Project description:Developing promising treatments in biomedicine often requires aggregation and analysis of data from disparate sources across the healthcare and research spectrum. To facilitate these approaches, there is a growing focus on supporting interoperation of datasets by standardizing data-capture and reporting requirements. Common Data Elements (CDEs)-precise specifications of questions and the set of allowable answers to each question-are increasingly being adopted to help meet these standardization goals. While CDEs can provide a strong conceptual foundation for interoperation, there are no widely recognized serialization or interchange formats to describe and exchange their definitions. As a result, CDEs defined in one system cannot be easily be reused by other systems. An additional problem is that current CDE-based systems tend to be rather heavyweight and cannot be easily adopted and used by third-parties. To address these problems, we developed extensions to a metadata management system called the CEDAR Workbench to provide a platform to simplify the creation, exchange, and use of CDEs. We show how the resulting system allows users to quickly define and share CDEs and to immediately use these CDEs to build and deploy Web-based forms to acquire conforming metadata. We also show how we incorporated a large CDE library from the National Cancer Institute's caDSR system and made these CDEs publicly available for general use.
Project description:Nanofabrication has seen an increasing demand for applications in many fields of science and technology, but its production still requires relatively difficult, time-consuming, and expensive processes. Here we report a simple but very effective one dimensional (1D) nano-patterning technology that suggests a new nanofabrication method. This new technique involves the control of naturally propagating cracks initiated through simple, manually generated indentation, obviating the necessity of complicated equipment and elaborate experimental environments such as those that employ clean rooms, high vacuums, and the fastidious maintenance of processing temperatures. The channel fabricated with this technique can be as narrow as 10?nm with unlimited length and very high cross-sectional aspect ratio, an accomplishment difficult even for a state-of-the-art technology such as e-beam lithography. More interestingly, the fabrication speed can be controlled and achieved to as little as several hundred micrometers per second. Along with the simplicity and real-time fabrication capability of the technique, this tunable fabrication speed makes the method introduced here the authentic nanofabrication for in situ experiments.
Project description:Floret fertility is a key determinant of the number of grains per inflorescence in cereals. During the evolution of wheat (Triticum sp.), floret fertility has increased, such that current bread wheat (Triticum aestivum) cultivars set three to five grains per spikelet. However, little is known regarding the genetic basis of floret fertility. The locus Grain Number Increase 1 (GNI1) is shown here to be an important contributor to floret fertility. GNI1 evolved in the Triticeae through gene duplication. The gene, which encodes a homeodomain leucine zipper class I (HD-Zip I) transcription factor, was expressed most abundantly in the most apical floret primordia and in parts of the rachilla, suggesting that it acts to inhibit rachilla growth and development. The level of GNI1 expression has decreased over the course of wheat evolution under domestication, leading to the production of spikes bearing more fertile florets and setting more grains per spikelet. Genetic analysis has revealed that the reduced-function allele GNI-A1 contributes to the increased number of fertile florets per spikelet. The RNAi-based knockdown of GNI1 led to an increase in the number of both fertile florets and grains in hexaploid wheat. Mutants carrying an impaired GNI-A1 allele out-yielded WT allele carriers under field conditions. The data show that gene duplication generated evolutionary novelty affecting floret fertility while mutations favoring increased grain production have been under selection during wheat evolution under domestication.
Project description:Traditionally, scanning probe lithography tools are limited in resolution by the radius of curvature of the tip used. Herein, an approach is described for patterning the ridge of piled-up polymer that naturally occurs when a scanning probe is pressed against a soft surface. The use of this phenomenon to transfer patterns to hard materials with 20 nm resolution is demonstrated.
Project description:There has been a compelling demand of fabricating high-resolution complex three-dimensional (3D) structures in nanotechnology. While two-photon lithography (TPL) largely satisfies the need since its introduction, its low writing speed and high cost make it impractical for many large-scale applications. We report a digital holography-based TPL platform that realizes parallel printing with up to 2000 individually programmable laser foci to fabricate complex 3D structures with 90 nm resolution. This effectively improves the fabrication rate to 2,000,000 voxels/sec. The promising result is enabled by the polymerization kinetics under a low-repetition-rate regenerative laser amplifier, where the smallest features are defined via a single laser pulse at 1 kHz. We have fabricated large-scale metastructures and optical devices of up to centimeter-scale to validate the predicted writing speed, resolution, and cost. The results confirm our method provides an effective solution for scaling up TPL for applications beyond laboratory prototyping.
Project description:Shaping ceramic materials at the nanoscale in 3D is a phenomenal engineering challenge, that can offer new opportunities in a number of industrial applications, including metamaterials, nano-electromechanical systems, photonic crystals, and damage-tolerant lightweight materials. 3D fabrication of sub-micrometer ceramic structures can be performed by two-photon laser writing of a preceramic polymer. However, polymer conversion to a fully ceramic material has proven so far unfeasible, due to lack of suitable precursors, printing complexity, and high shrinkage during ceramic conversion. Here, it is shown that this goal can be achieved through an appropriate engineering of both the material and the printing process, enabling the fabrication of preceramic 3D shapes and their transformation into dense and crack-free SiOC ceramic components with highly complex, 3D sub-micrometer architectures. This method allows for the manufacturing of components with any 3D specific geometry with fine details down to 450 nm, rapidly printing structures up to 100 µm in height that can be converted into ceramic objects possessing sub-micrometer features, offering unprecedented opportunities in different application fields.
Project description:The ability to handle single molecules as effectively as macroscopic building blocks would enable the construction of complex supramolecular structures inaccessible to self-assembly. The fundamental challenges obstructing this goal are the uncontrolled variability and poor observability of atomic-scale conformations. Here, we present a strategy to work around both obstacles and demonstrate autonomous robotic nanofabrication by manipulating single molecules. Our approach uses reinforcement learning (RL), which finds solution strategies even in the face of large uncertainty and sparse feedback. We demonstrate the potential of our RL approach by removing molecules autonomously with a scanning probe microscope from a supramolecular structure. Our RL agent reaches an excellent performance, enabling us to automate a task that previously had to be performed by a human. We anticipate that our work opens the way toward autonomous agents for the robotic construction of functional supramolecular structures with speed, precision, and perseverance beyond our current capabilities.
Project description:A tribochemistry-assisted method has been developed for nondestructive surface nanofabrication on GaAs. Without any applied electric field and post etching, hollow nanostructures can be directly fabricated on GaAs surfaces by sliding a SiO2 microsphere under an ultralow contact pressure in humid air. TEM observation on the cross-section of the fabricated area shows that there is no appreciable plastic deformation under a 4 nm groove, confirming that GaAs can be removed without destruction. Further analysis suggests that the fabrication relies on the tribochemistry with the participation of vapor in humid air. It is proposed that the formation and breakage of GaAs-O-Si bonding bridges are responsible for the removal of GaAs material during the sliding process. As a nondestructive and conductivity-independent method, it will open up new opportunities to fabricate defect-free and well-ordered nucleation positions for quantum dots on GaAs surfaces.
Project description:Cell fractionations and other biological separations frequently require several steps. They could be much more effectively done by filtration, if isoporous membranes would be available with high pore density, and sharp pore size distribution in the micro- and nanoscale. We propose a combination of two scalable methods, photolithography and dry reactive ion etching, to fabricate a series of polyester membranes with isopores of size 0.7 to 50 μm and high pore density with a demonstrated total area of 38.5 cm2. The membranes have pore sizes in the micro- and submicro-range, and pore density 10-fold higher than track-etched analogues, which are the only commercially available isoporous polymeric films. Permeances of 220,000 L m-2 h-1bar-1 were measured with pore size 787 nm. The method does not require organic solvents and can be applied to many homopolymeric materials. The pore reduction from 2 to 0.7 μm was obtained by adding a step of chemical vapor deposition. The isoporous system was successfully demonstrated for the organelle fractionation of Arabidopsis homogenates and could be potentially extended to other biological fractionations.
Project description:Focused ion beam (FIB) milling is an important rapid prototyping tool for micro- and nanofabrication and device and materials characterization. It allows for the manufacturing of arbitrary structures in a wide variety of materials, but establishing the process parameters for a given task is a multidimensional optimization challenge, usually addressed through time-consuming, iterative trial-and-error. Here, we show that deep learning from prior experience of manufacturing can predict the postfabrication appearance of structures manufactured by focused ion beam (FIB) milling with >96% accuracy over a range of ion beam parameters, taking account of instrument- and target-specific artifacts. With predictions taking only a few milliseconds, the methodology may be deployed in near real time to expedite optimization and improve reproducibility in FIB processing.