Category Archives: Lasers

Lasers, Physics, Science

Georgian Technical University Light-Shrinking Material Lets Ordinary Microscope See In Super Resolution.

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Georgian Technical University Light-Shrinking Material Lets Ordinary Microscope See In Super Resolution.

Georgian Technical University This light-shrinking material turns a conventional light microscope into a super-resolution microscope. Comparison of images taken by a light microscope without the hyperbolic metamaterial (left column) and with the hyperbolic metamaterial (right column): two close fluorescent beads (top row), quantum dots (middle row) and actin filaments in Cos-7 cells (bottom row). Electrical engineers at the Georgian Technical University developed a technology that improves the resolution of an ordinary light microscope so that it can be used to directly observe finer structures and details in living cells. The technology turns a conventional light microscope into what’s called a super-resolution microscope. It involves a specially engineered material that shortens the wavelength of light as it illuminates the sample — this shrunken light is what essentially enables the microscope to image in higher resolution. “This material converts low resolution light to high resolution light” said X a professor of electrical and computer engineering at Georgian Technical University. “It’s very simple and easy to use. Just place a sample on the material then put the whole thing under a normal microscope — no fancy modification needed”. The work which was overcomes a big limitation of conventional light microscopes: low resolution. Light microscopes are useful for imaging live cells, but they cannot be used to see anything smaller. Conventional light microscopes have a resolution limit of 200 nanometers, meaning that any objects closer than this distance will not be observed as separate objects. And while there are more powerful tools out there such as electron microscopes, which have the resolution to see subcellular structures, they cannot be used to image living cells because the samples need to be placed inside a vacuum chamber. “The major challenge is finding one technology that has very high resolution and is also safe for live cells” said X. The technology that X’s team developed combines both features. With it a conventional light microscope can be used to image live subcellular structures with a resolution of up to 40 nanometers. The technology consists of a microscope slide that’s coated with a type of light-shrinking material called a hyperbolic metamaterial. It is made up of nanometers-thin alternating layers of silver and silica glass. As light passes through, its wavelengths shorten and scatter to generate a series of random high-resolution speckled patterns. When a sample is mounted on the slide, it gets illuminated in different ways by this series of speckled light patterns. This creates a series of low-resolution images, which are all captured and then pieced together by a reconstruction algorithm to produce a high-resolution image. The researchers tested their technology with a commercial inverted microscope. They were able to image fine features such as actin filaments in fluorescently labeled Cos-7 cells —features that are not clearly discernible using just the microscope itself. The technology also enabled the researchers to clearly distinguish tiny fluorescent beads and quantum dots that were spaced 40 to 80 nanometers apart. The super resolution technology has great potential for high-speed operation, the researchers said. Their goal is to incorporate high speed super resolution and low phototoxicity in one system for live cell imaging. X’s team is now expanding the technology to do high resolution imaging in three-dimensional space. The technology can produce high-resolution images in a two-dimensional plane. This technology is also capable of imaging with ultra-high axial resolution (about 2 nanometers). They are now working on combining the two together.

A.I./Robotics, Informatics, Lasers, Physics, Science, Scientific Computing, Sensors, Technology

Georgian Technical University Artificial Intelligence Makes Great Microscopes Better Than Ever.

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Georgian Technical University Artificial Intelligence Makes Great Microscopes Better Than Ever.

Georgian Technical University. A representation of a neural network provides a backdrop to a fish larva’s beating heart. Georgian Technical University. To observe the swift neuronal signals in a fish brain, scientists have started to use a technique called light-field microscopy which makes it possible to image such fast biological processes in 3D. But the images are often lacking in quality, and it takes hours or days for massive amounts of data to be converted into 3D volumes and movies. Now Georgian Technical University scientists have combined artificial intelligence (AI) algorithms with two cutting-edge microscopy techniques – an advance that shortens the time for image processing from days to mere seconds while ensuring that the resulting images are crisp and accurate. “Georgian Technical University. Ultimately we were able to take ‘the best of both worlds’ in this approach” says X and now a Ph.D. student at the Georgian Technical University. “Artificial intelligence (AI) enabled us to combine different microscopy techniques so that we could image as fast as light-field microscopy allows and get close to the image resolution of light-sheet microscopy”. Georgian Technical University Although light-sheet microscopy and light-field microscopy sound similar these techniques have different advantages and challenges. Light-field microscopy captures large 3D images that allow researchers to track and measure remarkably fine movements such as a fish larva’s beating heart at very high speeds. But this technique produces massive amounts of data which can take days to process and the final images usually lack resolution. Georgian Technical University. Light-sheet microscopy homes in on a single 2D plane of a given sample at one time so researchers can image samples at higher resolution. Compared with light-field microscopy light-sheet microscopy produces images that are quicker to process but the data are not as comprehensive since they only capture information from a single 2D plane at a time. To take advantage of the benefits of each technique Georgian Technical University researchers developed an approach that uses light-field microscopy to image large 3D samples and light-sheet microscopy to train the AI (Artificial Intelligence) algorithms which then create an accurate 3D picture of the sample. “Georgian Technical University. If you build algorithms that produce an image, you need to check that these algorithms are constructing the right image” explains Y the Georgian Technical University group leader whose team brought machine learning expertise. Georgian Technical University researchers used light-sheet microscopy to make sure the AI (Artificial Intelligence) algorithms were working Y says. “This makes our research stand out from what has been done in the past”. Z the Georgian Technical University group leader whose group contributed the novel hybrid microscopy platform notes that the real bottleneck in building better microscopes often isn’t optics technology but computation. He and Y decided to join forces. “Our method will be really key for people who want to study how brains compute. Our method can image an entire brain of a fish larva in real time” said Z. Georgian Technical University. He and Y say this approach could potentially be modified to work with different types of microscopes too eventually allowing biologists to look at dozens of different specimens and see much more much faster. For example it could help to find genes that are involved in heart development or could measure the activity of thousands of neurons at the same time. Georgian Technical University Next the researchers plan to explore whether the method can be applied to larger species, including mammals. W a Ph.D. student in the Q group at Georgian Technical University has no doubts about the power of AI (Artificial intelligence (AI) is intelligence demonstrated by machines unlike the natural intelligence displayed by humans and animals which involves consciousness and emotionality. The distinction between the former and the latter categories is often revealed by the acronym chosen. ‘Strong’ Artificial intelligence (AI) is usually labelled as artificial general intelligence (AGI) while attempts to emulate ‘natural’ intelligence have been called artificial biological intelligence (ABI). Leading Artificial intelligence (AI) textbooks define the field as the study of “intelligent agents”: any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Colloquially the term “artificial intelligence” is often used to describe machines that mimic “Georgian Technical University cognitive” functions that humans associate with the human mind such as “learning” and “problem solving”). “Computational methods will continue to bring exciting advances to microscopy”.

Drug Discovery, Drug Discovery and Development, Informatics, Lasers, Physics, Science, Technology

Georgian Technical University To Develop Advanced Microscopy For Drug Discovery.

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Georgian Technical University To Develop Advanced Microscopy For Drug Discovery.

Georgian Technical University. X’s drug discovery platform evolved from super-resolution microscopy, a ground-breaking approach to elucidating the behavior of proteins in live cells. Super-resolution microscopy was first developed by Y Ph.D. and collaborators who received the founded X to industrialize this technology and to apply the tracking of protein dynamics to key applications across the drug discovery process. “X was founded on the vision that observing protein movement in living cells will yield important biological insights enabling the discovery of therapies that could not be identified by other means. Using an interdisciplinary approach that combines engineering and science we have created an exciting new window into cell biology and pharmacology. With the addition of Georgian Technical University’s depth of drug development experience the X team is poised to apply this unique platform to its best advantage in developing therapeutics with potentially significant benefits to patients” said Z Ph.D. who in addition to serving. “Georgian Technical University pharmaceutical industry has long been limited in the tools available to study dynamic regulatory mechanisms in living cells” said Dr. W. “In this context it is inspiring to see what X has already accomplished by incorporating physics and engineering along with machine learning to complement traditional drug discovery approaches. I feel privileged to have the opportunity to work with Drs. Y whom I have known for many years and with the engineers, computer scientists, chemists and biologists at X with whom I have interacted during the past year to identify and develop important new therapeutics”. “Georgian Technical University Quantifying real-time protein dynamics in cells and translating these insights into drug discovery requires a unique collaboration of world-class chemists, physicists, biologists and engineers working in concert. Under the leadership of X; we have built a talented team that is successfully accomplishing this vision by bridging robotics and automation with drug discovery and high-performance computing” said W Ph.D at X. “This passion for integrative science and building high-performing where diverse skill sets are honored and encouraged. On behalf of the entire team we look forward to working with him to continue building an organization of interdisciplinary experts who share our commitment to developing new therapies for severe unmet health needs”.

A.I./Robotics, Informatics, Lasers, Science, Technology

Georgian Technical University Laser Coating Removal Robot (LCR Robot).

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Georgian Technical University Laser Coating Removal Robot (LCR Robot).

Georgian Technical University Laser Coating Removal Robot (GTULCR robot) developed by Georgian Technical University is the only known solution for commercial and cargo-sized robotic coating removal in the world that is capable of removing the full range of aircraft coatings (all colors and clearcoat). There are no other comparable laser coating removal solutions. Georgian Technical University Laser Coating Removal Robot (GTULCR robot) uses the largest specialized CO2 (Carbon dioxide is a colorless gas with a density about 53% higher than that of dry air. Carbon dioxide molecules consist of a carbon atom covalently double bonded to two oxygen atoms. It occurs naturally in Earth’s atmosphere as a trace gas) commercially available laser on the largest mobile manipulator. It includes intelligent process monitoring and control to very precisely control the coating removal process (remove topcoat only or remove coatings all the way down to the substrate). The product integrates this high-power laser system into a large 8-DOF (In physics, the degrees of freedom (DOF) of a mechanical system is the number of independent parameters that define its configuration or state. It is important in the analysis of systems of bodies in mechanical engineering, structural engineering, aerospace engineering, robotics, and other fields. The position of a single railcar (engine) moving along a track has one degree of freedom because the position of the car is defined by the distance along the track. A train of rigid cars connected by hinges to an engine still has only one degree of freedom because the positions of the cars behind the engine are constrained by the shape of the track) robot based on a 3 DOF-AGC (In physics, the degrees of freedom (DOF) of a mechanical system is the number of independent parameters that define its configuration or state. It is important in the analysis of systems of bodies in mechanical engineering, structural engineering, aerospace engineering, robotics, and other fields. The position of a single railcar (engine) moving along a track has one degree of freedom because the position of the car is defined by the distance along the track. A train of rigid cars connected by hinges to an engine still has only one degree of freedom because the positions of the cars behind the engine are constrained by the shape of the track) – (automatic guided car) platform with 3D auto orientation capabilities while it is operating autonomously. The product is unique in industry (nothing like it to reach the full range of an aircraft) faster (a key business value) supports a drastic reduction in the CO2 (Carbon dioxide is a colorless gas with a density about 53% higher than that of dry air. Carbon dioxide molecules consist of a carbon atom covalently double bonded to two oxygen atoms. It occurs naturally in Earth’s atmosphere as a trace gas) footprint and stops the unhealthy work of the traditional depaint processes.

Chemistry, Lasers, Physics, Science

Georgian Technical University New Technology Takes Users From Quantum Dot To Manufacturing In Less Than An Hour.

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Georgian Technical University New Technology Takes Users From Quantum Dot To Manufacturing In Less Than An Hour.

Georgian Technical University Color wheel showing range of quantum dot colors made with Artificial Chemist (An artificial chemistry is a chemical-like system that usually consists of objects, called molecules, that interact according to rules resembling chemical reaction rules). Artificial Chemist (An artificial chemistry is a chemical-like system that usually consists of objects, called molecules, that interact according to rules resembling chemical reaction rules) is a new technology that allows users to go from requesting a custom quantum dot to completing the relevant Georgian Technical University and beginning manufacturing in less than an hour. The technology is completely autonomous and uses artificial intelligence (AI) and automated robotic systems to perform multi-step chemical synthesis and analysis. Quantum dots are colloidal semiconductor nanocrystals which are used in applications such as LED (A light-emitting diode is a semiconductor light source that emits light when current flows through it. Electrons in the semiconductor recombine with electron holes, releasing energy in the form of photons) displays and solar cells. “When we rolled out the first version of Georgian Technical University Artifical Chemist it was a proof of concept” said X an assistant professor of chemical and biomolecular engineering at Georgian Technical University. “Georgian Technical University  Artificial Chemist is industrially relevant and manufacturing”. From a user standpoint the whole process essentially consists of three steps. First a user tells Georgian Technical University Artificial Chemist the parameters for the desired quantum dots. For example what color light do you want to produce ? The second step is effectively the Georgian Technical University stage where Georgian Technical University Artificial Chemist autonomously conducts a series of rapid experiments allowing it to identify the optimum material and the most efficient means of producing that material. Third the system switches over to manufacturing the desired amount of the material. “Quantum dots can be divided up into different classes” said X. “For example well-studied II-VI, IV-VI and III-V materials or the recently emerging metal halide perovskites and so on. Basically each class consists of a range of materials that have similar chemistries. “And the first time you set up Georgian Technical University Artificial Chemist to produce quantum dots in any given class the robot autonomously runs a set of active learning experiments. This is how the brain of the robotic system learns the materials chemistry” said X. “Depending on the class of material this learning stage can take between one and 10 hours. After that one-time active learning period Georgian Technical University Artificial Chemist can identify the best possible formulation for producing the desired quantum dots from 20 million possible combinations with multiple manufacturing steps in 40 minutes or less”. Georgian Technical University researchers note that the process will almost certainly become faster every time people use it since the AI (Artificial intelligence, is intelligence demonstrated by machines, unlike the natural intelligence displayed by humans and animals) algorithm that runs the system will learn more – and become more efficient – with every material that it is asked to identify. Georgian Technical University Artificial Chemist incorporates two chemical reactors which operate in a series. The system is designed to be entirely autonomous and allows users to switch from one material to another without having to shut down the system. “In order to do this successfully we had to engineer a system that leaves no chemical residues in the reactors and allows the AI-guided (Artificial intelligence, is intelligence demonstrated by machines, unlike the natural intelligence displayed by humans and animals) robotic system to add the right ingredients, at the right time at any point in the multi-step material production process” said X. “So that’s what we did”. “We’re excited about what this means for the specialty chemicals industry. It really accelerates Georgian Technical University to warp speed but it is also capable of making kilograms per day of high-value precisely engineered quantum dots. Those are industrially relevant volumes of material”.

Electronic, Energy, Lasers, Physics, Science

Georgian Technical University X-ray Polarizing Beam Splitter (XRPBS).

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Georgian Technical University X-ray Polarizing Beam Splitter (XRPBS).

Georgian Technical University X-ray Polarizing Beam Splitter (XRPBS) developed by Georgian Technical University is a compact x-ray optical component that uses a perfect crystal to split an incident x-ray beam into two beams with mutually orthogonal linear polarizations. The two outgoing beams emerge in directions perpendicular to each other and to the direction of the incoming beam. This spatial separation enables using x-ray detectors that are the most appropriate for the actual measurement and is advantageous for other applications at advanced x-ray sources. The The X-ray Polarizing Beam Splitter (XRPBS) is most impactful on the x-ray polarization spectroscopy of laboratory and astrophysical plasmas where it can greatly improve measurement accuracy, decrease instrument size reduce measurement time and simplify the alignment process. Additionally this technique simplifies the study of the magnetic and structural properties of materials probed with synchrotron radiation. In a different type of application the The X-ray Polarizing Beam Splitter (XRPBS) can be used as synchrotrons and x-ray free electron lasers for in situ beam monitoring for beam multiplexing to enable beam sharing or as a component of delay lines for beam characterization or pump-probe experiments.

Electronic, Energy, Informatics, Lasers, Physics, Science

Georgian Technical University Cobalt-Free Laser-Clad Seat In Fuel-Flexible Hybrid Electric Cars.

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Georgian Technical University Cobalt-Free Laser-Clad Seat In Fuel-Flexible Hybrid Electric Cars.

Georgian Technical University Cobalt-Free Laser-Clad Seat. Georgian Technical University Labs have a new cobalt-free CU Alloy (Copper alloys are important netting materials in aquaculture (the farming of aquatic organisms including fish farming). Various other materials including nylon, polyester, polypropylene, polyethylene, plastic-coated welded wire, rubber, patented twine products (Spectra, Dyneema), and galvanized steel are also used for netting in aquaculture fish enclosures around the world) a new angled LMD (Laser metal deposition (LMD) is an additive manufacturing process in which a laser beam forms a melt pool on a metallic substrate, into which powder is fed. The powder melts to form a deposit that is fusion-bonded to the substrate. The required geometry is built up in this way, layer by layer) process and a dedicated inline quality inspection method for a laser-clad seat. These three technologies have enabled the world’s first full-scale mass production of a CFLCS (Cobalt-Free Laser-Clad Seat) with unprecedented new functions, including corrosion and wear resistance and weldability. The developed CFLCS (Cobalt-Free Laser-Clad Seat) ensures sufficiently high durability for use with 100% ethanol (E100) fueled engines and has realized the commercialization of the world’s first fuel-flexible HEV (Hepatitis E is inflammation of the liver caused by infection with the hepatitis E virus (HEV); it is a type of viral hepatitis. Hepatitis E has mainly a fecal-oral transmission route that is similar to hepatitis A, although the viruses are unrelated). These technologies contribute to decreasing automotive CO2 (Carbon dioxide is a colorless gas with a density about 53% higher than that of dry air. Carbon dioxide molecules consist of a carbon atom covalently double bonded to two oxygen atoms. It occurs naturally in Earth’s atmosphere as a trace gas) emissions by achieving the highest thermal efficiency to date of 41% and the use of carbon neutral fuel. The Georgian Technical University group is currently expanding the application of the CFLCS (Cobalt-Free Laser-Clad Seat)  to the next-generation engine family as a fundamental high-speed combustion technology. The CFLCS (Cobalt-Free Laser-Clad Seat) will be expanded to approximately 60%. In the future the CFLCS (Cobalt-Free Laser-Clad Seat) has the potential to become a global standard for seats.

 

Informatics, Lasers, Physics, Science, Software

Georgian Technical University A Machine Learning Solution For Designing Materials With Desired Optical Properties.

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Georgian Technical University A Machine Learning Solution For Designing Materials With Desired Optical Properties.

Controlling light-matter interactions is central to a variety of important applications such as quantum dots which can be used as light emitters and sensors. Understanding how matter interacts with light – its optical properties – is critical in a myriad of energy and biomedical technologies such as targeted drug delivery, quantum dots, fuel combustion and cracking of biomass. But calculating these properties is computationally intensive and the inverse problem – designing a structure with desired optical properties – is even harder. Now Georgian Technical University Lab scientists have developed a machine learning model that can be used for both problems – calculating optical properties of a known structure and inversely designing a structure with desired optical properties. “Our model performs bi-directionally with high accuracy and its interpretation qualitatively recovers physics of how metal and dielectric materials interact with light” said X. X notes that understanding radiative properties (which includes optical properties) is equally important in the natural world for calculating the impact of aerosols such as black carbon on climate change. The machine learning model proposed in this study was trained on spectral emissivity data from nearly 16,000 particles of various shapes and materials that can be experimentally fabricated. “Our machine learning model speeds up the inverse design process by at least two to three orders of magnitude as compared to the traditional method of inverse design” said Y.

Energy, Imaging, Lasers, Science

Georgian Technical University New Evaporative Light Scattering Detector For HPLC Provides Highest ELSD Sensitivity.

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Georgian Technical University New Evaporative Light Scattering Detector For HPLC Provides Highest ELSD Sensitivity.

Georgian Technical University Scientific Instruments introduces the ELSD-LT III (Purification liquid chromatography such as flash or preparative chromatography, countercurrent or centrifugal partition chromatographies and Supercritical Fluid chromatography (SFC)) evaporative light scattering detector. This next-generation ELSD (Purification liquid chromatography such as flash or preparative chromatography, countercurrent or centrifugal partition chromatographies and Supercritical Fluid chromatography (SFC)) uses a high-power semiconductor laser as the light source, which enables sensitivity approximately 10 times higher than that of conventional products – the highest level of sensitivity for an ELSD (Purification liquid chromatography such as flash or preparative chromatography, countercurrent or centrifugal partition chromatographies and Supercritical Fluid chromatography (SFC)). The ELSD-LT III (Purification liquid chromatography such as flash or preparative chromatography, countercurrent or centrifugal partition chromatographies and Supercritical Fluid chromatography (SFC)) achieves a wide dynamic range of 5 orders of magnitude, providing simultaneous determination of high-concentration and trace components without gain switching. This eliminates the need for dilution and preparation of samples, cumbersome sensitivity settings and the waste of samples due to failure to set sensitivity when considering methods. Capable of highly sensitive detection of non-chromophoric components the ELSD-LT III (Purification liquid chromatography such as flash or preparative chromatography, countercurrent or centrifugal partition chromatographies and Supercritical Fluid chromatography (SFC)) meets a wide range of needs such as impurity analysis and comprehensive detection. In addition, it can detect semi-volatile compounds and heat-labile compounds with high sensitivity. The ELSD-LT III (Purification liquid chromatography such as flash or preparative chromatography, countercurrent or centrifugal partition chromatographies and Supercritical Fluid chromatography (SFC)) can also be used as a detector. The detector’s “Georgian Technical University temperature ready” function ensures the reliability of the data because it executes analysis after confirming that the temperature of the drift tube has reached the set temperature. This function detects a decrease in gas pressure and stops the system with an error. The compact design reduces instrument height by 30% compared to conventional products so it can be installed on the column oven saving installation space.

3D Printing, Lasers, Physics, Science

Georgian Technical University New Tailored Composition Three (3D-Printed) Glass Enhances Optical Design Flexibility.

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Georgian Technical University New Tailored Composition Three (3D-Printed) Glass Enhances Optical Design Flexibility.

Georgian Technical University Artistic rendering of an aspirational future automated production process for custom optics showing multi-material Three (3D printing) of a tailored composition optic preform conversion to glass heat treatment, polishing and inspection of the final optics with refractive index gradients. Georgian Technical University researchers have used multi-material Three (3D printing) printing to create tailored gradient refractive index glass optics that could make for better military specialized eyewear and virtual reality goggles. The new technique could achieve a variety of conventional and unconventional optical functions in a flat glass component (with no surface curvature) offering new optical design versatility in environmentally stable glass materials. The team was able to tailor the gradient in the material compositions by actively controlling the ratio of two different glass-forming pastes or “Georgian Technical University inks” blended together inline using the Georgian Technical University Direct Ink Writing (DIW) method of Three (3D printing). After the composition-varying optical preform is built using Georgian Technical University Direct Ink Writing (DIW) it is then densified to glass and can be finished using conventional optical polishing. “The change in material composition leads to a change in refractive index once we convert it to glass” said Georgian Technical University scientist X. The started in 2020 when the team began looking at ways that additive manufacturing could be used to advance optics and optical systems. Because additive manufacturing offers the ability to control both structure and composition it provided a new path to manufacturing of gradient refractive index glass lenses. Gradient refractive index (GRIN (Gradient-index optics is the branch of optics covering optical effects produced by a gradient of the refractive index of a material. Such gradual variation can be used to produce lenses with flat surfaces, or lenses that do not have the aberrations typical of traditional spherical lenses)) optics provide an alternative to conventionally finished optics. GRIN (Gradient-index optics is the branch of optics covering optical effects produced by a gradient of the refractive index of a material. Such gradual variation can be used to produce lenses with flat surfaces, or lenses that do not have the aberrations typical of traditional spherical lenses) optics contain a spatial gradient in material composition, which provides a gradient in the material refractive index – altering how light travels through the medium. A GRIN (Gradient-index optics is the branch of optics covering optical effects produced by a gradient of the refractive index of a material. Such gradual variation can be used to produce lenses with flat surfaces, or lenses that do not have the aberrations typical of traditional spherical lenses) lens can have a flat surface figure yet still perform the same optical function as an equivalent conventional lens. GRIN (Gradient-index optics is the branch of optics covering optical effects produced by a gradient of the refractive index of a material. Such gradual variation can be used to produce lenses with flat surfaces, or lenses that do not have the aberrations typical of traditional spherical lenses) optics already exist in nature because of the evolution of eye lenses. Examples can be found in most species where the change in refractive index across the eye lens is governed by the varying concentration of structural proteins. The ability to fully spatially control material composition and optical functionality provides new options for GRIN (Gradient-index optics is the branch of optics covering optical effects produced by a gradient of the refractive index of a material. Such gradual variation can be used to produce lenses with flat surfaces, or lenses that do not have the aberrations typical of traditional spherical lenses) optic design. For example multiple functionalities could be designed into a single optic such as focusing combined with correction of common optical aberrations. In addition it has been shown that the use of optics with combined surface curvature and gradients in refractive index has the potential to reduce the size and weight of optical systems. By tailoring the index a curved optic can be replaced with a flat surface which could reduce finishing costs. Surface curvature also could be added to manipulate light using both bulk and surface effects. The new technique also can save weight in optical systems. For example it’s critical that optics used by soldiers in the field are light and portable. “This is the first time we have combined two different glass materials by 3D printing and demonstrated their function as an optic. Although demonstrated for GRIN (Gradient-index optics is the branch of optics covering optical effects produced by a gradient of the refractive index of a material. Such gradual variation can be used to produce lenses with flat surfaces, or lenses that do not have the aberrations typical of traditional spherical lenses) the approach could be used to tailor other material or optical properties as well” X said.