Spectral printing of paintings using a seven-color digital press

The human visual system is trichromatic and therefore reduces higher dimensional spectral data to three dimensions. Two stimuli with different spectral power curve shapes can result in the same cone response and therefore match each other. Color reproduction systems take advantage of this effect and match color by creating the same cone response as the original but with different colorants. ICC color management transforms all colors into a three-dimensional reference color space, which is independent from any input or output devices. This concept works well for a single defined observer and illumination conditions, but in practice, it is not possible to control viewing conditions leading to severe color mismatches, particularly for paintings. Paintings pose unique challenges because of the large variety of available colorants resulting in a very large color gamut and considerable spectral variability. This research explored spectral color reproduction using a seven-color electrophotographic printing process, the HP Indigo 7000. Because of the restriction to seven inks from the 12 basic inks supplied with the press, the research identified both the optimal seven inks and a set of eight artist paints which can be spectrally reproduced. The set of inks was Cyan, Magenta, Yellow, Black, Reflex Blue, Violet and Orange. The eight paints were Cadmium Red Medium, Cadmium Orange, Cadmium Yellow Light, Dioxazine Purple, Phthalo Blue Green Shade, Ultramarine Blue, Quinacridone Crimson and Carbon Black. The selection was based on both theoretical and experimental analyses. The final testing was computational indicating the possibility of both spectral and colorimetric color reproduction of paintings

Development of wearable, screen-printable conductive polymer biosensors on flexible and textile substrates

Wearable biosensors have great potential for real-time diagnostics, but have been encumbered by costly fabrication processes, rigid materials, and inadequate sensitivity for physiological ranges. Sweat has hitherto been an understudied sample for measurement of components like pH and lactate, which can provide meaningful guidance for wound healing, eczema, and sports medicine applications. This thesis presents the development of a flexible, textile-based, screen-printed electrode system for biosensing applications. Furthermore, a flexible, pH-sensitive composite for textile substrates is developed by mixing polyaniline with dodecylbenzene sulfonic acid and textile screen-printing ink. The optimized composite’s pH response is compared to electropolymerized and drop-cast polyaniline sensors via open circuit potential measurements. A linear response is observed for all sensors between pH 3-10, with the composite demonstrating sufficient response time and a sensitivity better than -20 mV/pH, exceeding existing flexible screen-printed pH sensors. Investigations into a potentiometric, non-enzymatic lactate sensor using polyaminophenylboronic acid are also discussed

Clustering via kernel decomposition

Spectral clustering methods were proposed recently which rely on the eigenvalue decomposition of an affinity matrix. In this letter, the affinity matrix is created from the elements of a nonparametric density estimator and then decomposed to obtain posterior probabilities of class membership. Hyperparameters are selected using standard cross-validation methods

Spectrally stable ink variability in a multi-primary printer

It was shown previously that a multi-ink printer can reproduce spectral reflectances within a specified tolerance range using many distinct ink combinations. An algorithm was developed to systematically analyze a printer to determine the amount of multi-ink variability throughout its spectral gamut. The advantage of this algorithm is that any spectral difference metric can be used as the objective function. Based on the results of the analysis for one spectral difference metric, six-dimensional density map displays were constructed to illustrate the amount of spectral redundancy throughout the ink space. One CMYKGO ink-jet printer was analyzed using spectral reflectance factor RMS as the spectral difference metric and selecting 0.02 RMS as the tolerance limit. For these parameters, the degree of spectral matching freedom for the printer reduced to five inks because the chromatic inks were able to reproduce spectra within the 0.02 tolerance limit throughout the printer\u27s gamut. Experiments were designed to exploit spectrally stable multi-ink variability within the analyzed printer. The first experiment used spectral redundancy to visually evaluate spectral difference metrics. Using the developed database of spectrally similar samples allows any spectral difference metric to be compared to a visual response. The second experiment demonstrated the impact of spectral redundancy on spectral color management. Typical color image processing techniques use profiles consisting of sparse multi-dimensional lookup tables that interpolate between adjacent nodes to prepare an image for rendering. It was shown that colorimetric error resulted when interpolating between lookup table nodes that were inconsistent in digital count space although spectrally similar. Finally, the analysis was used to enable spectral watermarking of images. To illustrate the significance of this watermarking technique, information was embedded into three images with varying levels of complexity. Prints were made verifying that information could be hidden while preserving the visual and spectral integrity of the original image

Rapid model-guided design of organ-scale synthetic vasculature for biomanufacturing

Our ability to produce human-scale bio-manufactured organs is critically limited by the need for vascularization and perfusion. For tissues of variable size and shape, including arbitrarily complex geometries, designing and printing vasculature capable of adequate perfusion has posed a major hurdle. Here, we introduce a model-driven design pipeline combining accelerated optimization methods for fast synthetic vascular tree generation and computational hemodynamics models. We demonstrate rapid generation, simulation, and 3D printing of synthetic vasculature in complex geometries, from small tissue constructs to organ scale networks. We introduce key algorithmic advances that all together accelerate synthetic vascular generation by more than 230-fold compared to standard methods and enable their use in arbitrarily complex shapes through localized implicit functions. Furthermore, we provide techniques for joining vascular trees into watertight networks suitable for hemodynamic CFD and 3D fabrication. We demonstrate that organ-scale vascular network models can be generated in silico within minutes and can be used to perfuse engineered and anatomic models including a bioreactor, annulus, bi-ventricular heart, and gyrus. We further show that this flexible pipeline can be applied to two common modes of bioprinting with free-form reversible embedding of suspended hydrogels and writing into soft matter. Our synthetic vascular tree generation pipeline enables rapid, scalable vascular model generation and fluid analysis for bio-manufactured tissues necessary for future scale up and production.Comment: 58 pages (19 main and 39 supplement pages), 4 main figures, 9 supplement figure