Development of a methodology for determining the parameters of semiconductor electronic components

A methodology for metrologically valid determination of the electrical parameters of semiconductor electronic components – diodes, zener diodes, bipolar and field-effect transistors – has been developed based on experimental current-voltage characteristics (IV characteristics). Regression analysis with linearization of physical models was used for data processing: the Shockley equation for a diode, a linear model for the zener diode stabilization section and the transfer characteristic of a bipolar transistor, and a quadratic model for a field-effect transistor. Model adequacy was assessed using the coefficient of determination, QQ plots, and the Shapiro-Wilk test, which made it possible to statistically confirm the normality of the residual distribution. A quantitative assessment of the total uncertainty of the measured parameters was performed with separation of random (statistical) and instrumental components in accordance with GOST 34100.3-2017. Instrumental error was estimated using the method of maximum consistent deviations, and statistical error was estimated based on the confidence intervals of the regression coefficients. To combine the components, geometric summation was used, calculating the effective number of degrees of freedom using the Welch-Satterthwaite formula. Experimental testing on the EE-OE laboratory bench for a 1N4007 rectifier diode, a 1N5338B zener diode, a BD139-16 bipolar transistor, and an IRF740 field-effect transistor showed that in all cases, the dominant contribution to the final error is made by the statistical component, caused by the deviation of actual thermal and physical processes in crystals from idealized models, especially in the high-current region. The resulting interval parameter estimates can be used for quality control and metrological support of semiconductor components.

1. Toledo F.J., Blanes J.M., Galiano V. Two-Step Linear Least-Squares Method For Photovoltaic Single-Diode Model Parameters Extraction. IEEE Transactions on Industrial Electronics. 2018;65(8):6301–6308. https://doi.org/10.1109/TIE.2018.2793216

2. Rohrer R., Fan S.P., Claudio L. Automated bipolar junction transistor d.c. model parameter determination. IEEE Journal of Solid-State Circuits. 1971;6(4):260–262. https://doi.org/10.1109/JSSC.1971.1050176

3. Tsvetkov R.V., Sushnikov V.A., Vanina P.Yu., Meshalkina M.N. Modeling the influence of drill runout during the manufacture of an elastic element of a strain-resistive force sensor in the form of a double cantilever beam on the measurement accuracy of force sensors. Science Prospects. 2024;(4):129–133. (In Russ.).

4. Vuddagiri T.V.S.N., Das S. Determination of Semiconductor Diode Parameters Using Multi-Objective Quantum-Inspired Particle Swarm Optimization Algorithm. In: Proceedings of the SoutheastCon 2025, 22–30 March 2025, Concord, NC, USA. IEEE; 2025. P. 1334–1335. https://doi.org/10.1109/SoutheastCon56624.2025.10971617

5. Strel'chuk A.M., Lebedev A.A., Bulat P.V. Characteristics of Schottky Rectifier Diodes Based on Silicon Carbide at Elevated Temperatures. Semiconductors. 2020;54(12):1624–1627. https://doi.org/10.1134/S1063782620120374

6. Cheung S.K., Cheung N.W. Extraction of Schottky diode parameters from forward current-voltage characteristics. Applied Physics Letters. 1986;49(2):85–87. https://doi.org/10.1063/1.97359

7. Almashary B.A. Genetic Algorithm Based Diode Model Parameters Extraction. Journal of King Saud University. Engineering Sciences. 2006;18(2):249–260. https://doi.org/10.1016/S1018-3639(18)30838-9

8. Olikh O. Review and test of methods for determination of the Schottky diode parameters. Journal of Applied Physics. 2015;118(2):024502. https://doi.org/10.1063/1.4926420

9. Dib S., De La Bardonnie M., Khoury A., Pelanchon F., Mialhe P. A new method for the extraction of diode parameters using a single exponential model. Active and Passive Electronic Components. 2000;22(3):157–163. https://doi.org/10.1155/2000/31390

10. Popov S.A., Korchagin A.F. Multiple-Response Models for Calculating Electronic Device Parameters. Measurement Techniques. 2003;46(4):391–396. https://doi.org/10.1023/A:1024873315296

11. Baturina N.Yu., Kalienko I.V. Construction of Two-Dimensional Regression Models of the Current-voltage Characteristics of the Output Current of Field-Effect Transistors Using the PLExp Information System. Measurement Techniques. 2020;62(11):980–988. https://doi.org/10.1007/s11018-020-01723-1

12. Ocaya R. Extraction of Semiconductor Diode Parameters: A Comparative Review of Methods and Materials. Cham: Springer; 2024. 174 p.

13. Meshalkina M., Sushnikov V., Kryzhova N. The estimation of formaldehyde concentration in indoor air. MATEC Web of Conferences. 2018;245(8):03003. https://doi.org/10.1051/matecconf/201824503003

14. Biryukov V.N. Extraction of transistor model parameters in uniform approximation. Journal of Radio Electronics. 2025;(10). https://doi.org/10.30898/1684-1719.2025.10.5

15. Tsvetkov R.V., Sushnikov V.A., Vanina P.Yu., Meshalkina M.N. Modeling the influence of drill positioning inaccuracy in the manufacture of an elastic element of a strain-resistive force sensor in the form of a double cantilever beam. Science Prospects. 2024;(4):134–137. (In Russ.).

16. Tretyakov T.I., Nikolayev I.I., Drozdova A.A. Software Module for Determining Parameters of a Bipolar Transistor SPICE-Model Using Static Volt-Ampere Characteristics. In: Proceedings of the 2023 IEEE 24th International Conference of Young Professionals in Electron Devices and Materials (EDM), 29 June – 30 July 2023, Novosibirsk, Russia. IEEE; 2023. P. 490–494. https://doi.org/10.1109/EDM58354.2023.10225154

17. Grigoryan L.R., Bogatov N.M., Grigoryan R.L., Sakhno M.A. Hase methods for solving measurement tasks for monitoring parameters of electronic devices. Measuring. Monitoring. Management. Control. 2025;(4):116–124. (In Russ.). https://doi.org/10.21685/2307-5538-2025-4-14

18. Vatansever F., Boz A.F. Diode parameter extractions and comparisons using the least square method, neural networks and genetic algorithms. Scientific Research and Essays. 2010;5(10):1155–1163.