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At least 199 records · Page 11

Numerical modeling of hydrogen mixing in a direct-injection engine fueled with gaseous hydrogen

Hydrogen is considered as one of the most promising options to achieve effective decarbonization of the energy and transportation sectors. As such, it has recently been receiving increasing attention because of its promising potential as an energy carrier for advanced energy and propulsion systems. With a focus on internal combustion engines, direct injection (DI) of gaseous hydrogen during the compression stroke offers great potential for high engine efficiency and specific power while reducing the risk of backfiring and pre-ignition issues. Therefore, many experimental and numerical efforts have recently been dedicated to understanding the physical and chemical behaviors of hydrogen in engine during mixing and combustion. This study focuses on computational fluid dynamics (CFD) modeling of the hydrogen DI process in a hydrogen optical research engine. Under the conditions studied, gaseous hydrogen is injected into the combustion chamber via a centrally located single-hole injector at a pressure of 100 bar. Two configurations, namely low-and high-tumble, are investigated to understand the impact of different in-cylinder flow patterns on the fuel-air mixture preparation. Simulations are carried out using the commercial CFD software CONVERGE. Here, the in-cylinder turbulence is modeled with an unsteady Reynolds-averaged Navier-Stokes (URANS) formulation closed by the renormalization group (RNG) k-ε model. Several numerical methods and model constants, including but not limited to turbulent Schmidt number, are evaluated. The numerical results are systematically compared against experimental measurements of velocity and hydrogen concentration fields on the vertical center plane to assess the performance of the CFD model, unveil the physics of hydrogen mixing, and establish best practices for modeling hydrogen DI under relatively high injection pressure conditions.

33 ADVANCED PROPULSION SYSTEMS↗

Multi-dimensional modeling of mixture preparation in a direct injection engine fueled with gaseous hydrogen

With the recent advances of direct injection (DI) technology, introducing hydrogen into the combustion chamber through DI is being considered as a viable approach to circumvent backfire and pre-ignition encountered in early generations of hydrogen engines. As part of a broader vision to develop a robust numerical model to study hydrogen spark ignition (SI) combustion in internal combustion (IC) engines, the present numerical investigation focuses on mixture preparation in a hydrogen DI SI engine. This study is carried out with a single hole injector with gaseous hydrogen injected at 100 bar injection pressure. Simulations are carried out for high and low tumble configurations and validated against optical data acquired from planar laser induced fluorescence (PLIF) measurements. Varying mesh configurations are investigated for the impact on in-cylinder mixture distribution. A particular emphasis is placed on the effect of nozzle geometry and mesh orientation near the wall. Overall, the computational model is found to predict the mixture distribution in the combustion cylinder reasonably well. The results showed that the alignment of mesh with the flow direction is important to achieve good agreement between numerical analysis and optical measurement data.

08 HYDROGEN↗

Multicycle large-eddy simulations of a direct-injection hydrogen-fueled optical engine

Hydrogen (H 2 ) is a carbon-free chemical energy carrier and one promising solution for achieving effective decarbonization of the transportation sector, particularly for internal combustion engines (ICEs). With a focus on ICEs, and compared to port-fuel injection, direct injection (DI) of gaseous H 2 during the compression stroke offers potential advantages, which include backfire avoidance and reduction of preignition occurrence. In these last two decades, much research, experimental and numerical, has been devoted to understanding H 2 's mixing and combustion processes in ICEs. Computational fluid dynamics modeling efforts commonly rely on unsteady Reynolds-averaged Navier Stokes (URANS) turbulence frameworks, mostly due to their computational affordability. However, many authors have pointed out the opportunity to perform large-eddy simulations (LESs) to investigate the cyclic variability of H 2 engines and assess potential advantages of using LES in place of URANS, especially for lean operation. This study addresses this knowledge gap and presents a computational fluid dynamics (CFD) study of the H 2 DI process in an optical engine operating at relatively low tumble conditions, using multicycle LESs. In conclusion, the manuscript presents a thorough validation of the results against experimental data available from the literature as well as direct comparison with URANS, demonstrating the feasibility of multicycle LESs for CFD modeling of DI H 2 -fueled ICEs.

Direct injection↗

Quantitative evaluation of common cause failures in high safety-significant safety-related digital instrumentation and control systems in nuclear power plants

Digital instrumentation and control (DI&C) systems at nuclear power plants (NPPs) have many advantages over analog systems. They are proven to be more reliable, cheaper, and easier to maintain given obsolescence of analog components. However, they also pose new engineering and technical challenges, such as possibility of common cause failures (CCFs) unique to digital systems. Here this paper proposes a Platform for Risk Assessment of DI&C (PRADIC) that is developed by Idaho National Laboratory (INL). A methodology for evaluation of software CCFs in high safety-significant safety-related DI&C systems of NPPs was developed as part of the framework. The framework integrates three stages of a typical risk assessment—qualitative hazard analysis and quantitative reliability and consequence analyses. The quantified risks compared with respective acceptance criteria provide valuable insights for system architecture alternatives allowing design optimization in terms of risk reduction and cost savings. A comprehensive case study performed to demonstrate the framework's capabilities is documented here in this paper. Results show that the PRADIC is a powerful tool capable to identify potential digital-based CCFs, estimate their probabilities, and evaluate their impacts on system and plant safety.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Improved Characterization of Soil Organic Matter by Integrating FT-ICR MS, Liquid Chromatography Tandem Mass Spectrometry, and Molecular Networking: A Case Study of Root Litter Decay under Drought Conditions

Understanding of how soil organic matter (SOM) chemistry is altered in a changing climate has advanced considerably; however, most SOM components remain unidentified, impeding the ability to characterize a major fraction of organic matter and predict what types of molecules, and from which sources, will persist in soil. Here we present a novel approach to better characterize SOM extracts by integrating information from three types of analyses, and we deploy this method to characterize decaying root-detritus soil microcosms subjected to either drought or normal conditions. To observe broad differences in composition, we employed direct infusion Fourier-transform ion cyclotron resonance mass spectrometry (DI-FT-ICR MS). We complemented this with liquid chromatography tandem mass spectrometry (LC-MS/MS) to identify components by library matching. Since libraries contain only a small fraction of SOM components, we also used fragment spectral cosine similarity scores to relate unknowns and library matches through molecular networks. This integrated approach allowed us to corroborate DI-FT-ICR MS molecular formulas using library matches, which included fungal metabolites and related polyphenolic compounds. We also inferred structures of unknowns from molecular networks and improved LC-MS/MS annotation rates from ~5 to 35% by considering DI-FT-ICR MS molecular formula assignments. Under drought conditions, we found greater relative amounts of lignin-like vs condensed aromatic polyphenol formulas and lower average nominal oxidation state of carbon, suggesting reduced decomposition of SOM and/or microbes under stress. Our integrated approach provides a framework for enhanced annotation of SOM components that is more comprehensive than performing individual data analyses in parallel.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Selective inhibition of cullin 3 neddylation through covalent targeting DCN1 protects mice from acetaminophen-induced liver toxicity

Cullin-RING E3 ligases (CRLs) regulate the turnover of approximately 20% of mammalian cellular proteins. Neddylation of individual cullin proteins is essential for the activation of each CRL. We report herein the discovery of DI-1548 and DI-1859 as two potent, selective and covalent DCN1 inhibitors. These inhibitors selectively inhibit neddylation of cullin 3 in cells at low nanomolar concentrations and are 2–3 orders of magnitude more potent than our previously reported reversible DCN1 inhibitor. Mass spectrometric analysis and co-crystal structures reveal that these compounds employ a unique mechanism of covalent bond formation with DCN1. DI-1859 induces a robust increase of NRF2 protein, a CRL3 substrate, in mouse liver and effectively protects mice from acetaminophen-induced liver damage. Taken together, this study demonstrates the therapeutic potential of selective inhibition of cullin neddylation.

59 BASIC BIOLOGICAL SCIENCES↗

Structures of the DarR transcription regulator reveal unique modes of second messenger and DNA binding

The mycobacterial repressor, DarR, a TetR family regulator (TFR), was the first transcription regulator shown to bind c-di-AMP. However, the molecular basis for this interaction and the mechanism involved in DNA binding by DarR remain unknown. Here we describe DarR-c-di-AMP and DarR-DNA structures and complementary biochemical assays. The DarR-c-di-AMP structure reveals a unique effector binding site for a TFR, located between DarR dimer subunits. Strikingly, we show this motif also binds cAMP. The location of the adenine nucleotide binding site between subunits suggests this interaction may facilitate dimerization and hence DNA binding. Indeed, biochemical assays show cAMP enhances DarR DNA binding. Finally, DarR-DNA structures reveal a distinct TFR DNA-binding mechanism involving two interacting dimers on the DNA. Thus, the combined data unveil a newly described second messenger binding motif and DNA binding mode for this important family of regulators.

59 BASIC BIOLOGICAL SCIENCES↗

Direct time-resolved detection and quantification of key reactive intermediates in diethyl ether oxidation at T = 450–600 K

High-pressure multiplexed photoionization mass spectrometry (MPIMS) with tunable vacuum ultraviolet (VUV) ionization radiation from the Lawrence Berkeley Labs Advanced Light Source is used to investigate the oxidation of diethyl ether (DEE). Kinetics and photoionization (PI) spectra are simultaneously measured for the species formed. Several stable products from DEE oxidation are identified and quantified using reference PI cross-sections. In addition, we directly detect and quantify three key chemical intermediates: peroxy (ROO˙), hydroperoxyalkyl peroxy (˙OOQOOH), and ketohydroperoxide (HOOP[double bond, length as m-dash]O, KHP). These intermediates undergo dissociative ionization (DI) into smaller fragments, making their identification by mass spectrometry challenging. Furthermore, with the aid of quantum chemical calculations, we identify the DI channels of these key chemical species and quantify their time-resolved concentrations from the overall carbon atom balance at T = 450 K and P = 7500 torr. This allows the determination of the absolute PI cross-sections of ROO˙, ˙OOQOOH, and KHP into each DI channel directly from experiment. The PI cross-sections in turn enable the quantification of ROO˙, ˙OOQOOH, and KHP from DEE oxidation over a range of experimental conditions that reveal the effects of pressure, O 2 concentration, and temperature on the competition among radical decomposition and second O 2 addition pathways.

42 ENGINEERING↗

Olefin metathesis over supported MoO x catalysts: influence of the oxide support

Here, a series of supported MoO x catalysts on different oxide supports (Al2O3, TiO2, ZrO2, SiO2) were synthesized and investigated for propylene metathesis, characterized with in situ spectroscopies (DRIFTS, Raman, UV-vis) and chemically probed with propylene-TPSR-MS, propylene-TPSR-IR, and ethylene/2-butene titration. Under dehydrated conditions at monolayer coverage or maximum surface dispersion, the surface MoO x sites are present as a mixture of isolated di-oxo (O=) 2 Mo(–O–Al) 2 and oligomeric mono-oxo O=Mo(–O–Al) 4/5 sites on Al 2 O 3 , primarily oligomeric mono-oxo O=Mo(–O–Ti) 4/5 on TiO 2 , isolated di-oxo (O=) 2 Mo(–O–Zr) 2 and oligomeric mono-oxo O=Mo(–O–Zr) 4/5 on ZrO 2 , and isolated di-oxo (O=) 2 Mo(–O–Si) 2 on SiO 2 . The bridged (S 2 -OH) and tri-coordinated (S 3 -OH) anchoring surface hydroxyls of the oxide supports with strong support cation electronegativity control the activation and number of active surface MoO x sites at low temperatures (<100 °C). The isolated anchoring surface hydroxyls (S-OH) of the oxide supports with strong support cation electronegativity control the activation and number of active surface MoO x sites at high temperatures (>350 °C). Olefin metathesis by the more redox active supported MoO x /TiO 2 and MoO x /ZrO 2 catalysts is retarded by the formation of stable surface acetone and acetate species that block olefin adsorption. The oxide supports are potent ligands that tune the activation and surface chemistry of the surface MoOx sites for olefin metathesis. This is the first time that the influence of oxide supports on the activation and surface chemistry of supported MoO x sites has been systematically examined.

02 PETROLEUM↗

Prediction of the structures and heats of formation of MO 2 , MO 3 , and M 2 O 5 for M = V, Nb, Ta, Pa

Structures for the mono-, di-, and tri-bridge isomers of M 2 O 5 as well as those for the MO 2 and MO 3 fragments for M = V, Nb, Ta, and Pa were optimized at the density functional theory (DFT) level. Single point CCSD(T) calculations extrapolated to the complete basis set (CBS) limit at the DFT geometries were used to predict the energetics. Here, the lowest energy dimer isomer was the di-bridge for M = V and Nb and the tri-bridge for M = Ta and Pa. The di-bridge isomers were predicted to be composed of MO 2 + and MO 3 - fragments, whereas the mono- and tri-bridge are two MO 2 + fragments linked by an O 2 - . The heats of formation of M 2 O 5 dimers, as well as MO 2 and MO 3 neutral and ionic species were predicted using the Feller–Peterson–Dixon (FPD) approach. The heats of formation of the MF 5 species were calculated to provide additional benchmarks. Dimerization energies to form the M 2 O 5 dimers are predicted to become more negative going down group 5 and range from -29 to -45 kcal mol -1 . The ionization energies (IEs) for VO 2 and TaO 2 are essentially the same at 8.75 eV whereas the IEs for NbO 2 and PaO 2 are 8.10 and 6.25 eV, respectively. The predicted adiabatic electron affinities (AEAs) range from 3.75 eV to 4.45 eV for the MO 3 species and vertical detachment energies from 4.21 to 4.59 eV for MO 3 - . The calculated M[double bond, length as m-dash]O bond dissociation energies increase from 143 kcal mol -1 for M = V to ~170 kcal mol -1 for M = Nb and Ta to ~200 kcal mol -1 for M = Pa. The M–O bond dissociation energies are all similar ranging from 97 to 107 kcal mol -1 . Natural bond analysis provided insights into the types of chemical bonds in terms of their ionic character. Pa 2 O 5 is predicted to behave like an actinyl species dominated by the interactions of approximately linear PaO 2 + groups.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantification of microtubule stutters: dynamic instability behaviors that are strongly associated with catastrophe

Microtubules (MTs) are cytoskeletal fibers that undergo dynamic instability (DI), a remarkable process involving phases of growth and shortening separated by stochastic transitions called catastrophe and rescue. Dissecting DI mechanism(s) requires first characterizing and quantifying these dynamics, a subjective process that often ignores complexity in MT behavior. We present a Statistical Tool for Automated Dynamic Instability Analysis (STADIA) that identifies and quantifies not only growth and shortening, but also a category of intermediate behaviors that we term “stutters.” During stutters, the rate of MT length change tends to be smaller in magnitude than during typical growth or shortening phases. Quantifying stutters and other behaviors with STADIA demonstrates that stutters precede most catastrophes in our in vitro experiments and dimer-scale MT simulations, suggesting that stutters are mechanistically involved in catastrophes. Related to this idea, we show that the anticatastrophe factor CLASP2γ works by promoting the return of stuttering MTs to growth. STADIA enables more comprehensive and data-driven analysis of MT dynamics compared with previous methods. The treatment of stutters as distinct and quantifiable DI behaviors provides new opportunities for analyzing mechanisms of MT dynamics and their regulation by binding proteins.

59 BASIC BIOLOGICAL SCIENCES↗

Natural diversity provides a broad spectrum of cyanobacteriochrome-based diguanylate cyclases

Cyanobacteriochromes (CBCRs) are spectrally diverse photosensors from cyanobacteria distantly related to phytochromes that exploit photoisomerization of linear tetrapyrrole (bilin) chromophores to regulate associated signaling output domains. Unlike phytochromes, a single CBCR domain is sufficient for photoperception. CBCR domains that regulate the production or degradation of cyclic nucleotide second messengers are becoming increasingly well characterized. Furthermore, cyclic di-guanosine monophosphate (c-di-GMP) is a widespread small-molecule regulator of bacterial motility, developmental transitions, and biofilm formation whose biosynthesis is regulated by CBCRs coupled to GGDEF (diguanylate cyclase) output domains. In this study, we compare the properties of diverse CBCR-GGDEF proteins with those of synthetic CBCR-GGDEF chimeras. Our investigation shows that natural diversity generates promising candidates for robust, broad spectrum optogenetic applications in live cells. Since light quality is constantly changing during plant development as upper leaves begin to shade lower leaves—affecting elongation growth, initiation of flowering, and responses to pathogens, these studies presage application of CBCR-GGDEF sensors to regulate orthogonal, c-di-GMP-regulated circuits in agronomically important plants for robust mitigation of such deleterious responses under natural growing conditions in the field.

59 BASIC BIOLOGICAL SCIENCES↗

LSTM-Based Data Integration to Improve Snow Water Equivalent Prediction and Diagnose Error Sources

Accurate prediction of snow water equivalent (SWE) can be valuable for water resource managers. Recently, deep learning methods such as long short-term memory (LSTM) have exhibited high accuracy in simulating hydrologic variables and can integrate lagged observations to improve prediction, but their benefits were not clear for SWE simulations. Here we tested an LSTM network with data integration (DI) for SWE in the western United States to integrate 30-day-lagged or 7-day-lagged observations of either SWE or satellite-observed snow cover fraction (SCF) to improve future predictions. SCF proved beneficial only for shallow-snow sites during snowmelt, while lagged SWE integration significantly improved prediction accuracy for both shallow- and deep-snow sites. The median Nash–Sutcliffe model efficiency coefficient (NSE) in temporal testing improved from 0.92 to 0.97 with 30-day-lagged SWE integration, and root-mean-square error (RMSE) and the difference between estimated and observed peak SWE values d max were reduced by 41% and 57%, respectively. DI effectively mitigated accumulated model and forcing errors that would otherwise be persistent. Moreover, by applying DI to different observations (30-day-lagged, 7-day-lagged), we revealed the spatial distribution of errors with different persistent lengths. For example, integrating 30-day-lagged SWE was ineffective for ephemeral snow sites in the southwestern United States, but significantly reduced monthly-scale biases for regions with stable seasonal snowpack such as high-elevation sites in California. These biases are likely attributable to large interannual variability in snowfall or site-specific snow redistribution patterns that can accumulate to impactful levels over time for nonephemeral sites. These results set up benchmark levels and provide guidance for future model improvement strategies.

54 ENVIRONMENTAL SCIENCES↗

Fast Dynamic Aperture Optimization with Reversal Integration

A fast method for dynamic aperture (DA) optimization of storage rings has been developed through the use of reversal integration. Even if dynamical systems have an exact reversal symme- try, a numerical forward integration di ers from its reversal. For chaotic trajectories, cumulative round-o errors are scaled, which results in an exponential growth in the di erence. The exponential e ect, intrinsically associated with the Lyapunov exponent, is a generic indicator of chaos because it represents the sensitivity of chaotic motion to an initial condition. A chaos indicator of the charged particle motion is then obtained by comparing the forward integrations of particle trajectories with corresponding reversals, a.k.a. \backward integrations." The indicator was con rmed to be ob- servable through short-term particle tracking simulations. Therefore, adopting it as an objective function could speed up optimization. The DA of the National Synchrotron Light Source II storage ring, and another test di raction-limited light source ring, were optimized using this method for the purpose of demonstration.

36 MATERIALS SCIENCE↗

Inverse-Velocity Transformation Wall Model for Reacting Turbulent Hypersonic Boundary Layers

The present study builds on prior work by taking advantage of the novel framework proposed by Griffin et al. (hereafter referred to as the GFM) as a baseline. The model is progressively extended to multicomponent reacting mixtures, accounting for differential diffusion and finite-rate chemistry in a similar fashion to Di Renzo & Urzay and Di Renzo et al. The accuracy of the present approach, as well the prior model of Di Renzo & Urzay, is assessed in an a priori sense for the first time in a turbulent reacting boundary layer, using the boundary-layer data of Williams et al. Five species are included in the present analysis, i.e., N s = 5, namely N 2 , O 2 , NO, N and O, a neutral mixture most representative of dissociation/recombination phenomena for temperatures below 6000 K. A schematic of a flow over a wedge representative of the described configuration is presented in Figure 1. The brief is organized as follows: In Section 2, the wall-model equations and the computational framework are presented. In Section 3, the a priori results of the proposed model are described and compared to the extended EWM. Finally, in Section 4, some conclusions are offered.

97 MATHEMATICS AND COMPUTING↗

Cellulose crystallinity index (CrI) of switchgrass measured by solid-state NMR

Here we present a curated dataset of switchgrass cellulose crystallinity index (CrI) measured using solid state nuclear magnetic resonance (NMR) spectroscopy. Seventy-two topline switchgrass lines grown in greenhouse were collected and ground to -20/+80 mesh. The switchgrass was then Soxhlet-extracted with toluene/ethanol for 24 h to remove extractives. The extractives-free switchgrass was holopulped by using peracetic acid at 5 g loading per g biomass and the solution consistency was adjusted to 5% with DI water. Holopulping was conducted at room temperature for 24 h with stirring. The obtained holocellulose was washed excessively with DI water and air-dried at room temperature for 24 h. The dried holocellulose was treated with hydrochloric acid (2.5 M) for 2 h to remove hemicellulose. The isolated cellulose was collected by filtration, rinsed with DI water, and used to analyze cellulose crystallinity by solid-state NMR. The NMR samples were prepared by packing the moisturized cellulose into 4-mm cylindrical Zirconia MAS rotors. Cross polarization/magic angle spinning (CP/MAS) NMR analysis of cellulose was carried out on a Bruker Avance III 400-MHz spectrometer operating at 100.59 MHz for 13C in a Bruker double-resonance MAS probe head at spinning speeds of 8 kHz. The CP/MAS experiments utilized a 5 ms (90°) proton pulse, 1.5 ms contact pulse, 4 s recycle delay and 4000 scans. The cellulose crystallinity index was determined from the areas of the cellulose crystalline C4 signal (δ 86-92 ppm) over the entire C4 regions (δ 79-92 ppm) in the NMR spectra.

Cellulose, crystallinity index, switchgrass, solid↗

N α -acetyl-L-ornithine deacetylase from Escherichia coli and a ninhydrin-based assay to enable inhibitor identification

Bacteria are becoming increasingly resistant to antibiotics, therefore there is an urgent need for new classes of antibiotics to fight antibiotic resistance. Mammals do not express N α -acetyl-L-ornithine deacetylase (ArgE), an enzyme that is critical for bacterial survival and growth, thus ArgE represents a promising new antibiotic drug target, as inhibitors would not suffer from mechanism-based toxicity. A new ninhydrin-based assay was designed and validated that included the synthesis of the substrate analog N 5 , N 5 -di-methyl N α -acetyl-L-ornithine (k cat /K m = 7.32 ± 0.94 × 10 4 M -1 s -1 ). This new assay enabled the screening of potential inhibitors that absorb in the UV region, and thus is superior to the established 214 nm assay. Using this new ninhydrin-based assay, captopril was confirmed as an ArgE inhibitor (IC 50 = 58.7 μM; K i = 37.1 ± 0.85 μM), and a number of phenylboronic acid derivatives were identified as inhibitors, including 4-(diethylamino)phenylboronic acid (IC 50 = 50.1 μM). Selected inhibitors were also tested in a thermal shift assay with ArgE using SYPRO Orange dye against Escherichia coli ArgE to observe the stability of the enzyme in the presence of inhibitors (captopril K i = 35.9 ± 5.1 μM). The active site structure of di-Zn Ec ArgE was confirmed using X-ray absorption spectroscopy, and we reported two X-ray crystal structures of E. coli ArgE. In summary, we describe the development of a new ninhydrin-based assay for ArgE, the identification of captopril and phenylboronic acids as ArgE inhibitors, thermal shift studies with ArgE + captopril, and the first two published crystal structures of ArgE (mono-Zn and di-Zn).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Influence of Microstructure on TCR for Inkjet-Printed Resistive Temperature Detectors Fabricated Using AgNO 3 /Ethylene-Glycol-Based Inks

This study investigated the influence of microstructure on the performance of Ag inkjet-printed, resistive temperature detectors (RTDs) fabricated using particle-free inks based on a silver nitrate (AgNO 3 ) precursor and ethylene glycol as the ink solvent. Specifically, the temperature coefficient of resistance (TCR) and sensitivity for sensors printed using inks that use monoethylene glycol (mono-EG), diethylene glycol (di-EG), and triethylene glycol (tri-EG) and subjected to a low-pressure argon (Ar) plasma after printing were investigated. Scanning electron microscopy (SEM) confirmed previous findings that microstructure is strongly influenced by the ink solvent, with mono-EG inks producing dense structures, while di- and tri-EG inks produce porous structures, with tri-EG inks yielding the most porous structures. RTD testing revealed that sensors printed using mono-EG ink exhibited the highest TCR (1.7 × 10 -3 /°C), followed by di-EG ink (8.2 × 10 -4 /°C) and tri-EG ink (7.2 × 10 -4 /°C). These findings indicate that porosity exhibits a strong negative influence on TCR. Sensitivity was not strongly influenced by microstructure but rather by the resistance of RTD. The highest sensitivity (0.84 Ω/°C) was observed for an RTD printed using mono-EG ink but not under plasma exposure conditions that yield the highest TCR.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗