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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Sensor Recommendations for Long Term Monitoring of the F-Area Seepage Basins

In mid-2018, a new paradigm for long-term monitoring was developed after of decade of applied research projects funded by the Department of Energy’s office of Environmental Management Technology Development program. The program at SRNL was focused on transitioning complex environmental waste sites from active to passive remediations strategies. A key result of these studies was that the use of enhanced attenuation approaches at radiologically contaminated sites will result in the creation of secondary source areas in the subsurface that will require monitoring for decades. Alternative monitoring approaches are being developed and tested at the Savannah River Site’s F-Area Hazardous Waste Management Facility, the new paradigm provides innovative solutions that will significantly lower costs of monitoring through the coupling of data collection, machine learning and deterministic groundwater modeling. The foundation of this approach is a well-optimized network of sensors for measuring hydrogeochemical master variables that control, and therefore act as indicators of groundwater contaminant transport. By monitoring changes in the controlling master variables over time arising from geological and environmental shifts, predictive modelling can assist with identifying new strategies for ensuring regulatory requirements are met if trends toward conditions for potential remobilization of attenuated contaminants are detected. In this report, we evaluated commercially available single parameter sensor platforms (e.g., temperature/depth) and configurable multi-parameter sensor platforms (e.g., pH, oxidation-reduction potential, temperature, depth, dissolved oxygen, and conductivity). Each was scored using an optimization function based on how well the system supports the proposed long-term monitoring paradigm, in general, and the site-specific conditions at F-Area, in particular. Several viable sensor systems were identified. Of these, a combined platform including the In-Situ Aqua TROLL 500 multi-parameter sensor platform and the In-Situ temperature/depth sensor had the highest rating and was identified as the most suitable candidate for installation and monitoring of the master variables and potentiometric surface that control groundwater contaminant plumes emanating from the F-Area Seepage Basins. The discussion of recommended potential deployment locations builds upon recommendations made by Denham et al (2019).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Decomposition and Algorithmic Approaches for Solving Large-Scale Process Family Design Problems

Our most recent work expands the water desalination case study from 76 variants to 10,897 variants using the equation-oriented model built in Pyomo as part of the PARETO project. Using the discretization formulation presented in Stinchfield (2024a), rather than solving for all 10,897 variants simultaneously, we decompose the formulation into subproblems containing subsets of variants from the process family. We solve the overall problem with Progressive Hedging (PH) deployed in parallel on a distributed HPC cluster using the open-source Python package mpi-sppy (Knueven et al., 2023). This approach allowed us to solve this process family design problem to ~1.5% relative optimality gap in about 5 hours; in comparison, Gurobi reached ~50% relative optimality gap in about 6 hours (Stinchfield et al., 2024b). However, this approach still requires discretization of the common unit module design ranges; additionally, PH acts as a heuristic for MILP’s with gap-closing capabilities. Ideally, we would not have to use ML surrogates or discretization to solve this problem, instead solving the process family design problem with the equation-oriented model directly to achieve the most accurate results. However, recall that we did not consider solving the MINLP directly due to complexity and size. In this work, we aim to decompose and solve this large-scale MINLP using a Structured Nonlinear Global Optimization algorithm presented by Cao and Zavala (2019).

Stinchfield, Georgia↗
DOE OSTI2025

Analysis of semivolatile organics in liquid radioactive residue using sorptive stir bar and solvent back-extraction

Current methods for semivolatiles analysis in radioactive samples can produce large volumes of radioactive solvent residue. A method utilizing stir-bar sorptive extraction has been explored in this work for its applicability to radioactive waste samples. This low solvent analytical method may accelerate remediation, minimize hazardous solvent waste, and reduce exposure risk to workers. Organic compounds (polyaromatic hydrocarbons, chlorinated aromatics, and phenolic compounds) were chosen as surrogates for common Liquid Waste System (LWS) contaminants at Savannah River Site (Aiken, SC). Stir-bar extraction parameters (extraction time, matrix modification, and effective pH range) and solvent back extraction parameters (solvent type, volume, and extraction time) were optimized experimentally for the chosen compounds. Affinity of the stir-bar extraction polymer to radionuclides Cs-137 and Am-241 was observed to determine radionuclide concentration effects. The stir-bar method achieved mean recovery of 100 ± 0.7% (1σ), relative to 114 ± 7% using solvent extraction, while reducing weekly method hands-on time by 93.4% and solvent volume consumption by 99.3%. Sensitivity was improved by 378% in simulated tank waste and 278% in real-world LWS matrix, relative to solvent extraction. This work has produced a safe and optimized method for the low solvent analysis of organics in legacy radioactive tank waste by stir-bar sorptive extraction.

GC-MS↗
DOE OSTI2020

High-throughput screening for discovery of benchtop separations systems for selected rare earth elements

Abstract Rare earth (RE) elements (scandium, yttrium, and the lanthanides) are critical for their role in sustainable energy technologies. Problems with their supply chain have motivated research to improve separations methods to recycle these elements from end of life technology. Toward this goal, we report the synthesis and characterization of the ligand tris[(1-hydroxy-2-oxo-1,2-dihydropyridine-3-carboxamido)ethyl]amine, H 3 1·TFA (TFA = trifluoroacetic acid), and complexes 1·RE (RE = La, Nd, Dy). A high-throughput experimentation (HTE) screen was developed to quantitatively determine the precipitation of 1·RE as a function of pH as well as equivalents of H 3 1·TFA. This method rapidly determines optimal conditions for the separation of RE mixtures, while minimizing materials consumption. The HTE-predicted conditions are used to achieve the lab-scale separation of Nd/Dy ( SF Nd/Dy = 213 ± 34) and La/Nd ( SF La/Nd = 16.2 ± 0.2) mixtures in acidic aqueous media.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Optimizing enzymes for plastic upcycling using machine learning design and high throughput experiments

Plastic use is ubiquitous in the modern world, and polyethylene terephthalate (PET) is one of the most abundantly produced plastics (and the most highly produced polyester), with ~65 million metric tons manufactured annually. To the consumer, PET is likely most recognizable as the plastic used to make beverage bottles. Like many plastics, traditional mechanical or chemical means of PET deconstruction and upcycling are costly and inefficient. Because of these challenges, recycled plastic is generally of lower quality and is more expensive to produce than virgin plastic derived from petroleum. Ultimately, this results in most plastic ending up as waste. We view plastic waste as an underutilized resource which, with the development of more efficient and high-quality recycling processes, could (1) generate significant economic value while (2) decreasing petroleum usage and greenhouse gas emissions, as well as (3) minimizing its negative environmental and health impacts. Biocatalytic recycling, or biomanufacturing the basic building blocks of new plastic from plastic waste, is a promising approach to plastic reuse that complements existing recycling technologies. Recently, biological enzymes capable of breaking down PET have garnered significant attention as an attractive means of dealing with the plastic problem. These enzymes are currently undergoing pilot studies for implementation in industrial-scale enzyme-based recycling. However, there are significant limitations to current enzymes, including the need to perform costly pre-processing of the plastic waste before the enzymes are able to work. Further optimization of these enzymes is necessary to make these technologies competitive, and ultimately incentivise industry-wide adoption of this biology-based green recycling technology. n this work we demonstrate a means to design and generate performant biological enzymes, capable of efficiently deconstructing plastic waste. Specifically, we applied recent advances in artificial intelligence, machine learning, and statistical analysis to design new versions and discover natural enzymes capable of breaking down PET. We focused on optimizing key properties that are important for industrial-scale enzymatic recycling such as pH and thermotolerance. Normal testing of enzymatic plastic-deconstruction is extremely labor intensive and so through this work we also developed a robotic-assisted experimental pipeline capable of characterizing thousands of candidate enzymes. The results of this iterative, AI-guided, multi-discipline approach have led to increases in enzymatic breakdown of over 150X over starting enzymes. This work supports the rapidly developing and transformative field of biocatalytic solutions to environmental problems beyond the discovery and predictive understanding of enzymes for polymer recycling, and has wide implications for tackling numerous energy problems such as carbon capture and fixation (e.g., engineering carbon monoxide dehydrogenase and the rubisco-pathway), biomining (e.g., design of lanthanide-binding proteins) and biomanufacturing (e.g., lignin-deconstruction enzymes).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Continuous Enzymatic Hydrolysis Development for Improved Saccharification Performance

The Continuous Enzymatic Hydrolysis Development (CEHD) project aims to reduce the cost and commercialization risks of Gen2 biorefinery sugar/lignin/ethanol production through development of a deployable continuous enzymatic hydrolysis process. Recent changes in the technical landscape of commercial enzymatic hydrolysis of Gen2 pretreated biomass dictate that the existing hybrid SSF approach be reconsidered. Most importantly, the current practice of "finishing hydrolysis" in SSF must be abandoned due to the fact that new cellulase/hemicellulose formulations from Novozymes, now the sole supplier of commercial Gen2 enzymes in North America, are now not rated for SSF (see NZ CTec3HS product bulletin). We have recently developed bench scale CEH tools to optimize saccharification of DMR pretreated biomass where, unlike SSF with yeast or Zymomonas, the pH, temperature, oxygen tension, LPMO mediator concentration, and/or removal of end-product inhibitors can be precisely controlled. In scale up, the goal is to use existing commercial cross flow ceramic membrane filtration external loops coupled to enzymatic hydrolysis (EH) reactors. Pretreated biomass solids and enzymes are retained for reaction while solubilized product sugars are removed in situ, with high extents of conversion and longer enzyme lifetimes achieved through a series of reactor-membrane unit stages. The CEHD project is focused on advancing CEH as a transformational, process-intensified, lower-cost method for producing soluble clarified biomass sugars and insoluble lignin-rich streams.

BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗
DOE OSTI2023

CFD modeling of crystallization fouling with CO 2 desorption incorporated for a falling-film evaporator in thermal desalination

Seawater flowing around horizontal tubes in falling-film evaporators is a common configuration for thermal desalination. Heat is transferred from in-tube steam condensation to the shell-side seawater by conduction through the tube wall and scaling layer, and conduction and convection to the evaporating liquid film. CO 2 is simultaneously released from seawater and mixed with the produced vapor. Fouling coupled with CO 2 desorption has deleterious impacts on both evaporation and condensation. The evaluation of spatiotemporal dependent crystallization fouling and CO 2 desorption is vital to selecting optimal operating conditions. Here, in this work, a CO 2 desorption model is integrated into CFD modeling for predictions of coupled heat and mass transfer, to understand and predict scale formation and CO 2 desorption with local and transient profiles of temperature, carbonate species concentrations, pH, and total alkalinity. The porosity of the scale layer is experimentally determined as 67.7% and invoked in the calculation of effective thermal conductivity. The simulation results reveal that high steam temperatures increase seawater total alkalinity and accelerate scale formation. The scale thickness on the bottom tube reaches 0.30 μm and 5.24 μm for steam temperatures of 60 °C and 80 °C, respectively. High salinity leads to a large CO 2 desorption rates. The CO 2 desorption rate increases 43% when the seawater salinity increases from 35 to 55 g/kg. The effects of operating conditions on carbonate speciation and pH have been compared and analyzed. This model can serve as a comprehensive tool for the design of thermal desalination systems and optimal operation.

42 ENGINEERING↗
DOE OSTI2026

3-Hydroxypropionic acid recovery from fermentation broth through novel downstream processing: Technoeconomic analysis

This study develops and validates a simplified, fully solvent-free downstream processing (DSP) strategy for high-purity recovery of 3-hydroxypropionic acid (3-HP) from real fermentation broth containing 62.3 g/L of 3-HP. Optimized activated carbon treatment achieved 98% color removal, while Amberlite IRA-67 was operated at pH 4.5 and 30 °C to minimize product loss. This is the first integrated demonstration of a fully solvent-free DSP enabling recovery of bio-based 3-HP as both a solid sodium salt and a concentrated aqueous solution, supported by techno-economic analysis. At lab scale, the process achieved 77.3% recovery of sodium 3-HP with 83.2% (w/w) purity and produced a 30% (w/v) aqueous solution. Techno-economic analysis yielded minimum selling prices of $0.551/kg for the solution and $0.892/kg for the salt, both below target thresholds for cost-competitive bio-acrylic acid production. Overall, these results demonstrate an efficient, scalable, and economically viable industrial pathway for 3-HP recovery.

09 BIOMASS FUELS↗
DOE OSTI2021

Detection and Aggregation of Listeria Monocytogenes Using Polyclonal Antibody Gold-Coated Magnetic Nanoshells Surface-Enhanced Raman Spectroscopy Substrates

Magnetic nanoshells with tailored surface chemistry can enhance bacterial detection and separation technologies. This work demonstrated a simple technique to detect, capture, and aggregate bacteria with the aid of end-functionalized polyclonal antibody gold-coated magnetic nanoshells (pAb-Lis-AuMNs) as surface-enhanced Raman spectroscopy (SERS) probes. Listeria monocytogenes were used as the pathogenic bacteria and the pAb-LisAuMNs, 300 nm diameter, were used as probes allowing facile magnetic separation and aggregation. An optimized covalent bioconjugation procedure between the magnetic nanoshells and the polyclonal antibody was performed at pH six via a carbodiimide crosslinking reaction. Spectroscopic and morphological characterization techniques confirmed the fabrication of stable pAb-Lis-AuMNs. The resulting pAb-Lis-AuMNs acted as a SERS probe for L. monocytogenes based on the targeted capture via surface binding interactions and magnetically induced aggregation. Label-free SERS measurements were recorded for the minimum detectable amount of L. monocytogenes based on the SERS intensity at the 1388 cm -1 Raman shift. L. monocytogenes concentrations exhibited detection limits in the range of 10 4 –10 7 CFU ml -1 , before and after aggregation. By fitting these concentrations, the limit of detection of this method was ~10 3 CFU ml -1 . Using a low-intensity magnetic field of 35 G, pAb-LisAuMNs aggregated L. monocytogenes as demonstrated with microscopy techniques, including SEM and optical microscopy. Overall, this work presents a label-free SERS probe method comprised of a surface-modified polyclonal antibody sub-micron magnetic nanoshell structures with high sensitivity and magnetic induced separation that could lead to the fabrication of multiple single-step sensors.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

Harnessing Heterologous Bacterial Two-Component Systems as Biosensors to Address Challenges in Fermentation Scale-Up

Scaling up bacterial fermentation from bench to industrial scale often results in unpredictable performance losses, possibly in part due to changes in microenvironmental conditions such as pH. To investigate this, we developed a suite of pH-sensitive biosensors from bacterial two-component systems (TCSs) that provide a dynamic, fluorescent readout in response to extracellular pH changes. TCSs consist of a periplasmic sensor histidine kinase (HK) that, in response to an extracellular stimulus, autophosphorylates intracellularly and subsequently transfers the phosphate to a cognate response regulator (RR) that modulates transcription of target genes. We utilized three pH-responsive TCSs (referred to here as CVJ1, CVJ30, and CVJ79) and linked their output to GFP. This was achieved by placing the RR promoter upstream of GFP or by constructing a chimeric RR composed of the native receiver domain and the DNA-binding domain of another well-characterized RR with a defined promoter. All components - HK, RR (native or chimeric), and GFP under its corresponding promoter - were cloned into a broad-host-range plasmid. Sensors were validated in Escherichia coli and Pseudomonas putida, including the muconic acid-producing strain P. putida TL207. All three biosensors successfully reported pH, with fluorescence (normalized to optical density) correlating strongly with media pH. Among the native sensors, CVJ79 showed the most robust performance while CVJ1 also performed best in its native form; CVJ30 exhibited improved functionality as a chimera, suggesting that modular RR design can enhance compatibility in some heterologous hosts. Further, CVJ79 was activated by alkaline conditions, while CVJ30 responded to acidic environments. Notably, CVJ1 was induced by high pH in wild-type E. coli and P. putida, but low pH in TL207. The observed differences in sensor activation between strains - particularly the divergent response of CVJ1 - suggest that host-specific regulatory pathways may influence how cells perceive and adapt to pH stress. Moving forward, these biosensors can be used to guide the rational design of more robust strains, optimize process conditions in real time, and inform strategies to minimize physiological heterogeneity during scale-up. Integrating these tools into high-throughput screening and bioreactors will be a key step toward improving predictability and performance in industrial bioprocesses.

09 BIOMASS FUELS↗
DOE OSTI2026

CO (2) Electroreduction on Borated Copper Surfaces: Boron Active Sites, Not Copper

Boron-doped copper has recently emerged as an active and stable catalyst for the electrochemical reduction of CO 2 to value-added C 2 products. Here, in this work, we develop a realistic model of CO electroreduction on surface borides of copper under operational conditions, taking into account the effects of electrode potential, electrolyte environment, and pH. We study the possible reconstruction of the electrocatalyst surface using grand canonical DFT and global optimization to obtain a potential-dependent grand canonical ensemble description of metastable, hydrogen-covered catalyst surfaces. Two key surface configurations, low H coverage (LC, −0.6 V SHE ) and high H coverage (HC, −0.8 V SHE ), dominate this ensemble, with the former being kinetically persistent and C 2 selective under strongly reducing conditions. Nonmetallic boron sites on the surface copper boride are found to bind CO more strongly than copper sites, and mechanistic investigation of CO electroreduction pathways presents a surprisingly unconventional case of boron-centered reactivity in contrast to typical copper-centered reactivity. Neighboring boron sites present along boron chains on the surface copper boride are found to facilitate C−C coupling, thereby driving the high C 2 selectivity of this electrocatalyst.

boron-doped copper↗
DOE OSTI2025

Engineering surface charges of nanofiltration membranes to maximize Li + /Mg 2+ separation properties

Polyamide-based nanofiltration (NF) membranes are attractive for Li + /Mg 2+ separation for lithium recovery from salt brine (containing mainly Mg 2+ ). However, Li + and Mg 2+ have similar hydration radii, resulting in a low separation factor (SF Li/Mg ). Herein, we demonstrate that SF Li/Mg can be significantly enhanced by optimizing the membrane surface positive charges. This results in an unexpected maximum SF Li/Mg at a solution pH slightly below its isoelectric point (IEP). Specifically, NF270 membrane was surface-grafted with 2-(methacryloyloxy)ethyltrimethylammonium chloride (META) or polyethylenimine (PEI) using bio-adhesive dopamine, forming a thin, stable, charged layer (20–40 nm) on the surface. The effects of solution pH and surface modification on the surface zeta potential (ZP) and single- and mixed-salt Li + /Mg 2+ separation properties are thoroughly investigated. For example, the META grafting increases the ZP from 9.2 to 16 mV and SF Li/Mg by 130 % from 35 to 80 at pH 4, superior to the state-of-the-art commercial NF membranes. Furthermore, this surface modification occurs at ≈22 °C in aqueous solutions and can be utilized to enhance commercial modules for practical applications.

Li+/Mg2+ separation↗
DOE OSTI2025

Enhancing the Multifunctional Photocatalytic Activity of Sustainable Magnetic Nanoparticles

The development of efficient photocatalytic materials has intensified in response to increasing emphasis on sustainable energy conversion and environmental restoration. However, the excessive use and indiscriminate release of heavy metals from photocatalytic nanoparticles pose potential environmental risks. This study provides insights into optimizing visible-light-active photocatalysts to enhance their photocatalytic properties and stability. Specifically, cobalt doping and controlled pH modulation are employed on the modified Fe 3 O 4 , forming two distinct samples: Co@Fe 3 O 4 -B (base-treated) and Co@Fe 3 O 4 -A (acid-treated) nanoparticles. Microscopic characterization reveals that Co@Fe 3 O 4 -A undergoes a phase transition to hematite, whereas Co@Fe 3 O 4 -B retains its mixed-phase configuration. Spectroscopic analyses confirm that the cobalt dopants decorate the outskirts of each nanoparticle, forming a core–shell structure. However, Co@Fe 3 O 4 -B exhibit Co 2+ states with a high oxygen vacancy content, whereas Co@Fe 3 O 4 -A contain mixed Co 2+/3+ states. The high density of defect states in the Co@Fe 3 O 4 -B results in superior photocatalytic efficiency, achieving near-complete oxidation of furfuraldehyde (97% conversion) and 5-hydroxymethylfurfural (94% conversion), as well as effective degradation of toluene (78% conversion). This study demonstrates that the combined approach of doping and pH treatment is promising for the surface-defect engineering of photocatalysts, enhancing their multifunctional performance and reusability for sustainable energy conversion.

Fe3 O4 nanoparticles↗
DOE OSTI2022

Hydration of alumina (Al 2 O 3 ) toward advancing aluminum particles for energy generation applications

Transforming metal particle combustion may require alteration of the metal oxide passivation shell surrounding the metal core. One approach for aluminum (Al) relies on the hydrated form of the metal oxide to incite surface reactions. Here, this study explores the conditions required for hydrating alumina (Al 2 O 3 ) particles and then extends those conditions toward hydration of the Al 2 O 3 passivation layer surrounding an Al core particle. By raising the pH of the water slurry to 11 and controlling temperature and time in slurry (i.e., aging), aluminum hydroxide Al(OH) 3 formation from Al 2 O 3 particles was optimized. The procedure was then extended to Al nanoparticles (nAl). Even though heating and extended aging time in slurry proved advantageous for Al 2 O 3 particles, these conditions were discarded for nAl particles because they favored formation of AlOOH, a less desirable hydrate. Through microscopy, spectroscopy, X-ray diffraction, and thermal analyses, results indicate that for a pH range of 11.26–11.56, the original Al 2 O 3 shell on Al particles transformed into Al(OH) 3 . Results indicate a feasible path forward towards producing new shell chemistries that may result in more directed energy from metal particle combustion.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Scaling up carboxylic acid production from cheese whey and brewery wastewater via methane-arrested anaerobic digestion

In a circular economy, organic waste streams are valuable resources for sustainably producing chemicals and fuels. This study investigates a new methane-arrested anaerobic digestion (MAAD) process that converts high-strength cheese whey and brewery wastewater into carboxylic acids. The process was developed and optimized under various bench-scale semi-continuous (fed-batch) operating conditions (e.g., retention time, organic loading rate, pH, and feed/harvest frequency). The MAAD responses to various control-failure scenarios were also systematically investigated. The highest total acid productivity was 26g/(L liq ·d) with a substrate conversion of 0.79g COD digested /g COD fed at a hydraulic retention time (HRT) of approximately 2 d in a 14-L digester. The most stable conditions for digester operation (HRT 3 d at pH 6.0 and 40°C) were selected for process scale-up to 100gal (~380 L). Semi-continuous, pilot-scale MAAD successfully produced a total acid concentration of 40.6+/-1.1 g/L with 8.1% acetic acid, 45.1% butyric acid, and 44.5% lactic acid. The links between wastewater characteristics, operation mode, digester scale, and microbial community structure were statistically analyzed. The results show genera Sporolactobacillus and Clostridium positively correlate with butyric acid production (Pearson correlation coefficient>0.5). Moreover, four kinetic models were developed and fit to batch MAAD experimental datasets (R 2 >95%) and were successfully applied to predict the total acid production in both bench-and pilot-scale semi-continuous MAADs. In conclusion, this study shows MAAD has the potential for industrial-scale applications and is a robust platform to valorize low- or negative-value waste streams into high-value bioproducts.

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

Sustainable Lactic Acid Production from Lignocellulosic Biomass

Lignocellulosic biomass is a promising feedstock for sustainable biofuels and bioproducts. Among emerging bioproducts, lactic acid has attracted significant interest because of its growing application in many industries (e.g., packaging, medical, and pharmaceutical). In this study, BioSTEAM—an open-source platform—was leveraged for the design, simulation, and evaluation (via techno-economic analysis, TEA, and life cycle assessment, LCA) of lignocellulosic lactic acid biorefineries. With a minimum product selling price (MPSP) between 1.38 and 1.91 kg –1 (5th–95th percentiles, baseline at 1.57 kg –1 ), the biorefinery was capable of producing market-competitive lactic acid (market price between 1.7 and 2.1 kg –1 ), and its performance could be further enhanced (e.g., MPSP down to 1.09 kg –1 , global warming potential of 2.79 kg CO 2 -eq·kg –1 , and fossil energy consumption of 31.7 MJ·kg –1 ) with advancements in key technological parameters (fermentation yield and separation process conversions) and optimization in process operation. Sensitivity analyses focused on the fermentation unit (across titer, yield, and productivity; neutral vs low-pH fermentation) and feedstock characteristics (carbohydrate content and price) were also included to quantify their impact on the sustainability of the biorefinery. Overall, this research highlights the ability of agile TEA/LCA to screen promising biorefinery designs, prioritize research needs, and establish a road map for the continued development of bioproducts and biofuels.

09 BIOMASS FUELS↗
DOE OSTI2025

Optimal production of Phanerochaete chrysosporium manganese peroxidases and Trametes sp. C30 laccase hybrid Lac131 in Aspergillus niger for lignin bioconversion

Background Incorporating the production of related ligninolytic enzymes into industrial filamentous fungus Aspergillus niger will enhance the bioconversion of lignocelluloses to various chemical products. Results In this study, transgenic expression of Phanerochaete chrysosporium manganese peroxidases (mnps) and Trametes sp. C30 laccase hybrid Lac131 (lac131) were examined and optimized in A. niger 11414 prtT∆ strain. Five mnps (mnp1, mnp2, mnp3, mnp4, and mnp5) and lac131 genes were expressed separately or in combination. The transgenic strain containing the entire mnp2 genomic coding sequence (gmnp2) exhibited the highest mnP activity among the five mnp over-expression strains in the modified minimal medium (mMM) with addition of 5 g/L bovine hemoglobin (bHg). We examined the effects of hemin and bHg on mnP production in the gmnp2 strain cultures and found that at least 1 g/L bHg was required, while hemin was not. Culture conditions for mnP production were further optimized for the gmnp2 strain and the highest mnP activities were detected in the cultures grown at 25 °C and 200 rpm with an initial pH of 4.5. Effects of soy protein, skim milk, and bovine serum albumin on mnP production were investigated; 5 g/L of soy proteins or skim milk had comparable effects to 2.5 g/L bHg, while cultures with bovine serum albumin had diminished mnP activity. Disruption of both prtT and vsm1 substantially augmented the mnP production and its activity reached 575 U/L. Trametes sp. C30 laccase hybrid lac131 was strongly expressed in either A. niger gmnp2 (1975 U/L) or 11414prtT∆ (3895 U/L) strain. Both mnP and laccase in the culture supernatants effectively decolorized selected phenolic compounds (dyes) and cleaved tagged model lignin dimers. Conclusion The mnP was successfully produced in A. niger by optimizing the culture conditions and host strain. Co-expression of all four mnp genes in the same expression host by multiplex CRISPR will lead to the mnP production reaching levels comparable to P. chrysosporium, while only requiring 36 h at 25 °C. The Lac131 activity in transgenic A. niger strain is 4- to 7-times higher than that in previous studies. Co-production of mnP and laccase in A. niger will enhance the lignin bioconversion efficiency.

Aspergillus niger↗