Techno-economic heat transfer optimization of large scale latent heat energy storage systems in solar thermal power plants

Concentrated solar power plants with integrated storage systems are key technologies for sustainable energy supply systems and reduced anthropogenic CO2-emissions. Developing technologies include direct steam generation in parabolic trough systems, which offer benefits due to higher steam temperatures and, thus, higher electrical efficiencies. However, no large scale energy storage technology is available yet. A promising option is a combined system consisting of a state-of-the art sensible molten salt storage system and a high temperature latent heat thermal energy storage system (LHTESS). This paper discusses the systematic development and optimization of heat transfer structures in LHTESS from a technological and economic point of view. Two evaluation parameters are developed in order to minimize the specific investment costs. First, the specific product costs determine the optimum equipment of the latent heat storage module, i.e. the finned tube. The second parameter reflects the interacting behavior of the LHTESS and the steam turbine during discharge. This behavior is described with a simplified power block model that couples both components

Modulation of μ‐opioid receptor activation by acidic pH is dependent on ligand structure and an ionizable amino acid residue

Background and Purpose: Adverse side effects of conventional opioids can be avoided if ligands selectively activate peripheral opioid receptors in injured tissue. Injury and inflammation are typically accompanied by acidification. In this study, we examined influences of low pH and mutation of the ionizable amino acid residue H297(6.52) on mu-opioid receptor binding and signalling induced by the mu-opioid receptor ligands fentanyl, DAMGO, and naloxone. Experimental Approach: HEK 293 cells stably transfected with mu-opioid receptors were used to study opioid ligand binding, [S-35]-GTP gamma S binding, and cAMP reduction at physiological and acidic pH. We used mu-opioid receptors mutated at H297(6.52) to A (MOR-H297(6.52)A) to delineate ligand-specific interactions with H297(6.52). Key Results: Low pH and the mutant receptor MOR-H297(6.52)A impaired naloxone binding and antagonism of cAMP reduction. In addition, DAMGO binding and G-protein activation were decreased under these conditions. Fentanyl-induced signalling was not influenced by pH and largely independent of H297(6.52). Conclusions and Implications: Our investigations indicate that low pH selectively impairs mu-opioid receptor signalling modulated by ligands capable of forming hydrogen bonds with H297(6.52). We propose that protonation of H297(6.52) at acidic pH reduces binding and subsequent signalling of such ligands. Novel agonists targeting opioid receptors in injured tissue might benefit from lack of hydrogen bond formation with H297(6.52)

Intake of silica nanoparticles by giant lipid vesicles: influence of particle size and thermodynamic membrane state

The uptake of nanoparticles into cells often involves their engulfment by the plasma membrane and a fission of the latter. Understanding the physical mechanisms underlying these uptake processes may be achieved by the investigation of simple model systems that can be compared to theoretical models. Here, we present experiments on a massive uptake of silica nanoparticles by giant unilamellar lipid vesicles (GUVs). We find that this uptake process depends on the size of the particles as well as on the thermodynamic state of the lipid membrane. Our findings are discussed in the light of several theoretical models and indicate that these models have to be extended in order to capture the interaction between nanomaterials and biological membranes correctly

Intake of silica nanoparticles by giant lipid vesicles: influence of particle size and thermodynamic membrane state

The uptake of nanoparticles into cells often involves their engulfment by the plasma membrane and a fission of the latter. Understanding the physical mechanisms underlying these uptake processes may be achieved by the investigation of simple model systems that can be compared to theoretical models. Here, we present experiments on a massive uptake of silica nanoparticles by giant unilamellar lipid vesicles (GUVs). We find that this uptake process depends on the size of the particles as well as on the thermodynamic state of the lipid membrane. Our findings are discussed in the light of several theoretical models and indicate that these models have to be extended in order to capture the interaction between nanomaterials and biological membranes correctly

Wound Healing in Mice with High-Fat Diet- or ob Gene-Induced Diabetes-Obesity Syndromes: A Comparative Study

In the past, the genetically diabetic-obese diabetes/diabetes (db/db) and obese/obese (ob/ob) mouse strains were used to investigate mechanisms of diabetes-impaired wound healing. Here we determined patterns of skin repair in genetically normal C57Bl/6J mice that were fed using a high fat diet (HFD) to induce a diabetes-obesity syndrome. Wound closure was markedly delayed in HFD-fed mice compared to mice which had received a standard chow diet (CD). Impaired wound tissue of HFD mice showed a marked prolongation of wound inflammation. Expression of vascular endothelial growth factor (VEGF) was delayed and associated with the disturbed formation of wound margin epithelia and an impaired angiogenesis in the reduced granulation tissue. Normal wound contraction was retarded and disordered. Wound disorders in obese C57Bl/6J mice were paralleled by a prominent degradation of the inhibitor of NFκB (IκB-α) in the absence of an Akt activation. By contrast to impaired wound conditions in ob/ob mice, late wounds of HFD mice did not develop a chronic inflammatory state and were epithelialized after 11 days of repair. Thus, only genetically obese and diabetic ob/ob mice finally developed chronic wounds and therefore represent a better suited experimental model to investigate diabetes-induced wound healing disorders

Gas-induced segregation in Pt-Rh alloy nanoparticles observed by in-situ Bragg coherent diffraction imaging

Bimetallic catalysts can undergo segregation or redistribution of the metals driven by oxidizing and reducing environments. Bragg coherent diffraction imaging (BCDI) was used to relate displacement fields to compositional distributions in crystalline Pt-Rh alloy nanoparticles. 3D images of internal composition showed that the radial distribution of compositions reverses partially between the surface shell and the core when gas flow changes between O2 and H2. Our observation suggests that the elemental segregation of nanoparticle catalysts should be highly active during heterogeneous catalysis and can be a controlling factor in synthesis of electrocatalysts. In addition, our study exemplifies applications of BCDI for in situ 3D imaging of internal equilibrium compositions in other bimetallic alloy nanoparticles

Modulation of G-protein activation, calcium currents and opioid receptor phosphorylation by the pH-dependent antinociceptive agonist NFEPP

N-(3-fluoro-1-phenethylpiperidine-4-yl)-N-phenyl propionamide is a newly-designed pain killer selectively activating G-protein-coupled mu-opioid receptors (MOR) in acidic injured tissues, and therefore devoid of central side effects which are typically elicited at normal pH values in healthy tissues. However, the neuronal mechanisms underlying NFEPP's antinociceptive effects were not examined in detail so far. Voltage-dependent Ca2+ channels (VDCCs) in nociceptive neurons play a major role in the generation and inhibition of pain. In this study, we focused on the effects of NFEPP on calcium currents in rat dorsal root ganglion (DRG) neurons. The inhibitory role of the G-protein subunits G(i/o) and G beta gamma on VDCCs was investigated using the blockers pertussis toxin and gallein, respectively. GTP gamma S binding, calcium signals and MOR phosphorylation were also investigated. All experiments were performed at acidic and normal pH values using NFEPP in comparison to the conventional opioid agonist fentanyl. At low pH, NFEPP produced more efficient G-protein activation in transfected HEK293 cells and significantly reduced VDCCs in depolarized DRG neurons. The latter effect was mediated by G beta gamma subunits, and NFEPP-mediated MOR phosphorylation was pH-dependent. Fentanyl's responses were not affected by pH changes. Our data indicate that NFEPP-induced MOR signaling is more effective at low pH and that the inhibition of calcium channels in DRG neurons underlies NFEPP's antinociceptive actions

Extrapolation and Prediction of User Behaviour from Wireless Home Automation Communication

Wireless home automation systems are becoming increasingly popular. They can help users save energy and increase the comfort.However, this increased convenience also comes with new attack vectors. Many available systems provide little to no security. In this paper, we explore the possibilities of passive attacks against these systems. We exemplarily investigate two real-world installations of off-the-shelf home automation systems to see what amount of information can be obtained by a passive adversary.Our results show that the systems provide no privacy. They leak information about the users' habits as well as their presence and can be abused to plan burglaries. Furthermore, we conclude that even encrypted communication does not fully protect against the attack presented here. In particular, it is still possible to predict user presence and absence even if individual actions cannot be identified

Simulating the mechanical stimulation of cells on a porous hydrogel scaffold using an FSI model to predict cell differentiation

3D-structured hydrogel scaffolds are frequently used in tissue engineering applications as they can provide a supportive and biocompatible environment for the growth and regeneration of new tissue. Hydrogel scaffolds seeded with human mesenchymal stem cells (MSCs) can be mechanically stimulated in bioreactors to promote the formation of cartilage or bone tissue. Although in vitro and in vivo experiments are necessary to understand the biological response of cells and tissues to mechanical stimulation, in silico methods are cost-effective and powerful approaches that can support these experimental investigations. In this study, we simulated the fluid-structure interaction (FSI) to predict cell differentiation on the entire surface of a 3D-structured hydrogel scaffold seeded with cells due to dynamic compressive load stimulation. The computational FSI model made it possible to simultaneously investigate the influence of both mechanical deformation and flow of the culture medium on the cells on the scaffold surface during stimulation. The transient one-way FSI model thus opens up significantly more possibilities for predicting cell differentiation in mechanically stimulated scaffolds than previous static microscale computational approaches used in mechanobiology. In a first parameter study, the impact of the amplitude of a sinusoidal compression ranging from 1% to 10% on the phenotype of cells seeded on a porous hydrogel scaffold was analyzed. The simulation results show that the number of cells differentiating into bone tissue gradually decreases with increasing compression amplitude, while differentiation into cartilage cells initially multiplied with increasing compression amplitude in the range of 2% up to 7% and then decreased. Fibrous cell differentiation was predicted from a compression of 5% and increased moderately up to a compression of 10%. At high compression amplitudes of 9% and 10%, negligible areas on the scaffold surface experienced high stimuli where no cell differentiation could occur. In summary, this study shows that simulation of the FSI system is a versatile approach in computational mechanobiology that can be used to study the effects of, for example, different scaffold designs and stimulation parameters on cell differentiation in mechanically stimulated 3D-structured scaffolds