A simple method for producing bio-based anode materials for lithium-ion batteries
Renewable biomaterials are catalytically converted to graphite for use in lithium-ion anodes using a simple and scalable process.
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Renewable biomaterials are catalytically converted to graphite for use in lithium-ion anodes using a simple and scalable process.
Lignin has been explored extensively as a renewable precursor for carbon materials, considering its abundance as a major component of plant cell walls and its sustainability as a byproduct of both lignocellulosic biorefinery and the paper-making industry. Despite the extensive efforts to define the process–property relationship, it remains largely unknown how lignin biosynthesis and its chemistry would impact the resultant carbon fiber properties, for both mechanical and electroconductive performances. Such inadequate understanding fundamentally limits feedstock design and selection to improve carbon fiber properties toward broader commercial applications. Using lignin from a broad range of biomass feedstocks for carbon fiber manufacturing, we have fundamentally explored the structure–function relationship between lignin chemistry and carbon fiber performance. Specifically, lignin extracted from hardwood (sugar maple), softwood (loblolly pine and red cedar), and herbaceous plants (corn stover and switchgrass) was used for carbon fiber manufacturing, considering the very different lignin structures from these feedstocks. Linear regression models were established to define the relationship between carbon fiber mechanical properties and lignin structural characteristics. The results highlighted that the content of β-O-4 linkages correlates significantly with the tensile strength and elastic modulus of lignin carbon fibers, indicating that more linear β-O-4 linkages would promote the carbon fiber mechanical performance. Moreover, electroconductive properties are essential for broader energy device application of lignin-based carbon fibers, yet the mechanisms controlling their electroconductivity are largely unknown. Furthermore, we hereby demonstrated that a higher β-O-4 content also promotes the electroconductivity of lignin carbon fibers. Microstructure analysis further revealed that the crystallite size and content of the pre-graphitic turbostratic carbon structure in lignin-based carbon fibers were enhanced as the β-O-4 linkages increased. The content of β-O-4 linkages has shown a strong correlation with the crystallite content in a linear regression model. This study thus revealed the underlying mechanisms regarding how the lignin structure in planta defines the resultant carbon fiber properties. Moreover, the study also highlighted the correlation between the mechanical and electroconductive properties of lignin-based carbon fibers, both of which were defined by the lignin structure.
In this study, a novel ammonia-based pretreatment for densified lignocellulosic biomass was developed to reduce ammonia usage and integrate with viable biomass logistics scenarios. The COmpacted Biomass with Recycled Ammonia (COBRA) pretreatment performed at 100 °C allows >95% conversion of sugarcane bagasse (SCB) carbohydrates into soluble monomeric and oligomeric sugars (glucose and xylose) using industrially relevant 6% glucan loading (~21% solids loading) enzymatic hydrolysis conditions at reduced enzyme loadings. Pretreatment via COBRA with simultaneous lignin extraction (COBRA-LE) improved Saccharomyces cerevisiae 424A(LNH-ST) metabolic yield from 89% to 97.5% relative to COBRA without delignification, allowing a process ethanol yield of 71.6%. A technoeconomic analysis on SCB biorefining to ethanol in the state of São Paulo, Brazil, compared COBRA to other mature technologies, such as AFEX and steam-explosion. Amongst all scenarios studied, biorefineries based on COBRA-LE pretreatment offered the lowest average minimum ethanol selling price of US$1.45 per gallon ethanol. COBRA pretreatment was subsequently tested on perennial grasses and hardwoods, and >80% total sugar yields were achieved for all cases.
This work demonstrates that reductive catalytic fractionation can be a feedstock-agnostic process on hardwoods, softwoods, agricultural residues, and grasses, especially with water-alcohol solvent mixtures.
Forestry residues have immense potential as alternative feedstocks to petroleum, yet their inherent complexity remains a major challenge to widespread use. Pairing the temporal rhythms of plant biology with biorefinery performance is critical to industrial-scale biorefinery development. Here, we provide the first report of a techno-economic analysis (TEA) and life cycle assessment (LCA) for a model integrated reductive catalytic fractionation (RCF)–molten salt hydrolysis process for forestry residues varying in tree part, species, and phenophase. All forestry residues resulted in net-negative greenhouse gas (GHG) emissions vs. comparable petroleum feedstocks, with GHG emissions potentially reduced >4.0× through composition-based feedstock selection (e.g., harvesting American beech bark in spring vs. summer). Moreover, American beech twigs/branchlets and bark in leafed and emergence phenophases, respectively, had 7.9× lower predicted phenolic minimum selling prices (MSPs) vs. other feedstocks and MSPs within the current global phenolic market range. Hemicellulose content and RCF yield emerged as key parameters impacting GHG emissions and biorefinery revenue, identifying hardwood twigs/branchlets in the leafed phenophase as optimal biofeedstocks. Biorefinery expenses were dominated by purchased equipment, raw materials, and utility costs, highlighting essential areas for future study. Notably, RCF reactor pressures drove 85–90% of equipment costs, but sensitivity analysis revealed that decreasing the pressure 20% could reduce the phenol MSP 4-fold. Structural carbohydrate dynamics were also investigated using a two-step acid hydrolysis method to resolve tissue- and species-level patterns in biomass composition throughout the year to enable harvest optimization based on TEA/LCA findings. Ultimately, elucidating the impact of biofeedstock dynamics on biorefinery performance enables harvest optimization, informed engineering design, and progress towards an expanded bioeconomy.
Eucalyptus grandis is a hardwood tree used worldwide as pure species or hybrid partner to breed fast-growing plantation forestry crops that serve as feedstocks of timber and lignocellulosic biomass for pulp, paper, biomaterials, and biorefinery products. The current v2.0 genome reference for the species served as the first reference for the genus and has helped drive the development of molecular breeding tools for eucalypts. Using PacBio HiFi long reads and Omni-C proximity ligation sequencing, we produced an improved, haplotype-phased assembly (v4.0) for TAG0014, an early-generation selection of E. grandis. The 2 haplotypes are 571 Mbp (HAP1) and 552 Mbp (HAP2) in size and consist of 37 and 46 contigs scaffolded onto 11 chromosomes (contig N50 of 28.9 and 16.7 Mbp), respectively. These haplotype assemblies are 70-90 Mbp smaller than the diploid v2.0 assembly but capture all except one of the 22 telomeres, suggesting that substantial redundant sequence was included in the previous assembly. A total of 35,929 (HAP1) and 35,583 (HAP2) gene models were annotated, of which 438 and 472 contain long introns (>10 kbp) in gene models previously (v2.0) identified as multiple smaller genes. These and other improvements have increased gene annotation completeness levels from 93.8 to 99.4% in the v4.0 assembly. We found that 6,493 and 6,346 genes are within tandem duplicate arrays (HAP1 and HAP2, respectively, 18.4 and 17.8% of the total) and >43.8% of the haplotype assemblies consists of repeat elements. Analysis of synteny between the haplotypes and the E. grandis v2.0 reference genome revealed extensive regions of collinearity, but also some major rearrangements, and provided a preview of population and pangenome variation in the species.
Abstract Automated guard cell detection and measurement are vital for understanding plant physiological performance and ecological functioning in global water and carbon cycles. Most current methods for measuring guard cells and stomata are laborious, time-consuming, prone to bias, and limited in scale. We developed StoManager1, a high-throughput tool utilizing geometrical, mathematical algorithms, and convolutional neural networks to automatically detect, count, and measure over 30 guard cell and stomatal metrics, including guard cell and stomatal area, length, width, stomatal aperture area/guard cell area, orientation, stomatal evenness, divergence, and aggregation index. Combined with leaf functional traits, some of these StoManager1-measured guard cell and stomatal metrics explained 90% and 82% of tree biomass and intrinsic water use efficiency (iWUE) variances in hardwoods, making them substantial factors in leaf physiology and tree growth. StoManager1 demonstrated exceptional precision and recall (mAP@0.5 over 0.96), effectively capturing diverse stomatal properties across over 100 species. StoManager1 facilitates the automation of measuring leaf stomatal and guard cells, enabling broader exploration of stomatal control in plant growth and adaptation to environmental stress and climate change. This has implications for global gross primary productivity (GPP) modeling and estimation, as integrating stomatal metrics can enhance predictions of plant growth and resource usage worldwide. Easily accessible open-source code and standalone Windows executable applications are available on a GitHub repository (https://github.com/JiaxinWang123/StoManager1) and Zenodo (https://doi.org/10.5281/zenodo.7686022).
Fungal mycelium is increasingly recognized as a central component of soil biogeochemical cycling, yet our current understanding of the ecological controls on fungal necromass decomposition is limited to single sites and vegetation types. By deploying common fungal necromass substrates in a temperate oak savanna and hardwood forest in the midwestern USA, we assessed the generality of the rate at which high- and low-quality fungal necromass decomposes; further, we investigated how the decomposer ‘necrobiome’ varies both across and within sites under vegetation types dominated by either arbuscular or ectomycorrhizal plants. In this work, the effects of necromass quality on decay rate were robust to site and vegetation type differences, with high-quality fungal necromass decomposing, on average, 2.5 times faster during the initial stages of decay. Across vegetation types, bacterial and fungal communities present on decaying necromass differed from bulk soil microbial communities and were influenced by necromass quality. Moulds, yeasts and copiotrophic bacteria consistently dominated the necrobiome of high-quality fungal substrates. Synthesis. We show that regardless of differences in decay environments, high-quality fungal substrates decompose faster and support different types of decomposer micro-organisms when compared with low-quality fungal tissues. These findings help to refine our theoretical understanding of the dominant factors affecting fast cycling components of soil organic matter and the microbial communities associated with rapid decay.
Fungal decomposition of soil organic matter depends on soil nitrogen (N) availability. This ecosystem process is being jeopardized by changes in N inputs that have resulted from a tripling of atmospheric N deposition in the last century. Soil fungi are impacted by atmospheric N deposition due to higher N availability, as soils are acidified, or as micronutrients become increasingly limiting. Fungal communities that persist with chronic N deposition may be enriched with traits that enable them to tolerate environmental stress, which may trade-off with traits enabling organic matter decomposition. We hypothesized that fungal communities would respond to N deposition by shifting community composition and functional gene abundances toward those that tolerate stress but are weak decomposers. We sampled soils at seven eastern US hardwood forests where ambient N deposition varied from 3.2 to 12.6 kg N ha -1 year -1 , five of which also have experimental plots where atmospheric N deposition was simulated through fertilizer application treatments (25–50 kg N ha -1 year -1 ). Fungal community and functional responses to fertilizer varied across the ambient N deposition gradient. Fungal biomass and richness increased with simulated N deposition at sites with low ambient deposition and decreased at sites with high ambient deposition. Fungal functional genes involved in hydrolysis of organic matter increased with ambient N deposition while genes involved in oxidation of organic matter decreased. One of four genes involved in generalized abiotic stress tolerance increased with ambient N deposition. In summary, we found that the divergent response to simulated N deposition depended on ambient N deposition levels. Fungal biomass, richness, and oxidative enzyme potential were reduced by N deposition where ambient N deposition was high suggesting fungal communities were pushed beyond an environmental stress threshold. Fungal community structure and function responses to N enrichment depended on ambient N deposition at a regional scale.
Microbial community structure and function regularly covary with soil pH, yet effects of these interactions on soil carbon are rarely tested experimentally within natural ecosystems. We investigated the enduring (25 year) impacts of liming on microbial community structure and decomposition at an acidic northern hardwood forest, where experimental liming increased pH one unit and surprisingly doubled the organic carbon stocks of the forest floor. Here we show that this increase in carbon storage corresponded with restructuring of the bacterial and fungal communities that drive decomposition. In the Oe horizon, liming reduced the activities of five extracellular enzymes that mediate decomposition, while the Oa horizon showed an especially large (64%) reduction in the activity of a sixth, peroxidase, which is an oxidative enzyme central to lignocellulose degradation. Decreased enzyme activities corresponded with loss of microbial taxa important for lignocellulose decay, including large reductions in the dominant ectomycorrhizal genera Russula and Cenococcum, saprotrophic and wood decaying fungi, and Actinobacteria (Thermomonosporaceae). These results demonstrate the importance of pH as a dominant regulator of microbial community structure and illustrate how changes to this structure can produce large, otherwise unexpected increases in carbon storage in forest soils.
Climate change is reshaping ecosystems, driving plants to adapt through leaf-trait plasticity that reflects strategies for growth and water use. Predicting biomass production and intrinsic water use efficiency (iWUE) remains challenging because of genetic, taxonomic, and environmental variability. Here, we used eastern cottonwood and Populus hybrids as a model system to test whether easily measurable leaf traits can serve as reliable predictors of performance, and whether adding stomatal and biochemical traits improves predictive power. Across two field sites in Mississippi, leaf mass per area (LMA), biomass production, iWUE, leaf area, and foliar nitrogen ( N %) differed significantly among taxa and sites, while other traits were conserved. Factorial analysis of mixed data (FAMD) revealed distinct clustering of taxa and sites, indicating coordinated variation among leaf and stomatal traits. Pairwise correlations highlighted fundamental trade-offs, with biomass positively related to LMA and petiole length but negatively associated with iWUE, N %, and carbon isotopic ratios (δ 13 C). Leaf temperature and leaf angle varied among taxa and were significantly correlated with LMA and petiole length, suggesting mechanisms of heat dissipation and leaf movability that link simple traits to gas exchange and productivity. Weighted multiple linear regression models explained 80%–91% of variation in biomass production and iWUE. Models using only LMA, petiole length, and stomatal metrics performed nearly as well as those incorporating N %, and δ 13 C, with complex traits adding approximately 10% explanatory power. These results demonstrate that simple morphological traits capture integrated functional trade-offs, while complex traits refine predictions. This tiered approach provides an efficient framework for selecting high-yielding, water-efficient genotypes of Populus and other hardwood species, offering practical pathways to enhance carbon uptake and iWUE under climate change.
Turning wood into honeycombs Wood is an attractive material for structural applications, but it usually works best as boards or sheets. Xiao et al . have developed a process for engineering hardwood that allows these sheets to be manipulated into complex structures (see the Perspective by Tajvidi and Gardner). The key is to manipulate the cell wall structure by shrinking and blasting open the fibers and vessels by drying and “water-shocking” them. This process creates a window wherein the wood can be manipulated without ripping or tearing. Honeycomb, corrugated, or other complex structures are locked in once the wood dries. —BG
Understanding how plant community assemblage is affected by spatial and temporal patterns is crucial to understanding forest ecosystem responses to disturbance, including future climate change. In this article, we tracked how diversity and composition are distributed through space and time in a midsuccessional mixed hardwood forest in northern lower Michigan, United States. This region’s geographically and abiotically distinct glacial landforms influence both the spatial and temporal dynamics of its forest communities. Vegetation sampling plots (n = 87) were established at the University of Michigan Biological Station in 1990 and resampled in 2015. Vegetation in the overstory, sapling, and groundcover layers was censused. Abiotic variables, including elevation, pH, and soil nutrients, were measured in a subset of plots (n = 40). There were strong differences in diversity and community composition among glacial landforms, with the moraine having a 31% greater species richness in the groundcover layer compared with those of the other glacial landforms. Surprisingly, plant communities across all three vegetation layers showed little change over the 25-year period, and we found no evidence of differences in successional rates among glacial landforms. Our findings indicate that glacial landforms have a large influence on the production and maintenance of local plant diversity and community composition in this area and suggest that successional dynamics may manifest themselves over much longer time periods in these northern biomes.
Abstract Background Multiple analytical methods have been developed to determine the ratios of aromatic lignin units, particularly the syringyl/guaiacyl (S/G) ratio, of lignin biopolymers in plant cell walls. Chemical degradation methods such as thioacidolysis produce aromatic lignin units that are released from certain linkages and may induce chemical changes rendering it difficult to distinguish and determine the source of specific aromatic lignin units released, as is the case with nitrobenzene oxidation methodology. NMR methods provide powerful tools used to analyze cell walls for lignin composition and linkage information. Pyrolysis-mass spectrometry methods are also widely used, particularly as high-throughput methodologies. However, the different techniques used to analyze aromatic lignin unit ratios frequently yield different results within and across particular studies, making it difficult to interpret and compare results. This also makes it difficult to obtain meaningful insights relating these measurements to other characteristics of plant cell walls that may impact biomass sustainability and conversion metrics for the production of bio-derived fuels and chemicals. Results The authors compared the S/G lignin unit ratios obtained from thioacidolysis, pyrolysis-molecular beam mass spectrometry (py-MBMS), HSQC liquid-state NMR and solid-state (ss) NMR methodologies of pine, several genotypes of poplar, and corn stover biomass. An underutilized approach to deconvolute ssNMR spectra was implemented to derive S/G ratios. The S/G ratios obtained for the samples did not agree across the different methods, but trends were similar with the most agreement among the py-MBMS, HSQC NMR and deconvoluted ssNMR methods. The relationship between S/G, thioacidolysis yields, and linkage analysis determined by HSQC is also addressed. Conclusions This work demonstrates that different methods using chemical, thermal, and non-destructive NMR techniques to determine native lignin S/G ratios in plant cell walls may yield different results depending on species and linkage abundances. Spectral deconvolution can be applied to many hardwoods with lignin dominated by S and G units, but the results may not be reliable for some woody and grassy species of more diverse lignin composition. HSQC may be a better method for analyzing lignin in those species given the wealth of information provided on additional aromatic moieties and bond linkages. Additionally, trends or correlations in lignin characteristics such as S/G ratios and lignin linkages within the same species such as poplar may not necessarily exhibit the same trends or correlations made across different biomass types. Careful consideration is required when choosing a method to measure S/G ratios and the benefits and shortcomings of each method discussed here are summarized.
Coarse woody debris (CWD) is a significant component of the forest biomass pool; hence a model is warranted to predict CWD decomposition and its role in forest carbon (C) and nutrient cycling under varying management and climatic conditions. A process-based model, CWDDAT (Coarse Woody Debris Decomposition Assessment Tool) was calibrated and validated using data from the FACE (Free Air Carbon Dioxide Enrichment) Wood Decomposition Experiment utilizing pine ( Pinus taeda ), aspen ( Populous tremuloides ) and birch ( Betula papyrifera ) on nine Experimental Forests (EF) covering a range of climate, hydrology, and soil conditions across the continental USA. The model predictions were evaluated against measured FACE log mass loss over 6 years. Four widely applied metrics of model performance demonstrated that the CWDDAT model can accurately predict CWD decomposition. The R 2 (squared Pearson’s correlation coefficient) between the simulation and measurement was 0.80 for the model calibration and 0.82 for the model validation ( P <0.01). The predicted mean mass loss from all logs was 5.4% lower than the measured mass loss and 1.4% lower than the calculated loss. The model was also used to assess the decomposition of mixed pine-hardwood CWD produced by Hurricane Hugo in 1989 on the Santee Experimental Forest in South Carolina, USA. The simulation reflected rapid CWD decomposition of the forest in this subtropical setting. The predicted dissolved organic carbon (DOC) derived from the CWD decomposition and incorporated into the mineral soil averaged 1.01 g C m -2 y -1 over the 30 years. The main agents for CWD mass loss were fungi (72.0%) and termites (24.5%), the remainder was attributed to a mix of other wood decomposers. These findings demonstrate the applicability of CWDDAT for large-scale assessments of CWD dynamics, and fine-scale considerations regarding the fate of CWD carbon.
This is the AmeriFlux version of the carbon flux data for the site US-BRG Bayles Road Grassland Tower. Site Description - The Bayles Road grassland tower is situated in an experimental field incorporated within the Indiana University Research and Teaching Preserve. The field was historically covered by bottomland hardwood forest and later maintained for plant genetics studies. Intermixed species of grasses, sedges, and forbs are currently maintained with occasional mowing.
This is the AmeriFlux version of the carbon flux data for the site US-xLE NEON Lenoir Landing (LENO). Site Description - This terrestrial field site is located in a hardwood bottomland with seasonal flooding each spring located in southwest Alabama. The meteorological/flux tower and tower sampling plots are located at Lenoir Landing and the distributed plots are located approximately 5 km south of the tower at Choctaw National Wildlife Refuge. The ecosystem at LENO is dominated by closed-canopy pine-oak mixed forest with a developed understory, and also includes a small fraction of meadows, wetlands, and smaller water bodies. Dominant plant species include American sweetgum (Liquidambar styraciflua), American hornbeam (Carpinus caroliniana), and loblolly pine (Pinus taeda). Choctaw National Wildlife Refuge also provides a protected wintering area for waterfowl and wood duck brood habitat. This site is colocated with the Lower Tombigbee river aquatic site.
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-MOz Missouri Ozark Site. This is the FLUXNET version of the carbon flux data for the site US-MOz Missouri Ozark Site produced by applying the standard ONEFlux (1F) software. Site Description - The site is located in the University of Missouri Baskett Wildlife Research area, situated in the Ozark region of central Missouri. The site is uniquely located in the ecologically important transitional zone between the central hardwood region and the central grassland region of the US. The land has been publically owned since the 1930s, and is on a land tract that was forested with the same dominant species before settlement in the early 1800s.