Cd₃As₂ Kinetic Inductance for Miniaturized Terahertz Circuits

Terahertz technologies and integrated systems remain constrained by geometry-dependent inductors. Cd₃As₂ spiral inductors harness giant kinetic inductance to enable compact, low-loss THz components and provide a scalable materials-driven route for next-generation on-chip circuits.

Published in Physics

Like

Share this post

Choose a social network to share with, or copy the URL to share elsewhere

This is a representation of how your post may appear on social media. The actual post will vary between social networks

Explore the Research

SpringerLink
SpringerLink SpringerLink

Harnessing large kinetic inductance in Cadmium Arsenide (Cd₃As₂) for miniaturized terahertz spiral inductors - Discover Electronics

The growing demand for high-speed connectivity, driven by the Internet of Things (IoT) and the emergence of 6G technologies, underscores the crucial role of terahertz (THz) frequencies (0.1-10 THz) in powering high-resolution imaging, ultrasensitive sensing, and ultrafast communication. However, translating these capabilities into real-world applications requires the development of electronic and optical components that can reliably operate at THz frequencies. The relatively low inductance of conventional metal-based inductors at micrometre scales has significantly limited their miniaturization and scalability to THz frequencies. In this work, a miniaturized spiral THz inductor is designed using Cadmium Arsenide (Cd₃As₂), a three-dimensional Dirac semimetal with remarkable electrical characteristics, such as low intrinsic losses and high kinetic inductance. For a spiral length of 1600 µm, the proposed inductor achieves a total inductance of 4.6 nH with a kinetic inductance contribution of 2.7 nH by taking advantage of the long momentum scattering time (τ = 157 fs) and low carrier density of Cd₃As₂. Its size is three times smaller than aluminium-based counterparts without sacrificing performance. Our device demonstrates enhanced scalability and, consequently, greater efficiency. These findings enable compact, high-performance on-chip components for integrated circuits, telecommunications, and IoT applications.

The terahertz (THz) region of the electromagnetic spectrum, long regarded as technologically elusive, is rapidly becoming central to next-generation communication, sensing, and integrated photonic-electronic systems. Its vast bandwidth and potential for ultralow-latency transmission make it an attractive candidate for future 6G networks and dense Internet-of-Things infrastructures. Yet the transition from experimental platforms to scalable chip-level THz technologies continues to face an unglamorous but fundamental obstacle: passive components have not kept pace with advances in sources, detectors, and active devices.

Inductors are a particularly stubborn bottleneck. In conventional electronics, inductance is governed by geometry, magnetic energy stored by currents flowing through patterned metallic conductors. As circuits shrink, geometry alone cannot sustain useful inductance, forcing a trade-off between footprint and performance. High conductivity metals such as aluminium or copper, therefore, impose severe footprint penalties when used in terahertz integrated circuits, limiting the density and scalability of on-chip THz systems. Addressing this constraint requires more than incremental design optimisation; it demands a shift in perspective toward materials that fundamentally alter how inductance is generated.

Our recent work (Discover Electronics 3, 14 (2026). https://doi.org/10.1007/s44291-026-00160-8) exploring spiral inductors fabricated from the Dirac semimetal Cd₃As₂ highlights the promise of such a shift. Instead of relying solely on magnetic-field storage dictated by geometry, this approach exploits carrier dynamics intrinsic to the material itself. Electromagnetic simulations comparing identically patterned aluminium and Cd₃As₂ inductors reveal a striking outcome: the Cd₃As₂ devices exhibit markedly lower resonance frequencies and significantly higher inductance despite identical dimensions. The enhancement arises from kinetic inductance, additional inductance due to inertia of the charge carriers in the oscillating electric fields.

In most conventional metals, kinetic inductance is negligible. High carrier density and rapid scattering allow electrons to follow alternating fields almost instantaneously, suppressing inertial energy storage. Materials hosting low-density, high-mobility carriers with longer relaxation times behave differently. Their carriers respond with finite delay, introducing an additional inductive component that becomes increasingly important at high frequencies. Cd₃As₂, with its linear band dispersion and Dirac-like carriers, falls squarely within this regime. Simulated compact spiral geometries show kinetic contributions dominating the total inductance, yielding values several times greater than those achievable with traditional metals.

This behaviour points to a conceptual pivot: inductance need not remain geometry limited. By embedding functionality in electronic structure rather than physical size, compact THz components can achieve performance previously unattainable through scaling alone. The implications extend well beyond a single material system. Weyl semimetals, topological conductors, and superconducting platforms may offer comparable opportunities, inviting systematic exploration of quantum-material electrodynamics as a design toolkit for passive device engineering.

Equally important is the potential for active tunability. Since kinetic inductance depends on carrier density and scattering dynamics, it can be modulated through optical excitation, temperature variation, or electrostatic gating. This enables frequency-agile resonant circuits and reconfigurable metamaterial elements without modifying the device geometry, which is highly desirable for multifunctional terahertz platforms operating in dynamic environments.

As terahertz technologies progress toward practical deployment, passive components will play a crucial role in determining integration and efficiency. Recent advances in Cd₃As₂-based inductors highlight the broader opportunity of engineering electromagnetic response through quantum-material properties. This approach offers new design flexibility beyond conventional metals, suggesting that future compact terahertz circuits may benefit more from advanced material choices than from geometric optimisation alone.

 

Sahu, A., Andola, B. & Srivastava, Y.K. Harnessing large kinetic inductance in Cadmium Arsenide (Cd₃As₂) for miniaturised terahertz spiral inductors. Discover Electronics 3, 14 (2026).

Miniaturised spiral inductor: a) Device design, (b) Total inductance of Aluminium and Cd₃As₂ inductor. (c) Kinetic inductance of Cd₃As₂ inductor, (d) Ratio of the total inductance of Cd₃As₂ inductor to that of the aluminium inductor.

Please sign in or register for FREE

If you are a registered user on Research Communities by Springer Nature, please sign in

Follow the Topic

Terahertz Optics
Physical Sciences > Physics and Astronomy > Optics and Photonics > Terahertz Optics
Applied Optics
Physical Sciences > Physics and Astronomy > Optics and Photonics > Applied Optics
Optics and Photonics
Physical Sciences > Physics and Astronomy > Optics and Photonics
Ultrafast Photonics
Physical Sciences > Physics and Astronomy > Optics and Photonics > Ultrafast Photonics

Your space to connect: The Polarised light Hub

A new Communities’ space to connect, collaborate, and explore research on Light-Matter Interaction, Optics and Photonics, Quantum Imaging and Sensing, Microscopy, and Spectroscopy!

Continue reading announcement

Related Collections

With Collections, you can get published faster and increase your visibility.

Physics-based Modeling and Simulation of Semiconductor Devices for Circuit and System Design

Semiconductor device models are mathematical representations of the behavior of electronic components, which are essential building blocks of modern electronic circuits. These models capture the complex physical phenomena underlying the operation of semiconductor devices, allowing circuit and system designers to accurately predict the performance and behavior of electronic systems.

To make the most of semiconductor devices, compact device models and design software are crucial. Predictive and physical device models that work with circuit design software can speed up development cycles and address issues of device efficiency, manufacturing yield, and product stability. The performance and accuracy of the design software depend on having accurate device models, especially compact models for circuit design.

The development of accurate and efficient semiconductor device models is crucial for the design and optimization of a wide range of electronic systems, from simple analog circuits to complex digital integrated circuits. These models enable designers to explore different circuit topologies, optimize component values, and analyze the impact of various design parameters on the overall system performance.

Incorporating semiconductor device models into circuit and system design tools enables engineers to evaluate electronic circuits and systems before physical implementation, saving time and resources. This allows for the exploration of design alternatives, the identification of potential issues, and the optimization of circuit and system performance, ultimately leading to the development of more reliable and efficient electronic products.

To fully harness the unique and promising potential of emerging technologies, it is crucial that their experimental discoveries and advancements are supported by a deep understanding of the underlying physics and their implications at the materials, device, circuit, and system levels. Modelling novel materials and devices is expected to play a pivotal role in accelerating this process. These models should provide valuable insights into material properties, device operation, and scalability, while also enabling efficient and accurate estimates of performance and energy efficiency for circuits based on emerging technologies. As we strive to achieve revolutionary breakthroughs in computing and storage, models at different levels of design abstraction will be essential.

In support of this grand challenge, this Collection aims to address key issues in the field of device modelling for circuit and system design.

Suggested topics include, but are not limited to:

1. Emerging Topics

- Linking Atomistic/TCAD simulation to compact modeling

- Machine learning and compact modeling

- Millimeter wave frequency modeling for IoT and 5G/6G applications

- Automated Parameter extraction

- Modeling for biosensors

2. Modeling of Silicon based Transistor

- Advanced Bulk and SOI MOSFETs

- Multi-Gate, Nanosheet and GAA MOSFETs

- Junctionless MuGFETs

- Power and high voltage MOSFETs

3. Compound semiconductor FET modeling

- GaN HEMTs, MISHEMTs, and MOSFETs

- Wide bandgap devices for power electronics

4. Emerging semiconductor devices

- Steep-Slope Devices: Tunnel FETs, Negative Capacitance Transistors etc.

- Molecular transistors

- Single Electron Transistors

- Quantum Dot Transistors

- Memories - MRAM, PCRAM etc.

- Spintronic devices

- Layered/2D materials

- MEMS/NEMS

- Neuromorphic devices

5. Modeling of physical effects

- Noise

- High frequency operation

- Variability including mismatch and process statistics

- Strain

- High energy particle interactions in ICs (radiation effects)

- Ballistic and quasi-ballistic transport

- Layout dependent effects

6. Reliability and Variability Modeling

- Hot carrier degradation

- Electromigration/ESD events

- Radiation effects

- NBTI/PBTI

- Variability including mismatch and process statistics

7. Photonic devices and Modeling

- Photodiodes

- Solar cells

- LED, OLED etc.

This Collection supports and amplifies research related to SDG 9.

Keywords: Nanoscale MOSFETs, Modeling & Simulation of Nanoscale Devices, MOSFET Characterization, Emerging Non-CMOS Devices, Quantum-Mechanical Devices, 2D Materials, Emerging Nanoscale Devices, Quantum Devices, TFET, ISFET, Graphene, MoS2, Carbon Nanotube Transistor, NEMS

Publishing Model: Open Access

Deadline: Jun 30, 2026

2D Materials for Advanced Electronics: Functional Properties, Device Integration, and Emerging Applications

This collection aims to highlight recent advances in the discovery, design, and functionalization of two-dimensional (2D) materials, including transition metal chalcogenides (TMCs), MXenes, phosphorene, their heterostructures, and quantum dots, for next-generation electronic, optoelectronic, and sensing systems.

We welcome contributions exploring theoretical, computational, and experimental investigations into the electronic, magnetic, optical, and thermal properties of 2D materials, with a strong emphasis on their integration into functional devices and engineered systems. Studies that leverage advanced spectroscopic techniques or first-principles modeling are especially encouraged, given their relevance to understanding structure–property relationships in both organic–inorganic hybrid systems and low-dimensional quantum materials.

Topics of interest include, but are not limited to:

- Data-driven and AI-assisted materials discovery and design

- Optoelectronic characterization and photonic behavior

- Synthesis and fabrication techniques tailored for device applications

- 2D materials in flexible electronics, bioelectronics, and quantum devices

- Electronic and optical sensors

- Nanostructures and hybrid systems for energy-efficient applications

This collection seeks to bridge fundamental materials research with practical applications in areas such as microelectronics, quantum electronics, circuit integration, and electronic materials—supporting the broader advancement of systems engineering, instrumentation, and applied electronic technologies.

This Collection supports and amplifies research related to SDG 9.

Keywords: 2D materials; MXenes; Transition metal chalcogenides (TMCs); Phosphorene; Quantum dots; Electronic materials; Data-driven material discovery; Device integration; Optoelectronic devices; Sensors and sensing systems; Functional electronic systems

Publishing Model: Open Access

Deadline: Oct 30, 2026