Liquid Crystal Display (LCD) masking is a 3D printing technique that can produce soft magnetic composite parts to high resolution and complexity for robotics and energy electronics applications. This additive manufacturing technique has the potential to produce larger, lighter-weight, more efficient, and more durable parts for automotive and mechanical applications. This study conducted a binder study to create a low-viscosity and stiff binder capable of loading at least 60 v/v% Fe-6.5 wt%Si particles. Percolation Theory was applied to anticipate the magnetic interaction of suspended particles. A series of binders were formulated, with adjustments to diluent ratios. The behavior of the binders was assessed by studying their rheological properties, conversion rates, and mechanical properties. A post-cure study was conducted across various energy settings using UV, thermal, and a combination of both energy sources to find the combination that provided the best mechanical properties. As a result, 64 v/v% Fe-6.5 wt%Si loading was achieved and cured using UV light of 405 nm wavelength. Vibrating Sample Spectroscopy (VSM) was used to characterize the composite’s magnetic behavior, and a significant increase in saturation magnetization and negligible change in coercivity was observed when the added load exceeded the percolation threshold.

Vat photopolymerization (VPP) is an additive manufacturing method that requires the design of photocurable resins to act as feedstock and binder for the printing of parts, both monolithic and composite. The design of a suitable photoresin is costly and time-consuming. The development of one formulation requires the consumption of kilograms of costly materials, weeks of printing and performance testing, as well as the need to have developers with the expertise and knowledge of the materials used, making the development process cost thousands. This paper presents a new characterization methodology for acrylates that allows for the computerization of the photoresin formulation development process, reducing the timescale to less than a week. Okoruwa Maximum Saturation Potential (OMSP) is a methodology that uses attenuated total reflection (ATR-FTIR) to study the functional group of acrylates, assigning numerical outputs to characterize monomers, oligomers and formulations, allowing for more precise distinguishment between materials. It utilizes the principles of Gaussian normal distribution for the storage, recall, and computerization of acrylate data and formulation design without the need to database numerous files of spectral data to an average coefficient of determination (R²) of 0.97. The same characterization method can be used to define the potential reactivity of acrylate formulations without knowing the formulation components, something not possible when using properties such as functionality. This allows for modifications to be made to unknown formulations without prior knowledge of their contents. Validation studies were performed to define the boundaries of the operation of OMSP and assess the methodology’s reliability as a characterization tool. OMSP can confidently detect changes caused by the presence of various acrylates made to the photoresin system and distinguish between acrylates of the same viscosity and functionality. OMSP can compare digitally mixed formulations to physically mixed formulations and provides a high degree of accuracy (R² of 0.9406 to 0.9964), highlighting the future potential for building foundations for artificial intelligence in VPP; the streamlining of photoresin formulation design; and transforming the way acrylates are characterized, selected, and used.