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Titanium hydride nanoinks are made by ball milling activated powders and tuned for aerosol jet printing. Photonic curing sinters nanoparticles to improve electrical conductivity, providing a viable route to diverse functionality in printed devices.
The electrochemical nitrate reduction reaction (NO3RR) on titanium introduces significant surface reconstruction and forms titanium hydride (TiH x , 0 < x ≤ 2). With ex situ grazing-incidence X-ray diffraction (GIXRD) and X-ray absorption spectroscopy (XAS), we demonstrated near-surface TiH2 enrichment with increasing NO3RR applied potential and duration. This quantitative relationship facilitated electrochemical treatment of Ti to form TiH 2 /Ti electrodes for use in NO3RR, thereby decoupling hydride formation from NO 3 RR performance. A wide range of NO 3 RR activity and selectivity on TiH2/Ti electrodes between -0.4 and -1.0 VRHE was observed and analyzed with density functional theory (DFT) calculations on TiH 2 (111). Finally, this work underscores the importance of relating NO 3 RR performance with near-surface electrode structure to advance catalyst design and operation.
Abstract not provided.
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Titanium hydride of varying TiH stoichiometry is used in pyrotechnic compositions. In order to yield consistent performance, manufacturing processes must be developed to ensure precise and reproducible material properties, including composition and morphology. Legacy synthesis protocols are not comprehensive nor are the required apparatuses still available. To guide the development of novel production procedures, this report reviews literature on relevant chemical reactions and diffusion events occurring at elevated temperature in the TiH (2-x) /TiO y system. Titanium hydride exposed to air spontaneously forms a passivating oxide layer. Upon heating, significant hydrogen release, which is accompanied by changes to the surface oxide layer, is noted by 375–400°C. At higher temperatures (above about 500°C) the oxide layer is reported to be essentially nonexistent as a result of oxide-layer dissolution processes and, potentially, oxide-layer reduction due to water formation. Based on the reviewed literature, we hypothesize that, by 500°C, the surface layer consists of an oxyhydride phase, which is a solid solution of oxygen in titanium hydride. We believe that hydrogen release from titanium hydride is controlled by the kinetics of molecular hydrogen desorption on the oxyhydride surface. No literature data is available for corresponding activation energies of the dynamic desorption process, and the equilibrium phase diagram of this three-component system remains largely unexplored as well. These gaps in knowledge might be addressed through coordinated computational modeling and experimental efforts.
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We investigated proton emission from titanium hydride (TiH 2 ) targets irradiated in vacuum by a 6-ns, 1064-nm Nd:YAG laser. Time-of-flight measurements with a Faraday cup and an electrostatic ion analyzer resolved distinct proton peaks at high pulse energies, with yields on the order of 10 9 protons per shot. Systematic scans over pulse energy and up to 1000 repeated shots showed that, while the peak amplitude gradually decreased, the integrated proton number remained nearly constant. This behavior is consistent with surface-induced broadening of the plasma expansion while bulk hydrogen is replenished by diffusion and repeated ablation of fresh TiH 2 layers. Using the measured proton numbers and pulse widths, a simple direct-plasma-injection-style scaling indicates peak currents of ∼100 mA and sub-microsecond pulse durations. The pulse structure and yield satisfy key ultra-high-dose-rate criteria and, together with sustained output over 1000 shots, support TiH 2 -based laser ion sources as practical candidates for FLASH-therapy (ultra-high-dose-rate)-oriented studies and injector development using direct plasma injection.
Nitrates from agricultural runoff and industrial waste streams are a notorious waste product and hazardous pollutant. Traditional electrochemical water remediation approaches aim to solve this problem by converting nitrates to environmentally benign N 2 while minimizing the production of environmentally hazardous side products such as ammonia and nitrous oxide in a process known as “denitrification”. We modify this concept and outline an opportunity to optimize the conversion of nitrates into ammonia, which is also a key commodity product used as a fertilizer, potential fuel, and chemical precursor. The electrochemical conversion of nitrates to ammonia recycles the fixed nitrogen and offers an appealing and supplementary alternative to the energy- and resource-intensive Haber-Bosch process. In this study, we investigated the effect of varying electrochemical conditions (pH, nitrate concentration, and applied potential) on the selective reduction of nitrate to ammonia at a titanium cathode. We observed that high concentrations of both protons and nitrate ions are needed to achieve high selectivity, reaching a peak of 82% Faradaic efficiency to ammonia at an applied potential of -1 V versus RHE and a partial current density to NH 3 of -22 mA/cm 2 , using 0.4 M [NO 3 – ] at pH ~0.77. The Ti electrode, as a poor hydrogen evolution catalyst with notable corrosion resistance, provides a large window of operating conditions to achieve high selectivity in the reduction of nitrate anions. Stability of the system was evaluated, and we found a high Faradaic efficiency throughout the course of an 8 h experiment. After electrochemical testing, titanium hydride was observed at the cathode surface. We also show a preliminary technoeconomic study, indicating that it may be feasible to employ an electrochemical strategy for the production of ammonium nitrate.
Porous metals find extensive applications in soundproofing, filtration, catalysis, and energy-absorbing structures, thanks to their unique internal pore structure and high specific strength. In recent years, there has been an increasing interest in fabricating porous metals using additive manufacturing (AM), leveraging its unique advantages, including improved design freedom, spatial material control, and cost-effective small-batch production. In this study, we conducted pioneering operando visualization of AM porous metal using a laser powder bed fusion (L-PBF) setup combined with a high-speed synchrotron x-ray imaging system. Single track printing experiments using Ti6Al4V (Ti64) combined with titanium hydride (TiH 2 ) and sodium carbonate (Na 2 CO 3 ) as foaming agents, with varying mixing ratios were performed under different processing conditions. Here. the results elucidate the dynamic development of porosity formation. The average pore size is significantly influenced by the particle size of foaming agents when pore coalescence is absent. For all foaming agent content tested in the current study, the number of pores is found to be more sensitive to changes in laser power than in laser scanning speed. Increasing linear energy density (increasing laser power or reducing laser scanning speed) promotes the foaming agent activation thereby porosity formation. However, high linear energy density skews pore distribution towards the surface despite forming deeper melt pools. In addition, the impact of additional factors including foaming agent's laser absorptivity and decomposition kinetics with respect to AM time scales should be carefully considered to avoid ineffective activation of foaming agents during the AM of porous metals.
Abstract Machine learning interatomic potentials (MLIPs) enable accurate simulations of materials at scales beyond that accessible by ab initio methods and play an increasingly important role in the study and design of materials. However, MLIPs are only as accurate and robust as the data on which they are trained. Here, we present DImensionality-Reduced Encoded Clusters with sTratified (DIRECT) sampling as an approach to select a robust training set of structures from a large and complex configuration space. By applying DIRECT sampling on the Materials Project relaxation trajectories dataset with over one million structures and 89 elements, we develop an improved materials 3-body graph network (M3GNet) universal potential that extrapolates more reliably to unseen structures. We further show that molecular dynamics (MD) simulations with the M3GNet universal potential can be used instead of expensive ab initio MD to rapidly create a large configuration space for target systems. We combined this scheme with DIRECT sampling to develop a reliable moment tensor potential for titanium hydrides without the need for iterative augmentation of training structures. This work paves the way for robust high-throughput development of MLIPs across any compositional complexity.
Semi-empirical quantum models such as Density Functional Tight Binding (DFTB) are attractive methods for obtaining quantum simulation data at longer time and length scales than possible with standard approaches. However, application of these models can require lengthy effort due to the lack of a systematic approach for their development. In this work, we discuss the use of the Chebyshev Interaction Model for Efficient Simulation (ChIMES) to create rapidly parameterized DFTB models, which exhibit strong transferability due to the inclusion of many-body interactions that might otherwise be inaccurate. We apply our modeling approach to silicon polymorphs and review previous work on titanium hydride. We also review the creation of a general purpose DFTB/ChIMES model for organic molecules and compounds that approaches hybrid functional and coupled cluster accuracy with two orders of magnitude fewer parameters than similar neural network approaches. In all cases, DFTB/ChIMES yields similar accuracy to the underlying quantum method with orders of magnitude improvement in computational cost. In conclusion, our developments provide a way to create computationally efficient and highly accurate simulations over varying extreme thermodynamic conditions, where physical and chemical properties can be difficult to interrogate directly, and there is historically a significant reliance on theoretical approaches for interpretation and validation of experimental results.
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Extended abstract for M&M2022. In this research, we employ state-of-the-art methods to unveil some of the mechanisms behind hydride formation and deformation to understand the hydrogen embrittlement of α-Ti alloys.
Light harvesting, separation of charge carriers, and surface reactions are three fundamental steps that are essential for an efficient photocatalyst. Here we show that these steps in the TiO 2 can be boosted simultaneously by disorder engineering. A solid-state reduction reaction between sodium and TiO 2 forms a core-shell c-TiO 2 @a-TiO 2-x (OH) y heterostructure, comprised of HO-Ti-[O]-Ti surface frustrated Lewis pairs (SFLPs) embedded in an amorphous shell surrounding a crystalline core, which enables a new genre of chemical reactivity. Specifically, these SFLPs heterolytically dissociate dihydrogen at room temperature to form charge-balancing protonated hydroxyl groups and hydrides at unsaturated titanium surface sites, which display high reactivity towards CO 2 reduction. This crystalline-amorphous heterostructure also boosts light absorption, charge carrier separation and transfer to SFLPs, while prolonged carrier lifetimes and photothermal heat generation further enhance reactivity. The collective results of this study motivate a general approach for catalytically generating sustainable chemicals and fuels through engineered disorder in heterogeneous CO 2 photocatalysts.
Abstract not provided.