The following article presents computer-aided design software for multi-stage amplifiers with bipolar transistors and field effect. It is composed of two units: a design and analysis unit that allows for step-by-step introduction of polarization and small signal values, the type of transistor to be used (bipolar or field effect) with their respective characterization values: current gain, thermal voltage, activation voltage, and saturation current, to result in the configurations and values of the resistors; and a theoretical unit that contains complete information on multi-stage amplifiers. A n-stage amplifier design method was developed, represented through a flowchart, and coded using a freely usable programming language. With the software, designs were made and simulated in a computational tool for academic use endorsed by the scientific community. The result for all variables evaluated was an average error of less than 2%. The research concludes that this software allows an effective design process of multi-stage amplifiers with bipolar transistors and field effect in a short time, it also allows changing the resistance values obtained for commercial values and calculating the error when implementing the circuit being a useful tool in the experimental area.

This article presents a computer tool that allows to carry out a mathematical analysis of the physical stability of the bipolar transistor in the design of amplifiers. The tool allows to introduce the values of voltage gain, output impedance and input impedance, current gain of transistors and power supplies, to give as a result the values of the resistances. It also allows modifying the transistor operating point and graphing in real time the behavior of the load line and the output signal of the amplifier. Different designs were made with the tool and the results obtained were compared with academic software approved by the scientific community. The errors in all variables evaluated were less than 1.5%. The results are important for semiconductor physics, taking into account that they reaffirmed the directly proportional relationship between the stability of the transistor in its amplification state and the power required to operate. Finally, we conclude that the computer tool allows us to design amplifiers with bipolar transistors with precision and, depending on the need or application of the amplifier, the operating point Q is located in the load line to obtain an output signal without distortion and with the least power dissipation.

Las herramientas tecnológicas mejoran el rendimiento académico haciendo más dinámicos y eficientes los procesos de enseñanza y aprendizaje. Se presenta una metodología de análisis y diseño de circuitos mediante el uso de una herramienta tecnológica en asignaturas de electrónica de la Universidad Francisco de Paula Santander. Se desarrolló una metodología ágil que consistió en cuatro elementos: planeación, diseño, codificación y prueba. En la planeación se consultaron las fuentes adecuadas y se desarrolló una metodología de análisis y diseño de circuitos con diodos y transistores. En el diseño se utilizó diagramación UML para el modelado del software. En codificación se utilizó lenguaje de programación java y se realizó una interfaz dinámica con la herramienta NetBeans. Finalmente se elaboraron pruebas a la interfaz, que consistieron en llevar a cabo diseños y análisis de circuitos con diodos y transistores, que fueron luego modelados en el software de simulación QUCS para calcular los errores en las variables y avalar la herramienta desarrollada. Los errores en todas las pruebas fueron inferiores al 2%, lo que implica que la interfaz es eficiente, interactiva e incentiva los procesos de enseñanza y aprendizaje haciéndolos más dinámicos.

The objective of this article is to present a computational estimate from a statistical physics approach and its contributions to Covid-19 in Colombia. Based on the daily data of contagions, recoveries and deaths, during the months of March to July, the estimation of the behavior of the epidemic was made using the nonlinear regression method with adjustment of curves by minimum squares. Highlighting the benefits that this method presents in the study of physical phenomena, it was used in the present research developing two types of modeling: exponential and Gaussian, and with these some predictions were made. The coefficients of determination of the exponential model were: 0.9641 for contagions, 0.9400 for recoveries and 0.9788 for deaths, and those of the Gaussian model were: 0.9799 for contagions, 0.9606 for recoveries and 0.9894 for deaths, showing a good correlation between the models and the real behavior of the pandemic, being the Gaussian one, the most approximate. This was also evidenced by comparing the prognosis of both models with the actual data for the first 13 days of August, concluding that the pandemic is beginning to mitigate, and the curve is flattening out.