Reconfigurable Surfaces for High-Efficiency RF Energy Harvesting

About the Project

Background and Motivation:

The increasing demand for sustainable and maintenance-free wireless technologies has accelerated interest in radio frequency (RF) energy harvesting, which converts electromagnetic waves into usable electrical power. This approach supports energy-autonomous IoT networks, sensors, and smart infrastructure. However, traditional rectenna-based systems have limited range, static operation, and low energy conversion efficiency, particularly in dynamic propagation environments. Reconfigurable surfaces—planar arrays of engineered subwavelength elements—offer a transformative solution. By dynamically controlling wave reflection and phase, they enable beam steering, energy focusing, and adaptive impedance matching without using power-intensive circuits.

These advantages make them ideal for directed wireless power transfer and long-range energy harvesting. Yet, efficiency and scalability remain limited by signal variation and the lack of real-time control. This project addresses these gaps through the development of a reconfigurable surface-assisted RF energy harvesting that combines intelligent design, simulation, and experimental validation for high-efficiency operation.

Research Aim and Objectives:

The project aims to develop an adaptive and low-loss RF energy harvesting system using reconfigurable surfaces to enhance wireless power transfer. It will focus on directional energy control, efficient conversion, and intelligent adaptability for dynamic wireless environments.

Specific objectives include:

1. Design and Optimization: Model reconfigurable surfaces for energy focusing and beam control, targeting a ≥20% efficiency improvement over conventional rectennas.
2. Simulation and Analysis: Use CST, ADS, and MATLAB for full-wave and circuit-level modeling, including multi-physics analysis of impedance and thermal effects.
3. Intelligent Control: Develop AI-based algorithms for adaptive tuning of surface parameters to optimize energy capture under varying channel and load conditions.
4. Experimental Validation: Fabricate and test prototypes, evaluating conversion efficiency, beam directivity, harvested power density, and operational range.

Methodology:

The research will combine electromagnetic design, AI-driven control, and experimental testing. Parametric modeling will optimize surface geometries to enhance focusing efficiency and minimize reflection loss. Learning-based algorithms will dynamically tune surface states for real-time adaptation. Simulation outcomes will guide prototype fabrication and laboratory validation under controlled wireless power transfer scenarios.

Metrics and Evaluation:

Performance will be measured using quantitative metrics:

• ≥20% increase in power transfer efficiency over baseline systems;
• Beam-steering accuracy ≥90% under variable conditions;
• Energy conversion efficiency ≥70% at the design frequency;
• and
• Response latency ≤10 ms during reconfiguration.

Expected Outcomes and Impact:

The project will establish a validated framework for reconfigurable surface-assisted RF energy harvesting, achieving high-gain, adaptive, and efficient wireless power transfer suitable for IoT and sensor applications. Outcomes include a compact tunable surface design, demonstrated efficiency gains through simulation and experiment, and a low-cost, scalable prototype for wireless power transfer.

Academic qualifications

A first degree (at least a 2.1) ideally in Electrical or Computer Engineering

English language requirement

IELTS score must be at least 6.5 (with not less than 6.0 in each of the four components). Other, equivalent qualifications will be accepted. Full details of the University’s policy are available online.

Essential attributes:

• Fundamental knowledge of Antennas and Microwave Engineering
• Experience of fundamental Antennas and Reconfigurable Surfaces.
• Competent in Signal Processing and CAD tools
• Knowledge of Energy Harvesting and Wireless Power Transferring
• Good Written and Oral Communication skills
• Strong Motivation, with Evidence of Independent Research Skills relevant to the project
• Good Time Management

Desirable attributes:

• Solid experience in RF circuits, signal processing
• RIS and antenna systems with a track record of publishing in high-quality journals and international conferences

APPLICATION CHECKLIST

• Completed application form
• CV
• 2 academic references, using the Postgraduate Educational Reference Form (download)
• Research project outline of 2 pages (list of references excluded). The outline may provide details about
  1. Background and motivation of the project. The motivation, explaining the importance of the project, should be supported also by relevant literature. You can also discuss the applications you expect for the project results.
  2. Research questions or objectives.
  3. Methodology: types of data to be used, approach to data collection, and data analysis methods.
  4. List of references.

The outline must be created solely by the applicant. Supervisors can only offer general discussions about the project idea without providing any additional support.

• Statement no longer than 1 page describing your motivations and fit with the project.
• Evidence of proficiency in English (if appropriate)

To be considered, the application must use

• the advertised title as project title

For informal enquiries about this PhD project, please contact n.OjaroudiParchin@napier.ac.uk

Application link: https://evision.napier.ac.uk/si/sits.urd/run/siw_sso.go?ElOlarlItFiG37xnH5PRRBvv3d563wLdwX4JfhYskMa3bJWTuc

PhD Start Date: October 2026

Funding Notes

International applicants should note that visa application costs and the NHS health surcharge are additional costs to be taken into consideration, and successful applicants will need to cover these expenses themselves.