In 2013, battle lines were drawn. Two stark competitors were looking to speed repairs and cut costs on parts for gas turbines. First to the drawing board was GE, who started using 3-D printing technology at its Global Research Center in Niskayuna, N.Y., to produce more than 85,000 fuel nozzles for its anticipated LEAP engine technology.
It’s a well-known fact that labs consume four times more energy per square foot than a typical...
In all manufacturing processes there are limits to the surface topographies that can be produced...
Engineering drawings remain at a core for any manufacturing organization as they communicate ideas that are expected to be transformed into a profitable product. Most companies begin developing engineering drawings using international drafting standards. However, with the course of time, and as the idea begins to shape up, there’s always a deviation from the standards followed.
In a world where most information is available in an instant, plant managers and engineers are continuously trying to find ways to improve the efficiency of processes along the manufacturing line. Analyzing these processes can be a difficult task. Until recently, days of laboratory work were often required to analyze any given sample segment or process in a manufacturing line.
Research in the pharmaceutical and industrial science industries has become increasingly global, multidisciplinary and data-intensive. This is made clear by the evolution in patent approvals, which can also be considered a reliable measure of innovation in these industries. Innovation itself is a cumulative effect, which requires access to multiple fragments of knowledge from disparate sources and exchange of technology and ideas.
Partnerships between universities and businesses are nothing new, but these partnerships have become especially relevant in the face of increasing economic pressure and global competition, the need for interdisciplinary approaches and the growing complexity of the problems need solutions. In recent years, there has been a resurgence of partnering between academic institutions and private industry.
Immediately following the passage of the Energy Independence and Security Act (EISA) of 2007, much research interest focused on the development of bio-based renewable energy sources (biofuels). EISA mandated increased production and use of biofuels for the long term. There also appeared to be substantial long-term government support for the implementation of a biofuel-based industry.
Compared to industrial and residential construction, labs are expensive as they are highly complex in nature. The end goal to constructing a functional lab is to provide valuable research results. At the heart of a lab is the research conducted and, as a result, lab owners can’t compromise research efforts by overlooking key aspects of the workspace—such as safety, comfort and sustainability.
Much equipment used in nanotech, physical and biological sciences can’t function properly if subjected to vibrations that exceed small threshold values. As a result, lab designers are faced with the challenge of developing designs where vibration disturbances are within acceptable limits to further science.
Image analysis is of growing importance in science, and trends are observed for different layers of image acquisition. Quantifiable and reproducible data is a prerequisite for scientific publications. And, today, it isn’t sufficient to just acquire aesthetically pleasing images with a microscope. To get powerful scientific results, scientists must get as much information as they can from an image.
At my home workstation, I have an old Fluke handheld digital multimeter (DMM) in its classic orange case, along with a very old analog voltage ohm-meter (VOM) in its similarly classic boxy black plastic case. Both of these instruments sit on a shelf below my laser printer and see constant temperatures and environments all year long.
Just a few years ago, many researchers working in alternative manufacturing methods believed the basic layering technologies integral to 3D printing limited the capability of this technique to build quality optical devices and lenses. But, as rapidly evolving as these techniques are, and as broad ranging as the applications it’s infiltrating, this limitation has been surmounted by a number of research groups around the world.
Gel permeation/size exclusion chromatography (GPC/SEC) is a vital analytical technique used to characterize synthetic and natural polymers, including biologically important macromolecules such as proteins and DNA. Evolving challenges tax the capabilities of traditional GPC/SEC and invite advances in the technology.
At the 66th annual Pittsburgh Conference on Analytical Chemistry and Applied Spectroscopy (Pittcon) this past March 7 – 13 in New Orleans, the spectroscopy- based new product introductions covered, quite literally, the entire analytical spectrum from the far-infrared to x-rays, along with Raman and mass spectrometry (MS) and nuclear magnetic resonance (NMR) products.
Geometrically, fractals have forms, or features, that repeat at different sizes over ranges of scales. These features can repeat exactly, such as the triangles that repeat with scale on a Koch snowflake or Minkowski sausage. Or, these features might repeat statistically, as on ground or abraded surfaces, where these repeating features create self-similar patterns of scratches or over a range of scales.
We live in an increasingly wireless world where self-powered devices are becoming integral to everyday life. A plethora of next-generation wireless technologies are seeing dramatic growth, involving both consumer and industrial applications. Some of the industrial applications include utility meter reading (AMR/AMI), wireless mesh networks, M2M and system control and data acquisition (SCADA) and data loggers, to name a few.
Repeatability underlies a researcher’s ability to control variation and increase sensitivity in an experiment. For sensitive analyses, such as cell-based assays, mass spectrometry and high-resolution protein structure determination, precise repeatability requires careful factorial design of experiments by systematically varying experimental parameters.