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—In contemporary digital logic, multipliers are essential compute units that have a direct influence on power,
performance, and area metrics in embedded systems, machine learning accelerators, and digital signal processors. This
work offers a thorough approach to constructing a 4x4 signed multiplier with low power consumption and fast speed at the
16nm technology node utilising Pass-Transistor Logic (PTL). XOR, AND, half adder, and full adder are examples of custom
transistor-level PTL gates that are tuned for fewer transistors, better signal integrity, and lower dynamic power. The
solution bridges device level simulation with automated digital backend implementation by combining a standard array
architecture with thorough signed operation verification and proving physical manufacturability using an open-source
RTL-to-GDSII pipeline. At bigger technology nodes, experimental results demonstrate notable gains over earlier PTL
implementations: compared to reference designs at 28nm, power consumption decreased by about 55%, propagation latency
by 40%, and silicon area by 18%. Benchmarking verifies that PTL designs are feasible for modern VLSI systems and attests
to their robustness and functional accuracy over all signed input combinations. In addition to laying the groundwork for
future research on higher-order multipliers, hybrid logic integration, and specialised application targets, the method creates
scalable, energy-efficient arithmetic build blocks. Index Terms
"Low-Power 4×4 Signed Multiplier Design Using Pass-Transistor Logic at 16nm PTM", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 4, page no.b430-b438, April-2026, Available :http://www.ijrti.org/papers/IJRTI2604194.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator