Abstract: A method for optimising battery design comprising receiving one or more battery performance targets indicating design constraints on one or more battery performance characteristics, applying one or more trained machine learning models to search and determine one or more optimal battery designs. The machine learning model(s) adapted to replace one or more replace complex computing intensive battery design physical/mechanical models for creating a plurality of battery designs complying with the design constraint(s) and compute their performance scores are trained to learn the physical/mechanical model(s), created using experimental data collected for a plurality of batteries, using a plurality of training samples extracted from simulations of the physical/mechanical model(s).

Abstract: The invention provides a device and a method for manufacturing 3D metal structures by a sequence of electroplating steps, each step adding a cross-section layer of the 3D structure via anodes, selected from a planar 2D anode grid array and forming a pattern template, creating a deposition image on a cathode plate.

Abstract: The application discloses a method of liquid cold welding (LCW) including: (a) engaging two or more porous conductive substrate layers between perforated non-conductive frames so that the substrate layers contact one another; (b) immersing the substrate layers in an electrolyte solution; and (c) applying electric current and/or voltage and/or electric power to the electrolyte solution. Apparatus suitable for performance of some embodiments of the method are also disclosed.