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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Effect of the ..beta..-Hydroxy Group on Ester Reactivity: Combustion Kinetics of Methyl Hexanoate and Methyl 3-Hydroxyhexanoate

One of the major biofuels used today is biodiesel, composed of fatty acid methyl esters. The fats and oils feedstocks used to make biodiesel are in relatively short supply. To meet increasing global demand, engineered microorganisms have been developed to catalyze conversion of sugar to fatty acid esters that contain unique ..beta..-hydroxy-esters. This study investigated the effect of a hydroxyl group on the combustion characteristics of methyl esters by comparing the chemical behavior of methyl hexanoate (MHx) and methyl 3-hydroxyhexanoate (M3OHHx) - used as surrogates for diesel-boiling-range esters with longer fatty acid chains. The oxidation of these esters was studied experimentally in a flow reactor at 0.84 and 10 bar, 600 to 1,100 K, and stoichiometric conditions; and in a constant volume combustion chamber at 5 and 10 bar, 600 to 900 K, and equivalence ratios of 0.3 and 0.6. MHx was more reactive in the constant volume chamber at temperatures below 800 K at 10 bar and equivalence ratio of 0.6. MHx also exhibited a higher indicated cetane number (16.4) than M3OHHx (8.1). We investigated this reactivity trend using an updated MHx kinetic model and M3OHHx model developed as part of this work. The kinetic models predicted that radicals formed from MHx were consumed by low-temperature chemistry reactions, whereas the M3OHHx reactivity was significantly governed by the ..beta..-radical (on the same carbon as the OH group) chemistry which mainly terminated via the less reactive chain propagation pathway to methyl-3-oxohexanoate + HO2. This study extends our understanding of structural effects on ester reactivity, which will allow for accurate surrogate formulation and performance simulations.

AFIDA↗
DOE OSTI2025

Improving Bond Dissociations of Reactive Machine Learning Potentials through Physics-Constrained Data Augmentation

In the field of computational chemistry, predicting bond dissociation energies (BDEs) presents well-known challenges, particularly due to the multireference character of reactive systems. Many chemical reactions involve configurations where single-reference methods fall short, as the electronic structure can significantly change during bond breaking. As generating training data for partially broken bonds is a challenging task, even state-of-the-art reactive machine learning interatomic potentials (MLIPs) often fail to predict reliable BDEs and smooth dissociation curves. By contrast, simple and inexpensive physics-based models, such as the well-established Morse potential, do not suffer from any such limitations. This work leverages the Morse potential to improve reactive MLIPs by augmenting the training data set with inexpensive Morse data along the dissociation pathways. Further, this physics-constrained data augmentation (PCDA) approach results in MLIPs with smooth bond dissociation curves as well as near coupled-cluster level BDEs, all without requiring any expensive multireference quantum mechanical calculations. A case study for methane combustion demonstrates how the PCDA approach can improve an existing reactive MLIP, namely, ANI-1xnr. In conclusion, not only are the BDEs and bond dissociation curves for all radicals and molecules significantly improved compared to ANI-1xnr but the PCDA-trained MLIP retains the reliability of ANI-1xnr when performing reactive molecular dynamics simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Exploring the frontiers of condensed-phase chemistry with a general reactive machine learning potential

Abstract Atomistic simulation has a broad range of applications from drug design to materials discovery. Machine learning interatomic potentials (MLIPs) have become an efficient alternative to computationally expensive ab initio simulations. For this reason, chemistry and materials science would greatly benefit from a general reactive MLIP, that is, an MLIP that is applicable to a broad range of reactive chemistry without the need for refitting. Here we develop a general reactive MLIP (ANI-1xnr) through automated sampling of condensed-phase reactions. ANI-1xnr is then applied to study five distinct systems: carbon solid-phase nucleation, graphene ring formation from acetylene, biofuel additives, combustion of methane and the spontaneous formation of glycine from early earth small molecules. In all studies, ANI-1xnr closely matches experiment (when available) and/or previous studies using traditional model chemistry methods. As such, ANI-1xnr proves to be a highly general reactive MLIP for C, H, N and O elements in the condensed phase, enabling high-throughput in silico reactive chemistry experimentation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Simulation of the Fast Reactor Fuel Assembly Duct-Bowing Reactivity Effect Using Monte Carlo Neutron Transport and Finite Element Analysis

This paper discusses a new method of simulating the fuel assembly duct-bowing reactivity coefficient for EBR-II run 138B. Quantification of the fuel assembly duct-bowing reactivity effect in liquid metal–cooled fast reactors has been a persistent problem since they were first designed and operated. Simulation of the duct-bowing reactivity effect is difficult because the level of detail required to simulate the effect has exceeded most modeling capabilities. The new method outlined in this paper utilizes the finite element analysis code ANSYS to analyze the thermal and structural components. Here, the displacement of the fuel assembly duct due to thermal expansion and mechanical interaction was calculated by ANSYS using recorded EBR-II run 138B temperature and power boundary value data. The displacement values were incorporated into to a Monte Carlo model of EBR-II run 138B and keff was calculated. Multiple Monte Carlo calculations were performed with duct displacement values corresponding to different reactor temperatures. Using the calculated keff values associated with the different duct displacement results allowed calculation of the duct-bowing reactivity coefficient. The duct-bowing reactivity coefficient was calculated to be –14.5 × 10 –4 $/°C/ ± 4.4%.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Synthetic dioxygenase reactivity by pairing electrochemical oxygen reduction and water oxidation

The reactivity of molecular oxygen is crucial to clean energy technologies and green chemical synthesis, but kinetic barriers complicate both applications. In synthesis, dioxygen should be able to undergo oxygen atom transfer to two organic molecules with perfect atom economy, but such reactivity is rare. Monooxygenase enzymes commonly reductively activate dioxygen by sacrificing one of the oxygen atoms to generate a more reactive oxidant. Here, we used a manganese-tetraphenylporphyrin catalyst to pair electrochemical oxygen reduction and water oxidation, generating a reactive manganese-oxo at both electrodes. This process supports dioxygen atom transfer to two thioether substrate molecules, generating two equivalents of sulfoxide with a single equivalent of dioxygen. This net dioxygenase reactivity consumes no electrons but uses electrochemical energy to overcome kinetic barriers.

Science & Technology - Other Topics↗
DOE OSTI2020

Verification and Validation of High Explosive Reactive Burn Models Implemented in LANL's EAP and LAP Code Base

Reactive burn models represent a significant leap in high explosive (HE) modeling capability. The first generation of engineering models of HE detonation are called programmed burn models and they are largely based on the distance between a prescribed detonation point and each zone in a simulation. There have been many advancements to programmed burn models over the years and when the assumptions upon which they are based are met, a properly tuned programmed burn model can be highly accurate but if any of their assumptions is not met, as is the case for corner turning or weakly initiated HE burn, they will give the wrong answer. Reactive burn models represent an entirely new way of modeling HE burn. They use the local conditions of a zone – e.g. temperature, pressure or density – as calculated by a hydrocode to determine if and when the zone is going to detonate and if so, how rapidly. This difference opens up an entirely new set of capabilities for HE modeling. It makes it possible to accurately and predictively model phenomena like the effect of confinement and the formation of dead zones. Reactive burn models have seen sustained development effort at LANL for at least the last decade but several recent developments make it timely to transition reactive burn models from a research topic to a production tool. The main goal of this milestone is to facilitate and accelerate the adoption of reactive burn as a commonly available modeling option, with recommendations on the resolution that will be required and uncertainties associated with their modeling choices. To achieve this, we have performed verification, validation, and uncertainty quantification (UQ) assessments of AWSD and SURF/SURFplus in xRage and FLAG on a variety of different problems.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2022

Fused Filament Fabrication of Polycarbonate in a Reactive Atmosphere

Fused Filament Fabrication (FFF) has become extremely useful in various industries, particularly when complex parts are needed in low volumes. However, the material properties available in FFF polymers are limited in scope. The properties of a FFF part can be changed in multiple ways. This study explores changing the bulk properties of a part by affecting each layer as it prints. Prior work has demonstrated the feasibility of altering polymer properties by layerwise exposure to a liquid chemical, but properties have never been modified in situ using a reactive gas. Here, FFF is done in the presence of a reactive gas. Specifically, the part is printed with polycarbonate in a reactive atmosphere of ozone and ultra-violet light. It was found that as each layer is exposed to a reactive gas, the bulk properties of the part change. A visual chemical change was seen, as well as confirmation of the reaction through Fourier transform infrared spectroscopy attenuated total reflectance. The change in mechanical properties was measured through Dynamic Mechanical Analysis shear tests, showing a bulk change can be efficiently produced through FFF in a reactive atmosphere.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Exploration of Fuel Property Impacts on the Combustion of Late Post Injections Using Binary Blends and High-Reactivity Ether Bioblendstocks

In this study, the impacts of fuel volatility and reactivity on com- bustion stability and emissions were studied in a light-duty single- cylinder research engine for a three-injection catalyst heating oper- ation strategy with late post-injections. N-heptane and blends of farnesane/2,2,4,4,6,8,8-heptamethylnonane were used to study the im- pacts of volatility and reactivity. The effect of increased chemical reac- tivity was also analysed by comparing the baseline #2 diesel operation with a pure blend of mono-ether components (CN > 100) representa- tive of potential high cetane oxygenated bioblendstocks and a 25 vol.% blend of the mono-ether blend and #2 diesel with a cetane number (CN) of 55. At constant reactivity, little to no variation in combustion performance was observed due to differences in volatility, whereas in- creased reactivity improved combustion stability and efficiency at late injection timings. Fuels with higher reactivity were found to reduce engine-out hydrocarbon and carbon monoxide emissions while also achieving stable combustion at post-injection timings later than those achievable with #2 diesel fuel. The pure ether blend had the latest achievable post-injection timing of +30.5 CAD while still maintaining stable combustion (coefficient of variation of gross-indicated mean ef- fective pressure < 5%). With post-injection timing adjusted to achieve a matched exhaust temperature of 300 °C, the ether-diesel CN 55 blend was observed to have slightly higher thermal efficiency in comparison to the baseline #2 diesel fuel. The results also indicate that cetane num- ber may serve as a good indicator of combustion characteristics at late injection timings used for aftertreatment thermal management opera- tion.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Design of Broadly Cross-Reactive M Protein–Based Group A Streptococcal Vaccines

Group A streptococcal infections are a significant cause of global morbidity and mortality. A leading vaccine candidate is the surface M protein, a major virulence determinant and protective Ag. An obstacle to the development of M protein–based vaccines is the >200 different M types defined by the N-terminal sequences that contain protective epitopes. Despite sequence variability, M proteins share coiled-coil structural motifs that bind host proteins required for virulence. In this study, we exploit this potential Achilles heel of conserved structure to predict cross-reactive M peptides that could serve as broadly protective vaccine Ags. Combining sequences with structural predictions, six heterologous M peptides in a sequence-related cluster were predicted to elicit cross-reactive Abs with the remaining five nonvaccine M types in the cluster. The six-valent vaccine elicited Abs in rabbits that reacted with all 11 M peptides in the cluster and functional opsonic Abs against vaccine and nonvaccine M types in the cluster. We next immunized mice with four sequence-unrelated M peptides predicted to contain different coiled-coil propensities and tested the antisera for cross-reactivity against 41 heterologous M peptides. Based on these results, we developed an improved algorithm to select cross-reactive peptide pairs using additional parameters of coiled-coil length and propensity. The revised algorithm accurately predicted cross-reactive Ab binding, improving the Matthews correlation coefficient from 0.42 to 0.74. These results form the basis for selecting the minimum number of N-terminal M peptides to include in potentially broadly efficacious multivalent vaccines that could impact the overall global burden of group A streptococcal diseases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Stability of gas atomized reactive powders through multiple step in-situ passivation

A method for gas atomization of oxygen-reactive reactive metals and alloys wherein the atomized particles are exposed as they solidify and cool in a very short time to multiple gaseous reactive agents for the in-situ formation of a protective reaction film on the atomized particles. The present invention is especially useful for making highly pyrophoric reactive metal or alloy atomized powders, such as atomized magnesium and magnesium alloy powders. The gaseous reactive species (agents) are introduced into the atomization spray chamber at locations downstream of a gas atomizing nozzle as determined by the desired powder or particle temperature for the reactions and the desired thickness of the reaction film.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The impact of mineral reactive surface area variation on simulated mineral reactions and reaction rates

Reactive transport modeling is an essential tool to simulate complex geochemical reactions in porous media that can impact formation properties including porosity and permeability. However, simulating these reactions is challenging due to uncertainties in model parameters, particularly mineral surface areas. Imaging has emerged as a powerful means of estimating model parameters including porosity and mineral abundance, accessibility and accessible surface area. However, these parameters, particularly mineral accessible surface area, vary with image resolution. This work aims to enhance understanding of the impact of image resolution and other means of estimating mineral reactive surface area on simulated mineral reactions and reaction rates. Mineral surface areas calculated from images with resolutions of 0.34 μm and 5.71 μm were used to simulate mineral reactions in the context of geologic CO 2 sequestration in the Paluxy formation at the continuum scale. Additional simulations were carried out using BET surface areas collected from the literature and geometric surface areas. Simulations were run for 7300 days and mineral volume fractions and effluent ion concentrations tracked and compared. Variations in mineral surface areas measured from images are within 1 order of magnitude and yield similar simulation results, indicating the impact of image resolution on simulated reactions and reaction rates is minimum for the resolutions and sample considered. In comparison, surface areas obtained from BET and geometric approaches are 1–4 orders of magnitude higher than image-obtained surface areas and result in greater simulated reaction rates and extents. Minerals with high reaction rates (calcite and siderite) are most impacted by surface area values at short times where simulated mineral volume fractions at longer times agree relatively well, even for simulations with several orders of magnitude variation in surface area. Phases with lower reaction rates, such as K-feldspar and muscovite, are predominantly impacted over longer times where variations in surface areas impact reaction extents and porosity evolution. Overall, variations in surface areas due to image resolution are small and result in little variation in simulated reactions and reaction rates while there are significant variations in simulation results when other surface area estimates are used. These variations, however, depend on the reactivity of the mineral phase where surface areas of fast-reacting phases largely impact simulations at short (hours to days) timescales and surface areas of slower-reactive phases impact longer term simulations (years).

58 GEOSCIENCES↗
DOE OSTI2025

Understanding how defects and dopant atoms in copper surface oxides affect reactivity

Copper and its oxides are key catalytic materials, on which reactions often occur at the metal/oxide interface. Here, in this work, we directly connect the induction period observed during methanol-driven reduction of thin-film copper oxides to their atomic-scale structural order. Using temperature-programmed desorption (TPD) methanol titrations combined with scanning tunneling microscopy, we show that highly ordered oxide phases – particularly the “29” structure with its low defect density – exhibit long induction periods and initially low reactivity. The induction period, defined as the number of methanol TPD cycles required to reach half of the maximum formaldehyde yield, scales with oxide order and oxygen coverage. Enhanced reactivity of well-ordered oxides emerges only after repeated methanol adsorption/desorption cycles generate oxygen vacancies and new Cu(111)/Cu x O interfacial sites. In contrast, disordered or sub-stoichiometric oxides, which contain more intrinsic defects and interfaces, are active from the first TPD cycle. We further examine how dilute Pt and Rh dopants influence oxide order and reactivity: 1% Pt increases defect density and catalytic activity, while 1% Rh promotes oxide ordering and longer induction periods. These findings demonstrate that dilute alloying provides a potential method for tuning the structure and reactivity of Cu(111)/Cu x O interfaces.

Cu(111)Methanol oxidation↗
DOE OSTI2024

Reactive transport modeling of the Aquifer Thermal Energy Storage (ATES) system at Stockton University, New Jersey during seasonal operations

Hydrogeochemical processes associated with Aquifer Thermal Energy Storage (ATES) operations can often impact the system performance owing to mineral precipitation either at the wellbore or in the aquifer owing to changes in temperature and fluid disequilibria. Although failure of ATES systems due to mineral precipitation ("fouling") is common, predictive reactive-transport models have rarely been applied to plan their design and operation. Here, the objective of this study is to develop a reactive-transport model by coupling thermal, hydrological, and chemical (THC) processes to evaluate effects of introduced atmospheric oxygen on water chemistry, mineral precipitation/dissolution, porosity, and permeability changes associated with an ATES system at Stockton University (New Jersey, USA). The THC model builds on a Thermal-Hydrological-Mechanical (THM) model of the site that evaluated system failure owing to possible fracturing in the caprock or around the wellbore. The causes of the system failure are not known – potential causes include hydraulic fracturing owing to elevated pump pressures that took place, a flow pathway created by one of the boreholes, or a pre-existing natural hydrologic connection between the upper unconfined aquifer and the ATES aquifer, any of which could have led to oxygenated water entering the reservoir and causing the observed Fe-oxide fouling on well screens. The THC model is used to evaluate some of the hypotheses and observations regarding system failure owing to geochemical processes. The reactive-transport code TOUGHREACT V4 was used to model the THC processes during seasonal heating and cooling operations at the Stockton ATES site over 6 years of operation. In the THC simulations, the primary effects on geochemistry were observed when the injection water is saturated with atmospheric oxygen. Simulations show greater precipitation of goethite near the cold wells as compared to the warm wells. Although volume fractions of Fe-hydroxides were relatively small, the model was aimed at processes in the aquifer at the scale of meters and larger rather than at the scale of mm or cm (i.e., a well screen). Kaolinite is the dominant precipitating phase, also around the cold wells. Illite dissolves near the cold wells and precipitates near the warm wells. There is a net decrease in the porosity near the cold wells and increase near the warm wells, although a slight amount of thermal contraction near the cold wells and expansion near the warm wells is responsible for a significant proportion of the porosity change. Owing to the coarse discretization of the numerical grid near the wells (compared to the screen thickness) the magnitude of permeability changes at the wellbore are likely underestimated. The reactive transport model in this study can be used for characterization of aquifers, optimizing the operational parameters (temperature, pressure, pH etc.), and planning of mitigation strategies for ATES systems.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

CO–induced roughening of Cu(111): formation and detection of reactive nanoclusters on metal surfaces

The formation of nanoclusters on metal surfaces in the presence of reactive environments is a phenomenon with important implications for catalysis. These nanoclusters are composed of atoms ejected from undercoordinated sites such as step edges, and their presence alters the catalytic properties of solid materials. We perform density functional theory (DFT) and kinetic Monte Carlo (KMC) simulations to investigate the formation and reactivity of copper clusters on Cu(111). Our results indicate a considerably higher reactivity of small copper nanoclusters, with up to seven atoms in size on roughened copper surfaces than on pristine Cu(111) and Cu(211). Regarding the restructuring events that give rise to nanoclusters under CO atmospheres, we determine that the ejection of Cu atoms from step edges and their migration therefrom to adjacent Cu(111) terraces are, by and large, driven by CO coverage effects. By means of KMC simulations, which account for CO–CO lateral interactions and CO–induced surface restructuring, we show that temperature programmed desorption (TPD) holds promise for the detection of highly reactive nanoclusters. Furthermore, our approach showcases how surface restructuring and surface–adsorbate bond breaking can be combined when modeling surface reactions and contributes to the development of an advanced understanding of the nature of active site under reaction conditions.

catalyst dynamic restructuring↗
DOE OSTI2021

Importance of Engineered and Learned Molecular Representations in Predicting Organic Reactivity, Selectivity, and Chemical Properties

Machine-readable chemical structure representations are foundational in all attempts to harness machine learning for the prediction of reactivities, selectivities, and chemical properties directly from molecular structure. The featurization of discrete chemical structures into a continuous vector space is a critical phase undertaken before model selection, and the development of new ways to quantitatively encode molecules is an active area of research. Here, we highlight the application and suitability of different representations, from expert-guided “engineered” descriptors to automatically “learned” features, in different prediction tasks relevant to organic and organometallic chemistry, where differing amounts of training data are available. These tasks include statistical models of stereo- and enantioselectivity, thermochemistry, and kinetics developed using experimental and quantum chemical data. The use of expert-guided molecular descriptors provides an opportunity to incorporate chemical knowledge, domain expertise, and physical constraints into statistical modeling. In applications to stereoselective organic and organometallic catalysis, where data sets may be relatively small and 3D-geometries and conformations play an important role, mechanistically informed features can be used successfully to obtain predictive statistical models that are also chemically interpretable. We provide an overview of several recent applications of this approach to obtain quantitative models for reactivity and selectivity, where topological descriptors, quantum mechanical calculations of electronic and steric properties, along with conformational ensembles, all feature as essential ingredients of the molecular representations used. Alternatively, more flexible, general-purpose molecular representations such as attributed molecular graphs can be used with machine learning approaches to learn the complex relationship between a structure and prediction target. This approach has the potential to out-perform more traditional representation methods such as “hand-crafted” molecular descriptors, particularly as data set sizes grow. One area where this is particularly relevant is in the use of large sets of quantum mechanical data to train quantitative structure–property relationships. A general approach toward curating useful data sets and training highly accurate graph neural network models is discussed in the context of organic bond dissociation enthalpies, where this strategy outperforms regression using precomputed descriptors. Finally, we describe how graph neural network predictions can be incorporated into mechanistically informed statistical models of chemical reactivity and selectivity. Once trained, this approach avoids the expensive computational overhead associated with quantum mechanical calculations, while maintaining chemical interpretability. We illustrate examples for which fast predictions of bond dissociation enthalpy and of the identities of radicals formed through cleavage of a molecule’s weakest bond are used in simple physical models of site-selectivity and reactivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Teaching an Old Reagent New Tricks: Synthesis, Unusual Reactivity, and Solution Dynamics of Borohydride Grignard Compounds

Grignard reagents of general formula RMgX (X = Cl - , Br - , I - ) have been utilized in various chemistries for over 100 years. Here, we report that replacing the halide in a Grignard reagent with a reactive borohydride anion adds a new synthetic dimension for these influential compounds. Here, we synthesized the series RMgBH 4 (R=Et, n-Bu, Ph, Bn) and characterized the reactivity toward both organic and inorganic molecules. Using butylmagnesium borohydride (BuMgBH 4 ) as an exemplar, we demonstrate that these compounds possess unique reactivity due to the presence of reducing borohydride groups, resulting in tandem reactivity with organic amides/esters to generate secondary and primary alcohols. Molecular dynamics simulations indicate the stability of BuMgBH 4 is comparable to that of Mg(BH 4 ) 2 + MgBu 2 , validating the Schlenk equilibrium in borohydride Grignard compounds. Metadynamics simulations confirm that the equilibrium is kinetically accessible through solvent-mediated processes. BuMgBH 4 also reacts with CO 2 and NH 3 , revealing potential uses for CO 2 utilization and as a mixed-anion metal borohydride/amide precursor.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Importance of the Heat Treatment Scheme on Self-Reducing Reactive Silver Inks

Self-reducing reactive silver inks can print high-quality silver at reasonable temperatures. While numerous studies have explored the impact of processing temperature on electrical properties, the role of the heat treatment scheme has not yet been studied. Common heat treatment schemes include printing and drying inks at room temperature before heat treatment, performing heat treatments while the inks are still wet, and directly printing the inks onto heated substrates. Each scheme generates distinct heat transfer and mass transport kinetics that can affect the silver morphology and electrical properties. However, to date, the impact of different schemes has not been systematically investigated. To address this knowledge gap, this work investigates how different heat treatment schemes impact metal formation, sintering, and the resultant electrical properties of printed self-reducing reactive silver inks. Heat treatment on room-temperature dried inks and wet inks, with top-down (oven) and bottom-up (hot plate) heating sources, were compared. Inks dried at room temperature resulted in extremely porous films that required high heat treatment temperatures (>100 °C) for silver densification. However, these dried films could only densify locally, and their high initial porosities resulted in voids and high resistances (~0.6 Ω mm –1 ) even after heat treatments above 300 °C. Inks that were wet during heat treatment showed moderate improvements in electrical properties with resistances on the order of 0.4 Ω mm –1 at heat treatments of 250 °C. Printing reactive inks directly onto heated substrates yielded the best low-temperature results, with 0.46 Ω mm –1 (5.5 × bulk silver) line resistances achieved at only 90 °C. Overall, this work’s experimental results provide detailed insights into why printing onto a heated substrate results in superior electrical performance compared to more common heat treatment schemes. Additionally, controlling where the precipitation reaction occurs is critical to controlling the film morphology and properties. As a result, this work shows that even an ammonia-based silver reactive ink can achieve good, low-temperature electrical properties with the proper heat treatment scheme.

14 SOLAR ENERGY↗
DOE OSTI2023

Coordination-Dependent Chemical Reactivity of TFSI Anions at a Mg Metal Interface

Charge transfer across the electrode–electrolyte interface is a highly complex and convoluted process involving diverse solvated species with varying structures and compositions. Despite recent advances in in situ and operando interfacial analysis, molecular specific reactivity of solvated species is inaccessible due to a lack of precise control over the interfacial constituents and/or an unclear understanding of their spectroscopic fingerprints. However, such molecular-specific understanding is critical to the rational design of energy-efficient solid–electrolyte interphase layers. We have employed ion soft landing, a versatile and highly controlled method, to prepare well-defined interfaces assembled with selected ions, either as solvated species or as bare ions, with distinguishing molecular precision. Equipped with precise control over interfacial composition, we employed in situ multimodal spectroscopic characterization to unravel the molecular specific reactivity of Mg solvated species comprising (i.e., bis(trifluoromethanesulfonyl)imide, TFSI – ) anions and solvent molecules (i.e., dimethoxyethane, DME/G1) on a Mg metal surface relevant to multivalent Mg batteries. In situ multimodal spectroscopic characterization revealed higher reactivity of the undercoordinated solvated species [Mg-TFSI-G1] + compared to the fully coordinated [Mg-TFSI-(G1) 2 ] + species or even the bare TFSI – . These results were corroborated by the computed reaction pathways and energy barriers for decomposition of the TFSI – within Mg solvated species relative to bare TFSI – . Finally, we evaluated the TFSI reactivity under electrochemical conditions using Mg(TFSI) 2 –DME-based phase-separated electrolytes representing different solvated constituents. Based on our multimodal study, we report a detailed understanding of TFSI – decomposition processes as part of coordinated solvated species at a Mg-metal anode that will aid the rational design of improved sustainable electrochemical energy technologies.

25 ENERGY STORAGE↗