Evidence map›Paper›PMID 42354732›Full record

ArticleMicromachines2026

Integrated Band-Stop Filter-Based 1.8 GHz RF Detection System for Sensitivity and Efficiency Enhancement in IoT Energy Harvesting.

Naimul Hasan, Kousik Roy, Subhadip Das, Parthapratim Sarkar

Abstract read
In one paragraph

Article in Micromachines, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Naimul HasanDepartment of Electronics & Communication Engineering, Sanaka Educational Trust's Group of Institutions, Durgapur 713212, West Bengal, India.ORCID 0000-0002-4904-7729
Kousik RoyDepartment of Computer Science & Engineering, Bengal College of Engineering and Technology, Durgapur 713212, West Bengal, India.
Subhadip DasDepartment of Computer Science & Engineering, Bengal College of Engineering and Technology, Durgapur 713212, West Bengal, India.ORCID 0009-0005-2663-6001
Parthapratim SarkarDepartment of Engineering and Technological Studies, Kalyani University, Kalyani 741235, West Bengal, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The growing expansion of the Internet of Things and wireless sensor networks has created an urgent demand for compact and reliable radio frequency energy-harvesting circuits. This study introduces the design, simulation and extensive performance of a high-efficiency single band radio frequency detection system optimized for 1.8 GHz operation. The detector is realized on a Rogers RO4003C substrate and employs the SMS7630-079LF Schottky diode, selected for its excellent detection capability and economic viability. The introduction of this filtering stage effectively suppresses undesired harmonic components produced during the rectification process, thereby improving the sensitivity and overall power conversion efficiency of the system. The circuit shows a sensitivity of 1.8 mV for every dBm through its simulation tests. The system shows increased sensitivity to 2.2 mV/dBm because of the band stop filter implementation. The system reaches its peak power conversion efficiency of 65.28% at a 1.5 kΩ load, which makes it suitable for applications that require low-power energy harvesting. These combined attributes establish the developed 1.8 GHz detector as a strong candidate for next-generation energy harvesting modules, self-powered sensor networks and intelligent embedded computing platforms within the expanding domain of the Internet of Things.

Indexed as

band stop filterefficiencyenergy harvestingIoTRF detectorsensitivity

Identifiers

PMID42354732
PMCPMC13303778

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.