Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “pathway analysis”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,207 records · Page 67

Supporting the Transition from Grid-Scale to Emerging Market Wave Energy Converter Design and Assessment

In the past decade there has been increasing interest in emerging markets for wave energy, both as a stepping stone for development and as a way to create new opportunities for offshore markets such as ocean observation or desalination. Developers who were once focused exclusively on grid-scale development have begun to engage with more unique markets. This has led researchers to begin examining means of assessing emerging-market devices. In this paper, we analyze the Technology Performance Level (TPL) Assessment for its potential use in the assessment of emerging market wave energy converters (EM-WECs). We use Quality Function Deployment (QFD) and a question-by-question analysis of the TPL assessment to determine the changes necessary for such an assessment to be applicable in emerging markets. We discuss how the primary differences between the markets could impact the viable development pathways for developers hoping to succeed in multiple markets. We determine that the different stakeholders and stakeholder requirements of some emerging markets compared to gridscale applications should be met with changes to cost-toperformance metrics, prototype testing processes, recovery planning, materials selection, optimization objectives, and public engagement.

blue economy↗

Mass Spectral Imaging to Map Plant–Microbe Interactions

Plant–microbe interactions are of rising interest in plant sustainability, biomass production, plant biology, and systems biology. These interactions have been a challenge to detect until recent advancements in mass spectrometry imaging. Plants and microbes interact in four main regions within the plant, the rhizosphere, endosphere, phyllosphere, and spermosphere. This mini review covers the challenges within investigations of plant and microbe interactions. We highlight the importance of sample preparation and comparisons among time-of-flight secondary ion mass spectroscopy (ToF-SIMS), matrix-assisted laser desorption/ionization (MALDI), laser desorption ionization (LDI/LDPI), and desorption electrospray ionization (DESI) techniques used for the analysis of these interactions. Using mass spectral imaging (MSI) to study plants and microbes offers advantages in understanding microbe and host interactions at the molecular level with single-cell and community communication information. More research utilizing MSI has emerged in the past several years. We first introduce the principles of major MSI techniques that have been employed in the research of microorganisms. An overview of proper sample preparation methods is offered as a prerequisite for successful MSI analysis. Traditionally, dried or cryogenically prepared, frozen samples have been used; however, they do not provide a true representation of the bacterial biofilms compared to living cell analysis and chemical imaging. New developments such as microfluidic devices that can be used under a vacuum are highly desirable for the application of MSI techniques, such as ToF-SIMS, because they have a subcellular spatial resolution to map and image plant and microbe interactions, including the potential to elucidate metabolic pathways and cell-to-cell interactions. Promising results due to recent MSI advancements in the past five years are selected and highlighted. The latest developments utilizing machine learning are captured as an important outlook for maximal output using MSI to study microorganisms.

59 BASIC BIOLOGICAL SCIENCES↗

The TLK-ASF1 histone chaperone pathway plays a critical role in IL-1β–mediated AML progression

Identifying and targeting microenvironment-driven pathways that are active across acute myeloid leukemia (AML) genetic subtypes should allow the development of more broadly effective therapies. The proinflammatory cytokine interleukin-1β (IL-1β) is abundant in the AML microenvironment and promotes leukemic growth. Through RNA-sequencing analysis, we identify that IL-1β–upregulated ASF1B (antisilencing function-1B), a histone chaperone, in AML progenitors compared with healthy progenitors. ASF1B, along with its paralogous protein ASF1A, recruits H3-H4 histones onto the replication fork during S-phase, a process regulated by Tousled-like kinase 1 and 2 (TLKs). Although ASF1s and TLKs are known to be overexpressed in multiple solid tumors and associated with poor prognosis, their functional roles in hematopoiesis and inflammation-driven leukemia remain unexplored. In this study, we identify that ASF1s and TLKs are overexpressed in multiple genetic subtypes of AML. We demonstrate that depletion of ASF1s significantly reduces leukemic cell growth in both in vitro and in vivo models using human cells. Using a murine model, we show that overexpression of ASF1B accelerates leukemia progression. Moreover, Asf1b or Tlk2 deletion delayed leukemia progression, whereas these proteins are dispensable for normal hematopoiesis. Through proteomics and phosphoproteomics analyses, we uncover that the TLK-ASF1 pathway promotes leukemogenesis by affecting the cell cycle and DNA damage pathways. Collectively, our findings identify the TLK1-ASF1 pathway as a novel mediator of inflammatory signaling and a promising therapeutic target for AML treatment across diverse genetic subtypes. Finally, selective inhibition of this pathway offers potential opportunities to intervene effectively, address intratumoral heterogeneity, and ultimately improve clinical outcomes in AML.

60 APPLIED LIFE SCIENCES↗

A Structural Basis for Inhibition of the Complement Initiator Protease C1r by Lyme Disease Spirochetes

Abstract Complement evasion is a hallmark of extracellular microbial pathogens such as Borrelia burgdorferi, the causative agent of Lyme disease. Lyme disease spirochetes express nearly a dozen outer surface lipoproteins that bind complement components and interfere with their native activities. Among these, BBK32 is unique in its selective inhibition of the classical pathway. BBK32 blocks activation of this pathway by selectively binding and inhibiting the C1r serine protease of the first component of complement, C1. To understand the structural basis for BBK32-mediated C1r inhibition, we performed crystallography and size-exclusion chromatography–coupled small angle X-ray scattering experiments, which revealed a molecular model of BBK32-C in complex with activated human C1r. Structure-guided site-directed mutagenesis was combined with surface plasmon resonance binding experiments and assays of complement function to validate the predicted molecular interface. Analysis of the structures shows that BBK32 inhibits activated forms of C1r by occluding substrate interaction subsites (i.e., S1 and S1’) and reveals a surprising role for C1r B loop–interacting residues for full inhibitory activity of BBK32. The studies reported in this article provide for the first time (to our knowledge) a structural basis for classical pathway–specific inhibition by a human pathogen.

Garrigues, Ryan J. (ORCID:0000000259233250)↗

Anodic Hydrogen Generation from Benzaldehyde on Au, Ag, and Cu: Rotating Ring-Disk Electrode Studies

Aldehydes are selectively oxidized to carboxylates on group 11 metals at low potentials (<0.4 V vs. RHE) in alkaline media. This process can occur by a pathway that generates H 2 gas from the aldehyde, known as electro-oxidative dehydrogenation (EOD) or anodic hydrogen production. The EOD process occurs with transfer of only one electron per aldehyde, whereas typical oxidation with discharge of hydrogen to form water is a two-electron process. Here, we study the catalytic activity and selectivity toward H 2 of Au, Ag, and Cu electrodes using benzaldehyde with rotating disk and ring-disk electrode (RDE/RRDE) techniques. The average number of electrons per benzaldehyde molecule obtained via H 2 detection by RRDE agrees with that obtained via Koutecký-Levich analysis conducted at various rotation rates. We find that Au and Ag have much higher H 2 and benzoate formation rates than Cu, but that Cu can perform the reaction at about 0.2 V lower overpotentials. On all three materials, benzaldehyde oxidation has high selectivity to anodic H 2 (one-electron pathway) below ∼0.5 V vs. RHE, but, with increasing potential, the selectivity shifts to H-oxidation forming water (two-electron pathway).

Ramos, Nathanael C. (ORCID:0000000247210350)↗

An Overview of Atmospheric Features Over the Western North Atlantic Ocean and North American East Coast - Part 1: Analysis of Aerosols, Gases, and Wet Deposition Chemistry

The Western North Atlantic Ocean (WNAO) and adjoining East Coast of North America are of great importance for atmospheric research and have been extensively studied for several decades. This broad region exhibits complex meteorological features, diverse cloud types, and a wide range of conditions associated with gas and particulate species that originate from many sources regionally and from other continents. As Part 1 of a 2-part paper series, this work provides a characterization of quantities associated with atmospheric chemistry, including gases, aerosols, and wet deposition, based on satellite observations, ground-based data, model simulations, and reanalysis products. Key results include spatial and seasonal differences in composition along the North American East Coast and over the WNAO associated with varying sources of smoke and dust and meteorological drivers such as temperature, moisture, and precipitation. Spatial and seasonal variations of tropospheric carbon monoxide and ozone highlight different pathways towards accumulation of these species in the troposphere. Spatial distributions of speciated aerosol optical depth and vertical profiles of aerosol mass mixing ratios show a clear seasonal cycle highlighting the influence of both natural and anthropogenic sources in addition to the impact of intercontinental transport on their vertical profiles. Analysis of long-term climate model simulations of aerosol species and satellite observations of carbon monoxide confirm that there has been a significant decline in recent decades among anthropogenic constituents owing to regulatory activities. The results can inform current and future lines of research for the region.

Corral, Andrea↗

Subsurface mafic and ultramafic rock mapping and analysis for carbon mineralization in the United States (SubMAP-CO 2 )

Achieving durable, gigaton-scale carbon dioxide (CO₂) removal will require the development of storage strategies that are both permanent and scalable. Among the available options, carbon mineralization in mafic and ultramafic rocks offers a uniquely robust pathway for long-term CO₂ sequestration, converting CO₂ into thermodynamically stable carbonate minerals. While surface exposures of these lithologies have been extensively studied, particularly in ophiolitic and volcanic settings, the potential for carbon mineralization in the subsurface remains comparatively underexplored at national scale. This gap limits the ability to assess storage capacity, accessibility, and deployment pathways for mineralization-based carbon management in the United States.

08 HYDROGEN↗

Large Ensemble Exploration of Global Energy Transitions Under National Emissions Pledges

Global climate goals require a transition to a deeply decarbonized energy system. Meeting the objectives of the Paris Agreement through countries' nationally determined contributions and long-term strategies represents a complex problem with consequences across multiple systems shrouded by deep uncertainty. Robust, large-ensemble methods and analyses mapping a wide range of possible future states of the world are needed to help policymakers design effective strategies to meet emissions reduction goals. This study contributes a scenario discovery analysis applied to a large ensemble of 5,760 model realizations generated using the Global Change Analysis Model. Eleven energy-related uncertainties are systematically varied, representing national mitigation pledges, institutional factors, and techno-economic parameters, among others. The resulting ensemble maps how uncertainties impact common energy system metrics used to characterize national and global pathways toward deep decarbonization. Results show globally consistent but regionally variable energy transitions as measured by multiple metrics, including electricity costs and stranded assets. Larger economies and developing regions experience more severe economic outcomes across a broad sampling of uncertainty. The scale of CO 2 removal globally determines how much the energy system can continue to emit, but the relative role of different CO 2 removal options in meeting decarbonization goals varies across regions. Previous studies characterizing uncertainty have typically focused on a few scenarios, and other large-ensemble work has not (to our knowledge) combined this framework with national emissions pledges or institutional factors. Our results underscore the value of large-ensemble scenario discovery for decision support as countries begin to design strategies to meet their goals.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Projected income data under different shared socioeconomic pathways for Washington state

Abstract High-resolution income projections under different Shared Socioeconomic Pathways (SSPs) are essential for the climate change research communities to devise climate change adaptation and mitigation strategies. To generate income projections for Washington state, we obtain state-level GDP per capita projections and convert them into projected annual household income. The resulting state-level income projections are subsequently downscaled to the census block-level based on the Longitudinal Origin-Destination Employment Statistics (LODES) dataset. For accuracy assessment, we downscale historical income data from state- level to block- and block group-level and compare the downscaled results against the actual income data from LODES. County-level accuracy assessment is also conducted based on American Community Survey. The results demonstrate a good agreement (Average R 2 of 0.67, 0.8, and 0.99 for block-, block group-, and county-level, respectively) between the downscaled income data and the reference data, thereby validating the methodology employed. Our approach is applicable to other states for income projections, which can be utilized by a broader audience, including those involved in demographic analysis, economic research, and urban planning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Electrolyte Reactivity on the MgV 2 O 4 Cathode Surface

Predictive understanding of the solvation-dependent reactivity and molecular interaction of electrolyte ions and solvent molecules on reactive electrodes has been a major challenge but is essential for addressing instabilities and surface passivation that occur at electrode-electrolyte interface (EEI) of multivalent Mg batteries. In this work, the isolated intrinsic reactivities of prominent chemical species present in magnesium bis(trifluoromethanesulfonimide) (Mg(TFSI) 2 ) in diglyme (G2) electrolytes, including ionic (TFSI - , [Mg(TFSI)] + , [Mg(TFSI):G2] + , [Mg(TFSI):2G2] + ) as well as neutral molecules (G2) on magnesium vanadate cathode (MgV 2 O 4 ) surface has been studied using a combination of first-principles calculations and multimodal analysis of well-defined cathode electrolyte interphase (CEI) layers. Here, our calculations show that non-solvated [Mg(TFSI)] + is the strongest adsorbing species on the MgV 2 O 4 surface compared to all other ions while fully solvated [Mg(TFSI):2G2] + are least favorable to decomposition. The cleavage of C-S bonds in TFSI - to form CF 3 - is predicted to be most desired pathway for all ionic species, which is followed by the cleavage of C-O bonds of G2 to yield CH 3 + or OCH 3 - species. The strong stabilization and electron transfer between ionic electrolyte species and MgV 2 O 4 is found to significantly favor these decomposition reactions on the surface compared to intrinsic gas phase dissociation. Experimentally, we used state-of-the-art ion soft landing to selectively deposit mass-selected TFSI - , [Mg(TFSI):G2] + and [Mg(TFSI):2G2] + on MgV 2 O 4 thin film to form well-defined electrolyte-MgV 2 O 4 interface. Analysis of soft-landed interphase using X-ray photoelectron, X-ray absorption near edge structure, electron energy-loss spectroscopies as well as transmission electron microscopy confirmed the presence of decomposition species (e.g., MgFx, carbonates) formed in the interfacial region and the higher amount of MgFx with [Mg(TFSI):G2] + , which corroborates the theoretical observation. Overall, we established the mechanistic pathway for the electrolyte-induced formation of passivating fluorides on MgV 2 O 4 cathode facilitated by the surface adsorption and charge transfer, which provided essential knowledge for rational design of stable electrolytes for multivalent cathodes.

Cathode-electrolyte interphase formation↗

Covalent labeling of the Arabidopsis plasma membrane H + ‐ ATPase reveals 3D conformational changes involving the C‐terminal regulatory domain

The plasma membrane proton pump is the primary energy transducing, electrogenic ion pump of the plasma membrane in plants and fungi. Compared to its fungal counterpart, the plant plasma membrane proton pump's regulatory C‐terminal domain (CTD) contains an additional regulatory segment that links multiple sensory pathways regulating plant cell length through phosphorylation and recruitment of regulatory 14‐3‐3 proteins. However, a complete structural model of a plant proton pump is lacking. Here, we performed covalent labeling with mass spectrometric analysis (CL‐MS) on the Arabidopsis pump AHA2 to identify potential interactions between the CTD and the catalytic domains. Our results suggest that autoinhibition in the plant enzyme is much more structurally complex than in the fungal enzyme.

Blackburn, Matthew R. [Department of Biochemistry ↗

Future projections and uncertainty assessment of precipitation extremes in the Korean peninsula from the CMIP5 ensemble

Abstract Projections of changes in extreme climate are sometimes predicted by multimodel ensemble methods that combine forecasts from individual simulation models using weighted averaging. One method to assign weight to each model is the Bayesian model averaging (BMA) in which posterior probability is used. For the cases of extreme climate, the generalized extreme value distribution (GEVD) is typically used. We applied the approach of GEV‐embedded BMA to a series of 35 years of the annual maximum daily precipitation data (both historical data and data gathered from simulation experiments for future periods) over the Korean peninsula as simulated by the models in the Coupled Model Intercomparison Project Phase 5 (CMIP5). Simulation data under two Representative Concentration Pathway (RCP) scenarios, namely RCP4.5 and RCP8.5, were used. Observed data and 17 CMIP5 models for 12 gird cells in Korea have been examined to predict future changes in precipitation extremes. A simple regional frequency analysis of pooling observations from three stations in each cell was employed to reduce the estimation variance and local fluctuations. A bias correction technique using the regression‐type transfer function was applied to these simulation data. Return levels spanning over 20 and 50 years, as well as the return periods relative to the reference years (1971–2005), were estimated for two future periods, namely Period 1 (2021–2050) and Period 2 (2066–2095). From these analyses, relative increase observed in the spatially averaged 20‐year (50‐year) return level was approximately 23% (16%) and 45% (36%) in the RCP4.5 and RCP8.5 experiments, respectively, by the end of the 21st century. We concluded that extreme rainfalls will likely occur two times and four times more frequently in the RCP4.5 and RCP8.5 scenarios, respectively, as compared to in the reference years by the end of the 21st century.

Lee, Youngsaeng↗

Upcycling mixed cathode materials to high-energy-density LiFe 0.75 Mn 0.25 PO 4

To address the demand for next-generation cathode materials with high energy density, upcycling LiFePO 4 into LiFe 0.75 Mn 0.25 PO 4 has attracted considerable attention. Nevertheless, existing strategies have yet to achieve both morphology and full elemental recovery under mild ambient conditions. Here, we report an upcycling route that can address this issue by combining leaching and a high-temperature treatment process. The upcycled LiFe 0.75 Mn 0.25 PO 4 exhibits enlarged lattice spacing and a high discharge plateau, and it delivers an energy density of 563.7 Wh/kg, 40.3 Wh/kg higher than recycled LiFePO 4 , which indicates the high value of the proposed upcycling strategy. At 1 C, LiFe 0.75 Mn 0.25 PO 4 also exhibits excellent cycling stability of 91% over 700 cycles. Techno-economic analysis also indicates impressive economic and environmental benefits, including 10.4% less raw materials usage and 12.2% less energy consumption and wastewater generation. This work demonstrates a scalable and economic upcycling strategy and provides a promising pathway for sustainable battery upcycling compatible with industrial conditions.

LMFP↗

Enhancing SWAT with mechanistic plant hydraulics: development and application in the Hanjiang River Basin

Plant transpiration plays a critical role in global water and energy cycles, requiring better process understanding as climate change intensifies drought stress and alters plant responses. Most hydrological models such as the widely-used SWAT lack representation of plant hydraulics, the mechanistic processes controlling plant water regulation and transpiration. Here, this study developed SWAT-PHS by integrating a plant hydraulics scheme (PHS) into SWAT hydrological model, enabling explicit simulation of root water uptake, sap flow, storage and transpiration at 30-minute timescales for watershed-scale modeling. In the Hanjiang River Basin, SWAT-PHS mitigated overestimation of runoff during the rainy season and underestimation during the dry season, reducing the overall simulation error by 29% across the entire simulation period. The model can simulate reasonable plant water dynamics, including diurnal transpiration patterns and drought responses showing declining transpiration flux, hydraulic buffering through stem water storage, and depth-dependent root water uptake strategies. Sensitivity analysis shows that SWAT-PHS captured mechanistic relationships between plant hydraulic traits and transpiration, with root distribution and stem capacitance positively affecting annual transpiration while vulnerability parameters showed negative effects. This work provides a pathway for improving hydrologic modeling and water resource management by better representing plant water regulation under climate change and expected intensifying water stress conditions.

China↗

Quantum Sensing of Electron Transfer Pathways in Natural Photosynthesis Using Time-Resolved High-Field Electron Paramagnetic Resonance/Electron–Nuclear Double Resonance Spectroscopy

Photosynthetic integral membrane reaction center (RC) proteins capture and convert sunlight into chemical energy via efficient charge separation achieved through a series of rapid, photoinitiated electron transfer steps. These fast electron transfers create an entangled spin qubit (radical) pair that contains detailed information about the weak magnetic interactions, structure, and dynamics of localized protein environments involved in charge separation events. In this work, we investigate how these entangled electron spin qubits interact with nuclear spins of the protein environment using the high spectral resolution of 130 GHz electron paramagnetic resonance (EPR) and electron-nuclear double resonance (ENDOR). Spectroscopic interrogation enabled the observation and probing of protons located in the electron transfer pathway between the membrane-spanning electron pair P + Q A - (where P + is the primary donor, a special pair of bacteriochlorophylls, and Q A is the primary quinone acceptor) in the bacterial RC. Spectroscopic analysis reveals hydrogen-bonding interactions involved in regulating the route that light-induced electrons travel through the RC protein during charge separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ethane Dehydrogenation on Single and Dual Centers of Ga-modified γ-Al 2 O 3

Density-functional theory calculations and microkinetic analysis are used to investigate the efficacy of Ga-modified γ-Al 2 O 3 (110) surfaces for the catalytic dehydrogenation of ethane and elucidate the synergy between Ga and Al sites. The model surfaces are modified by either Ga grafting or doping. We consider and analyze numerous active sites and rank them using microkinetic analysis. The kinetic parameters obtained from microkinetic modelling are compared with experimental values for ethane dehydrogenation over Ga 2 O 3 -Al 2 O 3 mixed oxides prepared by co-precipitation. The dominant reaction pathway proceeds via heterolytic C-H bond dissociation to a surface proton and a metal-carbanion intermediate that undergoes β-hydride elimination. We find that grafted Ga sites are catalytically inactive. In contrast, Ga-doped sites exhibit fivefold enhancement in catalytic activity when compared to the sites on pristine Al 2 O 3 , owed to the synergy between neighboring AlIII and GaIV sites. Furthermore, we model and investigate the effect of surface hydroxylation, demonstrate how surface water interferes with the aforementioned synergy between AlIII and GaIV sites and discuss the implications for the catalytic activity of the modified surfaces. Here, an increase in the partial pressure of H 2 O significantly increases the apparent activation energies of dehydrogenation and interestingly changes the most active site.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Life Cycle Assessment and Techno-Economic Assessment of Lithium Recovery from Geothermal Brine

Lithium-ion batteries (LIB) play an essential role in the electrification of the transportation sector, and battery demand for lithium compounds will see a significant increase in the coming decades. This has raised concerns on the supply of lithium, and as a result, technologies are being developed to process unconventional lithium sources. One promising technology is to extract lithium from geothermal brine using lithium-aluminum-layered double hydroxide chloride (LDH) sorbent and forward osmosis. A combined life cycle assessment (LCA) and techno-economic assessment (TEA) is conducted to evaluate the environmental and economic performance of this technology. It is assumed that the lithium extraction unit is an add-on to a 50 MW geothermal power plant located in California. The analysis is based on lab-scale experimental data and stoichiometry while considering the economy of scale for an industrial system. LCA results suggest that, compared with conventional LiOH and Li 2 CO 3 production pathways, the new technology achieves 1–95% reduction in environmental impacts. Even higher reduction can be achieved for LiOH produced via electrolysis. This add-on unit for lithium extraction could achieve a payback period of less than 1 year and reach net present values of $454M and $315M and internal rates of return of 792 and 1130% for LiOH and Li 2 CO 3 production pathways, respectively. The favorable environmental and economic performance suggests that LDH sorption coupled with forward osmosis has great potential to enable the domestic production of battery lithium compounds and that further development should be carried out.

15 GEOTHERMAL ENERGY↗

Assessment of Accelerated Stress Testing Data for Silicon Photovoltaics Using Tensor Decomposition Methods

In this work, we examine the use of high-order tensor decompositions to analyze degradation pathways emerging from accelerated stress testing of silicon photovoltaic (PV) modules. Matrix-based decompositions are powerful tools for studying two-dimensional data arrays and form the foundation of a host of classical data analysis techniques. Tensors are high-order extrapolations of matrices that are able to account for more parameter dimensions, and a variety of tensor decomposition methods have been developed that similarly seek to extend insights from matrix decompositions to higher dimensions. Applying and interpreting tensor decomposition methods to sequences of PV module image data, we seek to uncover and isolate different degradation modes occurring from accelerated stress testing procedures. Further, we consider the contributions of different modes to PV module performance degradations.

data analysis↗