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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 235 records · Page 13

Defining the Minimal Set of Microbial Genes Required for Valorization of Lignin Biomass (Final Report)

Project Goals: Lignin is the second most abundant biopolymer on earth and represents a critically underutilized biomass resource for hydrocarbon feedstocks. Despite substantial effort, there is still no efficient process to convert lignin to useable carbon-based platform chemicals and materials. The goal of this project is identify a minimal set of microbial enzymes necessary for lignin breakdown and sufficient for the synthesis of valuable chemical intermediates from lignin isolated as a byproduct of lignocellulosic ethanol production. These genes will be then used to engineer functional whole cell biocatalysts for tunable lignin metabolism. To date, although a number of enzymes have been associated with lignin degradation, most have been tested in isolation (as individual enzymes) and on drastically different substrates -- often dyes that are not related to lignin. In contrast, lignin utilization in nature likely occurs by microbial consortia with multiple enzymes acting synergistically. We propose to examine two separate stages of lignin breakdown carried out by the microbes that do it best: (1) early breakdown of native polymeric lignin into soluble fragments by a set of sequenced wood-rotting fungal species, and (2) downstream metabolism of these soluble lignin fragments to useful chemical intermediates by a panel of sequenced soil saprophytes. Our approach involves testing sets of genes that will be assayed combinatorially in the context of a heterologous expression host. The resulting engineered strains will be systematically assayed using soluble lignin fragments, synthetic defined polymeric lignin, and finally lignin directly sourced from lignocellulosic processing streams. In addition to resulting in a functional whole cell biocatalyst for lignin utilization, we anticipate that this approach will allow us to address key unanswered questions about lignin metabolism in nature, including: (1) Why does the Trametes versicolor genome contain 25 different class II peroxidases? (2) What is the role of laccases in lignin metabolism? Why do some aggressive lignin degraders have many laccases (e.g. >7 in T. versicolor) while others have none (e.g. P. chrysosporium)? (3) How is peroxide provided in a controlled manner to drive peroxidase activity without causing the enzyme inhibition that is so often observed in vitro? (4) What strategies do microbial lignin degraders use to avoid the problem of repolymerization during active lignin degradation? and (5) Can microbial lignin metabolism be diverted for high level production of defined aromatics? A final critical question is whether combining key minimal sets of enzymes from a wide range of organisms will result in engineered strains capable of highly efficient, streamlined pathways for lignin utilization that can be tuned for a specific carbon output. This effort will leverage DOE investments in microbial genome sequencing, and secure a critical channel for lignin biomass utilization that will also help to render lignocellulosic a viable feedstock for the production of renewable liquid biofuels.

59 BASIC BIOLOGICAL SCIENCES↗

Computationally Directed Discovery of MoBi 2

Incorporating bismuth, the heaviest element stable to radioactive decay, into new materials enables the creation of emergent properties such as permanent magnetism, superconductivity, and nontrivial topology. Understanding the factors that drive Bi reactivity is critical for the realization of these properties. Using pressure as a tunable synthetic vector, we can access unexplored regions of phase space to foster reactivity between elements that do not react under ambient conditions. Furthermore, combining computational and experimental methods for materials discovery at high-pressures provides broader insight into the thermodynamic landscape than can be achieved through experiment alone, informing our understanding of the dominant chemical factors governing structure formation. Herein, we report our combined computational and experimental exploration of the Mo–Bi system, for which no binary intermetallic structures were previously known. Using the ab initio random structure searching (AIRSS) approach, we identified multiple synthetic targets between 0–50 GPa. Highpressure in situ powder X-ray diffraction experiments performed in diamond anvil cells confirmed that Mo–Bi mixtures exhibit rich chemistry upon the application of pressure, including experimental realization of the computationally predicted CuAl 2 -type MoBi 2 structure at 35.8(5) GPa. Electronic structure and phonon dispersion calculations on MoBi 2 revealed a correlation between valence electron count and bonding in high-pressure transition metal–Bi structures as well as identified two dynamically stable ambient pressure polymorphs. Our study demonstrates the power of the combined computational–experimental approach in capturing highpressure reactivity for efficient materials discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nanopore Readable Activity Probes for Ribosomal Inactivating Protein (RIP) Toxins

Ribosome inactivating proteins (RIPs) such as ricin and abrin depurinate an adenine base in the sarcin/ricin loop in the large ribosomal subunit, leading to inhibtion of protein synthesis and cell death. Here, we demonstrate that RIP toxin activity can be detected via nanopore-based DNA sequencing using synthetic oligonucleotide substrates. This is achieved by monitoring the mismatch proportion at the canonical target sequences incorporated into the synthetic substrate and determining the sequence length distribution throughout the entire substrate sequence. The mismatch proportion increases and sequence length distribution decreases with increasing toxin concentration for both ricin and abrin in buffer as well as in more complex backgrounds such as saliva and nasal secretions.

Turner, Matthew W [Pacific Northwest National Labo↗

Composite Behavior of Nanopore Array Large Memristors

Synthetic nanopores were recently demonstrated with memristive and nonlinear voltage-current behaviors, akin to ion channels in a cell membrane. Such ionic devices are considered a promising candidate for the development of brain-inspired neuromorphic computing techniques. In this work, we show the composite behavior of nanopore-array large memristors, formed with different membrane materials, pore sizes, electrolytes, and device arrangements. Anodic aluminum oxide (AAO) membranes with 5 nm and 20 nm diameter pores and track-etched polycarbonate (PCTE) membranes with 10 nm diameter pores are tested and shown to demonstrate memristive and nonlinear behaviors with approximately 107–1010 pores in parallel when electrolyte concentration across the membranes is asymmetric. Ion diffusion through the large number of channels induces time-dependent electrolyte asymmetry that drives the system through different memristive states. The behaviors of series composite memristors with different configurations are also presented. In addition to helping understand fluidic devices and circuits for neuromorphic computing, the results also shed light on the development of field-assisted ion-selection-membrane filtration techniques as well as the investigations of large neurons and giant synapses. Further work is needed to de-embed parasitic components of the measurement setup to obtain intrinsic large memristor properties.

Chemistry↗

Robust reconstruction of single-cell RNA-seq data with iterative gene weight updates

Single-cell RNA-sequencing technologies have greatly enhanced our understanding of heterogeneous cell populations and underlying regulatory processes. However, structural (spatial or temporal) relations between cells are lost during cell dissociation. These relations are crucial for identifying associated biological processes. Many existing tissue-reconstruction algorithms use prior information about subsets of genes that are informative with respect to the structure or process to be reconstructed. When such information is not available, and in the general case when the input genes code for multiple processes, including being susceptible to noise, biological reconstruction is often computationally challenging. We propose an algorithm that iteratively identifies manifold-informative genes using existing reconstruction algorithms for single-cell RNA-seq data as subroutine. We show that our algorithm improves the quality of tissue reconstruction for diverse synthetic and real scRNA-seq data, including data from the mammalian intestinal epithelium and liver lobules.

59 BASIC BIOLOGICAL SCIENCES↗

Bacterium-enabled transient gene activation by artificial transcription factors for resolving gene regulation in maize

Abstract Understanding gene regulatory networks is essential to elucidate developmental processes and environmental responses. Here, we studied regulation of a maize (Zea mays) transcription factor gene using designer transcription activator-like effectors (dTALes), which are synthetic Type III TALes of the bacterial genus Xanthomonas and serve as inducers of disease susceptibility gene transcription in host cells. The maize pathogen Xanthomonas vasicola pv. vasculorum was used to introduce 2 independent dTALes into maize cells to induced expression of the gene glossy3 (gl3), which encodes a MYB transcription factor involved in biosynthesis of cuticular wax. RNA-seq analysis of leaf samples identified, in addition to gl3, 146 genes altered in expression by the 2 dTALes. Nine of the 10 genes known to be involved in cuticular wax biosynthesis were upregulated by at least 1 of the 2 dTALes. A gene previously unknown to be associated with gl3, Zm00001d017418, which encodes aldehyde dehydrogenase, was also expressed in a dTALe-dependent manner. A chemically induced mutant and a CRISPR-Cas9 mutant of Zm00001d017418 both exhibited glossy leaf phenotypes, indicating that Zm00001d017418 is involved in biosynthesis of cuticular waxes. Bacterial protein delivery of dTALes proved to be a straightforward and practical approach for the analysis and discovery of pathway-specific genes in maize.

59 BASIC BIOLOGICAL SCIENCES↗

Bipolar Membrane Capacitive Deionization for the Selective Capture of Lithium Ions from Brines and Conversion to Lithium Hydroxide

Meeting the increasing demand for lithium in vehicle electrification and renewable energy storage requires innovations in lithium-ion (Li + ) separations. Traditional solar evaporation methods for lithium recovery are slow and consume tremendous volumes of water and secondary chemicals (acids and bases). This study introduces a bipolar membrane capacitive deionization (BPM-CDI) unit for direct lithium extraction and LiOH production without the external addition of acids and bases. Utilizing de-lithiated lithium-iron-phosphate (LFP) coated carbon cloth electrodes, the BPM-CDI unit demonstrates selective Li + capture over competing ions. Molecular dynamics simulations and H-cell experiments elucidate pH inversion mechanisms during Li + release, yielding LiOH. The BPM-CDI platform efficiently removes Li + from synthetic brines featuring 8x higher Mg 2+ concentrations (200 ppm Mg 2+ ) and 26x higher Na + concentrations (682 ppm Na + ), achieving a LiOH concentration of 124 ppm (36 ppm Li + ) after 8 cycles of recirculation. Post-mortem analysis confirms electrode integrity and stability. BPM-CDI integrated with selective electrodes is a promising electrochemical separation-reactor platform for lithium recovery while producing LiOH.

Kulkarni, Tanmay↗

Synthetic data-driven deep learning for label-free autonomous atomic force microscopy

Atomic force microscopy (AFM) is a widely used tool for nanoscale characterization across materials science, energy research, and biology. However, its adoption in high-throughput materials discovery and statistically driven studies remains limited by a strong dependence on expert operator input and by the scarcity of annotated experimental AFM datasets needed to enable data-driven automation. Here, we introduce SimuScan, a synthetic-data–driven framework that enables reliable AFM feature identification, segmentation, and targeted imaging without requiring large manually labeled experimental datasets. SimuScan generates tunable, high-fidelity synthetic AFM images of defined morphologies while incorporating realistic experimental artifacts, including tip–sample convolution, noise, flattening distortions, and surface debris. These datasets are shown to support scalable, label-free training of modern deep learning models for AFM analysis. When integrated into data-driven AFM workflows, SimuScan-trained models can locate and analyze nanoscale structures across large datasets and guide targeted follow-up imaging. We validate this approach on nanostructured surfaces, DNA assemblies, and bacterial cells, demonstrating robust generalization across diverse sample types with minimal operator intervention. More broadly, this work establishes a general strategy for generating explicitly conditioned, task-relevant synthetic data to improve the reliability of downstream models in autonomous microscopy.

Millan-Solsona, Ruben [Oak Ridge National Laborato↗

Facilitated Direct Liquid Fuel Cells with High Temperature Membrane Electrode Assemblies

Dimethyl ether (DME) is a liquid fuel of great potential impact due to its exceptionally high energy density. However, it has received minimal prior investigation as an alternative to either purified hydrogen or other liquid fuels, including methanol (MeOH). In the limited published literature work on direct dimethyl ether fuel cells, regardless of operating temperature, PtRu (either supported or unsupported on carbon) has been established as the standard catalyst of choice. The majority of the work in this program also utilized a Johnson Matthey (JM) HiSPEC ® 12100 PtRu/C (nominally 50% Pt, 25% Ru) while looking at electrode optimizations, beginning of life (BoL) performance, pressure- and temperature-dependent studies to look at the effect of binding affinity of DME oxidation intermediates, mass transport effects, crossover studies, and durability. However, it does also investigate some promising alternatives to PtRu/C as well, which should be investigated in more detail in further work. Those catalysts include a pair of ternary PtRuPd/C catalysts (from Los Alamos National Laboratory (LANL) and Pajarito Powder, LLC. (PP)) as well as a Pt 2 Bi Black catalyst from Professor Anastasios Angelopoulos of the University of Cincinnati (UC). This work achieved several project objectives, including an optimization of the membrane electrode assembly (MEA) process using PtRu/C anode catalyst. Additionally, these direct dimethyl ether fuel cells (DDFCs) were able to match or exceed many performance metrics for the state-of-the-art (SOA) direct methanol fuel cells (DMFCs), a primary and more evolved competitor to direct dimethyl ether fuel cells. This included peak specific power, total platinum group metal (PGM) loading, crossover current, degradation rate, start/stop cycling losses, and anode specific current.

09 BIOMASS FUELS↗

Bat554: Machine Learning for Accelerated Life Prediction and Cell Design

This presentation describes work associated with the early prediction of life and failure modes using machine learning. Key areas which will be highlighted are the generation of synthetic data, the use of deep learning and other machine learning models and the use of machine learning to train life prediction models.

25 ENERGY STORAGE↗

Engineered Living Materials For Sustainability

Recent advances in synthetic biology and materials science have given rise to a new form of materials, namely engineered living materials (ELMs), which are composed of living matter or cell communities embedded in self-regenerating matrices of their own or artificial scaffolds. Like natural materials such as bone, wood, and skin, ELMs, which possess the functional capabilities of living organisms, can grow, self-organize, and self-repair when needed. They also spontaneously perform programmed biological functions upon sensing external cues. Currently, ELMs show promise for green energy production, bioremediation, disease treatment, and fabricating advanced smart materials. This review first introduces the dynamic features of natural living systems and their potential for developing novel materials. We then summarize the recent research progress on living materials and emerging design strategies from both synthetic biology and materials science perspectives. Lastly, we discuss the positive impacts of living materials on promoting sustainability and key future research directions.

36 MATERIALS SCIENCE↗

Advanced Pt-Based Core–Shell Electrocatalysts for Fuel Cell Cathodes

Proton-exchange membrane fuel cells (PEMFCs) are highly efficient energy storage and conversion devices. Thus, the platinum group metal (PGM)-based catalysts which are the dominant choice for the PEMFCs have received extensive interest during the past couple of decades. However, the drawbacks in the existing PGM-based catalysts (i.e., high cost, slow kinetics, poor stability, etc.) still limit their applications in fuel cells. The Pt-based core–shell catalysts potentially alleviate these issues through the low Pt loading with the associated low cost and the high corrosion resistance and further improve the oxygen reduction reaction’s (ORR’s) activity and stability. This Account focuses on the synthetic strategies, catalytic mechanisms, factors influencing enhanced ORR performance, and applications in PEMFCs for the Pt-based core–shell catalysts. We first highlight the synthetic strategies for Pt-based core–shell catalysts including the galvanic displacement of an underpotentially deposited non-noble metal monolayer, thermal annealing, and dealloying methods, which can be scaled-up to meet the requirements of fuel cell operations. Subsequently, catalytic mechanisms such as the self-healing mechanism in the Pt monolayer on Pd core catalysts, the pinning effect of nitrogen (N) dopants in N-doped PtNi core–shell catalysts, and the ligand effect of the ordered intermetallic structure in L10-Pt/CoPt core–shell catalysts and their synergistic effects in N-doped L10-PtNi catalysts are described in detail. Additionally, the core–shell structure in the Pt-based catalysts have two main effects for enhanced ORR performance: (i) the interaction between Pt shells and core substrates can tune the electronic state of the surface Pt, thus boosting the ORR activity and stability, and (ii) the outer Pt shell with modest thickness can enhance the oxidation and dissolution resistance of the core, resulting in improved durability. We then review the recent attempts to optimize the ORR performance of the Pt-based core–shell catalysts by considering the shape, composition, surface orientation, and shell thickness. The factors influencing the ORR performance can be grouped into two categories: the effect of the core and the effect of the shell. In the former, PtM core–shell catalysts which use different non-PGM element cores (M) are summarized, and in the latter, Pt-based core–shell catalysts with different shell structures and compositions are described. The modifications of the core and/or shell structure can not only optimize the intermediate-binding energetics on the Pt surface through tuning the strain of the surface Pt, which increases the intrinsic activity and stability, but also offer a significantly decreased catalyst cost. Finally, we discuss the membrane electrode assembly performance of Pt-based core–shell catalysts in fuel cell cathodes and evaluate their potential in real PEMFCs for light-duty and heavy-duty vehicle applications. Even though some challenges to the activity and lifetime in the fuel cells remain, the Pt-based core–shell catalysts are expected to be promising for many practical PEMFC applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

In-situ investigation of the vibrational properties of H 2 O CO 2 -bearing and dry K-rich basaltic glasses at high pressure by mid infrared spectroscopy

Here, the vibrational properties of CO 2 –H 2 O-bearing and dry synthetic K-rich basaltic glasses were investigated at room temperature and pressures between 0.0001–5.5 GPa using the diamond anvil cell combined with in situ reflectance and transmittance Fourier Transform infrared micro-spectroscopy. The absorption coefficient a(v) calculated from the Kramers-Kronig relation shows that glasses are dominated by the Q 2 aluminosilicate unit followed by Q 1 , Q 3 . The variation in Q n concentration upon compression suggests that glasses undergo polymerization from ambient pressure to 2 GPa followed by less marked structural changes up to 4 GPa, above which the structure is further polymerized. Once decompressed, glasses retained a polymerized structure. Our results show that 1.03 wt% CO 2 -1.42 wt% H 2 O in a glass with 3.10 wt% K 2 O and 46.77 wt% SiO 2 prevent the formation of fully polymerized connections when cold-compressed. Our results can be used to explain the effect of volatiles and alkali on the rheology of natural basaltic magmas.

36 MATERIALS SCIENCE↗

Adapting enzymes to improve their functionality in plants: why and how

Synthetic biology creates new metabolic processes and improves existing ones using engineered or natural enzymes. These enzymes are often sourced from cells that differ from those in the target plant organ with respect to, e.g. redox potential, effector levels, or proteostasis machinery. Non-native enzymes may thus need to be adapted to work well in their new plant context (‘plantized’) even if their specificity and kinetics in vitro are adequate. Hence there are two distinct ways in which an enzyme destined for use in plants can require improvement: In catalytic properties such as substrate and product specificity, kcat, and KM; and in general compatibility with the milieu of cells that express the enzyme. Continuous directed evolution systems can deliver both types of improvement and are so far the most broadly effective way to deliver the second type. Accordingly, in this review we provide a short account of continuous evolution methods, emphasizing the yeast OrthoRep system because of its suitability for plant applications. We then cover the down-to-earth and increasingly urgent issues of which enzymes and enzyme properties can — or cannot — be improved in theory, and which in practice are the best to target for crop improvement, i.e. those that are realistically improvable and important enough to warrant deploying continuous directed evolution. We take horticultural crops as examples because of the opportunities they present and to sharpen the focus.

Biochemistry & Molecular Biology↗

Targeting the Bet-Hedging Strategy with an Inhibitor of Bacterial Efflux Capacity Enhances Antibiotic Efficiency and Ameliorates Bacterial Persistence In Vitro

Persistence is a bet-hedging strategy in bacterial populations that increases antibiotic tolerance and leads to the establishment of latent infections. In this study, we demonstrated that a synthetic non-toxic taxane-based reversal agent (tRA), developed as an inhibitor of ABC transporter systems in mammalian cancer cells, enhanced antibiotic killing of persister populations from different pathogens, including Burkholderia, Pseudomonas, Francisella, and Yersinia. Acting as an inhibitor of bacterial efflux at 100 nM, tRA99020 enhanced antibiotic efficiency and suppressed the production of natural products of Burkholderia species polyketide synthase (PKS) function. We demonstrate that the metabolites produced by PKS in response to stress by different antibiotics act as inhibitors of mammalian histone deacetylase activity and stimulate cell death. Applying a single-molecule fluorescence in situ hybridization (smFISH) assay, we analyzed on a single-cell level the activation profiles of the persistence regulating pks gene in Burkholderia thailandensis treated with tRA99020 and antibiotics. We posit that a multi-pronged approach encompassing antibiotic therapies and inhibition of efflux systems and fatty acid catabolism will be required for efficient eradication of persistent bacterial populations.

59 BASIC BIOLOGICAL SCIENCES↗

A roadmap to understanding and anticipating microbial gene transfer in soil communities

Engineered microbes are being programmed using synthetic DNA for applications in soil to overcome global challenges related to climate change, energy, food security, and pollution. However, we cannot yet predict gene transfer processes in soil to assess the frequency of unintentional transfer of engineered DNA to environmental microbes when applying synthetic biology technologies at scale. This challenge exists because of the complex and heterogeneous characteristics of soils, which contribute to the fitness and transport of cells and the exchange of genetic material within communities. Here, we describe knowledge gaps about gene transfer across soil microbiomes. Here, we propose strategies to improve our understanding of gene transfer across soil communities, highlight the need to benchmark the performance of biocontainment measures in situ, and discuss responsibly engaging community stakeholders. We highlight opportunities to address knowledge gaps, such as creating a set of soil standards for studying gene transfer across diverse soil types and measuring gene transfer host range across microbiomes using emerging technologies. By comparing gene transfer rates, host range, and persistence of engineered microbes across different soils, we posit that community-scale, environment-specific models can be built that anticipate biotechnology risks. Such studies will enable the design of safer biotechnologies that allow us to realize the benefits of synthetic biology and mitigate risks associated with the release of such technologies.

bioccontainment↗

Light-powered CO 2 fixation in a chloroplast mimic with natural and synthetic parts

Nature integrates complex biosynthetic and energy-converting tasks within compartments such as chloroplasts and mitochondria. Chloroplasts convert light into chemical energy, driving carbon dioxide fixation. We used microfluidics to develop a chloroplast mimic by encapsulating and operating photosynthetic membranes in cell-sized droplets. These droplets can be energized by light to power enzymes or enzyme cascades and analyzed for their catalytic properties in multiplex and real time. We demonstrate how these microdroplets can be programmed and controlled by adjusting internal compositions and by using light as an external trigger. We showcase the capability of our platform by integrating the crotonyl–coenzyme A (CoA)/ethylmalonyl-CoA/hydroxybutyryl-CoA (CETCH) cycle, a synthetic network for carbon dioxide conversion, to create an artificial photosynthetic system that interfaces the natural and the synthetic biological worlds.

Miller, Tarryn E.↗