<![CDATA[This research examines recent advancements in advanced materials and extractive metallurgy for optimizing mineral and energy resource value chains. The study's purpose is to synthesize current research, emerging technologies, and future prospects in resource value chain optimization. The novelty lies in the comprehensive analysis of synergies between advanced materials, innovative extractive techniques, and cutting-edge technologies like AI and biotechnology. A systematic literature review methodology was employed, focusing on peer-reviewed papers from 2018 onwards, with data extracted and analyzed using standardized forms and qualitative software. Key findings include significant improvements in extraction efficiency and selectivity through nanostructured materials and high-performance membranes, with lab-scale efficiency increases of 50-70% translating to 20-30% in industrial settings. Bio-inspired techniques in extractive metallurgy have shown promise, reducing energy consumption by up to 40% in some processes. The integration of AI and machine learning has demonstrated potential for optimizing complex ore beneficiation, improving overall recovery rates. The study discusses challenges in scaling up laboratory innovations to industrial applications and the need to address hidden environmental costs of new technologies. Limitations include the exclusion of non-English studies and potential delays in reflecting very recent advancements. This review contributes to the field by offering insights for researchers, industry professionals, and policymakers to foster sustainable and efficient resource utilization practices, highlighting the transformative potential of integrating advanced materials, extractive metallurgy innovations, and emerging technologies in reshaping resource value chains.]]>
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