Oxidative Addition of the CαCβ Bond in β-O-4 Linkage of Lignin to Transition Metals Using a Relativistic Pseudopotential-Based ccCA-ONIOM Method

Salicornia dolichostachya organosolv fractionation: towards establishing a halophyte biorefinery

Halophytes are a potential source of lignocellulosic material for biorefinery, as they can be grown in areas unsuitable for the cultivation of crops aimed at food production. To enable the viable use of halophytes in biorefineries, the present study investigated how different organosolv process parameters affected the fractionation of green pressed fibers of Salicornia dolichostachya. We produced pretreated solids characterized by up to 51.3% ± 1.7% cellulose, a significant increase from 25.6% ± 1.3% in untreated fibers. A delignification yield of as high as 60.7%, and hemicellulose removal of as high as 86.1% were also achieved in the current study. The obtained cellulose could be completely converted to glucose via enzymatic hydrolysis within 24 h. The lignin fractions obtained were of high purity, with sugar contamination of only 1.22% w/w and ashes below 1% w/w in most samples. Finally, up to 29.1% ± 0.4% hemicellulose was recovered as a separate product, whose proportion of oligomers to total sugars was 69.9% ± 3.0%. To the best of our knowledge, this is the first report in which Salicornia fibers are shown to be a suitable feedstock for organosolv biomass fractionation. These results expand the portfolio of biomass sources for biorefinery applications.

An organosolv method was developed for the fractionation of fibers of a halophyte plant in a biorefinery approach. Salicornia dolichostachya was used as raw material allowing the production of cellulose, hemicellulose, and lignin fractions.

Understanding Plant Biomass via Computational Modeling

Plant biomass, especially wood, has been used for structural materials since ancient times. It is also showing great potential for new structural materials and it is the major feedstock for the emerging biorefineries for building a sustainable society. The plant cell wall is a hierarchical matrix of mainly cellulose, hemicellulose, and lignin. Herein, the structure, properties, and reactions of cellulose, lignin, and wood cell walls, studied using density functional theory (DFT) and molecular dynamics (MD), which are the widely used computational modeling approaches, are reviewed. Computational modeling, which has played a crucial role in understanding the structure and properties of plant biomass and its nanomaterials, may serve a leading role on developing new hierarchical materials from biomass in the future.

Domain-based local pair natural orbital methods within the correlation consistent composite approach

Ab initio composite approaches have been utilized to model and predict main group thermochemistry within 1 kcal mol^-1 , on average, from well-established reliable experiments, primarily for molecules with less than 30 atoms. For molecules of increasing size and complexity, such as biomolecular complexes, composite methodologies have been limited in their application. Therefore, the domain-based local pair natural orbital (DLPNO) methods have been implemented within the correlation consistent composite approach (ccCA) framework, namely DLPNO-ccCA, to reduce the computational cost (disk space, CPU (central processing unit) time, memory) and predict energetic properties such as enthalpies of formation, noncovalent interactions, and conformation energies for organic biomolecular complexes including one of the largest molecules examined via composite strategies, within 1 kcal mol^-1 , after calibration with 119 molecules and a set of linear alkanes. © 2019 Wiley Periodicals, Inc.

Depolymerization Pathways for Branching Lignin Spirodienone Units Revealed with ab Initio Steered Molecular Dynamics

Lignocellulosic biomass is an abundant, rich source of aromatic compounds, but direct utilization of raw lignin has been hampered by both the high heterogeneity and variability of linking bonds in this biopolymer. Ab initio steered molecular dynamics (AISMD) has emerged both as a fruitful direct computational screening approach to identify products that occur through mechanical depolymerization (i.e., in sonication or ball-milling) and as a sampling approach. By varying the direction of force and sampling over 750 AISMD trajectories, we identify numerous possible pathways through which lignin depolymerization may occur in pyrolysis or through catalytic depolymerization as well. Here, we present eight unique major depolymerization pathways discovered via AISMD for the recently characterized spirodienone lignin branching linkage that may comprise around 10% weight of all lignin in some softwoods. We extract representative trajectories from AISMD and carry out reaction pathway analysis to identify energetically favorable pathways for lignin depolymerization. Importantly, we identify dynamical effects that could not be observed through more traditional calculations of bond dissociation energies. Such effects include thermodynamically favorable recovery of aromaticity in the dienone ring that leads to near-barrierless subsequent ether cleavage and hydrogen-bonding effects that stabilize newly formed radicals. Some of the most stable spirodienone fragments that reside at most 1 eV above the reactant structure are formed with only 2 eV barriers for C-C bond cleavage, suggesting key targets for catalyst design to drive targeted depolymerization of lignin.

A computationally efficient double hybrid density functional based on the random phase approximation

A new double hybrid density functional (PWRB95) based on GGA orbitals and RPA is presented and its performance is investigated compared to standard DFT and wavefunction methods.

Solv-ccCA: Implicit Solvation and the Correlation Consistent Composite Approach for the Determination of pKa

Direct theoretical methods are advantageous for the prediction of pKa, as relative methods rely upon the experimental values of reference acid molecules that can limit application of the method to well-characterized systems. Here, a direct route is introduced, which incorporates the SMD universal solvation model1 within the correlation consistent Composite Approach (ccCA). This Solv-ccCA methodology has been used for the prediction of theoretical pKa values for nitrogen-containing species to within a mean absolute deviation (MAD) of 1.0 pKa unit from experimental values by utilizing a thermodynamic cycle that combines gas-phase and solution-phase calculations. Several density functionals, including B3LYP, B97-1, B97-2, B98, BMK, M06, and M06-2X, were also evaluated for use with SMD and for comparison to Solv-ccCA.

ReaxFF study of the oxidation of lignin model compounds for the most common linkages in softwood in view of carbon fiber production

Lignin is an underused but major component of biomass. One possible area of utilization is the production of carbon fiber. A necessary processing step is the stabilization of lignin fiber (typically in an oxygen environment) before high temperature treatment. We investigate oxidative, thermal conversion of lignin using computational methods. Dilignol model compounds for the most common (seven) linkages in softwood are chosen to represent the diverse structure of lignin. We perform molecular dynamics simulation where the potential energy surface is described by a reactive force field (ReaxFF). We calculate overall activation energies for model conversion and reveal initial mechanisms of formaldehyde formation. We record fragmentation patterns and average carbon oxidation numbers at various temperatures. Most importantly, we identify mechanisms for stabilizing reactions that result in cyclic and rigid connections in softwood lignin fibers that are necessary for further processing into carbon fibers.

Benchmark study of the performance of density functional theory for bond activations with (ni,pd)-based transition-metal catalysts

The performance of 23 density functionals, including one LDA, four GGAs, three meta-GGAs, three hybrid GGAs, eight hybrid meta-GGAs, and ten double-hybrid functionals, was investigated for the computation of activation energies of various covalent main-group single bonds by four catalysts: Pd, PdCl⁻, PdCl₂, and Ni (all in the singlet state). A reactant complex, the barrier, and reaction energy were considered, leading to 164 energy data points for statistical analysis. Extended Gaussian AO basis sets were used in all calculations. The best functional for the complete benchmark set relative to estimated CCSD(T)/CBS reference data is PBE0-D3, with an MAD value of 1.1 kcal mol⁻¹ followed by PW6B95-D3, the double hybrid PWPB95-D3, and B3LYP-D3 (1.9 kcal mol⁻¹ each). The other tested hybrid meta-GGAs perform less well (M06-HF: 7.0 kcal mol⁻¹; M06-2X: 6.3 kcal mol⁻¹; M06: 4.9 kcal mol⁻¹) for the investigated reactions. In the Ni case, some double hybrids show larger errors due to partial breakdown of the perturbative treatment for the correlation energy in cases with difficult electronic structures (partial multi-reference character). Only double hybrids either with very low amounts of perturbative correlation (e.g., PBE0-DH) or that use the opposite-spin correlation component only (e.g., PWPB95) seem to be more robust. We also investigated the effect of the D3 dispersion correction. While the barriers are not affected by this correction, significant and mostly positive results were observed for reaction energies. Furthermore, six very recently proposed double-hybrid functionals were analyzed regarding the influence of the amount of Fock exchange as well as the type of perturbative correlation treatment. According to these results, double hybrids with <50–60 % of exact exchange and ∼30 % perturbative correlation perform best.