between 2010 and 2040.[ 1 ] Sustainability is critical because current affordable energy, mainly from fossil fuels, is being rapidly depleted, while world demand increases. Even if the supply were unlimited, the use of fossil fuels is accompanied by environmental problems, such as pollution and the greenhouse effect. [ 2 ] Efforts to harness sustainable energy from solar, wind, nuclear, and other sources have shown promise, but cost and effi ciency remain signifi cant challenges to widespread adoption. Approximately 60% of all energy produced is wasted as heat, [ 3 ] which has driven the development of thermoelectric (TE) materials over the past two decades. [ 4 ] Heat is an abundant energy supply that can be harvested from a multitude of sources (engines, human body, etc.) with no moving parts. The TE performance is directly related to a dimensionless fi gureof-merit ( ZT = S 2 σ T κ −1 ), where S is the Seebeck coeffi cient, σ is the electrical conductivity, and κ is the thermal conductivity at a given temperature T . It is clear that a large σ and S , with a small κ , are desired to achieve high effi ciency ( ZT ≈ 1 corresponds to 4%-5% conversion effi ciency), [ 5 ] but there is a well-known confl ict among the three parameters that imposes limitations on traditional thermoelectric semiconductor development. [ 6 ] The best inorganic TE materials have achieved a ZT > 2, [ 7 ] but it should be noted that this value is measured at temperatures >600 K. The ZT of these materials at room temperature is <0.5, with a power factor (PF) <400 µW m −1 K −2 . These best commercially available materials are bismuth telluride-based alloys that are expensive and plagued by scarcity and toxicity concerns. Additionally, TE materials would need a ZT ≥ 3 to be effi cient enough to enter the power generation fi eld, making them commercially viable for more than niche applications. [ 8 ] Alternatively, low cost and lightweight materials that are printable (or paintable) could be useful even with relatively low conversion effi ciency.More recently, size effects in nanostructured systems such as nanowires, [ 9 ] quantum dots, [ 10 ] superlattices, [ 11 ] and a wide variety of composites with irregular nanosized inclusions have led to signifi cant improvements in thermoelectric efficiency over traditional bulk semiconductors. [ 12,13 ] For instance,In an effort to create a paintable/printable thermoelectric material, comprised exclusively of organic components, polyaniline (PANi), graphene, and double-walled nanotube (DWNT) are alternately deposited from aqueous solutions using the layer-by-layer assembly technique. Graphene and DWNT are stabilized with an intrinsically conductive polymer, poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS). An 80 quadlayer thin fi lm (≈1 µm thick), comprised of a PANi/graphene-PEDOT:PSS/PANi/DWNT-PEDOT:PSS repeating sequence, exhibits unprecedented electrical conductivity ( σ ≈ 1.9 × 10 5 S m −1 ) and Seebeck coeffi cient ( S ≈ 120 µV K −1 ) for a completely organic material. These t...

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Passive-dynamic ankle-foot orthosis (PD-AFO) bending stiffness is a key functional characteristic for achieving enhanced gait function. However, current orthosis customization methods inhibit objective premanufacture tuning of the PD-AFO bending stiffness, making optimization of orthosis function challenging. We have developed a novel virtual functional prototyping (VFP) process, which harnesses the strengths of computer aided design (CAD) model parameterization and finite element analysis, to quantitatively tune and predict the functional characteristics of a PD-AFO, which is rapidly manufactured via fused deposition modeling (FDM). The purpose of this study was to assess the VFP process for PD-AFO bending stiffness. A PD-AFO CAD model was customized for a healthy subject and tuned to four bending stiffness values via VFP. Two sets of each tuned model were fabricated via FDM using medical-grade polycarbonate (PC-ISO). Dimensional accuracy of the fabricated orthoses was excellent (average 0.51 ± 0.39 mm). Manufacturing precision ranged from 0.0 to 0.74 Nm/deg (average 0.30 ± 0.36 Nm/deg). Bending stiffness prediction accuracy was within 1 Nm/deg using the manufacturer provided PC-ISO elastic modulus (average 0.48 ± 0.35 Nm/deg). Using an experimentally derived PC-ISO elastic modulus improved the optimized bending stiffness prediction accuracy (average 0.29 ± 0.57 Nm/deg). Robustness of the derived modulus was tested by carrying out the VFP process for a disparate subject, tuning the PD-AFO model to five bending stiffness values. For this disparate subject, bending stiffness prediction accuracy was strong (average 0.20 ± 0.14 Nm/deg). Overall, the VFP process had excellent dimensional accuracy, good manufacturing precision, and strong prediction accuracy with the derived modulus. Implementing VFP as part of our PD-AFO customization and manufacturing framework, which also includes fit customization, provides a novel and powerful method to predictably tune and precisely manufacture orthoses with objectively customized fit and functional characteristics.

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