  Inexpensive tags powered by energy harvesting (EH) can realize green
(energy-efficient) Internet of Things (IoT) networks. However, tags are
vulnerable to energy insecurities, resulting in poor communication ranges,
activation distances, and data rates. To overcome these challenges, we explore
the use of a reconfigurable intelligent surface (RIS) for EH-based IoT
networks. The RIS is deployed to enhance RF power at the tag, improving EH
capabilities. We consider linear and non-linear EH models and analyze
single-tag and multi-tag scenarios. For single-tag networks, the tag's maximum
received power and the reader's signal-to-noise ratio with the optimized RIS
phase-shifts are derived. Key metrics, such as received power, harvested power,
achievable rate, outage probability, bit error rate, and diversity order, are
also evaluated. The impact of RIS phase shift quantization errors is also
studied. For the multi-tag case, an algorithm to compute the optimal RIS
phase-shifts is developed. Numerical results and simulations demonstrate
significant improvements compared to the benchmarks of no-RIS case and random
RIS-phase design. For instance, our optimal design with a \num{200}-element RIS
increases the activation distance by \qty{270}{\percent} and \qty{55}{\percent}
compared to those benchmarks. In summary, RIS deployment improves the energy
autonomy of tags while maintaining the basic tag design intact.
