Bernard M'Passi-Mabiala

In the context of increasing energy demand and limited access to clean cooking and heating fuels in the Republic of Congo, agricultural and forestry residues represent a promising resource for energy production. This study aims to identify, quantify and assess the energy potential of the residues generated across eight departments of the country. Ten residues were characterized: sugarcane bagasse, peanut shells, corn stalks and cobs, rice husks, cassava stalks and peelings, sawdust, wood chips and wood slabs. Proximate analyses were carried out using a muffle furnace and an oven, while the calorific value was estimated using empirical formulas. Results of the proximate analysis showed that moisture content ranged from 8.80 ± 0.14% to 45.17 ± 1.57%, ash content from 1.00 ± 0.23 to 15.07 ± 0.15%, volatile matter content from 67.86 ± 0.02 to 82.14 ± 0.14% and fixed carbon content from 12.13 ± 0.33 to 19.87 ± 0.37%. The lower calorific value ranged between 14.98 and 18.04 MJ/kg. Approximately 137,921.16 tons of the assessed residues were estimated to be generated in 2025, corresponding to a first-order theoretical energy potential of approximately 1876.78 TJ/year. These findings provide useful evidence for public policies aimed at promoting the sustainable valorization of agricultural, agro-industrial, and forestry residues, diversifying the national energy mix and supporting the development of decentralized bioenergy systems in the Republic of Congo.

The Republic of the Congo is facing significant challenges in terms of access to electricity, particularly in the extensive rural and remote areas. A reliable assessment of solar resources and photovoltaic (PV) potential is needed to support the development of decentralized sustainable energy solutions. This study evaluates the potential for photovoltaic electricity production in Brazzaville based on in situ radiation measurements. The potential was extended across the country using satellite data from SolarGIS through calibration, although this requires further validation of satellite data in certain transition zones, ranging from the southern savannas to the dense equatorial forests in the north of the country. Measurements taken over a year at the Cité Scientifique de Brazzaville using LP02 and CS300 pyranometers were compared to SolarGIS estimates using statistical performance indicators. There is better agreement between these sensors, with R² = 0.80 and an RMSE = 0.47 kWh/m²/day. However, we observed between the SolarGIS data and the LP02 measurements an R² = 0.91 and an RMSE = 0.17 kWh/m²/day (3.8%), whereas with the CS300 we obtained R² = 0.77 and RMSE = 0.59 kWh/m²/day (14%), which shows a better performance of LP02 compared with CS300. In terms of photovoltaic energy production, the average photovoltaic solar yield was estimated at 3.9 kWh/kWp/day for the LP02 and 3.5 kWh/kWp/day for the CS300, with an annual yield of approximately 1424 kWh/kWp for the LP02, corresponding to estimated discrepancies in photovoltaic production of 0.14 kWh/kWp/day. Based on this, we estimated that a 50 kWp photovoltaic solar system would produce approximately an annual power of 71,200 kWh, which would supply 285 households for a village. These results confirm both the significant potential of solar photovoltaics for decentralized rural electrification and the usefulness of calibrated SolarGIS data for assessing solar resources in areas with limited site-level data. These efforts align well with the planning and investment needs deployed by the Republic of Congo to ensure sustainable electrification of rural areas (PND 2022–2026; National Energy Pact (NEP) and Mission 300).

In the context of increasing energy demand and limited access to clean cooking and heating fuels in the Republic of Congo, agricultural and forestry residues represent a promising resource for energy production. The aim of this study is to identify, quantify and assess the energy potential of the residues generated across eight departments of the Country. Ten residues were characterized: sugarcane bagasse, peanut shells, corn stalks and cobs, rice husks, cassava stalks and peelings, sawdust, wood chips and wood slabs. Proximate analyses were carried out using a muffle furnace and an oven, while the calorific value was estimated using empirical formulas. Results of proximate analysis showed that moisture content ranged between 8.80 ± 0.14 % and 45.17 ± 1.57 %, ash content from 1.00 ± 0.23 to 15.07 ± 0.15 %, volatile matter content from 67.86 ± 0.02 to 82.14 ± 0.14 % and fixed carbon content from 12.13 ± 0.33 to 19.87 ± 0.37 %. The lower calorific value ranged between 14.98 and 18.04 MJ/kg. Approximately 137 921.16 tonnes of available residues were generated in 2025, representing an estimated energy potential of 1876.78 TJ/year. These residues constitute a significant resource for solid biofuel production and decentralized electricity generation.

We report ab‐initio DFT calculations of metal‐phthalocyanines (MPcs; M = Cu, Fe, Ni) adsorbed on graphene containing a single‐vacancy (SVG), B‐ or N‐dopant defects, i.e., MPcSVG, MPcBGr, and MPcNGr respectively. The MPcs are adsorbed with adsorption energies () ranging from −2.40 eV to −2.81 eV, which suggest strong adsorption and a chemisorption process. Also, MPcZ (M = Fe, Cu, Ni; Z = SVG, BGr, and NGr) are metallic and magnetic, the latter being largely contributed by the metallic M. In most cases, the magnetic moment of associated MPc in MPcD is either enhanced or remained the same (i.e., relative to free molecular MPc) after adsorption. Furthermore, both CuPc and FePc molecule retained their out‐of‐plane magnetic anisotropy energy (MAE) when deposited on the SVG and BGr. The perpendicular MAE coupled with strong in CuPcSVG, MPcBGr ( M = Cu, Fe), and in CuPcNGr, make them potential nanocomposites for molecular spintronics applications.

The ground state structural, electronic and magnetic properties of CaMnO ₃ , Ca _0.875 Gd _0.125 MnO ₃ and Ca _0.75 Gd _0.25 MnO ₃ have been investigated by mean of spin polarized DFT+U calculations using plane waves and pseudopotential method, in order to understand the influence of Gd doping on the electronic and magnetic properties of CaMnO ₃ material. CaMnO ₃ is a G-type antiferromagnetic insulator; Ca _0.875 Gd _0.125 MnO ₃ and Ca _0.75 Gd _0.25 MnO ₃ stabilize in the orthorhombic pnma antiferromagnetic and ferromagnetic metallic respectively, in agreement with experimental results. As the doping concentration increases, the volume and magnetic moment of each manganese atom both increase. This observed change of behavior is due to the double exchange between Mn ⁴⁺ and Mn ³⁺ on the one hand and to the presence of the magnetic ion Gd ³⁺ , highlighting the sensitivity of CaMnO ₃ material to the internal magnetic field, making it a potential candidate in magnetic tunneling junctions and magnetic field sensors.

This study assesses and characterizes six woody biomass (WB) species commonly harvested in the Republic of Congo: Millettia laurentii (WB1), Millettia eetveldeana (WB2), Hymenocardia ulmoides (WB3), Markhamia tomentosa (WB4), Pentaclethra eetveldeana (WB5), and Hymenocardia acida (WB6). Characterization was performed using proximate analysis with a Thermo Gravimetric Analyser (TGA), ultimate analysis with a CHNS Analyser, higher heating value (HHV) determination, metal content analysis by X-ray fluorescence (XRF), and aboveground biomass (AGB) estimation. The proximate analysis results showed that volatile matter varied between 74.6% and 77.3%, while the ultimate analysis indicated that carbon content ranged from 43% to 46%, with low nitrogen content. XRF analysis revealed low levels of heavy metals in all samples. The HHV results, using three models (Dulong’s equation, Friedl, and proximate analysis), showed higher values with Friedl’s method (17.3–18.2 MJ/kg) and proximate analysis (15.26–19.23 MJ/kg) compared to Dulong’s equation (13.9–14.9 MJ/kg). Savannah biomass (WB6) exhibited high AGB (7.28 t), 14.55 t/ha, and carbon stock (7.28 t). Compared to forest biomass, savannah biomass presents a higher potential for bioenergy production. Minimal statistical analysis of wood biomass showed that parameters such as volatile matter (VM), carbon (C), hydrogen (H), and calculated HHV have low variability, suggesting the biomass is relatively homogeneous. However, moisture and nitrogen showed significant standard deviations, indicating variability in storage conditions or sample nature. Statistical analysis of forest biomass estimation revealed different mean values for diameter, AGB (t and t/ha), and carbon stock, with high standard deviations, indicating a heterogeneous forest with both young and mature trees. These analyses and estimates indicate that these WB species are suitable for biofuel and bioenergy production using gasification, pyrolysis, and combustion processes. Among these thermochemical processes, gasification is the most efficient compared to combustion and pyrolysis.

Installing Photovoltaic (PV) systems is becoming a viable solution for rural areas, with an innovative approach consisting of interconnecting autonomous PV-powered households. This study analyses the performance of interconnected autonomous PV households under different weather conditions using the Matlab Simulink R2016a software. Over and above this interconnection analysis, in this study, a new mathematical model to predict PV power is also proposed and compared to the simulation's results and other approaches allowing to prosumer to control their interconnection to others. The interconnection demonstrated the improving performance of microgrids and mutual energy compensation, increasing efficiency by 9% in houses with a deficit. To manage the energy flow of these autonomous houses, the households' energy management is independent and the bus Voltage (Vdc) is maintained at around 52V, corresponding to the maximum bus voltage setpoint, thanks to integrated Proportional control (PI). The results of the simulation of the interconnection using the Matlab Simulink R2016a software show that irradiation and temperature have an impact on photovoltaic production and the results of the new mathematical approach are approximately 2% of those of the simulations.