layers. Microcracks and pores mainly occur in the transition zone.Regardless of these defects, the thermal diffusivity of bimetallic parts with 50vol% of CuCr1Zr significantly increases by 70%–150%compared to pure M300. The thermal diffusivity of CuCr1Zr and the hardness of M300 steel can be enhanced simultaneously by applying the aging heat treatment.

Stiffness of In-Situ Formed Interleaving Polymeric Nanofiber-Epoxy Nanocomposites

This study proposes a facile, but precise method to back-calculate the effective modulus of nanocomposite interleaving plies. Adaptation of a conventional dry-reinforcement resin film infusion (RFI) approach allows interleaving neat epoxy layers (NE) with the epoxy-infused nanofibrous plies (XE) of constant thickness. The final cured nanocomposite laminate thus has the form (NE/XE)n, where “n” denotes the number of the repeats and enables clear distinction of the nanocomposite interlayers through the thickness. Mechanical testing of neat epoxy and laminated nanocomposite specimens can be coupled with the classical lamination theory for back-calculating in-plane elastic modulus of the individual epoxy-infused nanofibrous plies (EXE). Finite element analysis (FEA) and testing the laminated nanocomposite subject to flexural loading (3-point bending) are proposed to validate the analytically back-calculated EXE. It is shown that the FEA prediction incorporating EXE and testing for flexural modulus of (NE/XE)20 laminated nanocomposites correlate well and the results are within 5%. This finding suggests that the back-calculation scheme reported herein would be attractive for accurately determining the properties of an individual nanocomposite building block layer. The proposed framework is beneficial for modelling laminated structural composites incorporating XE-like nanocomposite interlayers.

The Variation of Microbial Communities in a Depth Profile of an Acidic,Nutrient-Poor Boreal Bog in Southwestern Finland

Natural bacterial communities impact the motility of isotopes, such as radionuclides, in the environment. As a result of post glacial crustal rebound radionuclides may escape the deep geological repository for spent nuclear fuel on Olkiluoto Island, Finland, and reach surface environments. Lastensuo Bog, a 5300-year-old raised bog in southwestern Finland, functions as analogue ecotope for bogs formed in Olkiluoto due to the crustal rebound. A core comprising the depth profile (0 - 7 m depth) of the bog including surface Sphagnum moss, peat and bottom clay was obtained using a stainless steel corer. High throughput sequencing was used to characterize the bacterial communities throughout the bog’s depth profile. A total of 12,680 bacterial Operational Taxonomic Units (OTUs) (97% sequence similarity) were detected comprising altogether 40 different bacterial phyla. Of these, 13 phyla were present at all depths, accounting for 97% - 99% of the whole bacterial community. The bacterial communities differed notably through the bog’s depth profile, dividing it into five distinct strata: 1) the Sphagnum moss layer;2) 0.5 - 3.7 m;3) 3.7 - 4.0 m;4) 5.5 - 6.0 m deep peat;5) the former seabed clay at 6.5 - 7.0 m depth. Acidobacteria, α- and γ-Proteobacteria dominated the surface community, but in the peat Acidobacteria contributed with up to 85% of the bacterial community. The estimated bacterial population density ranged between 2 × 109 and 5 × 1010 16S rRNA gene copies g-1 dry-weight peat. This study revealed that Lastensuo Bog had a highly diverse bacterial community. Most of the taxonomic groups belonged to thus far poorly characterized and uncultured bacteria with unknown physiological role. However, new insights into the distribution of bacterial taxa and their putative roles in organic carbon break down within the bog ecosystem have been obtained and an important baseline for further studies has been established.

Semantic segmentation-based semantic communication system for image transmission

With the rapid development of artificial intelligence and the widespread use of the Internet of Things, semantic communication, as an emerging communication paradigm, has been attracting great interest. Taking image transmission as an example, from the semantic communication's view, not all pixels in the images are equally important for certain receivers. The existing semantic communication systems directly perform semantic encoding and decoding on the whole image, in which the region of interest cannot be identified. In this paper, we propose a novel semantic communication system for image transmission that can distinguish between Regions Of Interest (ROI) and Regions Of Non-Interest (RONI) based on semantic segmentation, where a semantic segmentation algorithm is used to classify each pixel of the image and distinguish ROI and RONI. The system also enables high-quality transmission of ROI with lower communication overheads by transmissions through different semantic communication networks with different bandwidth requirements. An improved metric θPSNR is proposed to evaluate the transmission accuracy of the novel semantic transmission network. Experimental results show that our proposed system achieves a significant performance improvement compared with existing approaches, namely, existing semantic communication approaches and the conventional approach without semantics.

Self-Learning of Multivariate Time Series Using Perceptually Important Points

In machine learning,positive-unlabelled(PU)learning is a special case within semi-supervised learning.In positiveunlabelled learning,the training set contains some positive examples and a set of unlabelled examples from both the positive and negative classes.Positive-unlabelled learning has gained attention in many domains,especially in time-series data,in which the obtainment of labelled data is challenging.Examples which originate from the negative class are especially difficult to acquire.Self-learning is a semi-supervised method capable of PU learning in time-series data.In the self-learning approach,observations are individually added from the unlabelled data into the positive class until a stopping criterion is reached.The model is retrained after each addition with the existent labels.The main problem in self-learning is to know when to stop the learning.There are multiple,different stopping criteria in the literature,but they tend to be inaccurate or challenging to apply.This publication proposes a novel stopping criterion,which is called Peak evaluation using perceptually important points,to address this problem for time-series data.Peak evaluation using perceptually important points is exceptional,as it does not have tunable hyperparameters,which makes it easily applicable to an unsupervised setting.Simultaneously,it is flexible as it does not make any assumptions on the balance of the dataset between the positive and the negative class.

Effect of weld microstructure on brittle fracture initiation in the thermallyaged boiling water reactor pressure vessel head weld metal

Effects of the weld microstructure and inclusions on brittle fracture initiation are investigated in a thermally aged ferritic high-nickel weld of a reactor pressure vessel head from a decommissioned nuclear power plant.As-welded and reheated regions mainly consist of acicular and polygonal ferrite,respectively.Fractographic examination of Charpy V-notch impact toughness specimens reveals large inclusions(0.5-2.5μm)at the brittle fracture primary initiation sites.High impact energies were measured for the specimens in which brittle fracture was initiated from a small inclusion or an inclusion away from the V-notch.The density,geometry,and chemical composition of the primary initiation inclusions were investigated.A brittle fracture crack initiates as a microcrack either within the multiphase oxide inclusions or from the debonded interfaces between the uncracked inclusions and weld metal matrix.Primary fracture sites can be determined in all the specimens tested in the lower part of the transition curve at and below the 41-J reference impact toughness energy but not above the mentioned value because of the changes in the fracture mechanism and resulting changes in the fracture appearance.

Biopolymer Films and Coatings in Packaging Applications--A Review of Recent Developments

This review covers the recent developments in the field of biobased packaging materials. Special emphasis is placed on the barrier properties, which are crucial in terms of food packaging. The state-of-the-art of several biopolymers including pectin, starch, chitosan, xylan, galactoglucomannan, lignin and cellulose nanofibrils is discussed. As in most cases the packaging related properties of single layer biopolymer films are inadequate, the thin film coatings, such as sol-gel and ALD (atomic layer deposition), as well as the multilayer coatings are also briefly touched.

Assessment and prediction of tablet properties using transmission and backscattering Raman spectroscopy and transmission NIR spectroscopy

This study investigated whether Raman and Near Infrared(NIR) spectroscopy could predict tablet properties. Granules were produced on a continuous line by varying granulation parameters. Tableting process parameters were adjusted to obtain uniform tablet weight and thickness. Spectra were collected offline and tablet properties determined with traditional analyzing methods. Partial Least Squares(PLS) regression was used to correlate spectral information to tablet properties, but predictive models couldn’t be established. Principal component analysis(PCA) was effectively used to distinguish theophylline concentrations and hydration levels and multiple linear regression(MLR) analysis allowed insight on how granulation parameters affect granule and tablet properties.

Tribological Performance of Coated Surfaces

The fundamentals of coating tribology is presented in a generalised holistic approach to friction and wear mechanisms of coated surfaces in dry sliding contacts. It is based on a classification of the tribological contact process into macromechanical, micromechanical, tribochemical contact mechanisms and material transfer. The tribological contact process is dominated by the macromechanical mechanisms, which have been systematically analysed by using four main parameters: the coating-to-substrate hardness relationship, the film thickness, the surface roughness and the debris in the contact. In this paper special attention is given to the microlevel mechanisms, and in particular new techniques for modelling the elastic, plastic and brittle behaviour of the surface by finite element (FEM) computer simulations. The contact condition with a sphere sliding over a plate coated with a very thin hard coating is analysed. A three dimensional FEM model has been developed for calculating the first principal stress distribution in the scratch tester contact of a diamond spherical tip moving with increased load on a 2 thick titanium nitride (TiN) coated steel surface. The model is comprehensive in that sense that it considers elastic, plastic and fracture behaviour of the contact surfaces. By identifying from a scratch experiment the location of the first crack and using this as input data can the fracture toughness of the coating be determined.

Effect of probiotic Lactobacillus rhamnosus GG intervention on global serum lipidomic profiles in healthy adults

AIM: To investigate the effect of three weeks’ intervention with a probiotic Lactobacillus rhamnosus GG (LGG) bacteria on global serum lipidomic profiles and evaluate whether the changes in inflammatory variables (CRP, TNF-α and IL-6) are reflected in the global lipidomic profiles of healthy adults. METHODS: We performed UPLC/MS-based global lipidomic platform analysis of serum samples (n = 26) in a substudy of a randomised, double-blind, placebo- controlled 3-wk clinical intervention trial investigating the immunomodulatory effects of probiotics in healthy adults. RESULTS: A total of 407 lipids were identified, corresponding to 13 different lipid classes. Serum samples showed decreases in the levels of lysophosphatidylcholines (LysoGPCho), sphingomyelins (SM) and several glycerophosphatidylcholines (GPCho), while triacylglycerols (TAG) were mainly increased in the probiotic LGG group during the intervention. Among the inflammatory variables, IL-6 was moderatelyassociated by changes in global lipidomic profiles, with the top-ranked lipid associated with IL-6 being the proinflammatory LysoGPCho (20:4). There was a weak association between the lipidomic profiles and the two other inflammatory markers, TNF-α and CRP. CONCLUSION: This was the first study to investigate the effects of probiotic intervention on global lipidomic profiles in humans. There are indications that probiotic LGG intervention may lead to changes in serum global lipid profiles, as reflected in decreased GPCho, LysoGPCho and SM as well as mainly increased TAG.

Bridging mapping and simulation modelling in the ecosystem service assessments of boreal forests:effects of bioenergy production on carbon dynamics

Background:Increasing the use of forest harvest residues for bioenergy production reduces greenhouse emissions from the use of fossil fuels.However,it may also reduce carbon stocks and habitats for deadwood dependent species.Consequently,simple tools for assessing the trade-offs of alternative management practices on forest dynamics and their services to people are needed.The objectives of this study were to combine mapping and simulation modelling to investigate the effects of forest management on ecosystem services related to carbon cycle in the case of bioenergy production;and to evaluate the suitability of this approach for assessing ecosystem services at the landscape level.Stand level simulations of forest growth and carbon budget were combined with extensive multi-source forest inventory data across a southern boreal landscape in Finland.Stochastic changes in the stand age class distribution over the study region were simulated to mimic variation in management regimes.Results:The mapping framework produced reasonable estimates of the effects of forest management on a set of key ecosystem service indicators:the annual carbon stocks and fluxes of forest biomass and soil,timber and energy-wood production and the coarse woody litter production over a simulation period 2012–2100.Regular harvesting,affecting the stand age class distribution,was a key driver of the carbon stock changes at a landscape level.Extracting forest harvest residues in the final felling caused carbon loss from litter and soil,particularly with combined aboveground residue and stump harvesting.It also reduced the annual coarse woody litter production,demonstrating negative impacts on deadwood abundance and,consequently,forest biodiversity.Conclusions:The refined mapping framework was suitable for assessing ecosystem services at the landscape level.The procedure contributes to bridging the gap between ecosystem service mapping and detailed simulation modelling in boreal forests.It allows for visualizing ecosystem services as fine resolution maps to support sustainable land use planning.In the future,more detailed models and a wider variety of ecosystem service indicators could be added to develop the method.

Adaptive Matrix/Vector Gradient Algorithm for Design of IIR Filters and ARMA Models

This work describes a novel adaptive matrix/vector gradient (AMVG) algorithm for design of IIR filters and ARMA signal models. The AMVG algorithm can track to IIR filters and ARMA systems having poles also outside the unit circle. The time reversed filtering procedure was used to treat the unstable conditions. The SVD-based null space solution was used for the initialization of the AMVG algorithm. We demonstrate the feasibility of the method by designing a digital phase shifter, which adapts to complex frequency carriers in the presence of noise. We implement the half-sample delay filter and describe the envelope detector based on the Hilbert transform filter.

Reconstruction of UWB Impulse Train by Parallel Sampling of Cascaded Identical RC Filters

In this framework we present a new method for measurement of the UWB impulse train based on the parallel sampling of the cascaded identical RC filters. We show that the amplitudes and time locations of p sequential impulses can be reconstructed from simultaneous measurement of the outputs from 2p cascaded identical RC filters. The parallel sampling scheme has a wide range of applications including the detection of the ultra wideband (UWB) impulses. Due to identical analog RC filters and buffer amplifiers, the parallel sampling scheme is flexible to implement in VLSI applications.

A GIS-Based Methodology to Estimate the Regional Balance of Potential and Demand of Forest Chips

Finland’s national aim for annual consumption of forest chips is 25 terawatt hours (TWh) (equivalent to 13.5 million solid cubic metres) in combined heat and power (CHP) production and heat production in 2020. On average, the techno-economic potential of forest chips enables reaching the target at the national level. However, there is a geographical mismatch between the supply and demand regions. In this study, the regional balance of potential and demand from 2012 until 2020 was assessed using GIS-based methods. Economical, technical and ecological constraints were taken into account when different scenarios for municipality-level potentials were calculated. The forest chips’ consumption scenarios for plant-level were determined statistically (2012) or predicted (2020) by assuming that the total consumption of forest chips will reach the 13.5 Mm3. With help of procurement model, the use of different forest energy fuel types (stumps, logging residues and small-sized thinning wood) was spread to the procurement ring with the help of GIS coding. The forest chips’ regional balance map was made by subtracting the use of heat and combined heat and power plants’ (CHP) forest chips’ consumption from the municipality level potential data. The GIS-based method for balance calculation requires a significant amount of computer power but works well for local, municipality, regional and national-level balance calculations. The study showed that there are enough forest chips to supply the current and future demand when all forest energy assortments are used efficiently and in a sustainable manner. However, the results indicate that already at the present rate of forest chip consumption, in some areas there will not be any extra potential left. When consumption increases, the zero-potential area, in particular on the coast, expands. The highest free potential can be found in eastern and northern areas of Finland while the western and southern areas lack free potential.

Simulation of Structural Characteristics and Depth Filtration Elements in Interconnected Nanofibrous Membrane Based on Adaptive Image Analysis

Due to their unique structural features, electrospun membranes have gained considerable attention for use in applications where quality of depth filtration is a dominant performance factor. To elucidate the depth filtration phenomena it is important to quantify the intrinsic structural properties independent from the dynamics of transport media. Several methods have been proposed for structural characterization of such membranes. However, these methods do not meet the requirement for the quantification of intrinsic structural properties in depth filtration. This may be due to the complex influence of transport media dynamics and structural elements in the depth filtration process. In addition, the different morphological architectures of electrospun membranes present obstacles to precise quantification. This paper seeks to quantify the structural characteristics of electrospun membranes by introducing a robust image analysis technique and exploiting it to evaluate the permeation-filtration mechanism. To this end, a nanostructured fibrous network was simulated as an ideal membrane using adaptive local criteria in the image analysis. The reliability of the proposed approach was validated with measurements and comparison of structural characteristics in different morphological conditions. The results were found to be well compatible with empirical observations of perfect membrane structures. This approach, based on optimization of electrospinning parameters, may pave the way for producing optimal membrane structures for boosting the performance of electrospun membranes in end-use applications.

Effect of Climate Change on Transformers Loading Conditions in the Future Smart Grid Environment

The steady-state calculations are performed using IEC guidelines to determine the hot spot temperatures of distribution and power transformers in the worst projected Finnish environment due to long summer periods. Moreover, the effect of increase in winding resistance due to increase in ambient temperatures has been taken into account. The primary objective of the research is to investigate the possible extreme circumstances due to climate change. It is concluded that the power and distribution transformers should be progressively de-rated under such circumstances for their safe operations, which will not only prove cost-effective for utilities but also improve the reliability of the power supply to their valued customers in the challenging future smart grid environment.

Engineered Hydrophobin for Biomimetic Mineralization of Functional Calcium Carbonate Microparticles

In this study, the modified hydrophobin, engineered for biomimetic mineralization, has been employed as a structure-directing agent for mineralization of calcium carbonate. For the first time amphiphilic calcium carbonate particles have been obtained, using engineered proteins. The mineral microparticles have been characterized by optical microscopy, scanning electron microscopy (SEM) and X-ray diffraction (XRD). While mineralization in the presence of non-modified hydrophobin results in polymorph mineral structures, uniform microspheres with an average particle diameter of one micron are obtained by employing hydrophobin which has been modified with an additional ceramophilic protein sequence. Owing to the tri-functionality of the modified hydrophobin (hydrophilic, hydrophobic and ceramophilic), the obtained mineral microparticles exhibit amphiphilic properties. Potential applications are in the areas of functional fillers and pigments, like biomedical and composite materials. Pickering emulsions have been prepared as a demonstration of the emulsion-stabilizing properties of the obtained amphiphilic mineral microspheres. The structure-directing effects of the studied engineered hydrophobins are compared with those of synthetic polymers (i.e. polycarboxylates) used as crystallization and scaling inhibitors in industrial applications.

Effect of Additional Surfaces on Ordinary Portland Cement Early-Age Hydration

Early-age hydration of Ordinary Portland Cement (OPC) was studied in the presence of two additional surfaces. Additional surfaces are known to accelerate the early-age hydration of OPC. Autocatalytic reaction modelling was used to determine acceleration mechanism of additional surfaces. Heat development of the hydration was measured with semi-adiabatic calorimetry and the results were modelled with an autocatalytic reaction. Autocatalytic reaction modelling was able to determine number of initially active nucleation sites in early-age hydration. OPC hydration followed autocatalytic reaction principles throughout induction period and accelerating period. Both of the added surfaces, limestone filler and calcium-silicate-hydrate (C-S-H) coated limestone filler accelerated the early-age hydration. According to autocatalytic modelling, the C-S-H coated filler increased the number of initially active nucleation sites. Pristine limestone filler accelerated the early-age hydration by providing the additional nucleation sites throughout the early-age hydration. The difference was explained with common theories of nucleation and crystal growth. Autocatalytic model and measured calorimeter curve started to significantly deviate at the inflection point, where the reaction mode changed. The reaction mode change depended on the average particle distance. Early-age hydration, modelled as autocatalytic reaction was able to improve understanding of OPC early-age hydration and quantify the number of initially active nucleation sites. Understanding and quantifying the acceleration mechanisms in early-age hydration will aid larger utilization of supplementary cementitious materials where understanding the early-age strength development is crucial.