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Computer-aided design (CAD) programs are essential to engineering as they allow for better designs through low-cost iterations. While CAD programs are typically taught to undergraduate students as a job skill, such software can also help students learn engineering concepts. A current limitation of CAD programs (even those that are specifically designed for educational purposes) is that they are not capable of providing automated real-time help to students. To encourage CAD programs to build in assistance to students, we used data generated from students using a free, open-source CAD software called Aladdin to demonstrate how student data combined with machine learning techniques can predict how well a particular student will perform in a design task. We challenged students to design a house that consumed zero net energy as part of an introductory engineering technology undergraduate course. Using data from 128 students, along with the scikit-learn Python machine learning library, we tested our models using both total counts of design actions and sequences of design actions as inputs. We found that our models using early design sequence actions are particularly valuable for prediction. Our logistic regression model achieved a >60% chance of predicting if a student would succeed in designing a zero net energy house. Our results suggest that it would be feasible for Aladdin to provide useful feedback to students when they are approximately halfway through their design. Further improvements to these models could lead to earlier predictions and thus provide students feedback sooner to enhance their learning. 

Soft actuators have been studied and analyzed as a new solution for soft robotic technologies. These types of actuators have many advantages due to their predictable deformations and their ease of control, enabling them to hold and move delicate objects performing complex movements in confined spaces. Soft actuators can be made using different manufacturing processes, but the most common is mold casting. However, this manufacturing process involves several steps, increasing the manufacturing time and hindering changes in the design. This paper presents a novel design of a 3D printed soft pneumatic actuator based on additive manufacturing, achieving design versatility and performance. The produced actuator has seven segments that can be individually controlled. The actuators were made using fused deposition modeling (FDM) technology in one continuous process and without support material. The mechanical performance of the soft actuators was demonstrated, analyzing the deformation in the z-axis based on input pressure. 

Additive manufacturing, commonly known as 3D printing, significantly simplifies the manufacturing process for soft electronics. This work demonstrates the feasibility of a fully 3D‐printed flexible poly(vinylidene fluoride) (PVdF) capacitive temperature sensor. The sensor is constructed using fused deposition modeling (FDM)‐printed PVdF film as the dielectric (thickness ≈180–280 μm) sandwiched between two parallel Direct Ink Writing (DIW) printed silver electrodes (entire device thickness ≈200–380 μm). The motion of the nozzle can facilitate mechanical drawing to the molten PVdF filament, which is a necessary condition to increase the β‐phase content (critical for the sensitivity of the sensor). With optimized printing parameters, the highest β‐phase content (21.30%) is achieved when printing with a nozzle temperature of 200 °C and a print speed of 70 mm s⁻¹. The research demonstrates the application of the device as a temperature sensor by applying heating‐and‐cooling cycles from room temperature (25 °C) up to 140 °C while measuring the capacitance as a function of frequency under different temperatures. The sensor exhibits a stable sensitivity of 3 pF °C⁻¹at 10² Hz and higher frequencies and improved sensitivities at frequencies higher than 10² Hz after dielectric polarization via the corona poling method.

 

Dielectric electroactive polymers (DEAPs) represent a subclass of smart materials that are capable of converting between electrical and mechanical energy. These materials can be used as energy harvesters, sensors, and actuators. However, current production and testing of these devices is limited and requires multiple step processes for fabrication. This paper presents an alternate production method via 3D printing using Thermoplastic Polyurethane (TPU) as a dielectric elastomer. This study provides electromechanical characterization of flexible dielectric films produced by additive manufacturing and demonstrates their use as DEAP actuators. The dielectric material characterization of TPU includes: measurement of the dielectric constant, percentage radial elongation, tensile properties, pre-strain effects on actuation, surface topography, and measured actuation under high voltage. The results demonstrated a high dielectric constant and ideal elongation performance for this material, making the material suitable for use as a DEAP actuator. In addition, it was experimentally determined that the tensile properties of the material depend on the printing angle and thickness of the samples thereby making these properties controllable using 3D printing. Using surface topography, it was possible to analyze how the printing path, affects the roughness of the films and consequently affects the voltage breakdown of the structure and creates preferential deformation directions. Actuators produced with concentric circle paths produced an area expansion of 4.73% uniformly in all directions. Actuators produced with line paths produced an area expansion of 5.71% in the direction where the printed lines are parallel to the deformation direction, and 4.91% in the direction where the printed lines are perpendicular to the deformation direction. 

Dielectric electroactive polymers are materials capable of mechanically adjusting their volume in response to an electrical stimulus. However, currently these materials require multi-step manufacturing processes which are not additive. This paper presents a novel 3D printed flexible dielectric material and characterizes its use as a dielectric electroactive polymer (DEAP) actuator. The 3D printed material was characterized electrically and mechanically and its functionality as a dielectric electroactive polymer actuator was demonstrated. The flexible 3-D printed material demonstrated a high dielectric constant and ideal stress-strain performance in tensile testing making the 3-D printed material ideal for use as a DEAP actuator. The tensile stress- strain properties were measured on samples printed under three different conditions (three printing angles 0°, 45° and 90°). The results demonstrated the flexible material presents different responses depending on the printing angle. Based on these results, it was possible to determine that the active structure needs low pre-strain to perform a visible contractive displacement when voltage is applied to the electrodes. The actuator produced an area expansion of 5.48% in response to a 4.3 kV applied voltage, with an initial pre-strain of 63.21% applied to the dielectric material.