How Do Semiconductors Work? A Quantum Mechanical Perspective

By Abdul Ahad NazakatReviewed by Louis CastelJul 18 2025

Semiconductors are materials whose electrical conductivity falls between that of conductors and insulators, an essential property that makes them the foundation of modern electronics. Although classical physics describes some aspects of their behavior, it does not fully account for key phenomena such as the formation of energy bands, the controlled conduction under specific conditions, or the mechanisms behind devices like flash memory and LEDs. From a quantum mechanical perspective, these properties are explained by how electrons occupy conduction and valence bands within a crystal lattice, how they can tunnel through potential barriers, and how quantum confinement effects become increasingly important at the nanoscale.

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What Makes a Semiconductor?

Semiconductors are crystalline materials where atoms arrange in regular, repeating patterns called crystal lattices.¹ Silicon, a commonly used semiconductor, forms a diamond cubic structure where each atom bonds covalently with four neighbors. This atomic arrangement creates the specific electronic properties that distinguish semiconductors from other materials.

Understanding semiconductor behavior involves energy bands. In isolated atoms, electrons occupy discrete energy levels, but when atoms combine in a crystal, these levels split and merge into bands. The valence band contains electrons bound to atoms, while the conduction band contains free electrons that can carry electrical current. The energy gap between these bands, the bandgap, determines whether a material behaves as a conductor, semiconductor, or insulator.

Pure semiconductors have bandgaps typically between 0.1 and 4.0 electron volts (eV). When energy is applied through heat or light, electrons can jump across this gap into the conduction band, enabling controlled current flow. In conductors, overlapping bands allow electrons to flow freely, while insulators have large bandgaps that prevent conductivity.² This intermediate conductivity between conductors and insulators makes semiconductors useful for electronic devices

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Quantum Mechanics behind Semiconductor Behavior

Classical models cannot fully explain electron behavior within semiconductors. Electrons in a crystal behave as waves described by wavefunctions, which define their probable locations and energy states. This wave nature creates the conduction and valence bands shaped by the periodic lattice potential.^{3, 4}

The Pauli Exclusion Principle ensures that no two electrons can occupy the same quantum state, determining how electrons fill available energy levels. At any given temperature, electrons arrange themselves according to Fermi-Dirac statistics, which influence a material's conductivity and thermal properties.^{3, 4}

Additionally, quantum tunneling represents a particularly important effect where electrons can move through energy barriers they could not overcome classically. This phenomenon is fundamental to flash memory operation and quantum dot devices. As device dimensions shrink to the nanoscale, quantization effects become significant, creating discrete energy levels in nanostructures that enhance optical and electronic functionality.^{5, 6}

Doping and Charge Carriers

Pure semiconductors have limited conductivity because few electrons possess sufficient thermal energy to reach the conduction band. Doping involves adding controlled amounts of impurity atoms to create additional charge carriers. Donor atoms like phosphorus in silicon provide additional electrons, resulting in n-type materials with Fermi levels closer to the conduction band. Acceptor atoms like boron create holes, leading to p-type semiconductors with Fermi levels nearer the valence band.⁷

Higher doping concentrations increase charge carriers but can reduce their mobility due to impurity scattering. In nanoscale devices, quantum effects become more prominent as impurity energy levels may become pinned, altering binding energies and affecting carrier dynamics. This precise control of carrier type and concentration enables the development of diverse semiconductor devices.⁸

Semiconductor Devices and Quantum Functionality

The p-n junction forms the basis of most semiconductor devices. When p-type and n-type materials are joined, electrons diffuse from the n-side to the p-side which creates a depletion region with an electric field. Quantum tunneling influences how electrons cross the junction, determining the current-voltage behavior critical to diodes and LEDs. As devices scale down, band-to-band tunneling becomes an essential mechanism in silicon transistors.⁹

Under forward bias, external voltage reduces the barrier height, allowing current to flow. Reverse bias increases the barrier, blocking current flow except for small leakage current. This rectifying behavior enables diodes to convert alternating current to direct current.

Modern transistors rely on band manipulation and quantum effects for operation. Devices like high-electron-mobility transistors (HEMTs) and single-electron transistors leverage quantum confinement to control current more precisely.¹⁰ Tunnel FETs, which operate through tunneling rather than thermal excitation, offer reduced power consumption as traditional MOSFETs approach scaling limits.¹¹ These advances demonstrate how quantum mechanics both explains semiconductor behavior and drives design innovation.

Real-World Applications and Technologies

Semiconductor physics impacts numerous technologies. Microprocessors containing billions of transistors rely on quantum-aware design to maintain performance. Optoelectronic devices, including laser diodes and solar cells, exploit direct bandgap materials for efficient light emission and absorption.¹

Quantum computing extends these applications further. IBM explores superconducting qubits and quantum algorithms, while Intel investigates silicon-based spin qubits to integrate quantum devices with established chip manufacturing. TSMC, a major chip foundry, supports this research by exploring scalable quantum processor fabrication. These initiatives demonstrate how quantum mechanics serves both as an explanatory tool and a design driver for future technologies.^{12, 13, 14, 15}

Future Developments in Quantum Semiconductor Technology

Emerging technologies aim to harness quantum properties more directly. Quantum dots, nanocrystals with quantized energy levels, are being studied for logic circuits, including quantum dot gate FETs (QDGFETs) that enable multi-valued logic and charge storage. Optical control of these dots shows potential for scalable quantum computing, using exciton or electron spin states as qubits.^{16, 17}

Two-dimensional (2D) materials like graphene and molybdenum disulfide (MoS₂) offer distinctive electrical and optical properties, including strong spin-orbit coupling and potential for quantum entanglement. These features make them candidates for next-generation, energy-efficient quantum devices.¹⁸

However, significant challenges remain. Producing uniform, defect-free quantum dots and 2D materials at scale is technically demanding. Integrating them into dense circuits adds complexity, and for quantum computing, decoherence poses an obstacle. Decoherence occurs when qubits lose their delicate quantum superposition states through interactions with their environment, as vibrations from neighboring atoms, electromagnetic fields, or temperature fluctuations can cause a qubit to collapse from being simultaneously in multiple states to a single classical state within microseconds. This environmental sensitivity makes it extremely difficult to maintain the quantum properties necessary for computation long enough to perform useful calculations.

Outlook

Semiconductors demonstrate the integration of material science and quantum mechanics through electron control in silicon lattices and manipulation of quantum tunneling and spin states. As research addresses challenges like decoherence and defect control, these materials are advancing beyond classical devices toward quantum processors and logic circuits. The connection between quantum theory and engineering applications enables semiconductors to contribute to developments in computing, communication, and technology.

References and Further Reading

1. Nogueira, A. E., Ribeiro, L. S., Nogueira, F. G. E., & Torres, J. A. (2024). Semiconductors (pp. 1–11). Informa. https://doi.org/10.1201/9781003450146-1
2. Lathe, A., & Palve, A. M. (2024). Types and Properties of Semiconductors (pp. 26–39). Informa. https://doi.org/10.1201/9781003450146-3
3. Kim, D. M. (2010). Introductory Quantum Mechanics for Semiconductor Nanotechnology. https://www.amazon.com/Introductory-Quantum-Mechanics-Semiconductor-Nanotechnology/dp/3527409750
4. Sutton, A. P. (n.d.). Quantum Behaviour. https://doi.org/10.1093/oso/9780192846839.003.0006
5. Capasso, F., Faist, J., & Sirtori, C. (1996). Mesoscopic phenomena in semiconductor nanostructures by quantum design. Journal of Mathematical Physics, 37(10), 4775–4792. https://doi.org/10.1063/1.531669
6. Ihn, T. (2010). Semiconductor Nanostructures: Quantum states and electronic transport. https://www.amazon.com/Semiconductor-Nanostructures-Quantum-electronic-transport/dp/019953442X
7. Doverspike, K., & Pankove, J. I. (1997). Chapter 9 Doping in the III-Nitrides (Vol. 50, pp. 259–277). Elsevier. https://doi.org/10.1016/S0080-8784(08)63090-2
8. Norberg, N. S., Dalpian, G. M., Chelikowsky, J. R., & Gamelin, D. R. (2006). Energetic pinning of magnetic impurity levels in quantum-confined semiconductors. Nano Letters, 6(12), 2887–2892. https://doi.org/10.1021/NL062153B
9. Solomon, P. M., Jopling, J., Frank, D. J., D’Emic, C., Dokumaci, O. H., Ronsheim, P., & Haensch, W. (2004). Universal tunneling behavior in technologically relevant P/N junction diodes. Journal of Applied Physics, 95(10), 5800–5812. https://doi.org/10.1063/1.1699487
10. Fu, Y. (2014). Electronic Quantum Devices (pp. 185–269). Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7174-1_4
11. Pala, M. G., & Esseni, D. (2019). Full band quantum transport modelling with EP and NEGF methods; application to nanowire transistors. International Conference on Simulation of Semiconductor Processes and Devices. https://doi.org/10.1109/SISPAD.2019.8870406
12. Premi, M. S. G., Susitra, D., Mana, S. C., Velvizhi, Ms. R., & Nair, Ms. M. C. (2025). Quantum computing. https://doi.org/10.47716/978-93-92090-62-2
13. Maturi, M. H., Satish, S., Meduri, K., & Nadella, G. S. (2020). Quantum Computing in 2020: A Systematic Review of Algorithms, Hardware Development, and Practical Applications. Universal Research Reports, 7(10), 140–154. https://doi.org/10.36676/urr.v7.i10.1427
14. Das, D. K., Patnaik, P., Das, S., Baral, M., & Nayak, N. (2024). Semiconductor Technologies for Quantum Computing Hardware. Advances in Mechatronics and Mechanical Engineering (AMME) Book Series, 115–138. https://doi.org/10.4018/979-8-3693-7076-6.ch006
15. LIU, D., LI, S., LI, H., & GUO, G. (n.d.). Silicon Semiconductor Quantum Computation. https://doi.org/10.3969/j.issn.1008-9217.2020.07.005
16. Karmakar, S., & Jain, F. C. (2012). Future Semiconductor Devices for Multi-Valued Logic Circuit Design. Materials Sciences and Applications, 3(11), 807–814. https://doi.org/10.4236/MSA.2012.311117
17. Li, X., Steel, D. G., Gammon, D., & Sham, L. J. (2004). Optically Driven Quantum Computing Devices Based on Semiconductor Quantum Dots. Quantum Information Processing, 3(1), 147–161. https://doi.org/10.1007/S11128-004-0416-1
18. Pal, A., Zhang, S., Chavan, T., Agashiwala, K., Yeh, C.-H., Cao, W., & Banerjee, S. (2022). Quantum‐Engineered Devices Based on 2D Materials for Next‐Generation Information Processing and Storage. Advanced Materials, 35(27). https://doi.org/10.1002/adma.202109894​​​​

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