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In the relentless pursuit of sustainable energy solutions, this study pioneers an innovative approach to integrating thermoelectric generators (TEGs) and photovoltaic (PV) modules within hybrid systems. Uniquely, it employs neural networks for an exhaustive analysis of a plethora of parameters, including a diverse spectrum of semiconductor materials, cooling film coefficients, TE leg dimensions, ambient temperature, wind speed, and PV emissivity. Leveraging a rich dataset, the neural network is meticulously trained, revealing intricate interdependencies among parameters and their consequential impact on power generation and the efficiencies of TEG, PV, and integrated PV-TE systems. Notably, the hybrid system witnesses a striking 23.1% augmentation in power output, escalating from 0.26 W to 0.32 W, and a 20% ascent in efficiency, from 14.68% to 17.62%. This groundbreaking research illuminates the transformative potential of integrating TEGs and PV modules and the paramountcy of multifaceted parameter optimization. Moreover, it exemplifies the deployment of machine learning as a powerful tool for enhancing hybrid energy systems. This study, thus, stands as a beacon, heralding a new chapter in sustainable energy research and propelling further innovations in hybrid system design and optimization. Through its novel approach, it contributes indispensably to the arsenal of clean energy solutions.

Thermal pyrolysis of Thai Napier grass, cassava stalk and rice straw were studied thermogravimetrically, which was followed by a kinetic analysis assuming multiple kinetic schemes and a distributed activation energy model (DAEM) with reaction order n = 1 and n ? 1. The results showed that the DAEM described well the experimental data. The assumption of multiple kinetic schemes appeared more reasonable than that of similar studies reported in the literature assuming a single kinetic scheme. Consequently, the kinetic parameters extracted from the present study are more realistic and within reasonable ranges. Overall, the activation energies are within 31.6–223.53 kJ mol-1. The reaction orders are within 1.02–1.32 for the assumption of n ? 1.

Hydrogen has emerged its importance for decarbonization to approach net-zero emissions in 2050. This study aims to develop three highly-porous Ni-Cu/Al2O3 catalysts (Ni-to-Cu weight ratio = 10 %, 20 %, and 30 %) for hydrogen production from the steam reforming of “Green” methanol (or bio-methanol). The prepared catalysts require no organic templates, thereby efficiently reducing unnecessary costs. With Taguchi orthogonal array design and analysis of variance (ANOVA), the impacts of selected operating factors on hydrogen productivity under ultrasonic sprays are investigated. The results reveal that the carrier gas flow rate is the most influential factor in H2 yield at the steam-to-methanol molar ratio (S/C) of 1.5, whereas the temperature is the most impactful factor at S/C = 2.0. The regression between the Taguchi effect value and the ANOVA F value develops a strong linear relationship. The optimal experimental conditions of Ni-Cu(30 %)/Al2O3, reaction temperature of 300 °C, N2 flow rate of 1,000 mL⋅min−1, and S/C = 2.0, achieve 100 % methanol conversion, 39.74 vol% H2 concentration in the product gas, and 2.93 mol⋅(mol CH3OH)-1 H2 yield. Thes data also show superior performance compared to those in the literature. In long-term stability tests, the prepared catalysts also exhibit high stability and effectiveness commensurate with commercialized Cu-based catalysts.

In this work, a novel Ni–Cu/Al2O3 catalyst is used to trigger the partial oxidation of methanol (POM) for hydrogen production. This reaction system also employed ultrasonic sprays to aid in dispersing methanol fuel. The prepared catalyst is analyzed by scanning electron microscope (SEM), energy-dispersive X-ray (EDX) spectroscopy, and X-ray diffraction (XRD) to explore the catalyst's surface structure, elemental composition, and physical structure, respectively. The Box-Behnken design (BBD) of response surface methodology (RSM) is utilized for experimental design to achieve process optimization. The operating parameters comprise the O2/C molar ratio (0.5–0.7), preheating temperature (150–250 °C), and weight percent (wt%) of Ni (10–30%) in the catalyst. The results show that methanol conversion is 100% in all the operating conditions, while the reaction temperature for H2 production ranges from 160 to 750 °C, stemming from heat released by POM. The significance and suitability of operating conditions are also analyzed by analysis of variance (ANOVA). It indicates that the highest H2 yield is 2 mol (mol CH3OH)−1, occurring at O2/C = 0.5, preheating temperature = 150 °C, and Ni wt% = 10. Compared with the commercial h-BN-Pt/Al2O3 catalyst, the prepared Ni–Cu/Al2O3 catalysts have higher activity for H2 production. The O2/C ratio is the most influential factor in the H2 yield. Moreover, the interaction of the O2/C ratio and Ni content is sound, reflecting that changing Ni content in the catalyst will affect the trend of H2 yield under each O2/C.

For proton exchange membrane fuel cells (PEMFCs), the distribution of reactant streams in the reactor is critical to their efficiency. This study aims to investigate the optimal design of the inlet/outlet flow channel in the fuel cell stack with different geometric dimensions of the tube and intermediate zones (IZ). The tube-to-IZ length ratio, the IZ width, and the tube diameter are adjusted to optimize the geometric dimensions for the highest pressure uniformity. Four different methods, including the Taguchi method, analysis of variance (ANOVA), neural network (NN), and multiple adaptive regression splines (MARS), are used in the analyses. The results indicate the tube diameter is the most impactive one among the three factors to improve the pressure uniformity. The analysis suggests that the optimal geometric design is the tube-to-IZ length ratio of 9, the IZ width of 14 mm, and the tube diameter of 9 mm with the pressure uniformity of 0.529. The relative errors of the predicted pressure uniformity values by NN and MARS under the optimal design are 1.62% and 3.89%, respectively. This reveals that NN and MARS can accurately predict the pressure uniformity, and are promising tools for the design of PEMFCs.

International audience

Hydrogen sourced from energy recovery processes and conversion of waste materials is a method of providing both a clean fuel and a sustainable waste management alternative to landfill and incineration. The question is whether waste-to–hydrogen can become part of the zero-carbon future energy mix and serve as one of the cleaner hydrogen sources which is economically viable and environmentally friendly. This work critically assessed the potential of waste as a source of hydrogen production via various thermochemical (gasification and pyrolysis) and biochemical (fermentation and photolysis) processes. Research has shown hydrogen production yields of 33.6 mol/kg and hydrogen concentrations of 82% from mixed waste feedstock gasification. Biochemical methods such as fermentation can produce hydrogen up to 418.6 mL/g. Factors including feedstock quality, process requirements and technology availability were reviewed to guide technology selection and system design. Current technology status and bottlenecks were discussed to shape future development priorities. These bottlenecks include expensive production and operation processes, heterogeneous feedstock, low process efficiencies, inadequate management and logistics, and lack of policy support. Improvements to hydrogen yields and production rates are related to feedstock processing and advanced energy efficiency processes such as torrefaction of feedstock which has shown thermal efficiency of gasification up to 4 MJ/kg. This will affect the economic feasibility and concerns around required improvements to bring the costs down to allow waste to viewed as a serious competitor for hydrogen production. Recommendations were also made for financially competitive waste-to-hydrogen development to be part of a combined solution for future energy needs.

The most extensively used sunscreen protecting agent, Ensulizole, has been proven to exhibit hormone disrupting effects. To establish efficient processes to destruct Ensulizole in water, SO4•−-involved advanced oxidation processes using monopersulfate (MPS) seem useful. Since cobalt (Co) is the most capable of metal for activating MPS, Co3O4 appears as a promising heterogeneous catalyst for activating MPS to degrade Ensulizole. As catalytic activities of metal oxide catalysts are strongly associated with their morphologies, and surficial properties, nanoscale Co3O4 with functional nanostructures would be expected as advantageous catalysts for activating MPS. Therefore, three Co3O4 materials with distinct nanostructures and shapes were fabricated in this study, including Co3O4 cone ball (COCB), Co3O4 plate lump (COPL), and Co3O4 needle sheaf (CONS). Their surficial properties are also noticeably distinct with different fractions of Co2+, and Co3+, various oxygen vacancies, textural features and surface defects. Through comparing these three nanostructured Co3O4 for activating MPS to degrade Ensulizole, CONS exhibits the tremendously higher catalytic activity than COCB and COPL for activating MPS to eliminate Ensulizole completely and rapidly. The Ea value of Ensulizole degradation of CONS is also significantly low as 9.8 kJ/mol, which is the lowest Ea ever reported in literatures. CONS could also retain its catalytic activities over 5 continuous cycles to rapidly degrade Ensulizole. The activation mechanism of MPS by CONS and Ensulizole degradation pathway are also comprehensively elucidated via experimental evidences and the theoretical calculation to offer insightful information of development of Co-based heterogeneous catalysts for Ensulizole degradation.

International audience

Potassium is a natural catalyst in biomass thermochemical conversion and plays an essential role in plant's growth. To figure out the catalytic effects of potassium on the thermochemical behaviors of biomass, the pyrolysis, combustion, and torrefaction characteristics of rubber wood are comprehensively studied using a thermogravimetric analyzer where the biomass is impregnated by potassium carbonate (K2CO3) at different concentrations. The impregnated potassium is clearly exhibited in the spectra of Fourier-transform infrared spectroscopy, while X-ray diffraction indicate that the cellulose crystallinity decreases with increasing the potassium concentration which increases the biomass reactivity in pyrolysis. The ignition temperature of the potassium-impregnated biomass is lowered slightly when compared with the raw biomass; alternatively, its burnout temperature is reduced profoundly, suggesting that the addition of potassium into the biomass can substantially intensify its oxidative reactivity. Considering the treated biomass torrefaction, its cellulose decomposition at 250 degrees C is intensified, rendering a reduction in the solid yield with increasing potassium concentration. With the same mass loss at 200-300 degrees C, at least 28% of torrefaction time can be saved for the potassium-impregnated biomass. Accordingly, the catalytic effect of potassium on biomass thermochemical conversion is clearly outlined. Moreover, the produced potassium-rich biochar is conducive to the developments of carbon storage, soil amendment, and negative emissions technologies.

International audience

Scanning ion conductance microscopy (SICM) is a technique for non-contact topographic imaging. In this thesis, a biophysical investigation into Alzheimer's Disease (AD) was carried, with toxic oligomers dosed locally and quantitatively on to single astrocytes using SICM and simultaneously monitoring the response of the target cell. Examination of the effectiveness of antibodies that bind to Abeta or alpha-synuclein (Asyn)peptides depends on the measurement of oligomer-induced abnormal calcium homeostasis in single astrocytes. The method was shown to work at physiological concentrations of oligomers. A series of experiments measuring the reduction in calcium inux in mixtures of antibodies and cerebrospinal fluid (CSF) of AD patients suggested that the binding to co-oligomers composed of Abeta and Asyn may be crucial in the treatment of AD. Furthermore, it may be beneficial to test antibodies before the clinical trial using this assay. The mechanism of this entry of calcium is hypothesised to be the result of the formation of oligomer-induced transient pores in the cell membrane. To verify this hypothesis, a new SICM instrument was built with two nanopipettes; one for dosing and one for detection of the adenosine triphosphate (ATP) release from these pores. A variety of different ATP sensors were made. The best had a sensitivity of 10 micro molar and works as a hexokinase-cofunctioned electrolyte-gated organic field-effect-transistor. However no statistically significant results for ATP release have been obtained in the experiments performed to date. Overall this thesis describes new biophysical methods to study the effect of protein aggregates on live cells and the effectiveness of potential therapies, such as antibodies and nanobodies, to reduce these aggregate induced effects. It can be applied to synthetic aggregates of Abeta or the aggregates present in human CSF., Taiwan-Cambridge Scholarship

One potential therapeutic strategy for Alzheimer's disease (AD) is to use antibodies that bind to small soluble protein aggregates to reduce their toxic effects. However, these therapies are rarely tested in human CSF before clinical trials because of the lack of sensitive methods that enable the measurement of aggregate-induced toxicity at low concentrations. We have developed highly sensitive single vesicle and single-cell-based assays that detect the Ca 2+ influx caused by the CSF of individuals affected with AD and healthy controls, and we have found comparable effects for both types of samples. We also show that an extracellular chaperone clusterin; a nanobody specific to the amyloid-β peptide (Aβ); and bapineuzumab, a humanized monoclonal antibody raised against Aβ could all reduce the Ca 2+ influx caused by synthetic Aβ oligomers but are less effective in CSF. These assays could be used to characterize potential therapeutic agents in CSF before clinical trials. Drews et al. develop and implement sensitive in vitro assays to quantitatively measure the Ca 2+ influx caused by human cerebrospinal fluid. If a given chaperone, antibody, or nanobody is effective in reducing Ca 2+ influx, the authors determine what concentration is needed to prevent Ca 2+ influx.

International audience; Thermal modification is an efficient way to improve some wood properties, like equilibrium moisture content (EMC), dimensional stability and durability (Esteves and Pereira 2009), to produce a wood modified material. According to the literature (Candelier et al. 2016), it has been observed that the thermal degradation of wood has a high dependence on the initial wood characteristics (wood specie, density) and process parameters, such as drying stage, heating medium, and treatment intensity (heating rate, temperature and duration). The objective of this study is to predict the treatment duration in order to reach a particular level of wood modification under industrial conditions. For that, the mass loss dynamics during the treatment are recorded and modelled. The flow chart of research methodology is shown in Fig. 1. The obtained results are encouraging for a future development of a numerical tool able to conduct performing the heat treatment of wood in industry. The experiments were carried out on wood boards (30 x 22 x 2.5 cm3) in a pilot scale system, under conditions close to the industrial ones (heat transfer by conduction with 0.2°C min-1 heating rate under vacuum). Two different wood species, a hardwood: the poplar (Populus nigra) and a softwood: the fir (Picea abies), were used. The heat treatment was conducted at 230 °C for 14 hours under low air pressure (200 hPa) with less than 5% oxygen content. 14 hours duration is examined to obtain kinetic profiles required for the modelling, while usual treatment duration in the industry is close to 1 to 5 hours. Results of the present work are shown in Fig. 2. They indicate that the mass loss of poplar (14.21 wt%) is higher than fir (10.45 wt%). The difference of thermal sensitivity between poplar and fir is due to the hemicelluloses composition of hardwood and softwood (Chaouch et al. 2010). Moreover, if the target of the wood modification is to reach 10 wt% of mass loss, the duration for the poplar is closed to 750 min and 1200 min for the fir. This first observation allowed selecting the hardwood specie in priority to limit the heating energy consumption and carbon footprint, as well as optimize the economical balance. A two-step kinetic model (Di Blasi and Lanzetta 1997) is adopted to predict the mass loss dynamics of poplar and fir. The kinetic parameters are calculated from experimental data by curve-fitting. A good agreement between modelled and experimental data is achieved for both two species. This model can be integrated in the development of a numerical tool able to give recommendations to the industry by the prediction of the treatment time to modify wood specie for reach required properties. (Résumé d'auteur)

Thermal modification is an efficient way to improve some wood properties, like equilibrium moisture content (EMC), dimensional stability and durability (Esteves and Pereira 2009), to produce a wood modified material. According to the literature (Candelier et al. 2016), it has been observed that the thermal degradation of wood has a high dependence on the initial wood characteristics (wood specie, density) and process parameters, such as drying stage, heating medium, and treatment intensity (heating rate, temperature and duration). The objective of this study is to predict the treatment duration in order to reach a particular level of wood modification under industrial conditions. For that, the mass loss dynamics during the treatment are recorded and modelled. The flow chart of research methodology is shown in Fig. 1. The obtained results are encouraging for a future development of a numerical tool able to conduct performing the heat treatment of wood in industry. The experiments were carried out on wood boards (30 x 22 x 2.5 cm3) in a pilot scale system, under conditions close to the industrial ones (heat transfer by conduction with 0.2°C min-1 heating rate under vacuum). Two different wood species, a hardwood: the poplar (Populus nigra) and a softwood: the fir (Picea abies), were used. The heat treatment was conducted at 230 °C for 14 hours under low air pressure (200 hPa) with less than 5% oxygen content. 14 hours duration is examined to obtain kinetic profiles required for the modelling, while usual treatment duration in the industry is close to 1 to 5 hours. Results of the present work are shown in Fig. 2. They indicate that the mass loss of poplar (14.21 wt%) is higher than fir (10.45 wt%). The difference of thermal sensitivity between poplar and fir is due to the hemicelluloses composition of hardwood and softwood (Chaouch et al. 2010). Moreover, if the target of the wood modification is to reach 10 wt% of mass loss, the duration for the poplar is closed to 750 min and 1200 min for the fir. This first observation allowed selecting the hardwood specie in priority to limit the heating energy consumption and carbon footprint, as well as optimize the economical balance. A two-step kinetic model (Di Blasi and Lanzetta 1997) is adopted to predict the mass loss dynamics of poplar and fir. The kinetic parameters are calculated from experimental data by curve-fitting. A good agreement between modelled and experimental data is achieved for both two species. This model can be integrated in the development of a numerical tool able to give recommendations to the industry by the prediction of the treatment time to modify wood specie for reach required properties.

When light is absorbed by a nanoring consisting of 6–24 porphyrin units, the excitation delocalizes over the whole molecule within 200 fs. Highly symmetric nanorings exhibit thermally enhanced super-radiance., Rings of chlorophyll molecules harvest sunlight remarkably efficiently during photosynthesis in purple bacteria. The key to their efficiency lies in their highly delocalized excited states that allow for ultrafast energy migration. Here we show that a family of synthetic nanorings mimic the ultrafast energy transfer and delocalization observed in nature. π-Conjugated nanorings with diameters of up to 10 nm, consisting of up to 24 porphyrin units, are found to exhibit excitation delocalization within the first 200 fs of light absorption. Transitions from the first singlet excited state of the circular nanorings are dipole-forbidden as a result of symmetry constraints, but these selection rules can be lifted through static and dynamic distortions of the rings. The increase in the radiative emission rate in the larger nanorings correlates with an increase in static disorder expected from Monte Carlo simulations. For highly symmetric rings, the radiative rate is found to increase with increasing temperature. Although this type of thermally activated superradiance has been theoretically predicted in circular chromophore arrays, it has not previously been observed in any natural or synthetic systems. As expected, the activation energy for emission increases when a nanoring is fixed in a circular conformation by coordination to a radial template. These nanorings offer extended chromophores with high excitation delocalization that is remarkably stable against thermally induced disorder. Such findings open new opportunities for exploring coherence effects in nanometer molecular rings and for implementing these biomimetic light-harvesters in man-made devices.

Wood heat-treatment technique has been developed rapidly in the past decades, it is an attractive way to improve the properties of wood, such as equilibrium moisture content (EMC), dimensional stability and durability [Candelieret al., 2013]. The treatment temperatures are in the range from 180 to 240 °C, underan inert atmosphere [Candelieret al., 2016; Estevesand Pereira2009]. Some advantages of wood treatment by the vacuum reactor are reported. The drying time of wood is decreased, and the end-product with lower volatiles which accelerate the degradation phenomena of wood [Torreset al., 2011; Sandaket al., 2015]. In the present work, the thermal degradation of wood under vacuum condition is investigated. Two different wood species, poplar (Populus nigra) and sapin (Picea abies), are examined in this study. The effects of operating conditions (temperature, heating rate and duration of treatment) on wood thermal degradation are studied. The reaction system involved four subsystems: heat treatment, balance measurement, vacuum compressor, and data collection. In addition, the properties of heated wood, such as higher heating value (HHV) and elemental analysis are examined. The experimental flow chart is shown in Fig. 1. These data will be useful to increase and improve an kinetic model to predict the weight loss percentage of wood during the heat treatment under vacuum condition. The kinetic model is based on Di Blasi approach [Di Blasic and Lanzetta 1997] and the kinetic parameters are calculated from the experiment results. As a whole, the obtained results and developing model are conducive to performing the heat treatment of wood in industry. Moreover, the operating cost of wood heat treatment can be reduced. (Texte intégral)

International audience

This thesis is concerned with ultrafast photophysics and excitation energy transfer in biomimetic and biosensing molecular nanomaterials, which have been investigated using timeresolved photoluminescence spectroscopy. Artificially-synthesised fully pi-conjugated nanorings with 6-24 units of porphyrins incorporated have demonstrated remarkable full delocalisation of the absorbing excited state across the entire ring on an ultrafast timescale. The largest ring of 24 porphyrin units with a diameter of ~10 nm is the largest man-made molecular nanoring at present. The constraint that the lowest electronic transition is forbidden due to their high molecular symmetries is released by static and dynamic distortions in the solution. These findings provide promising opportunities for using these man-made light-harvesting materials that match the efficiency of their natural counterparts in technological applications. On the other hand, self-assembled organic fluorescent nanoparticles (NPs) formed of amphiphilic monomers with targeting ligands exhibit potential to be used in bio-sensing applications. Homotransfer and heterotransfer of excitation energy in nanoparticles have been investigated, where mannose covalently linked on Amp1-B monomers provide binding sites for Concanavalin A which is attached with energy acceptors. Increasing the molar ratios of Amp1-B-mannose and Amp3-B can increase the binding sites and forming directional energetic cascades towards the NP surface, respectively. However, the amount of these two monomers must be optimised in order to reach the highest donor-acceptor energy transfer rate in the system.

In this paper, a novel hybrid algorithm featuring a simple index modulation profile with fast-converging optimization is proposed towards the design of dense wavelength-division-multiplexing systems (DWDM) multichannel fiber Bragg grating (FBG) filters. The approach is based on utilizing one of other FBG design approaches that may suffer from spectral distortion as the first step, then performing Lagrange multiplier optimization (LMO) for optimized correction of the spectral distortion. In our design examples, the superposition method is employed as the first design step for its merits of easy fabrication, and the discrete layer-peeling (DLP) algorithm is used to rapidly obtain the initial index modulation profiles for the superposition method. On account of the initially near-optimum index modulation profiles from the first step, the LMO optimization algorithm shows fast convergence to the target reflection spectra in the second step and the design outcome still retains the advantage of easy fabrication.

A longitudinal computer-generated hologram is incorporated into the Fabry-Pérot cavity of a terahertz quantum cascade laser which displays two distinct spectral gain peaks. The combined cavity and hologram feedback mechanisms lead to digitally selective dual-mode emission with a difference frequency which may be electronically tuned from 190 GHz to 267 GHz.

Time domain modeling is used investigate a laser system based on a Fabry-Perot cavity modified with a weak longitudinal computer-generated hologram. The combined cavity and hologram feedback mechanisms lead to highly selective single mode emission which may be discretely tuned with gain position and an additional phase shift.

A transverse computer-generated hologram (CGH) diffracts and provides flexible control of incident light by steering it to any point in the projected image plane - i.e. CGHs are able to direct the light to where it is needed and away from where it is not. In addition, the number of resolvable points in the image projection plane is a function of the CGH's pixel count. Here we report a longitudinal CGH (LCGH), a photonic structure, which swaps the ability to steer light toward fixed spatial points for digital control in the frequency domain. This is of particular interest in the context of tunable lasers. In this regard, an LCGH offers two important degrees-of-freedom (DOFs): 1) provides high-resolution wavevector or k space resolution within the Brillouin zone; 2) enables full control to define or modify the reflectivity at each resolvable k point, so attaining a target spectral response. We demonstrate the flexibility of our LCGH approach by achieving purely electronic tuning between six digitally-selected operating frequencies in a single section terahertz (THz) quantum cascade laser (QCL). These switchable single-frequency devices will simplify combining the power and flexibility of THz QCLs with spectroscopic applications, such as remote sensing, spectral analysis, and both security and medical imaging., 17 pages, 4 Figures, submitted to Nature Photonics

We present a perturbative aperiodic distributed feedback grating embedded within a Fabry-Pérot cavity. Time domain modelling revealed electronic switching functionality, occurring only in the presence of facet reflections. The switching behaviour was experimentally verified.

Optimization correction of spectral distortion for superimposed DWDM multichannel fiber Bragg grating filters is performed with a hybrid Lagrange multiplier optimization algorithm to enable fast convergence as well as to retain the easy-fabrication merits.

A holographically designed, aperiodic distributed feedback grating is used as a multi-resonance filter and embedded within an existing Fabry-Pérot (FP) terahertz (THz) quantum cascade laser (QCL) cavity. Balancing the feedback strengths of the filter resonances and the FP cavity creates a system capable of a high degree of single-mode selectivity, which is sensitive to changes in driving current. Multi-moded QCLs operating around 2.9 THz are thus modified to achieve purely electronic discrete tuning spanning over 160 GHz with an average tuning resolution of 30 GHz. Applying the same multi-resonance filter to QCLs with gain peaks around 2.65 and 2.9 THz leads to dual-mode lasing with an electrically controlled frequency separation of between 190 and 267 GHz. A phase sensitive mode selection mechanism is experimentally confirmed by the observation of divergent fine-tuning of the lasing modes. © 2012 Optical Society of America.

One potential therapeutic strategy for Alzheimer's disease (AD) is to use antibodies that bind to small soluble protein aggregates to reduce their toxic effects. However, these therapies are rarely tested in human CSF before clinical trials because of the lack of sensitive methods that enable the measurement of aggregate-induced toxicity at low concentrations. We have developed highly sensitive single vesicle and single-cell-based assays that detect the Ca2+ influx caused by the CSF of individuals affected with AD and healthy controls, and we have found comparable effects for both types of samples. We also show that an extracellular chaperone clusterin; a nanobody specific to the amyloid-β peptide (Aβ); and bapineuzumab, a humanized monoclonal antibody raised against Aβ, could all reduce the Ca2+ influx caused by synthetic Aβ oligomers but are less effective in CSF. These assays could be used to characterize potential therapeutic agents in CSF before clinical trials.

International audience

Torrefaction is a thermochemical conversion process, and it is adopted to improve the drawbacks of raw biomass (such as high hygroscopicity, low calorific values and energy density). During this process, biomass is thermally degraded in an inert or nitrogen environment at temperature range of 200-300 degrees C for several minutes to several hours. In this study, high homogeneous torrefied wood samples were produced by torrefaction at 200, 210, 220, and 230 degrees C. The equilibrium moisture content (EMC) of raw and torrefied wood and the contact angle of sample surface are examined to evaluate the hygroscopicity changes of torrefied wood. The results indicate that the EMC of the torrefied wood decreased by 35% or more compared to the EMC of raw material. An increasing of contact angle of torrefied wood surface is observed with increasing torrefaction temperature, and it is in the range of 103-113 degrees which is correspond to hydrophobic surface (>900). Meanwhile, the detailed mechanisms about the changes of biomass hygroscopicity after torrefacion are also illustrated in the present work.