Gemini: Engaging Experiential and Feature Scales Through Multimaterial Digital Design and Hybrid Additive–Subtractive Fabrication

Gemini is a chaise lounge constructed using hybrid fabrication involving 3D printing of a textured polymeric skin combined with CNC milling of a wooden chassis. The texture of the chaise was inspired by the seed geometry of the Ornithogalum dubium flower and designed using a computational implementation of an inhomogeneous Poisson process. The 3D-printed texture was informed by the weight distribution of a person with the goal of delivering structural support and comfort on the one hand and maximizing the absorption of sound emanating from exterior sources of noise on the other. Gemini is the first functional object produced using the Stratasys Objet500 Connex3 color multimaterial 3D printer including the Tango+ soft material. It represents one of the first cases of a hybrid additive–subtractive manufacturing approach, which combines the strength of both of these techniques

Magnetostatic field noise near metallic surfaces

We develop an effective low-frequency theory of the electromagnetic field in equilibrium with thermal objects. The aim is to compute thermal magnetic noise spectra close to metallic microstructures. We focus on the limit where the material response is characterized by the electric conductivity. At the boundary between empty space and metallic microstructures, a large jump occurs in the dielectric function which leads to a partial screening of low-frequency magnetic fields generated by thermal current fluctuations. We resolve a discrepancy between two approaches used in the past to compute magnetic field noise spectra close to microstructured materials.Comment: 9 pages, 1 figure, EPJ D style, accepted in Topical Issue on "Atom Chips

On learning discontinuous dependencies from positive data

International audienceThis paper is concerned with learning in the model of Gold the Categorial Dependency Grammars (CDG), which express discontin- uous (non-projective) dependencies. We show that rigid and k-valued CDG (without optional and iterative types) are learnable from strings. In fact, we prove that the languages of dependency nets coding rigid CDGs have finite elasticity, and we show a learning algorithm. As a standard corollary, this result leads to the learnability of rigid or k- valued CDGs (without optional and iterative types) from strings

Magnetic interactions of cold atoms with anisotropic conductors

We analyze atom-surface magnetic interactions on atom chips where the magnetic trapping potentials are produced by current carrying wires made of electrically anisotropic materials. We discuss a theory for time dependent fluctuations of the magnetic potential, arising from thermal noise originating from the surface. It is shown that using materials with a large electrical anisotropy results in a considerable reduction of heating and decoherence rates of ultra-cold atoms trapped near the surface, of up to several orders of magnitude. The trap loss rate due to spin flips is expected to be significantly reduced upon cooling the surface to low temperatures. In addition, the electrical anisotropy significantly suppresses the amplitude of static spatial potential corrugations due to current scattering within imperfect wires. Also the shape of the corrugation pattern depends on the electrical anisotropy: the preferred angle of the scattered current wave fronts can be varied over a wide range. Materials, fabrication, and experimental issues are discussed, and specific candidate materials are suggested.Comment: Selected as a Highlight paper in the European Physical Journal

Reduction of Magnetic Noise in Atom Chips by Material Optimization

We discuss the contribution of the material type in metal wires to the electromagnetic fluctuations in magnetic microtraps close to the surface of an atom chip. We show that significant reduction of the magnetic noise can be achieved by replacing the pure noble metal wires with their dilute alloys. The alloy composition provides an additional degree of freedom which enables a controlled reduction of both magnetic noise and resistivity if the atom chip is cooled. In addition, we provide a careful re-analysis of the magnetically induced trap loss observed by Yu-Ju Lin et al. [Phys. Rev. Lett. 92, 050404 (2004)] and find good agreement with an improved theory.Comment: 25 pages with 9 figures ep

Grown, Printed, and Biologically Augmented: An Additively Manufactured Microfluidic Wearable, Functionally Templated for Synthetic Microbes

Despite significant advances in synthetic biology at industrial scales, digital fabrication challenges have, to date, precluded its implementation at the product scale. We present, Mushtari, a multimaterial 3D printed fluidic wearable designed to culture microbial communities. Thereby we introduce a computational design environment for additive manufacturing of geometrically complex and materially heterogeneous fluidic channels. We demonstrate how controlled variation of geometrical and optical properties at high spatial resolution can be achieved through a combination of computational growth modeling and multimaterial bitmap printing. Furthermore, we present the implementation, characterization, and evaluation of support methods for creating product-scale fluidics. Finally, we explore the cytotoxicity of 3D printed materials in culture studies with the model microorganisms, Escherichia coli and Bacillus subtilis. The results point toward design possibilities that lie at the intersection of computational design, additive manufacturing, and synthetic biology, with the ultimate goal of imparting biological functionality to 3D printed products.National Science Foundation (U.S.) (DGE1144152)United States. Department of Energy (DE-SC0012658

Active Printed Materials for Complex Self-Evolving Deformations

We propose a new design of complex self-evolving structures that vary over time due to environmental interaction. In conventional 3D printing systems, materials are meant to be stable rather than active and fabricated models are designed and printed as static objects. Here, we introduce a novel approach for simulating and fabricating self-evolving structures that transform into a predetermined shape, changing property and function after fabrication. The new locally coordinated bending primitives combine into a single system, allowing for a global deformation which can stretch, fold and bend given environmental stimulus

Addressing the structural sophistication of meat via plant-based tissue engineering

The escalating environmental impact of traditional livestock farming, particularly beef production, has spurred the search for sustainable meat alternatives. This study introduces a novel Plant-Based Tissue Engineering (PBTE) approach, to replicate the complex structure and sensory experience of whole-muscle cuts of meat using plant-based ingredients. Leveraging principles of tissue engineering and advanced food manufacturing technologies, PBTE deconstructs meat into its fundamental components: muscle, fat, and connective tissue, and reconstructs them using a combination of plant proteins, fats and polysaccharide materials. The muscle component is reassembled to mimic the anisotropic fibrous structure of beef, while the fat component is engineered through lipid encapsulation within a hydrocolloid matrix. Advanced manufacturing techniques, including additive manufacturing and robotics, are utilized for precise spatial configuration and assembly of these components. Our findings demonstrate that PBTE can effectively replicate the mechanical integrity, texture, and sensory attributes of traditional meat, presenting a promising alternative that could significantly reduce the environmental footprint of meat production. This approach aligns with the principles of Soft Matter in the manipulation of artificial structures and materials for mimicking naturally occurring designs, such as whole cut meat foods. It also holds substantial potential for revolutionizing the alternative protein industry by catering to a broader consumer base, including flexitarians and meat-eaters