Abstract: Systems and methods for prediction of state of charge (SOH), state of health (SOC) and other characteristics of batteries using acoustic signals, includes determining acoustic data at two or more states of charge and determining a reduced acoustic data set representative of the acoustic data at the two or more states of charge. The reduced acoustic data set includes time of flight (TOF) shift, total signal amplitude, or other data points related to the states of charge. Machine learning models use at least the reduced acoustic dataset in conjunction with non-acoustic data such as voltage and temperature for predicting the characteristics of any other independent battery.

Abstract: Systems and methods for prediction of state of charge (SOH), state of health (SOC) and other characteristics of batteries using acoustic signals, includes determining acoustic data at two or more states of charge and determining a reduced acoustic data set representative of the acoustic data at the two or more states of charge. The reduced acoustic data set includes time of flight (TOF) shift, total signal amplitude, or other data points related to the states of charge. Machine learning models use at least the reduced acoustic dataset in conjunction with non-acoustic data such as voltage and temperature for predicting the characteristics of any other independent battery.

Abstract: This disclosure provides a system and method for producing ultrasound images based on Full Waveform Inversion (FWI). The system captures acoustic/(an)elastic waves transmitted through and reflected and/or diffracted from a medium. The system performs an FWI process in a time domain in conjunction with an accurate wave propagation solver. The system produces 3D maps of physical parameters that control wave propagation, such as shear and compressional wavespeeds, mass density, attenuation, Poisson's ratio, bulk and shear moduli, impedance, and even the fourth-order elastic tensor containing up to 21 independent parameters, which are of significant diagnostic value, e.g., for medical imaging and non-destructive testing.

Abstract: The invention provides an electrolyte composition which is adapted for use in a rechargeable alkaline electrochemical cell, and especially preferably adapted for use in a rechargeable manganese zinc electrochemical cell, which electrolyte composition imparts improved performance characteristics to the rechargeable alkaline electrochemical cell. The electrolyte composition includes an electrolyte composition in which contains a potassium hydroxide and lithium hydroxide in a concentration and a respective molar ratio of about 1 molar potassium hydroxide to 2.5-3.7 (preferably 1:3) molar lithium hydroxide (1 M KOH:2.5-3.7 M LiOH). Also provided are alkaline electrochemical cells and alkaline batteries comprising the electrolyte compositions. The resultant alkaline electrochemical cells and alkaline batteries exhibit improved performance characteristics, as the electrolyte composition significantly inhibits the passivation of Zn, and may also be useful in this role in other battery chemistries.

Abstract: Systems and methods for prediction of state of charge (SOH), state of health (SOC) and other characteristics of batteries using acoustic signals, includes determining acoustic data at two or more states of charge and determining a reduced acoustic data set representative of the acoustic data at the two or more states of charge. The reduced acoustic data set includes time of flight (TOF) shift, total signal amplitude, or other data points related to the states of charge. Machine learning models use at least the reduced acoustic dataset in conjunction with non-acoustic data such as voltage and temperature for predicting the characteristics of any other independent battery.

Abstract: The invention provides an electrolyte composition which is adapted for use in a rechargeable alkaline electrochemical cell, and especially preferably adapted for use in a rechargeable manganese zinc electrochemical cell, which electrolyte composition imparts improved performance characteristics to the rechargeable alkaline electrochemical cell. The electrolyte composition includes an electrolyte composition in which contains a potassium hydroxide and lithium hydroxide in a concentration and a respective molar ratio of about 1 molar potassium hydroxide to 2.5-3.7 (preferably 1:3) molar lithium hydroxide (1 M KOH:2.5-3.7 M LiOH). Also provided are alkaline electrochemical cells and alkaline batteries comprising the electrolyte compositions. The resultant alkaline electrochemical cells and alkaline batteries exhibit improved performance characteristics, as the electrolyte composition significantly inhibits the passivation of Zn, and may also be useful in this role in other battery chemistries.

Abstract: Disclosed are hyper-dendritic nanoporous zinc foam electrodes, viz., anodes, methods of producing the same, and methods for their use in electrochemical cells, especially in rechargeable electrical batteries.

Abstract: Disclosed are hyper-dendritic nanoporous zinc foam electrodes, viz., anodes, methods of producing the same, and methods for their use in electrochemical cells, especially in rechargeable electrical batteries.

Abstract: An exhaust brake for an internal combustion engine is disclosed. The exhaust brake includes a main valve and a bypass valve for restricting the flow of exhaust gas. The main valve may be selectively closed, while the bypass valve is biased into a closed position with a selective biasing force. Closing the main valve may cause exhaust back pressure to build against the bypass valve until the biasing force is overcome. When the biasing force is surpassed by the exhaust back pressure, the bypass valve opens to relieve the back pressure. The bypass valve closes when back pressure falls below the biasing force. The biasing force may be varied to operate the exhaust brake at a maximum back pressure for a given engine speed and/or engine condition. A method of operating the exhaust brake is also disclosed.