Abstract: An article that includes a substrate; a first layer including yttria and zirconia or hafnia, where the first layer has a columnar microstructure and includes predominately the zirconia or hafnia; a second layer on the first layer, the second layer including zirconia or hafnia, ytterbia, samaria, and at least one of lutetia, scandia, ceria, neodymia, europia, and gadolinia, where the second layer includes predominately zirconia or hafnia, and where the second layer has a columnar microstructure; and a third layer on the second layer, the third layer including zirconia or hafnia, ytterbia, samaria, and a rare earth oxide including at least one of lutetia, scandia, ceria, neodymia, europia, and gadolinia, where the third layer has a dense microstructure and has a lower porosity than the second layer.

Abstract: In some examples, an article may include a substrate and a coating system on the substrate. The coating system may include a layer comprising a plurality of voids, wherein respective voids of the plurality of voids define respective void volumes; and a nucleating agent within at least some of the respective void volumes of the layer, wherein the nucleating agent is configured to induce crystallization of the molten CMAS. The coating system may include an environmental barrier coating, thermal barrier coating, and/or abradable coating.

Abstract: An example system includes at least one acoustic sensor and one optical sensor to monitor a thermal spray system controlled by a plurality of control parameters and performing a process associated with a plurality of process outputs. The system includes a computing device including a machine learning module and a control module. The machine learning module is configured to determine, based on at least the plurality of control parameters, an at least one time-dependent acoustic data signal, an at least one image data signal, and the plurality of process outputs, a relationship between the plurality of control parameters and the plurality of process outputs by machine learning. The control module is configured to control the thermal spray system to adjust the plurality of process outputs toward a plurality of respective operating ranges.

Abstract: An article that includes a substrate; a first layer including yttria and zirconia or hafnia, where the first layer has a columnar microstructure and includes predominately the zirconia or hafnia; a second layer on the first layer, the second layer including zirconia or hafnia, ytterbia, samaria, and at least one of lutetia, scandia, ceria, neodymia, europia, and gadolinia, where the second layer includes predominately zirconia or hafnia, and where the second layer has a columnar microstructure; and a third layer on the second layer, the third layer including zirconia or hafnia, ytterbia, samaria, and a rare earth oxide including at least one of lutetia, scandia, ceria, neodymia, europia, and gadolinia, where the third layer has a dense microstructure and has a lower porosity than the second layer.

Abstract: An example system includes at least one acoustic sensor configured to generate at least one time-dependent acoustic data signal indicative of an acoustic signal generated by a thermal spray system performing a process possessing a plurality of process attributes, and a computing device including an acoustic data signal processing module configured to receive the at least one time-dependent acoustic data signal, and transform the at least one time-dependent acoustic data signal to a frequency-domain spectrum, wherein each process attribute of the plurality of process attributes is associated with at least one respective frequency band, and a correlation module configured to determine a process attribute of the plurality of process attributes by identifying at least one characteristic of the frequency-domain spectrum.

Abstract: An example system includes at least one acoustic sensor configured to generate at least one time-dependent acoustic data signal indicative of an acoustic signal generated by a thermal spray system performing a process associated with a plurality of process attributes. The example system includes a computing device including an acoustic data signal module and a control module. The acoustic data signal processing module may transform the at least one time-dependent acoustic data signal to a frequency-domain spectrum. The control module may determine a process attribute of the plurality of process attributes that deviates from a predetermined operating range by identifying at least one characteristic of the frequency-domain spectrum, selecting at least one component of the thermal spray system based on the process attribute, and controlling the thermal spray system to adjust the process attribute toward the predetermined operating range by sending a control signal to the at least one component.

Abstract: An article having a substrate that includes a ceramic or a ceramic matrix composite, a bond layer on the substrate that includes silicon metal and a boria stabilizing agent, and at least one additional layer on the bond layer.

Abstract: An article may include a substrate including a metal or alloy; a bond coat directly on the substrate; an intermediate ceramic layer on the bond coat; and an abradable ceramic layer directly on the intermediate ceramic layer. The intermediate ceramic layer includes a stabilized tetragonal prime phase constitution and defines a first porosity. The abradable ceramic layer includes zirconia or hafnia stabilized in the tetragonal prime phase by a second mixture including between about 5 wt. % and about 10 wt. % ytterbia, between about 0.5 wt. % and about 2.5 wt. % samaria, and between about 1 wt. % and about 4 wt. % of at least one of lutetia, scandia, ceria, neodymia, europia, or gadolinia, and a balance zirconia or hafnia. The abradable ceramic layer defines a second porosity, and the second porosity is higher than the first porosity.

Abstract: An example system includes at least one acoustic sensor and one optical sensor to monitor a thermal spray system controlled by a plurality of control parameters and performing a process associated with a plurality of process outputs. The system includes a computing device including a machine learning module and a control module. The machine learning module is configured to determine, based on at least the plurality of control parameters, an at least one time-dependent acoustic data signal, an at least one image data signal, and the plurality of process outputs, a relationship between the plurality of control parameters and the plurality of process outputs by machine learning. The control module is configured to control the thermal spray system to adjust the plurality of process outputs toward a plurality of respective operating ranges.

Abstract: In some examples, an article may include a substrate and a coating system on the substrate. The coating system may include a layer comprising a plurality of voids, wherein respective voids of the plurality of voids define respective void volumes; and a nucleating agent within at least some of the respective void volumes of the layer, wherein the nucleating agent is configured to induce crystallization of the molten CMAS. The coating system may include an environmental barrier coating, thermal barrier coating, and/or abradable coating.

Abstract: A characteristic of a component having an engineered internal space can be analyzed by recording acoustic signals produced by fluid flow through the internal space at controlled flow rates, and determining one or more acoustic frequencies and acoustic intensities that are indicative of the characteristic of the component. A state and/or a source of the component can be predicted based on the results of such analysis.

Abstract: An article may include a substrate including a ceramic or a CMC; a bond layer on the substrate; and a diffusion barrier layer between the substrate and the bond layer. The diffusion barrier layer may include at least one of molybdenum metal, tantalum metal, tungsten metal, or niobium metal. In some examples, the article may include a stabilizing layer that includes at least one of a silicide of molybdenum (MoSi2), tantalum (TaSi2), tungsten (WSi2), or niobium (NbSi2), between the diffusion barrier layer and the bond layer.

Abstract: An example system includes at least one acoustic sensor configured to generate at least one acoustic data signal indicative of an acoustic signal generated by a thermal spray system comprising a flowstream, a computing device, and an acoustic data signal processing module operable by the computing device to determine an ignition attribute of the thermal spray system by analyzing at least a pre-ignition window of the acoustic data signal received by the computing device.

Abstract: An article that includes a substrate; a first layer including yttria and zirconia or hafnia, where the first layer has a columnar microstructure and includes predominately the zirconia or hafnia; a second layer on the first layer, the second layer including zirconia or hafnia, ytterbia, samaria, and at least one of lutetia, scandia, ceria, neodymia, europia, and gadolinia, where the second layer includes predominately zirconia or hafnia, and where the second layer has a columnar microstructure; and a third layer on the second layer, the third layer including zirconia or hafnia, ytterbia, samaria, and a rare earth oxide including at least one of lutetia, scandia, ceria, neodymia, europia, and gadolinia, where the third layer has a dense microstructure and has a lower porosity than the second layer.

Abstract: An article having a substrate that includes a ceramic or a ceramic matrix composite, a bond layer on the substrate that includes silicon metal and a boria stabilizing agent, and at least one additional layer on the bond layer.

Abstract: In some examples, an article includes a substrate and a coating on the substrate. The coating includes a stabilized microstructure including Magnéli oxide phase including an oxide of at least one of W, Mo, Nb, Ta, or Re. In some examples, a technique may include forming a coating including a refractory metal on a surface of a substrate. The technique also may include heat treating the coating at a temperature between about 500° C. and about 700° C. to form a coating including a stabilized microstructure including Magnéli oxide phase. The stabilized microstructure including Magnéli oxide phase may include an oxide of at least one of W, Mo, Nb, Ta, or Re. In some examples, the coating including the stabilized microstructure including Magnéli oxide phase exhibits a coefficient of friction that is at least 25% less than the coefficient of friction exhibited by the as-deposited coating under similar conditions.

Abstract: An example system includes at least one acoustic sensor configured to generate at least one time-dependent acoustic data signal indicative of an acoustic signal generated by a thermal spray system performing a process associated with a plurality of process attributes. The example system includes a computing device including an acoustic data signal module and a control module. The acoustic data signal processing module may transform the at least one time-dependent acoustic data signal to a frequency-domain spectrum. The control module may determine a process attribute of the plurality of process attributes that deviates from a predetermined operating range by identifying at least one characteristic of the frequency-domain spectrum, selecting at least one component of the thermal spray system based on the process attribute, and controlling the thermal spray system to adjust the process attribute toward the predetermined operating range by sending a control signal to the at least one component.

Abstract: An example system includes at least one acoustic sensor configured to generate at least one acoustic data signal indicative of an acoustic signal generated by a thermal spray system comprising a flowstream, a computing device, and an acoustic data signal processing module operable by the computing device to determine an ignition attribute of the thermal spray system by analyzing at least a pre-ignition window of the acoustic data signal received by the computing device.

Abstract: An example system includes at least one acoustic sensor configured to generate at least one time-dependent acoustic data signal indicative of an acoustic signal generated by a thermal spray system performing a process possessing a plurality of process attributes, and a computing device including an acoustic data signal processing module configured to receive the at least one time-dependent acoustic data signal, and transform the at least one time-dependent acoustic data signal to a frequency-domain spectrum, wherein each process attribute of the plurality of process attributes is associated with at least one respective frequency band, and a correlation module configured to determine a process attribute of the plurality of process attributes by identifying at least one characteristic of the frequency-domain spectrum.

Abstract: An article may include a substrate including a ceramic or a CMC; a bond layer on the substrate; and a diffusion barrier layer between the substrate and the bond layer. The diffusion barrier layer may include at least one of molybdenum metal, tantalum metal, tungsten metal, or niobium metal. In some examples, the article may include a stabilizing layer that includes at least one of a silicide of molybdenum (MoSi2), tantalum (TaSi2), tungsten (WSi2), or niobium (NbSi2), between the diffusion barrier layer and the bond layer.