Direct ink writing of vancomycin-loaded polycaprolactone/ polyethylene oxide/ hydroxyapatite 3D scaffolds

Novel inks were formulated by dissolving polycaprolactone (PCL), a hydrophobic polymer, in organic solvent systems; polyethylene oxide (PEO) was incorporated to extend the range of hydrophilicity of the system. Hydroxyapatite (HAp) with a weight ratio of 55–85% was added to the polymer-based solution to mimic the material composition of natural bone tissue. The direct ink writing (DIW) technique was applied to extrude the formulated inks to fabricate the predesigned tissue scaffold structures; the influence of HAp concentration was investigated. The results indicate that in comparison to other inks containing HAp (55%, 75%, and 85%w/w), the ink containing 65% w/w HAp had faster ink recovery behavior; the fabricated scaffold had a rougher surface as well as better mechanical properties and wettability. It is noted that the 65% w/w HAp concentration is similar to the inorganic composition of natural bone tissue. The elastic modulus values of PCL/PEO/HAp scaffolds were in the range of 4–12 MPa; the values were dependent on the HAp concentration. Furthermore, vancomycin as a model drug was successfully encapsulated in the PCL/PEO/HAp composite scaffold for drug release applications. This paper presents novel drug-loaded PCL/PEO/HAp inks for 3D scaffold fabrication using the DIW printing technique for potential bone scaffold applications.     

Automated prediction system of household energy consumption in cities using web crawler and optimized artificial intelligence

The supply of electrical energy is critical to convenient and comfortable living. However, people consume a large amount of energy, contributing to an energy crisis and global warming, and damaging some ecological cycles. Residential electricity consumption has greater elasticity than industrial and business consumption; it therefore has high energy-saving potential. This work establishes an automated platform, which provides information about residential electricity consumption in each city in Taiwan. Machine learning was used to forecast future residential electricity demand. A nature-inspired optimization method was applied to enhance the accuracy of the best machine learner, yielding an even better hybrid ensemble model. Performance measures indicate that the resulting model is accurate and provides effective information for reference. An automatic web-based system based on the model was combined with a web crawler and scheduled to run automatically to provide information on monthly residential electricity consumption in each county and city. By providing energy consumption information across the country, power providers and government can discuss policy and set different goals for energy use. The results of this study can facilitate the early implementation of energy-saving and carbon emission-reducing in cities and aid utility companies in establishing energy conservation guidelines.     

Fabrication of alumina ceramics with functional gradient structures by digital light processing 3D printing technology

Alumina ceramics with different unit numbers and gradient modes were prepared by digital light processing (DLP) 3D printing technology. The side length of each functional gradient structure was 10 mm, the porosity ratio was controlled to 70%, and the number of units were (1 × 1 × 1 unit) and (2 × 2 × 2 unit) respectively. The different gradient modes were named FCC, GFCC-1, GFCC-2 and GFCC-3. SEM, XRD, and other characterization methods proved that these gradient structures of alumina ceramics had only α-Al2O3 phase and good surface morphology. The mechanical properties and energy absorption properties of alumina ceramics with different functional gradient structures were studied by compression test. The results show that the gradient structure with 1 × 1 × 1 unit has better mechanical properties and energy absorption properties when the number of units is different. When the number of units is the same, GFCC-2 and GFCC-3 gradient structures have better compressive performance and energy absorption potential than FCC structures. The GFCC-2 gradient structure with 1 × 1 × 1 unit has a maximum compressive strength of 19.62 MPa and a maximum energy absorption value of 2.72 × 105 J/m3. The good performance of such functional gradient structures can provide new ideas for the design of lightweight and compressive energy absorption structures in the future.     

Additional deepwater sampling of prey fish in Lake Michigan annual bottom trawl survey reveals new insights for depth distribution dynamics

Beginning in 2013, sites at the 128-m bottom depth contour were added to the sampling design of the annual Lake Michigan bottom trawl survey for prey fish, which has been conducted by the U.S. Geological Survey Great Lakes Science Center (GLSC) each fall since 1973, to better assess fish depth distributions in a changing ecosystem. The standard sampling design included bottom depths from 9 to 110 m, although the GLSC also sporadically conducted bottom trawl tows at the 128-m bottom depth contour during 1973–1988. Enactment of this new sampling design in 2013 revealed that mean biomass density of deepwater sculpins (Myoxocephalus thompsonii) at the 128-m depth exceeded the sum of mean biomass densities at shallower depths, indicating that the bulk of the deepwater sculpin population is residing in waters deeper than 110 m. Thus, our findings supported the hypothesis that the depth distribution of the deepwater sculpin population had shifted to deeper waters beginning in 2007, thereby explaining, at least in part, the marked decline in deepwater sculpin abundance since 2006 based on the standard sampling design. In contrast, our results did not support the hypothesis that the slimy sculpin (Cottus cognatus) population had shifted to deeper waters sometime after 2000. A portion of the burbot (Lota lota) population may have also shifted in depth distribution to waters deeper than 110 m after 2007, based on our results. Our findings have served as an impetus to further expand the range of depths sampled in our bottom trawl survey.     

Modulation of electrical transport in calcium cobaltite ceramics and thick films through microstructure control and doping

Ca₃Co₄O₉ is a promising p-type thermoelectric oxide material having intrinsically low thermal conductivity. With low cost and opportunities for automatic large scale production, thick film technologies offer considerable potential for a new generation of micro-sized thermoelectric coolers or generators. Here, based on the chemical composition optimized by traditional solid state reaction for bulk samples, we present a viable approach to modulating the electrical transport properties of screen-printed calcium cobaltite thick films through control of the microstructural evolution by optimized heat-treatment. XRD and TEM analysis confirmed the formation of high-quality calcium cobaltite grains. By creating 2.0 at% cobalt deficiency in Ca_2.7Bi_0.3Co₄O_9+δ, the pressureless sintered ceramics reached the highest power factor of 98.0 μWm^?1 K^-2 at 823 K, through enhancement of electrical conductivity by reduction of poorly conducting secondary phases. Subsequently, textured thick films of Ca_2.7Bi_0.3Co_3.92O_9+δ were efficiently tailored by controlling the sintering temperature and holding time. Optimized Ca_2.7Bi_0.3Co_3.92O_9+δ thick films sintered at 1203 K for 8 h exhibited the maximum power factor of 55.5 μWm^?1 K^-2 at 673 K through microstructure control.     

Single Cell Bioprinting with Ultrashort Laser Pulses

Tissue engineering requires the precise positioning of mammalian cells and biomaterials on substrate surfaces or in preprocessed scaffolds. Although the development of 2D and 3D bioprinting technologies has made substantial progress in recent years, precise, cell-friendly, easy to use, and fast technologies for selecting and positioning mammalian cells with single cell precision are still in need. A new laser-based bioprinting approach is therefore presented, which allows the selection of individual cells from complex cell mixtures based on morphology or fluorescence and their transfer onto a 2D target substrate or a preprocessed 3D scaffold with single cell precision and high cell viability (93–99% cell survival, depending on cell type and substrate). In addition to precise cell positioning, this approach can also be used for the generation of 3D structures by transferring and depositing multiple hydrogel droplets. By further automating and combining this approach with other 3D printing technologies, such as two-photon stereolithography, it has a high potential of becoming a fast and versatile technology for the 2D and 3D bioprinting of mammalian cells with single cell resolution.     

4D Printing of Shape Memory Materials for Textiles: Mechanism,Mathematical Modeling,and Challenges

Shape memory materials (SMMs) in 3D printing (3DP) technology garnered much attention due to their ability to respond to external stimuli, which direct this technology toward an emerging area of research, “4D printing (4DP) technology.” In contrast to classical 3D printed objects, the fourth dimension, time, allows printed objects to undergo significant changes in shape, size, or color when subjected to external stimuli. Highly precise and calibrated 4D materials, which can perform together to achieve robust 4D objects, are in great demand in various fields such as military applications, space suits, robotic systems, apparel, healthcare, sports, etc. This review, for the first time, to the best of the authors’ knowledge, focuses on recent advances in SMMs (e.g., polymers, metals, etc.) based wearable smart textiles and fashion goods. This review integrates the basic overview of 3DP technology, fabrication methods, the transition of 3DP to 4DP, the chemistry behind the fundamental working principles of 4D printed objects, materials selection for smart textiles and fashion goods. The central part summarizes the effect of major external stimuli on 4D textile materials followed by the major applications. Lastly, prospects and challenges are discussed, so that future researchers can continue the progress of this technology.     

Preparation of P(St-NMA) microsphere inks and their application in photonic crystal patterns with brilliant structural colors

Patterned photonic crystals with structural colors on textile substrates have attracted a special attention due to the great advantages in application, which currently become a research hot-spot. This study utilized an ink-jet printing technology to prepare high-quality photonic crystal patterns with structural colors on polyester substrates. The self-assembly temperature of poly(styrene-N-methylol acrylamide) (P(St-NMA)) microspheres set to construct photonic crystals were deeply optimized. Moreover, the structural colors of prepared photonic crystal patterns were characterized and evaluated. When the mass fraction of P(St-NMA) microspheres was 1.0 wt.%, the pH value ranged from 5 to 7, and the surface tension was in the range of 63.79 to 71.20 mN/m, inks could present the best print performance. At 60 °C, prepared P(St-NMA) microsphere inks were good for printing to obtain patterned photonic crystals with regular arrangement and beautiful structural colors. Specifically, photonic crystals with different colors could be constructed by regulating the diameter of microspheres in inks, and prepared structural colors exhibited distinct iridescent phenomenon. The present results could provide a theoretical basis for the industrial realization of patterned photonic crystals by ink-jet printing technology.     

Directed Molecular Collection by E‐Jet Printed Microscale Chemical Potential Wells in Hydrogel Films

A facile approach to locally concentrate analytes of interest will significantly enhance miniaturized, integrated chemical‐analysis systems. Here, the directed analyte transport and concentration using ≈200 µm‐diameter E‐jet printed chemical potential wells in a polyacrylamide hydrogel is demonstrated. Using a cationic well as the model system, anionic analytes are accumulated into a microscale area with a local concentration enhancement of >50‐fold relative to the surrounding area. By downscaling the diameter of the chemical potential well from a few millimeters to 100s of micrometers, it is found, using both fluorescence and Raman microscopy, that the molecular collection capacity of the well is greatly improved. Additionally, it is shown that molecules can be simultaneously transported and concentrated to arrays of microscale regions using an array of microscale chemical potential wells. This approach enhances many‐fold the limit of detection, enables the formation of microscale potential well arrays with a variety of chemical properties, and provides a novel microscale molecular manipulation technique as an alternative to traditional microfluidic‐based systems.