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DOE OSTI2021

Hydrolysis of lignocellulose by anaerobic fungi produces free sugars and organic acids for two–stage fine chemical production with Kluyveromyces marxianus

Development of the bioeconomy is driven by our ability to access the energy-rich carbon trapped in recalcitrant plant materials. Current strategies to release this carbon rely on expensive enzyme cocktails and physicochemical pretreatment, producing inhibitory compounds that hinder subsequent microbial bioproduction. Anaerobic fungi are an appealing solution as they hydrolyze crude, untreated biomass at ambient conditions into sugars that can be converted into value-added products by partner organisms. However, some carbon is lost to anaerobic fungal fermentation products. To improve efficiency and recapture this lost carbon, we built a two-stage bioprocessing system pairing the anaerobic fungus Piromyces indianae with the yeast Kluyveromyces marxianus, which grows on a wide range of sugars and fermentation products. In doing so we produce fine and commodity chemicals directly from untreated lignocellulose. P. indianae efficiently hydrolyzed substrates such as corn stover and poplar to generate sugars, fermentation acids, and ethanol, which K. marxianus consumed while producing 2.4 g/L ethyl acetate. An engineered strain of K. marxianus was also able to produce 550 mg/L 2-phenylethanol and 150 mg/L isoamyl alcohol from P. indianae hydrolyzed lignocellulosic biomass. Despite the use of crude untreated plant material, production yields were comparable to optimized rich yeast media due to the use of all available carbon including organic acids, which formed up to 97% of free carbon in the fungal hydrolysate. Furthermore, this work demonstrates that anaerobic fungal pretreatment of lignocellulose can sustain the production of fine chemicals at high efficiency by partnering organisms with broad substrate versatility.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2015

The Role of Metal Halides in Enhancing the Dehydration of Xylose to Furfural

The dehydration of xylose yields furfural, a product of considerable value as both a commodity chemical and a platform for producing a variety of fuels. When xylose is dehydrated in aqueous solution in the presence of a Brønsted acid catalyst, humins are formed via complex side processes that ultimately result in a loss in the yield of furfural. Such degradative processes can be minimized via the insitu extraction of furfural into an organic solvent. The partitioning of furfural from water into a given extracting solvent can be enhanced by the addition of salt to the aqueous phase, a process that increases the thermodynamic activity of furfural in water. Although the thermodynamics of using salts to improve liquid-liquid extraction are well studied, their impact on the kinetics of xylose dehydration catalyzed by a Brønsted acid are not. The aim of the present study was to understand how metal halide salts affect the mechanism and kinetics of xylose dehydration in aqueous solution. We found that the rate of xylose consumption is affected by both the nature of the salt cation and anion, increasing in the order no salt < K + < Na + < Li + and no salt < Cl - < Br - < I - . Furfural selectivity increases similarly with respect to metal cations, but in the order no salt < I - < Br - < Cl - for halide anions. Multinuclear NMR was used to identify the interactions of cations and anions with xylose and to develop a model for explaining xylose-metal halide and water-metal halide interactions. The results of these experiments coupled with 18 O-labeling experiments indicate that xylose dehydration is initiated by protonation at the C 1 OH and C 2 OH sites, with halide anions acting to stabilize critical intermediates. Finally, the means by which metal halides affect the formation of humins was also investigated, and the role of cations and anions in affecting the selectivity to humins is discussed.

anions↗

DOE OSTI2020

Light Hydrocarbon Separations Using Porous Organic Framework Materials

Light hydrocarbons (C 1 –C 3 ) are used as basic energy feedstocks and as commodity organic compounds for the production of many industrially necessary chemicals. Due to the nature of the raw materials and production processes, light hydrocarbons are generated as mixtures, but the high-purity single-component products are of vital importance to the petrochemical industry. Consequently, the separation of these C 1 –C 3 products is a crucial industrial procedure that comprises a significant share of the total global energy consumption per year. As a complement to traditional separation methods (distillation, partial hydrogenation, etc.), adsorptive separations using porous solids have received widespread attention due to their lower energy costs and higher efficiency. Extensive research has been devoted to the use of porous materials such as zeolites and metal-organic frameworks (MOFs) as solid adsorbents for these key separations, owing to the high porosity, tunable pore structures, and unsaturated metal sites present in these materials. Recently, porous organic framework (POF) materials composed of organic building blocks linked by covalent bonds have also shown excellent properties in light hydrocarbon adsorption and separation, sparking interest in the use of these materials as adsorbents in separation processes. In this Minireview we summarize the recent advances in the use of POFs for light hydrocarbon separations, including the separation of mixtures of methane/ethane, methane/propane, ethylene/ethane, acetylene/ethylene, and propylene/propane, while highlighting the relationships between the structural features of these materials and their separation performances. Finally, the difficulties, challenges, and opportunities associated with leveraging POFs for light hydrocarbon separations are discussed to conclude the review.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Iodine-Catalyzed Isomerization of Dimethyl Muconate

cis,cis -Muconic acid is a platform biobased chemical that can be upgraded to drop-in commodity and novel monomers. Among the possible drop-in products, dimethyl terephthalate can be synthesized via esterification, isomerization, Diels-Alder cycloaddition, and dehydrogenation. The isomerization of cis,cis -dimethyl muconate ( cc DMM) to the trans,trans -form ( tt DMM) can be catalyzed by iodine; however, studies have yet to address (i) the mechanism and reaction barriers unique to DMM, and (ii) the influence of solvent, potential for catalyst recycle, and recovery of high-purity tt DMM. To address this gap, we apply a joint computational and experimental approach to investigate iodine-catalyzed isomerization of DMM. Density functional theory calculations identified unique regiochemical considerations due to the large number of halogen-diene coordination schemes. Both transition state theory and experiments estimate significant barrier reductions with photodissociated iodine. Solvent selection was critical for rapid kinetics, likely due to solvent complexation with iodine. Under select conditions, tt DMM yields of 95% were achieved in <1 h with methanol, followed by high purity recovery (>98%) with crystallization. Lastly, post-reaction iodine can be recovered and recycled with minimal loss of activity. Altogether, these findings provide new insight into the mechanism and conditions necessary for DMM isomerization with iodine to advance the state-of-the-art for biobased chemicals.

09 BIOMASS FUELS↗

DOE OSTI2020

Sustainable Direct Recycling of Lithium-Ion Batteries via Solvent Recovery of Electrode Materials

Separation of electrode materials from their current collectors is an enabling step toward recovering critical materials from spent lithium-ion batteries. In this study, a highly efficient, cost-effective, and environmentally sustainable separation process was developed for that purpose. Ethylene glycol, a vital commodity chemical as an antifreeze and polymer precursor, is used to delaminate electrode materials at low temperatures in seconds without altering the crystalline structure and morphology of active electrode materials. The recovered current collectors were intact without any corrosion. The authors also found that the solvent could be continuously reused, leading to the development of a closed-loop ecosystem and lithium-ion battery circular economy. The ultrafast delamination was driven by the competitive inhibition of binding through the weakening of hydrogen bonding. The ethylene glycol-based separation is a sustainable electrode recovery process that paves the way for battery recycling.

25 ENERGY STORAGE↗

DOE OSTI2024

Production of Biomass–Derived p –Hydroxybenzamide: Synthesis of p –Aminophenol and Paracetamol

As we work to transition the modern society that is based on non-renewable chemical feedstocks to a post-modern society built around renewable sources of energy, fuels, and chemicals, there is a need to identify the renewable resources and processes for converting them to platform chemicals. Herein, we explore a strategy for utilizing the p-hydroxybenzoate in biomass feedstocks (e.g., poplar and palm trees) and converting it into a portfolio of commodity chemicals. The targeted bio-derived product in the first processing stage is p-hydroxybenzamide produced from p-hydroxybenzoate esters found in the plant. In the second stage a continuous reaction process converts the p-hydroxybenzamide to p-aminophenol via the Hofmann rearrangement and recovers the unreacted p-hydroxybenzamide. In the third stage the p-aminophenol can be acetylated to form paracetamol, which is readily isolated by liquid/liquid extraction at >95 % purity and an overall p-hydroxybenzamide-to-paracetamol process yield of ~90 %. We explore how utilization of protecting groups alters the challenges in this process and expands the portfolio of possible products to include p-(methoxymethoxy)aniline and N-acetyl-p-(methoxymethoxy)aniline. These target compounds could become value-added renewably-sourced platform chemicals that could be used to produce biodegradable plastics, pigments, and pharmaceuticals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

Performance analysis of a 3D unstructured mesh hydrodynamics code on multi‐core and many‐core architectures

SUMMARY Several next generation high performance computing platforms are or will be based on the so‐called many‐core architectures, which represent a significant departure from commodity multi‐core architectures. A key issue in transitioning large‐scale simulation codes from multi‐core to many‐core systems is closing the serial performance gap, that is, overcoming the large difference in single‐core performance between multi‐core and many‐core systems. In this paper, we discuss how this problem was addressed for a 3D unstructured mesh hydrodynamics code, describe how Amdahl's law can be used to estimate performance targets and guide optimization efforts, and present timing studies performed on multi‐core and many‐core platforms. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

Waltz, J.↗

DOE OSTI2017

Accuracy of finite-difference harmonic frequencies in density functional theory

Analytic Hessians are often viewed as essential for the calculation of accurate harmonic frequencies, but the implementation of analytic second derivatives is nontrivial and solution of the requisite coupled-perturbed equations engenders a sizable memory footprint for large systems, given that these equations are not required for energy and gradient calculations in density functional theory. Here, we benchmark the alternative approach to harmonic frequencies based on finite differences of analytic first derivatives, a procedure that is amenable to large-scale parallelization. Not only for absolute frequencies but also for isotopic and conformer-dependent frequency shifts in flexible molecules, we find that the finite-difference approach exhibits mean errors < 0.1 cm -1 as compared to results based on an analytic Hessian. For very small frequencies corresponding to nonbonded vibrations in noncovalent complexes (for which the harmonic approximation is questionable anyway), the finite-difference error can be larger, but even in these cases the errors can be reduced below 0.1 cm -1 by judicious choice of the displacement step size and a higher-order finite-difference approach. Finally, the surprising accuracy and robustness of the finite-difference results suggests that availability of the analytic Hessian is not so important in today's era of commodity processors that are readily available in large numbers.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2022

The effect of polymer grafting on the mechanical properties of PEG-grafted cellulose nanocrystals in poly(lactic acid)

Poly(lactic acid) (PLA) is a commercially available bio-based polymer that is a potential alternative to many commodity petrochemical-based polymers. However, PLA's thermomechanical properties limit its use in many applications. Incorporating polymer-grafted cellulose nanocrystals (CNCs) is one potential route to improving these mechanical properties. One key challenge in using these polymer-grafted nanoparticles is to understand which variables associated with polymer grafting are most important for improving composite properties. In this work, poly(ethylene glycol)-grafted CNCs are used to study the effects of polymer grafting density and molecular weight on the properties of PLA composites. All CNC nanofillers are found to reinforce PLA above the glass transition temperature, but non-grafted CNCs and CNCs grafted with short PEG chains (<2 kg mol –1 ) are found to cause significant embrittlement, generally resulting in less than 3% elongation-at-break. By grafting higher molecular weight PEG (10 kg mol –1 ) onto the CNCs at a grafting density where the polymer chains are predicted to be in the semi-dilute polymer brush conformation (~0.1 chains nm –2 ), embrittlement can be avoided.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Coupled‐cluster singles, doubles and perturbative triples with density fitting approximation for massively parallel heterogeneous platforms

Abstract A high‐performance implementation of the coupled‐cluster singles, doubles, and perturbative triples [CCSD(T)] is developed in the Massively Parallel Quantum Chemistry program. Novel features include: (1) reduced memory requirements via a density‐fitting (DF) CCSD implementation utilizing distributed lazy evaluation for tensors with more than two unoccupied indices and (2) the ability to utilize efficiently many‐core nodes (Intel Xeon Phi) and heterogeneous nodes with multiple NVIDIA GPUs on each node. All data that are greater than quadratic in the system size are distributed among processes. Excellent strong scaling is observed on distributed‐memory computers equipped with conventional CPUs, Intel Xeon Phi processors, and heterogeneous nodes with multiple NVIDIA GPUs Canonical CCSD(T) energies can be evaluated for systems containing 200 electrons and 1000 basis functions in a few days using a small size commodity cluster, with even larger computations possible on leadership‐class computing resources.

Peng, Chong↗

DOE OSTI2012

Thought Leaders during Crises in Massive Social Networks

The vast amount of social media data that can be gathered from the internet coupled with workflows that utilize both commodity systems and massively parallel supercomputers, such as the Cray XMT, open new vistas for research to support health, defense, and national security. Computer technology now enables the analysis of graph structures containing more than 4 billion vertices joined by 34 billion edges along with metrics and massively parallel algorithms that exhibit near-linear scalability according to number of processors. The challenge lies in making this massive data and analysis comprehensible to an analyst and end-users that require actionable knowledge to carry out their duties. Simply stated, we have developed language and content agnostic techniques to reduce large graphs built from vast media corpora into forms people can understand. Specifically, our tools and metrics act as a survey tool to identify thought leaders' -- those members that lead or reflect the thoughts and opinions of an online community, independent of the source language.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Framework for assessing land‐management effects on at‐risk species: Example of SE USA wood pellet production and gopher tortoise ( Gopherus polyphemus )

Abstract Land‐management choices made for economic and societal gains intrinsically influence landscapes and species that are dependent upon them. We propose a simple analysis framework to examine critical intersections between land‐management choices and the life‐history conditions of selected species of concern, thereby facilitating the identification of mitigation practices that can reduce negative impacts on species at risk. We test the proposed framework through application to gopher tortoise ( Gopherus polyphemus ), a keystone species that is the focus of conservation efforts across the southeastern region of United States of America, where wood pellets are being produced for bioenergy. Production of these wood pellets for export to Europe and Asia has drastically increased in the past decade, raising concerns about potential harm to biodiversity since many species in the forests sourcing pellet production were already at risk prior to the development of this new commodity. Identifying the mechanisms of potential impacts of wood pellet production on species of concern is essential to establishing meaningful management recommendations that can enhance conservation efforts while supporting sustainable bioenergy. By considering the intersections between life‐history conditions of gopher tortoise and forest‐management practices related to woody biomass extraction for pellet production, we identify several mechanisms by which the wood‐pellet industry might affect this species of concern, both positively and negatively. We then identify mitigation practices that can help offset the potential impacts of logging, thinning, and dead wood removal on gopher tortoise. Our analysis framework may be transferable to other species of concern and land‐management practices across diverse landscapes. This article is categorized under: Bioenergy > Economics and Policy Bioenergy > Climate and Environment

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Wind power costs driven by innovation and experience with further reductions on the horizon

The costs of wind power have declined to levels on par with or below those of conventional sources in many parts of the world. Wind power has become one of the fastest-growing sources of new electricity generation. We take stock of wind power cost evolution over the past 20 years, review methodologies commonly used for cost assessment, discuss the potential for continued cost reduction, and identify anticipated cost and value drivers. Our scope includes both onshore and offshore wind technologies. We draw from a vast body of literature on these topics to highlight key trends, approaches, and limitations. Furthermore, we discuss strategies for wind power assets to enhance their marginal economic value to the broader power system and consumers. We identify a myriad of factors that are expected to influence the future cost and value of wind power, including siting, project scale, turbine size, operational synergies, commodity prices, advancements in turbine technologies, enhanced management of the wind resource, and novel control technologies that provide value for the electricity grid. Because the common methods for forecasting future costs each have their own strengths and weaknesses, we find the best insights are elicited from a combination of methods. Overall, researchers and analysts anticipate further sizable cost reductions for onshore and offshore wind. Midrange forecasts for levelized cost of energy in 2050 are generally between $20 and $30/MWh for onshore wind and $40 and $60/MWh for offshore wind, a reduction to approximately half of today's levels. Optimistic forecasts anticipate these levels as early as 2030.

17 WIND ENERGY↗

DOE OSTI2024

Formally Verified ZTA Requirements for OT/ICS Environments with Isabelle/HOL

The clean energy transformation includes the integration of distributed energy resources with the power grid, which has led to a substantial increase in the complexity of power grids infrastructure and the underlying operational technology environment. Power grids infrastructure represents an operational technology environment that has become a system of systems, integrating heterogeneous devices which are both software-and hardware-intensive; as a result, there are increasing demands to exploit advances in the commodity of software-hardware infrastructures to improve energy systems requirements such as cybersecurity and resilience. In such a setting, system requirements at different levels mix, which leads to vulnerabilities and undesirable outcomes. The use of formal methods to characterize and prove system requirements removes ambiguity, increases automation, and provides high levels of assurance and reliability. In this paper, we contribute a methodology and a framework for the system-level verification of zero trust architecture requirements in operational technology environments. We define a formal specification for the core functionalities of operational technology environments, the corresponding invariants, and security proofs. Of particular note is our modular approach for the formal verification of asynchronous interactions in operational technology environments. The formal specification and the proofs have been mechanized using the interactive theorem proving environment Isabelle/HOL.

formal methods↗

DOE OSTI2014

Fast Multiresolution Reads of Massive Simulation Datasets

Today’s massively parallel simulation codes can produce output ranging up to many terabytes of data. Utilizing this data to support scientific inquiry requires analysis and visualization, yet the sheer size of the data makes it cumbersome or impossible to read without computational resources similar to the original simulation. We identify two broad classes of problems for reading data and present effective solutions for both. The first class of data reads depends on user requirements and available resources. Tasks such as visualization and user-guided analysis may be accomplished using only a subset of variables with a restricted spatial extent at a reduced resolution. The other class of reads requires full resolution multivariate data to be loaded, for example to restart a simulation. We show that utilizing the hierarchical multiresolution IDX data format enables scalable and efficient serial and parallel read access on a variety of hardware from supercomputers down to portable devices. Here, we demonstrate interactive view-dependent visualization and analysis of massive scientific datasets using low-power commodity hardware, and we compare read performance with other parallel file formats for both full and partial resolution data.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

GoFFish: A Sub-Graph Centric Framework for Large-Scale Graph Analytics1

Large scale graph processing is a major research area for Big Data exploration. Vertex centric programming models like Pregel are gaining traction due to their simple abstraction that allows for scalable execution on distributed systems naturally. However, there are limitations to this approach which cause vertex centric algorithms to under-perform due to poor compute to communication overhead ratio and slow convergence of iterative superstep. In this paper we introduce GoFFish a scalable sub-graph centric framework co-designed with a distributed persistent graph storage for large scale graph analytics on commodity clusters. We introduce a sub-graph centric programming abstraction that combines the scalability of a vertex centric approach with the flexibility of shared memory sub-graph computation. We map Connected Components, SSSP and PageRank algorithms to this model to illustrate its flexibility. Further, we empirically analyze GoFFish using several real world graphs and demonstrate its significant performance improvement, orders of magnitude in some cases, compared to Apache Giraph, the leading open source vertex centric implementation. We map Connected Components, SSSP and PageRank algorithms to this model to illustrate its flexibility. Further, we empirically analyze GoFFish using several real world graphs and demonstrate its significant performance improvement, orders of magnitude in some cases, compared to Apache Giraph, the leading open source vertex centric implementation.

Simmhan, Yogesh↗

DOE OSTI2016

Conversion of lignin into value-added materials and chemicals via laccase-assisted copolymerization

With today’s environmental concerns and the diminishing supply of the world’s petroleum-based chemicals and materials, much focus has been directed toward alternative sources. Woody biomass presents a promising option due to its sheer abundance, renewability, and biodegradability. Lignin, a highly irregular polyphenolic compound, is one of the major chemical constituents of woody biomass and is the second most abundant biopolymer on Earth, surpassed only by cellulose. The pulp and paper and cellulosic ethanol industries produce lignin on the scale of millions of tons each year as a by-product. Traditionally, lignin has been viewed as a waste material and burned as an inefficient fuel. However, in recent decades, research has focused on more economical ways to convert lignin into value-added commodities, such as biofuels, biomaterials, and biochemicals, thus developing and strengthening the concept of fully integrated biorefineries. Owing to the phenolic structure of lignin, it is possible to enzymatically graft molecules onto its surface using laccases (benzenediol:oxygen oxidoreductases, EC 1.10.3.2) to create exciting novel biomaterials. These environmentally friendly enzymes use oxygen as their only co-substrate and produce water as their sole by-product, and have thus found great industrial application. Furthermore, this mini-review highlights recent advances in the field of laccase-facilitated functionalization of lignin as well as promising future directions for lignin-based polymers.

09 BIOMASS FUELS↗

DOE OSTI2017

Laccase-mediated synthesis of lignin-core hyperbranched copolymers

Lignin, one of the major chemical constituents of woody biomass, is the second most abundant biopolymer found in nature. The pulp and paper industry has long produced lignin on the scale of millions of tons annually as a by-product of the pulping process, and the dawn of cellulosic ethanol production has further contributed to this amount. Historically, lignin has been perceived as a waste material and burned as a fuel for the pulping process. But, recent research has been geared toward developing cost-effective technologies to convert lignin into valuable commodities. Attributing to the polyphenolic structure of lignin, enzymatic modification of its surface using laccases (benzenediol:oxygen oxidoreductases, EC 1.10.3.2) has demonstrated to be highly successful. The current study aims at developing lignin-core hyperbranched copolymers via the laccase-assisted copolymerization of kraft lignin with methylhydroquinone and a trithiol. Based on the physical properties of the resulting material, it is likely that crosslinking reactions have taken place during the drying process to produce a copolymeric network rather than discrete hyperbranched copolymers, with NMR data providing evidence of covalent bonding between monomers. A preliminary thermal analysis data reveals that the copolymeric material possesses a moderate glass transition temperature and exhibits good thermostability, thus may have potential application as a lignin-based thermoplastic. Scanning electron microscopy images confirm the smooth, glossy surface of the material and that it is densely packed. Our results are a sustainable, ecofriendly, economic method to create an exciting novel biomaterial from a renewable feedstock while further enhancing lignin valorization.

09 BIOMASS FUELS↗