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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Exploring the Performance and Reliability of Screen-Printable Fire-Through Copper Paste on PERC Solar Cells

In this work, we present the performance and reliability of a fire-through copper (Cu) paste which has been screen printed on c-Si solar cell with passivated emitter rear contact (PERC). The Cu paste is fired through silicon nitride (SiN) anti-reflection coating at a peak temperature of 630 degrees C . SEM images of the Cu paste show a Cu core with ~200 nm oxide shell around the particles. This conductive oxide layer acts as a diffusion barrier between Cu and Si and prevents the degradation of cell performance during accelerated aging conditions. An efficiency of 19.250% has been achieved with Voc=654mV,FF= 76.68%, Jsc=38.40 m.A/cm 2 for champion PERC cells. Accelerated testing of the PERC mini-modules in damp heat chamber with 85 degrees C and 85% humidity have demonstrated that the devices are operational even after 1,500 hours. Devices with screen printed Ag contacts on the front side have been studied in parallel to the Cu contacts for comparison.

copper↗
DOE OSTI2023

Development of Human Carbonic Anhydrase II Heterobifunctional Degraders

Human carbonic anhydrase II (hCAII) is a metalloenzyme essential to critical physiological processes in the body. hCA inhibitors are used clinically for the treatment of indications ranging from glaucoma to epilepsy. Targeted protein degraders have emerged as a promising means of inducing the degradation of disease-implicated proteins by using the endogenous quality control mechanisms of a cell. Here, a series of heterobifunctional degrader candidates targeting hCAII were developed from a simple aryl sulfonamide fragment. Degrader candidates were functionalized to produce either cereblon E3 ubiquitin ligase (CRBN) recruiting proteolysis targeting chimeras (PROTACs) or adamantyl-based hydrophobic tags (HyTs). Screens in HEK293 cells identified two PROTAC small-molecule degraders of hCA. Optimization of linker length and composition yielded a degrader with sub-nanomolar potency and sustained depletion of hCAII over prolonged treatments. Mechanistic studies suggest that this optimized degrader depletes hCAII through the same mechanism as previously reported CRBN-recruiting heterobifunctional degraders.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

On Single-Cell Enzyme Assays in Marine Microbial Ecology and Biogeochemistry

Extracellular enzyme activity is a well-established parameter for evaluating microbial biogeochemical roles in marine ecosystems. The presence and activity of extracellular enzymes in seawater provide insights into the quality and quantity of organic matter being processed by the present microorganisms. A key challenge in our understanding of these processes is to decode the extracellular enzyme repertoire and activities of natural communities at the single-cell level. Current measurements are carried out on bulk or size-fractionated samples capturing activities of mixed populations. This approach – even with size-fractionation – cannot be used to trace enzymes back to their producers, nor distinguish the active microbial members, leading to a disconnect between measured activities and the producer cells. By targeting extracellular enzymes and resolving their activities at the single-cell level, we can investigate underlying phenotypic heterogeneity among clonal or closely related organisms, characterize enzyme kinetics under varying environmental conditions, and resolve spatio-temporal distribution of individual enzyme producers within natural communities. In this perspective piece, we discuss state-of-the-art technologies in the fields of microfluidic droplets and functional screening of prokaryotic cells for measuring enzyme activity in marine seawater samples, one cell at a time. We further elaborate on how this single-cell approach can be used to address research questions that cannot be answered with current methods, as pertinent to the enzymatic degradation of organic matter by marine microorganisms.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Organic Photovoltaic Efficiency Predictor: Data-Driven Models for Non-Fullerene Acceptor Organic Solar Cells

In the design of organic solar cells, there has been a need for materials with high power conversion efficiencies. Scharber’s model is commonly used to predict efficiency; however, it exhibits poor performance with new non-fullerene acceptor (NFA) devices, since it was designed for fullerene-based devices. In this work, an empirical model is proposed that can be a more accurate alternative for NFA organic solar cells. Additionally, many screening studies use computationally expensive methods. A model based on using semiempirical simplified time-dependent density functional theory (sTD-DFT) as an alternative method can accelerate the calculations and yield a similar accuracy. The models presented in this paper, termed organic photovoltaic efficiency predictor (OPEP) models, have shown significantly lower errors than previous models, with OPEP/B3LYP yielding errors of 1.53% and OPEP/sTD- DFT of 1.55%. As a result, the proposed computational models can be used for the fast and accurate screening of new high-efficiency NFAs/donor pairs.

14 SOLAR ENERGY↗
DOE OSTI2020

Improving biomass and lipid yields of Desmodesmus armatus and Chlorella vulgaris through mutagenesis and high-throughput screening

Advancement of microalgae for use as biofuel feedstock depends on bioprospecting novel strains and then applying classical strain improvement techniques to enhance desirable traits. Here we successfully demonstrate this approach using two novel strains of green algae, identified as Desmodesmus armatus and Chlorella vulgaris, to improve biomass and lipid yields. UV irradiation was utilized to generate random mutations and the resulting populations were analyzed via flow cytometry to quantify lipid fluorescence while enriching for high lipid variants using fluorescence activated cell sorting. Secondary screening was performed via in situ fluorescence staining to identify the single highest lipid producing mutants from each strain. This approach produced a Desmodesmus armatus mutant that exhibited both increased biomass productivity and higher lipid content, which doubled lipid yield from the culture. The resulting Chlorella vulgaris mutant exhibited an increase in growth only, resulting in a 33% increase in lipid yield.

09 BIOMASS FUELS↗
DOE OSTI2024

A Comprehensive Investigation of Active Learning Strategies for Conducting Anti-Cancer Drug Screening

It is well-known that cancers of the same histology type can respond differently to a treatment. Thus, computational drug response prediction is of paramount importance for both preclinical drug screening studies and clinical treatment design. To build drug response prediction models, treatment response data need to be generated through screening experiments and used as input to train the prediction models. In this study, we investigate various active learning strategies of selecting experiments to generate response data for the purposes of (1) improving the performance of drug response prediction models built on the data and (2) identifying effective treatments. Here, we focus on constructing drug-specific response prediction models for cancer cell lines. Various approaches have been designed and applied to select cell lines for screening, including a random, greedy, uncertainty, diversity, combination of greedy and uncertainty, sampling-based hybrid, and iteration-based hybrid approach. All of these approaches are evaluated and compared using two criteria: (1) the number of identified hits that are selected experiments validated to be responsive, and (2) the performance of the response prediction model trained on the data of selected experiments. The analysis was conducted for 57 drugs and the results show a significant improvement on identifying hits using active learning approaches compared with the random and greedy sampling method. Active learning approaches also show an improvement on response prediction performance for some of the drugs and analysis runs compared with the greedy sampling method.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Learning curves for drug response prediction in cancer cell lines

Motivated by the size and availability of cell line drug sensitivity data, researchers have been developing machine learning (ML) models for predicting drug response to advance cancer treatment. As drug sensitivity studies continue generating drug response data, a common question is whether the generalization performance of existing prediction models can be further improved with more training data. We utilize empirical learning curves for evaluating and comparing the data scaling properties of two neural networks (NNs) and two gradient boosting decision tree (GBDT) models trained on four cell line drug screening datasets. The learning curves are accurately fitted to a power law model, providing a framework for assessing the data scaling behavior of these models. The curves demonstrate that no single model dominates in terms of prediction performance across all datasets and training sizes, thus suggesting that the actual shape of these curves depends on the unique pair of an ML model and a dataset. The multi-input NN (mNN), in which gene expressions of cancer cells and molecular drug descriptors are input into separate subnetworks, outperforms a single-input NN (sNN), where the cell and drug features are concatenated for the input layer. In contrast, a GBDT with hyperparameter tuning exhibits superior performance as compared with both NNs at the lower range of training set sizes for two of the tested datasets, whereas the mNN consistently performs better at the higher range of training sizes. Moreover, the trajectory of the curves suggests that increasing the sample size is expected to further improve prediction scores of both NNs. These observations demonstrate the benefit of using learning curves to evaluate prediction models, providing a broader perspective on the overall data scaling characteristics. A fitted power law learning curve provides a forward-looking metric for analyzing prediction performance and can serve as a co-design tool to guide experimental biologists and computational scientists in the design of future experiments in prospective research studies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Detailed investigation of electrical and optical properties of textured n-type and roughened p-type tunnel oxide passivated contacts for screen-printed double-side passivated contact silicon solar cell application

Here, this paper presents detailed characterization and analyses of the optical, electrical, and contact properties of a 35 nm phosphorus-doped (n-type) polysilicon (poly-Si) and a 250 nm boron-doped (p-type) poly-Si deposited respectively on textured and roughed surface. These layers could be applied respectively to the front and rear sides of an n-type Si to produce back junction bifacial screen-printed double-side tunnel oxide passivated contacts (DS-TOPCon) solar cells. Optical and device modeling revealed a short circuit current density loss of 1.5 mA/cm 2 and 0.5 mA/cm 2 due to absorption in the front n-TOPCon and rear side p-TOPCon layers, respectively. The passivation and contact properties including metalized and unmetallized recombination current density (J 0 ), as well as contact resistivity, were determined as a function of contact firing temperature in the range of 700~800°C. The passivation quality of the front thin n-TOPCon was found to deteriorate with increased firing temperature while the rear thick p-TOPCon improved. The study showed that the simulated contact firing at 730°C resulted in the best unmetallized double-side TOPCon precursor, with an excellent implied open-circuit voltage of 730 mV and implied fill factor of ~86 %. However, the metalized J0 increased and contact resistivity decreased monotonically with the increase in the firing temperature. The 2D device simulations revealed that these layers can produce screen-printed DS-TOPCon cells with an efficiency of ~22.5 %. Solar cell modeling also showed that the DS-TOPCon solar cell efficiency can reach 24.1 % by decreasing the n-TOPCon thickness to 20 nm and lowering the full area metalized J 0 to ~100 mA/cm 2 .

14 SOLAR ENERGY↗
DOE OSTI2023

Potent transmission-blocking monoclonal antibodies from naturally exposed individuals target a conserved epitope on Plasmodium falciparum Pfs230

Pfs230 is essential for Plasmodium falciparum transmission to mosquitoes and is the protein targeted by the most advanced malaria-transmission-blocking vaccine candidate. Prior understanding of functional epitopes on Pfs230 is based on two monoclonal antibodies (mAbs) with moderate transmission-reducing activity (TRA), elicited from subunit immunization. Here, we screened the B cell repertoire of two naturally exposed individuals possessing serum TRA and identified five potent mAbs from sixteen Pfs230 domain-1-specific mAbs. Structures of three potent and three low-activity antibodies bound to Pfs230 domain 1 revealed four distinct epitopes. Highly potent mAbs from natural infection recognized a common conformational epitope that is highly conserved across P. falciparum field isolates, while antibodies with negligible TRA derived from natural infection or immunization recognized three distinct sites. Our study provides molecular blueprints describing P. falciparum TRA, informed by contrasting potent and non-functional epitopes elicited by natural exposure and vaccination.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Ligand dependent interaction between PC-TP and PPARδ mitigates diet-induced hepatic steatosis in male mice

Phosphatidylcholine transfer protein (PC-TP; synonym StarD2) is a soluble lipid-binding protein that transports phosphatidylcholine (PC) between cellular membranes. To better understand the protective metabolic effects associated with hepatic PC-TP, we generated a hepatocyte-specific PC-TP knockdown (L-Pctp -/- ) in male mice, which gains less weight and accumulates less liver fat compared to wild-type mice when challenged with a high-fat diet. Hepatic deletion of PC-TP also reduced adipose tissue mass and decreases levels of triglycerides and phospholipids in skeletal muscle, liver and plasma. Gene expression analysis suggest that the observed metabolic changes are related to transcriptional activity of peroxisome proliferative activating receptor (PPAR) family members. An in-cell protein complementation screen between lipid transfer proteins and PPARs uncovered a direct interaction between PC-TP and PPARδ that was not observed for other PPARs. We confirmed the PC-TP– PPARδ interaction in Huh7 hepatocytes, where it was found to repress PPARδ-mediated transactivation. Mutations of PC-TP residues implicated in PC binding and transfer reduce the PC-TP-PPARδ interaction and relieve PC-TP-mediated PPARδ repression. Reduction of exogenously supplied methionine and choline reduces the interaction while serum starvation enhances the interaction in cultured hepatocytes. Together our data points to a ligand sensitive PC-TP– PPARδ interaction that suppresses PPAR activity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Sorting for secreted molecule production using a biosensor-in-microdroplet approach

Significance The design–build–test cycle of metabolic engineering is swiftly becoming test limited owing to advances in DNA synthesis and library design. At the same time, improving extracellular production requires high-throughput studies to detect extracellular (not intracellular) content. Traditional approaches that utilize chromatography-based analysis or plate-based fluorescence assays are relatively throughput limited and require a high degree of liquid handling. These limitations are avoided here by creating a generalizable approach for small molecule production screening. Namely, this paradigm combines “off-the-shelf” biosensors with large library screening from producing cells in a cell-type agnostic manner.

Bowman, Emily K.↗
DOE OSTI2023

Mitigation of chromosome loss in clinical CRISPR-Cas9-engineered T cells

CRISPR-Cas9 genome editing has enabled advanced T cell therapies, but occasional loss of the targeted chromosome remains a safety concern. To investigate whether Cas9-induced chromosome loss is a universal phenomenon and evaluate its clinical significance, we conducted a systematic analysis in primary human T cells. Arrayed and pooled CRISPR screens revealed that chromosome loss was generalizable across the genome and resulted in partial and entire loss of the targeted chromosome, including in preclinical chimeric antigen receptor T cells. T cells with chromosome loss persisted for weeks in culture, implying the potential to interfere with clinical use. A modified cell manufacturing process, employed in our first-in-human clinical trial of Cas9-engineered T cells (NCT03399448), reduced chromosome loss while largely preserving genome editing efficacy. Expression of p53 correlated with protection from chromosome loss observed in this protocol, suggesting both a mechanism and strategy for T cell engineering that mitigates this genotoxicity in the clinic.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

CRAGE-mediated insertion of fluorescent chromosomal markers for accurate and scalable measurement of co-culture dynamics in Escherichia coli

Monitoring population dynamics in co-culture is necessary in engineering microbial consortia involved in distributed metabolic processes or biosensing applications. However, it remains difficult to measure strain-specific growth dynamics in high-throughput formats. This is especially vexing in plate-based functional screens leveraging whole-cell biosensors to detect specific metabolic signals. Here, we develop an experimental high-throughput co-culture system to measure and model the relationship between fluorescence and cell abundance, combining chassis-independent recombinase-assisted genome engineering (CRAGE) and whole-cell biosensing with a PemrR-green fluorescent protein (GFP) monoaromatic reporter used in plate-based functional screening. CRAGE was used to construct Escherichia coli EPI300 strains constitutively expressing red fluorescent protein (RFP) and the relationship between RFP expression and optical density (OD600) was determined throughout the EPI300 growth cycle. A linear equation describing the increase of normalized RFP fluorescence during deceleration phase was derived and used to predict biosensor strain dynamics in co-culture. Measured and predicted values were compared using flow cytometric detection methods. Induction of the biosensor lead to increased GFP fluorescence normalized to biosensor cell abundance, as expected, but a significant decrease in relative abundance of the biosensor strain in co-culture and a decrease in bulk GFP fluorescence. Taken together, these results highlight sensitivity of population dynamics to variations in metabolic activity in co-culture and the potential effect of these dynamics on the performance of functional screens in plate-based formats. The engineered strains and model used to evaluate these dynamics provide a framework for optimizing growth of synthetic co-cultures used in screening, testing and pathway engineering applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Impact of Electrolyte Additives on the Lifetime of High Voltage NMC Lithium-Ion Pouch Cells

This work involves improving the lifetime of lithium-ion cells during high voltage cycling using electrolyte additives. Three generations of electrolyte additives were investigated and screened in NMC442/graphite pouch cells using a 24 h voltage-hold protocol at 40 degrees C to accelerate oxidative reactions occurring at 4.4 V. Once promising additives and combinations were identified, they were then tested in cobalt-free NMC640/graphite cells for long-term cycling to upper cutoff voltages of 4.3, 4.4, and 4.5 V at temperatures of 20, 40, and 55 degrees C. Degradation mechanisms were probed using dV/dQ analysis, micro-X-ray fluorescence spectroscopy, and electrochemical impedance spectroscopy. The primary failure mode of cells held at high voltages is due to increase in cell impedance, which is correlated to the dissolution of transition metals, specifically manganese, originating from the positive electrode. We believe this dissolution is presumably due to the formation of a high impedance rock salt surface layer on the NMC positive electrode particles. Such deleterious outcomes can be limited by selecting an appropriate electrolyte additive package. It is hoped that this paper can provide a starting point for developing NMC Li-ion cells that can operate to voltages as high as 4.4 V and still display long lifetimes.

Azam, Saad↗
DOE OSTI2020

Fundamentals of Using Cracked Film Lithography to Pattern Transparent Conductive Metal Grids for Photovoltaics

The fundamentals of using cracked film lithography (CFL) to fabricate metal grids for transparent contacts in solar cells were studied. The underlying physics of drying-induced cracks were well-predicted by an empirical correlation relating crack spacing to capillary pressure. CFL is primarily controlled by varying the crack template thickness, which establishes a three-way tradeoff between the areal density of cracks, crack width, and spacing between cracks, which in turn determine final grid transmittance, grid sheet resistance, and the semiconductor resistance for a given solar cell. Since CFL uses a lift-off process, an additional constraint is that the metal thickness must be less than 1/3 of the crack template thickness. Furthermore, the transmittance/grid sheet resistance/wire spacing tradeoffs measured in this work were used to calculate solar cell performance: CFL-patterned grids should outperform screen-printed grids for narrow cells (0.5–2 cm wide) and/or cells with high semiconductor sheet resistance (=100 O/sq), making CFL attractive for monolithically integrated thin-film photovoltaic modules.

14 SOLAR ENERGY↗
DOE OSTI2021

Discovery of amivantamab (JNJ-61186372), a bispecific antibody targeting EGFR and MET

A bispecific antibody (BsAb) targeting the epidermal growth factor receptor (EGFR) and mesenchymal–epithelial transition factor (MET) pathways represents a novel approach to overcome resistance to targeted therapies in patients with non–small cell lung cancer. In this study, we sequentially screened a panel of BsAbs in a combinatorial approach to select the optimal bispecific molecule. The BsAbs were derived from different EGFR and MET parental monoclonal antibodies. Initially, molecules were screened for EGFR and MET binding on tumor cell lines and lack of agonistic activity toward MET. Hits were identified and further screened based on their potential to induce untoward cell proliferation and cross-phosphorylation of EGFR by MET via receptor colocalization in the absence of ligand. After the final step, we selected the EGFR and MET arms for the lead BsAb and added low fucose Fc engineering to generate amivantamab (JNJ-61186372). The crystal structure of the anti-MET Fab of amivantamab bound to MET was solved, and the interaction between the two molecules in atomic details was elucidated. Amivantamab antagonized the hepatocyte growth factor (HGF)-induced signaling by binding to MET Sema domain and thereby blocking HGF β-chain—Sema engagement. The amivantamab EGFR epitope was mapped to EGFR domain III and residues K443, K465, I467, and S468. Furthermore, amivantamab showed superior antitumor activity over small molecule EGFR and MET inhibitors in the HCC827-HGF in vivo model. Based on its unique mode of action, amivantamab may provide benefit to patients with malignancies associated with aberrant EGFR and MET signaling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Exploring the Performance and Reliability of Screen-Printable Fire-Through Copper Paste on PERC Solar Cells

For 40 TW of PV required to transition our planet to 100% renewables, the silver (Ag) should disappear from PV production. Advantages of copper (Cu) over silver (Ag) include 1) bulk Cu has a similar conductivity to Ag (1.7 mu O-cm for Cu, 1.6 mu O-cm for Ag) and 2) Cu is approximately 100 times cheaper than Ag, making it an excellent potential replacement. Problems associated with copper (Cu) contacts include 1) easy oxidation and 2) diffusion into the Si cell and recombination activity.

copper paste↗