Materials science has become one of the prime drivers of scientific and technological progress. Nanoscience and nanotechnology emerged quickly in the late twentieth century, continue to expand well into the twenty-first. Materials research has conventionally developed within the restricted boundaries of chemistry, physics, biology, and material science and engineering. While this disciplinary specialization has enabled substantial progress, it has also, at times, limited the exchange of ideas across traditional boundaries. Nanoscience has bridged these divides, offering a common framework for understanding material properties in terms of dimension, surface, interface, defect, and electronic structure.
A central assertion of nanoscience is that size and dimensionality substantially govern material behavior. At the nanoscale, variations in surface-to-volume ratio, quantum confinement, defect density, surface energy, and electronic structure can produce properties significantly different from the bulk. Gold nanoparticles illustrate this principle well: their catalytic activity is not intrinsic but depends strongly on particle size, support, oxidation state, exposed facets, preparation route, and reaction conditions. Materials of identical chemical composition can therefore behave very differently once their size, morphology, and surface structure are varied.
Nanomaterials are generally defined as those with at least one external dimension, surface, or internal feature in the 1-100 nm range. They may be engineered as zero-, one-, or two-dimensional nanostructures, or assembled into three-dimensional architectures from nanoscale building blocks, spanning nanoparticles, nanorods, nanotubes, nanowires, nanosheets, porous frameworks, and hierarchical structures. Their optical, electrical, magnetic, catalytic, and photocatalytic properties are further shaped by crystallinity, defects, surface chemistry, interfaces, and dopants, offering a rich design space through doping, surface functionalization, cocatalyst deposition, heterostructure formation, and alloying.
Advances in characterization have been central to this progress. High-resolution electron microscopy, scanning probe microscopy, X-ray photoelectron spectroscopy, Raman spectroscopy, X-ray absorption techniques, and advanced optical and electrochemical methods now allow detailed probing of nanoscale morphology, crystallinity, surface composition, and electronic structure. In situ and operando methods extend this further, enabling structural and chemical changes to be tracked under real operating conditions and revealing dynamic surface species, charge-transfer pathways, intermediates, and degradation routes that connect structure to activity.
Nanomaterial performance is always together with synthesis and processing. Particle size, morphology, crystallinity, defect density, and surface chemistry are all sensitive to precursor chemistry, temperature, pressure, pH, reaction time, additives, nucleation and growth pathways, and post-treatment. Reproducibility therefore remains a significant challenge: small changes in synthesis or post-treatment conditions can substantially alter material properties and performance. Standardized protocols, thorough documentation, rigorous physicochemical characterization, and appropriate statistical analysis are essential for reliable comparison across laboratories. Reporting nominal composition alone is insufficient; particle-size distribution, morphology, crystallinity, and surface chemistry should be reported wherever possible.
These tunable characteristics have driven the use of nanomaterials in catalysis, photocatalysis, energy conversion and storage, environmental remediation, sensing, electronics, optoelectronics, healthcare, agriculture, and advanced manufacturing. In energy and environmental contexts specifically, nanomaterials are being explored for photocatalytic H2 generation, CO2 conversion, pollutant degradation, solar energy harvesting, batteries, supercapacitors, fuel cells, and water purification, with their high surface area and tunable surface chemistry reinforcing the principle that “less is more” in catalytic design.
Advanced architectures such as single-atom catalysts, bimetallic alloys, core-shell nanoparticles, supported catalysts, and heterostructures offer additional control over electronic structure, charge transport, surface reactivity, and stability. Single-atom catalysts can significantly improve metal-atom utilization and exhibit distinctive catalytic behavior arising from their coordination environment and substrate interactions. Alloying allows catalytic properties to be tuned and can, in some cases, reduce reliance on costly or scarce elements, while core-shell and heterostructured designs can improve both stability and functional performance.
Computational science, automation, artificial intelligence (AI), and machine learning (ML) are increasingly integral to this field. Density functional theory and related computational approaches provide insight into electronic structure, adsorption, defect chemistry, reaction pathways, and stability, while AI and ML are emerging as tools to predict material properties, uncover structure-property relationships, optimize synthesis conditions, and accelerate discovery. Well-structured datasets, built through design of experiments and high-throughput experimentation, underpin this work, and text-mining approaches can help organize the growing scientific literature, though outputs still require expert verification. The reliability of AI/ML predictions ultimately depends on data quality, representativeness, experimental consistency, validation, and uncertainty assessment; these methods should therefore supplement, not replace, experimental confirmation and scientific reasoning. Including well-documented negative or failed results can meaningfully strengthen predictive models.
As nanomaterials move from laboratory study toward practical application, greater attention must be paid to sustainability, scalability, cost-effectiveness, safety, and environmental impact. Strong functional performance alone does not guarantee technological viability; techno-economic assessment, life-cycle impact, resource availability, energy consumption, toxicity, recyclability, and end-of-life strategy must be considered from the earliest stages of material design. Future progress in nanomaterials research will depend on stronger integration of synthesis, advanced characterization, computational modeling, AI/ML, process engineering, and sustainability assessment. Greater emphasis on reproducible synthesis, standardized characterization, transparent data reporting, and independent validation will strengthen both the credibility and the translational potential of the field.
This special issue, “Fundamentals and Advances in Nanomaterials for Energy and Environmental Applications,” brings together perspectives on these rapidly evolving developments, spanning fundamental principles, advanced synthesis and characterization, emerging nanoscale architectures, computational and data-driven approaches, and applications in energy conversion, environmental protection, and sustainable technology. Collectively, these advances suggest that nanotechnology has moved beyond simply identifying materials with remarkable properties. The next challenge lies in understanding why such properties emerge, how to improve the reliability of experimental results, how sustainably the materials can be produced, and how effectively they perform in real-world environment. By integrating nanoscale science with digital technologies, engineering, and sustainability thinking, nanomaterials research can meaningfully advance cleaner energy systems, effective environmental technologies, resource-efficient processes, and next-generation functional materials.
Prof. Shankar Muthukonda Venkatakrishnan, FRSC
Invited-BP Professor
Konkuk University
Republic of Korea
AND
Professor
Yogi Vemana University
India
