Solid-state NMR at natural isotopic abundance for bioenergy applications

Abstract

Lignocellulosic biomass offers a vast and renewable resource for biofuel production and carbon management solutions. The effective conversion of lignocellulosic biomass into economically competitive biofuels and bioproducts demands a comprehensive understanding of its complex structure and composition, often requiring a range of analytical tools to achieve meaningful insights. However, for the analysis of rigid solids, many traditional methods necessitate dissolution or chemical/physical modification of the sample, which limit our ability to capture an intact view of its structural components. This highlights the need for non-destructive approaches, such as solid-state nuclear magnetic resonance (ssNMR), which preserves the sample’s natural state while providing deep, molecular-level insights. While advanced multi-dimensional ssNMR on ¹³C-enriched materials has recently proven exceptionally valuable for elucidating the complex macrostructure of biomass, isotopic enrichment is expensive, laborious and is clearly infeasible at large scales. In this review, we explore the role of solid-state NMR methods at natural isotopic abundance as essential tools for the non-destructive, in-depth characterization of lignocellulosic biomass and bioenergy materials in their native and unaltered state. After a brief introduction to the basic principles of solid-state NMR, we first describe the acquisition and interpretation of routine 1D ¹³C ssNMR spectra of lignocellulose and other related biopolymers and products. We then delve into more advanced ssNMR approaches, including key spectral editing techniques, probing polymer dynamics, and various 2D methods applicable at natural abundance. Understanding of domain miscibility as observed from proton-based spin diffusion effects is a theme throughout. Our aim is to highlight key examples where ssNMR provides valuable insights into the composition, structure, dynamics, and morphology of rigid biomaterials relevant to the bioenergy economy, revealing both the native structures and fundamental transformations that occur across conversion and decomposition pathways. We hope that this review encourages a broader adoption of ssNMR methods in bioenergy research, where it can serve as a pivotal analytical tool for achieving sustainable biomass utilization and advancing a carbon-efficient bioeconomy.