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Review Article| Open Access
Volume 16 | Issue 04 | Page 161-186| https://doi.org/10.15228/2026.v16.i4.p17
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A review on Intelligent Manufacturing of Two-Dimensional Materials: From Batch Exfoliation to Automated, In-Line, and Continuous-Flow Production
Aoun Muhammad
Department of Chemistry, School of Natural Sciences(SNS), National University of Sciences and Technology (NUST), H-12, Islamabad, 44000, Pakistan.
| Received 26 July, 2026 |
Accepted 31 August, 2026 |
Published 01 September, 2026 |
ABSTRACT:
Two-dimensional (2D) nanomaterials, including graphene, hexagonal boron nitride (h-BN), transition-metal dichalcogenides (TMDs), and MXenes, possess unique electronic, mechanical, and surface properties that make them promising for electronics, energy storage, catalysis, and sensing. However, the industrial translation of exfoliation technologies remains limited because existing methods have rarely been assessed using consistent manufacturing-readiness criteria. This review evaluates mechanical, hydrothermal, electrochemical, and laser-assisted exfoliation methods based on production rate, yield, quality uniformity, reproducibility, cost, and tunability. Among the approaches reviewed, PEI-assisted sticky ball milling achieved over 40 g per batch with 97.9% monolayer content, while dual-electrode and alternating-current electrochemical exfoliation exceeded 25 g.h⁻¹ for graphene. Intermediate-assisted grinding exfoliation (iMAGE) demonstrated a favorable cost performance balance, achieving 67% h-BN yield at an energy consumption of 3.01 × 10⁶ J.g⁻¹ using low-cost feedstocks. Emerging technologies such as machine learning, automated quality classification, in-line monitoring, and continuous-flow processing could further accelerate scale-up; robotic Bayesian optimization reduced experimental trials by approximately 21-fold, while GPU-based optical classification achieved about 95% pixel-level accuracy for flake thickness and coverage. However, no reported system has yet achieved fully closed-loop AI-controlled exfoliation, and most processes remain batch-based. Reliable industrial production will therefore require standardized cross-laboratory data, improved reactor and process control, continuous-flow systems, real-time quality monitoring, automation, and comprehensive techno-economic assessment.
Keywords: 2D materials, exfoliation, graphene; h-BN, TMDs
How to Cite this paper?
APA- Style
Muhammad A., (2026) A review on Intelligent Manufacturing of Two-Dimensional Materials: From Batch Exfoliation to Automated, In-Line, and Continuous-Flow Production Pakistan Journal of Chemistry, 16(3), 160-186. https://doi.org/10.15228/2026.v16.i4.p17.
ACS Style
A. Muhammad, A review on Intelligent Manufacturing of Two-Dimensional Materials: From Batch Exfoliation to Automated, In-Line, and Continuous-Flow Production Pakistan Journal of Chemistry, 16(3), 160-186. https://doi.org/10.15228/2026.v16.i4.p17.
AMA Style
A. Muhammad; A review on Intelligent Manufacturing of Two-Dimensional Materials: From Batch Exfoliation to Automated, In-Line, and Continuous-Flow Production 2026 Pakistan Journal of Chemistry, 16(3), 160-186. https://doi.org/10.15228/2026.v16.i4.p17.
Chicago/Turabian Style
A Muhammad, A review on Intelligent Manufacturing of Two-Dimensional Materials: From Batch Exfoliation to Automated, In-Line, and Continuous-Flow Production Pakistan Journal of Chemistry, 16(3), 160-186. https://doi.org/10.15228/2026.v16.i4.p17.
This work is licensed under a Creative Commons Attribution 4.0 International License.
