• Energy Research
• Research Council of Finland close

A central concern for large-scale sensor networks and the Internet of Things (IoT) has been battery capacity and how to recharge it. Recent advances have pointed to a technique capable of collecting energy from radio frequency (RF) waves called radio frequency-based energy harvesting (RF-EH) as a solution for low-power networks where cables or even changing the battery is unfeasible. The technical literature addresses energy harvesting techniques as an isolated block by dealing with energy harvesting apart from the other aspects inherent to the transmitter and receiver. Thus, the energy spent on data transmission cannot be used together to charge the battery and decode information. As an extension to them, we propose here a method that enables the information to be recovered from the battery charge by designing a sensor network operating with a semanticfunctional communication framework. Moreover, we propose an event-driven sensor network in which batteries are recharged by applying the technique RF-EH. In order to evaluate system performance, we investigated event signaling, event detection, empty battery, and signaling success rates, as well as the Age of Information (AoI). We discuss how the main parameters are related to the system behavior based on a representative case study, also discussing the battery charge behavior. Numerical results corroborate the effectiveness of the proposed system.

Abstract Oxygenic photosynthesis evolved with cyanobacteria, the ancestors of plant chloroplasts. The highly oxidizing chemistry of water splitting required concomitant evolution of efficient photoprotection mechanisms to safeguard the photosynthetic machinery. The role of flavodiiron proteins (FDPs), originally called A-type flavoproteins or Flvs, in this context has only recently been appreciated. Cyanobacterial FDPs constitute a specific protein group that evolved to protect oxygenic photosynthesis. There are four FDPs in Synechocystis sp. PCC 6803 (Flv1 to Flv4). Two of them, Flv2 and Flv4, are encoded by an operon together with a Sll0218 protein. Their expression, tightly regulated by CO2 levels, is also influenced by changes in light intensity. Here we describe the overexpression of the flv4-2 operon in Synechocystis sp. PCC 6803 and demonstrate that it results in improved photochemistry of PSII. The flv4-2/OE mutant is more resistant to photoinhibition of PSII and exhibits a more oxidized state of the plastoquinone pool and reduced production of singlet oxygen compared with control strains. Results of biophysical measurements indicate that the flv4-2 operon functions in an alternative electron transfer pathway from PSII, and thus alleviates PSII excitation pressure by channeling up to 30% of PSII-originated electrons. Furthermore, intact phycobilisomes are required for stable expression of the flv4-2 operon genes and for the Flv2/Flv4 heterodimer-mediated electron transfer mechanism. The latter operates in photoprotection in a complementary way with the orange carotenoid protein-related nonphotochemical quenching. Expression of the flv4-2 operon and exchange of the D1 forms in PSII centers upon light stress, on the contrary, are mutually exclusive photoprotection strategies among cyanobacteria.

Using previously reported thermogravimetric analysis measurements, the effects of calcium and potassium on the char gasification rate of spruce wood were modeled. Spruce wood was leached of inorganic ash elements and doped with measured amounts of potassium and calcium. The wood was gasified in an isothermal thermogravimetric analysis device in CO2 where the devolatilization of the wood, char formation and char gasification all occurred inside the preheated reactor. A new method for separating the effects of devolatilization and char gasification is presented. Kinetic models were evaluated for their ability to describe the observed catalytic effects of potassium and calcium on the gasification rate. Two modified versions of the random pore model were able to accurately describe the measured conversion rates and the parameters of the kinetic models were found to be dependent on the calcium and potassium concentrations. Empirical correlations were developed to predict the char conversion rate from only the potassium and calcium concentration of the sample.

The optimization of photovoltaic solar power plants location in Atacama Desert, Chile, is presented in this study. The study considers three objectives: (1) Find sites with the highest solar energy potential, (2) determine sites with the least impact on the environment, and (3) locate the areas which produce small social impact. To solve this task, multi-criteria decision analyses (MCDAs) such as analytical hierarchy process and ordered weighted averaging were applied in a GIS environment. In addition, survey results of social impacts were analyzed and included into the decision-making process, including landscape values. The most suitable sites for solar energy projects were found near roads and power lines throughout the study area. Large suitable areas were found also from central valley from Arica and Parinacota to the north edge of Atacama region. In Atacama region, most suitable sites were found in the Andes. On the contrary, Andes were also found to have high environmental values and scenically valuable landscapes. Moderate and low suitability were found on the coast, especially in Atacama region. Factors such as slope and distance to power lines and roads influenced largely the sensitivity analysis. Area of high suitability increased by 15% when distance to roads was excluded and 18% when distance to power lines or slope was removed. MCDA-GIS method was found to be useful and applicable to the optimization of solar power plant locations in northern Chile.

The optical performance of a multilayer antireflective coating incorporating lithography-free nanostructured alumina is assessed. To this end, the performance of single-junction GaInP solar cells and four-junction GaInP/GaAs/GaInNAsSb/GaInNAsSb multijunction solar cells incorporating the nanostructured alumina is compared against the performance of similar solar cells using conventional double-layer antireflective coating. External quantum efficiency measurements for GaInP solar cells with the nanostructured coating demonstrate angle-independent operation, showing only a marginal difference at 60° incident angle. The average reflectance of the nanostructured antireflective coating is ∼3 percentage points smaller than the reflectance of the double-layer antireflective coating within the operation bandwidth of the GaInP solar cell (280-710 nm), which is equivalent of ∼0.2 mA/cm2 higher current density at AM1.5D (1000 W/m2). When used in conjunction with the four-junction solar cell, the nanostructured coating provides ∼0.8 percentage points lower average reflectance over the operation bandwidth from 280 to 1380 nm. However, it is noted that only the reflectance of the bottom GaInNAsSb junction is improved in comparison to the planar coating. In this respect, since in such solar cells the bottom junction typically is limiting the operation, the nanostructured coating would enable increasing the current density ∼0.6 mA/cm2 in comparison to the standard two-layer coating. The light-biased current-voltage measurements show that the fabrication process for the nanostructured coating does not induce notable recombination or loss mechanisms compared to the established deposition methods. Angle-dependent external quantum efficiency measurements incline that the nanostructured coating excels in oblique angles, and due to low reflectance at a 1000-1800 nm wavelength range, it is very promising for next-generation broadband multijunction solar cells with four or more junctions.

Coastal seas are highly productive systems, providing an array of ecosystem services to humankind, such as processing of nutrient effluents from land and climate regulation. However, coastal ecosystems are threatened by human-induced pressures such as climate change and eutrophication. In the coastal zone, the fluxes and transformations of nutrients and carbon sustaining coastal ecosystem functions and services are strongly regulated by benthic biological and chemical processes. Thus, to understand and quantify how coastal ecosystems respond to environmental change, mechanistic modeling of benthic biogeochemical processes is required. Here, we discuss the present model capabilities to quantitatively describe how benthic fauna drives nutrient and carbon processing in the coastal zone. There are a multitude of modeling approaches of different complexity, but a thorough mechanistic description of benthic-pelagic processes is still hampered by a fundamental lack of scientific understanding of the diverse interactions between the physical, chemical and biological processes that drive biogeochemical fluxes in the coastal zone. Especially shallow systems with long water residence times are sensitive to the activities of benthic organisms. Hence, including and improving the description of benthic biomass and metabolism in sediment diagenetic as well as ecosystem models for such systems is essential to increase our understanding of their response to environmental changes and the role of coastal sediments in nutrient and carbon cycling. Major challenges and research priorities are (1) to couple the dynamics of zoobenthic biomass and metabolism to sediment reactive-transport in models, (2) to test and validate model formulations against real-world data to better incorporate the context-dependency of processes in heterogeneous coastal areas in models and (3) to capture the role of stochastic events.

The high cost of drilling deep wells is the main barrier to the widespread exploitation of deep geothermal energy. Percussive drilling is one of the significant drilling technologies used in energy exploration projects. However, there is no good quantitative understanding of how much energy in percussive drilling is consumed in pulverization, heating, the kinetic energy of particles, acoustic emission, etc. In this study, energy efficiency is quantitatively investigated to understand the percussive drilling process better. The dynamic percussive drilling was evaluated using a modified split Hopkinson pressure bar (SHPB) system and non-contact measurements. The amount of energy dissipated in different processes and the overall energy efficiency was estimated for Kuru granite, Balmoral granite, and Kivijärvi gabbro. The energy spent on the kinetic energy Ek of fragments was evaluated using a high-speed camera, whereas the energy consumed on heat or the thermal energy Et was obtained by high-speed infrared imaging. The cracking energy Ec was measured by using the surface energy of rock and the total newly created surface areas. The results indicate that the fragment size distribution of these three rocks generally varies with the penetration speed, and the fragmentation level of these rocks increases with the penetration speed. The input energy and the energy consumption grow with the increase of the penetration speed. The proportions of Et, Ek, and Ec in the total energy consumption for these three rocks increase with the penetration speed. The energy efficiency obtained from the dynamic indentation experiments for the three rocks generally increases with the penetration speed and almost approaches a limit value when the penetration speed is high. A model is improved to describe the relationship between energy efficiency and penetration speed quantitatively. Therefore, the penetration process should be optimized to balance the high drilling efficiency and the low energy consumption.