Modeling and Parameter Characterization of A Betavoltaic Cell

Betavoltaic cells are a type of nuclear battery where kinetic energy from beta particles are converted into electricity. The goal of this research is to evaluate betavoltaic cell electrical performance and predict its response to temperature changes for potential implementation. To achieve this goal, three tasks were performed: betavoltaic cells were electrically characterized under temperature, critical betavoltaic semiconductor parameters were experimentally determined, and the Shockley-Diode model was used to predict electrical performance and compared to experimental results. Betavoltaic cells were evaluated from -30◦Cto70◦C. I-V curves were gathered at each temperature step in order to determine open circuit voltage and short circuit current. Open-circuit voltage was observed to decrease with temperature due to the increase in dark current from thermal excitation while short-circuit current increased with temperature due to the increase in mobility in electrons and holes. Open-circuit voltage was 0.75 V and short-circuit current was 70 nA at room temperature. Critical parameters, such as parasitic resistance and doping density were determined. Parasitic resistance was found by evaluating the slopes of I-V curves when I =0 and V = 0 for shunt and series resistance, respectively, and were determined to be 2.3 × 108 Ωand 1 × 106 Ω, respectively. Doping density was found by determining the capacitance of the cell under AC voltage bias and was determined to be 1 × 1017 cm−3. Absorption depths were determined in MCNP6 where a monoenergetic point source emitted beta electrons onto a GaAs substrate. Absorption depth was determined at the depth where 99% of energy was deposited into the GaAs substrate for all energies. Backscattering coefficients were also determined by the number of electrons passing through the top layer of the GaAs substrate. The number of particles emitted through the bottom face of the source film was determined in MCNP6 with the F1 tally. Critical parameters were used to model the NanoTritiumTM cells with the Shockley-Diode model. The model was solved numerically using MATLAB’s fzero function and was also solved explicitly using the lambert-W function. For I-V curves, the lambert-W function was inaccurate, producing curves that shifted 0.1 V, while solving the model numerically was accurate to experimental results. For determining both open-circuit voltage and short-circuit current, the numerical method was accurate while the lambert-W function could not determine results outside of certain temperature ranges

Temperature Dependence of Electrical Performance of Tritium Sourced Betavoltaic Cells

There is an increasing need for devices that can be powered for extended periods of time where it is impossible for maintenance or replacement, such as pacemakers, long term space flight or undisturbed sensors for military use. Since 1971, most devices run off a Lithium-Iodide battery, which gives a high amount of power but could only last approximately 2 to 5 years, requiring frequent replacement. However, replacement is unnecessary for betavoltaic cells as they can last at least 20 years. Commercially available tritium betavoltaic cells provided by City Labs Inc. were tested at a temperature range of -50°C to 150°C without any degradation. In order to fully determine the effectiveness of a betavoltaic cell, the electrical performance needs to be evaluated in temperature cycles ranging from -30°C to 70°C. This was evaluated by plotting I-V curves of a betavoltaic and a photovoltaic cell at multiple temperatures and evaluating the short circuit current and open circuit voltage to determine maximum power to compare electrical performance. Evaluation determined that the maximum theoretical power of the betavoltaic decreased by half as temperature increased from -30°C to 70°C, suggesting that betavoltaic cells are not temperature resistant. However, due to the power output of these cells, this can be negligible, and betavoltaics are ideal to run in below freezing conditions, as well as being reliable to operate at night unlike photovoltaic cells

Modeling and Parameter Characterization of a Betavoltaic Cell

Betavoltaic cells are a type of nuclear battery where kinetic energy from beta particles are converted into electricity. The goal of this research is to evaluate betavoltaic cell electrical performance and predict its response to temperature changes for potential implementation. To achieve this goal, three tasks were performed: betavoltaic cells were electrically characterized under temperature, critical betavoltaic semiconductor parameters were experimentally determined, and the Shockley-Diode model was used to predict electrical performance and compared to experimental results. Betavoltaic cells were evaluated from -30°C to 70°C. I-V curves were gathered at each temperature step in order to determine open circuit voltage and short circuit current. Open-circuit voltage was observed to decrease with temperature due to the increase in dark current from thermal excitation while short-circuit current increased with temperature due to the increase in mobility in electrons and holes. Open-circuit voltage was 0.75 V and short-circuit current was 70 nA at room temperature. Critical parameters, such as parasitic resistance and doping density were determined. Parasitic resistance was found by evaluating the slopes of I-V curves when I = 0 and V = 0 for shunt and series resistance, respectively, and were determined to be 2.3 × 108 Ω and 1 × 106 Ω, respectively. Doping density was found by determining the capacitance of the cell under AC voltage bias and was determined to be 1 × 1017 cm−3 . Absorption depths were determined in MCNP6 where a monoenergetic point source emitted beta electrons onto a GaAs substrate. Absorption depth was determined at the depth where 99% of energy was deposited into the GaAs substrate for all energies. Backscattering coefficients were also determined by the number of electrons passing through the top layer of the GaAs substrate. The number of particles emitted through the bottom face of the source film was determined in MCNP6 with the F1 tally. Critical parameters were used to model the NanoTritium TM cells with the Shockley-Diode model. The model was solved numerically using MATLAB\u27s fzero function and was also solved explicitly using the lambert-W function. For I-V curves, the lambert-W function was inaccurate, producing curves that shifted 0.1 V, while solving the model numerically was accurate to experimental results. For determining both open-circuit voltage and short-circuit current, the numerical method was accurate while the lambert-W function could not determine results outside of certain temperature ranges

Pharmacokinetics of rituximab and clinical outcomes in patients with anti-neutrophil cytoplasmic antibody associated vasculitis

Objectives. To study the determinants of the pharmacokinetics (PK) of rituximab (RTX) in patients with ANCA-associated vasculitis (AAV) and its association with clinical outcomes. Methods. This study included data from 89 patients from the RTX in AAV trial who received the full dose of RTX (four weekly infusions of 375 mg/m(2)). RTX was quantified at weeks 2, 4, 8, 16 and 24, and summarized by computing the trapezoidal area under the curve. We explored potential determinants of the PK-RTX, and analysed its association with clinical outcomes: achievement of remission at 6 months, duration of B-cell depletion and time to relapse in patients who achieved complete remission. Results. RTX serum levels were significantly lower in males and in newly diagnosed patients, and negatively correlated with body surface area, baseline B-cell count and degree of disease activity. In multivariate analyses, the main determinants of PK-RTX were sex and new diagnosis. Patients reaching complete remission at month 6 had similar RTX levels compared with patients who did not reach complete remission. Patients with higher RTX levels generally experienced longer B-cell depletion than patients with lower levels, but RTX levels at the different time points and area under the curve were not associated with time to relapse. Conclusion. Despite the body-surface-area-based dosing protocol, PK-RTX is highly variable among patients with AAV, its main determinants being sex and newly diagnosed disease. We did not observe any relevant association between PK-RTX and clinical outcomes. The monitoring of serum RTX levels does not seem clinically useful in AAV