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Naik, Mandar T.

Publications and source records attributed to Naik, Mandar T..

5 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Molecular Engineering of Biorefining Lignin Waste for Solid-State Electrolyte

Lignin is the second most abundant renewable biopolymer on Earth but also a waste in both the paper industry and lignocellulosic biorefineries. Recently, lignin valorization has been extensively sought after to return economics, enhance carbon efficiency, and improve the bioeconomy, but the commercial value and size compatibility still hinder its applications. In this study, we developed a facile strategy to apply lignin waste into a solid-state electrolyte (SSE), which represents a safe next generation energy storage. Here, lignin was grafted with polyethylene glycol (PEG), an efficient lithium-ion (Li + ) conductive polymer, to enable its ion conduction. The synthesized PEG-g-lignin was mixed with poly(vinylidene fluoride)-co-hexafluoropropylene (PVDF-HFP) and PEG-g-lignin-based bis(trifluoromethanesulfonyl)imide (LiTFSI) to prepare a solid polymer electrolyte (SPE), which has an ionic conductivity of 2.5 × 10 –5 S/cm at 25 °C. This result was further enhanced to 6.5 × 10 –5 S/cm by adding an ion-conductive ceramic of Li 6.4 La 3 Ga 0.2 Zr 2 O 12 (LLGZO), which is referred to as composite polymer electrolyte (CPE). These data represent the highest ones among reported polymer-based SSE. A mechanistic study by using 2D HSQC NMR revealed that PEG-g-lignin has increased ether type β–O–4 linkages that can promote the interchain hopping of Li+ between lignin polymer chains, and 31 P NMR revealed that the lignin phenolic end can be associated by Li + . Moreover, the abundant aromatic moieties and methoxyl in PEG-g-lignin also enhanced Li + association and improved its ionic conductivity. The superior ionic conductivity of PEG-g-lignin-based SSE can enable massive applications of this biorefining waste in all-solid-state lithium batteries (ASSLBs), which has potential to promote the energy sector by promoting the bioeconomy and enhancing the renewability and sustainability of future energy storage.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Enhancing the multi-functional properties of renewable lignin carbon fibers via defining the structure–property relationship using different biomass feedstocks

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.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Predicting the viability of beta-lactamase: How folding and binding free energies correlate with beta-lactamase fitness

One of the long-standing holy grails of molecular evolution has been the ability to predict an organism’s fitness directly from its genotype. With such predictive abilities in hand, researchers would be able to more accurately forecast how organisms will evolve and how proteins with novel functions could be engineered, leading to revolutionary advances in medicine and biotechnology. In this work, we assemble the largest reported set of experimental TEM-1 β-lactamase folding free energies and use this data in conjunction with previously acquired fitness data and computational free energy predictions to determine how much of the fitness of β-lactamase can be directly predicted by thermodynamic folding and binding free energies. We focus upon β-lactamase because of its long history as a model enzyme and its central role in antibiotic resistance. Based upon a set of 21 β-lactamase single and double mutants expressly designed to influence protein folding, we first demonstrate that modeling software designed to compute folding free energies such as FoldX and PyRosetta can meaningfully, although not perfectly, predict the experimental folding free energies of single mutants. Interestingly, while these techniques also yield sensible double mutant free energies, we show that they do so for the wrong physical reasons. We then go on to assess how well both experimental and computational folding free energies explain single mutant fitness. We find that folding free energies account for, at most, 24% of the variance in β-lactamase fitness values according to linear models and, somewhat surprisingly, complementing folding free energies with computationally-predicted binding free energies of residues near the active site only increases the folding-only figure by a few percent. This strongly suggests that the majority of β-lactamase’s fitness is controlled by factors other than free energies. Overall, our results shed a bright light on to what extent the community is justified in using thermodynamic measures to infer protein fitness as well as how applicable modern computational techniques for predicting free energies will be to the large data sets of multiply-mutated proteins forthcoming.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗