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Iowa State University and Ames Laboratory researchers have developed a method to produce sintered, final-shape magnets with high density and aligned microstructure.The resulting permanent magnets feature higher energy product and improved remanence versus standard processing, with improved performance in motors and generators.
Iowa State University and Ames Laboratory researchers have developed a process to create AlNiCo magnets in near final shape with improved energy product and remanence versus magnets produced without using directional solidification or zone refinement. Magnets resulting from this process are characterized by highly controlled and aligned microstructure in the solid state.Magnet alloy precursor powder is aligned while being added to the mold, with compression molding locking the aligned particles in place. The resulting microstructural template for grain growth persists through a thermal de-binding treatment and sintering of the magnet. Magnets produced by this molding process display enhanced energy density, as well as optimized coercivity and magnetization, and have the potential for high volume manufacturing because they are manufactured in near-final shapes.
Iowa State University and Ames Laboratory Critical Materials Institute researchers have developed a cost effective step that easily separates rare earth oxalates into a light rare earth stream and a heavy rare earth stream.
For many rare earth ores, the percentage of the valuable heavy rare earths (in particular, terbium, europium, dysprosium, yttrium and gadolinium) in the ore is very low, making separation and recovery of these elements from the other rare earths not cost-effective. Iowa State University and Ames Laboratory researchers have developed a process that can be added on to conventional ore processing that readily separates rare earth oxalates into two streams, one containing the light rare earths (La – Sm) and the other containing heavy rare earths (Gd – Y). This one step process requires no special equipment and minimal capital investment. The process is water-based, and uses a “green” extractant to remove the heavy REEs from the light REEs.
A fundamental technology issue occurring in many organizations today involves balancing limited log management resources with the increasing supply of log data. The high number of log sources, inconsistent content, and variable format all contribute to this issue. Log management and analysis are key processes in dealing with security issues, fraud, and operational issues. Logs can also assist with record keeping, establishing baselines, identifying trends and performing audits. However, the lack of real-time or near real-time analysis significantly reduces the effectiveness of logs.
nSnare™, developed at the National Renewable Energy Laboratory, is a software that analyses and categorizes log messages generated by various and customizable third party software packages using a custom multi-tiered rules engine. Each log message is either determined to be a false positive, or it is assigned a score based on the severity of the potential attack and confidence that the activity described by the log message is not a false positive. Log messages are then assigned to an event, which is a collection of log messages related to a single potential attack. Meta-analysis rules run on the collection of all logs within an event to correlate multiple related logs into a single known attack signature. When the sum of the scores of all logs within an event exceeds a pre-defined threshold, the event is labelled as an attack and an automated response is generated to block the attacker from connecting to any protected resources, called quarantining within the application, for a variable length of time. The length of time that the quarantine lasts for is based on the severity and frequency of the attack, along with historical information on the attacker and any third party provided threat intelligence data that the system has gathered. An additional random length of time is added to each quarantine so the algorithm cannot be easily learned and bypassed by a persistent attacker. A confidence score is generated based on a proprietary algorithm that determines the likelihood that the data which led to the attacker getting quarantined was a false positive. A threat intelligence record is created for each detected attack, with details on the attacker, a summary of what triggered the quarantine, the severity of the attack and the confidence the system has that the attack is not the result of false data, which can then be shared with external entities so that they can also protect themselves from a related attack.
nSnare™ also includes a web based front end for analyzing the current quarantined attacks, removing a quarantine in the case of a false positive, viewing previously quarantined attacks, and tracking suspicious activity that the system is evaluating. The web interface also allows the creation and modification of rules used by the rules engine, and the maintenance of a whitelist of known good systems that should never be automatically quarantined.
Computers and automated systems have accelerated productivity and improved quality and reliability for nearly everything in our modern world, and are destined to take on increasing roles as time moves on. One major limiting factor for automated systems is their inability to categorize and recognize objects, particularly under changing lighting or other conditions. Examples of how this could be useful include automatically detecting manufacturing defects, analyzing changes between two images (e.g. medical scans), noise filtering in radio frequency communications, and extracting weak signals or images from various sources.
Current approaches to making “smart” systems generally build custom solutions for every problem with very specific outcomes. Examples include self-driving car systems and facial recognition software, which have very specific features and approaches built in that usually do not translate to other applications very well. Other examples, such as automatic defect detection, require tightly controlled lighting and often require the object being inspected to be in the same position to be able to identify problems. Generally, these automated systems can, when conditions match the programmed expectations, identify that there is a problem, but have very limited ability when measurement conditions are dynamic or the situation changes in unanticipated ways.
Researchers at INL have developed an analysis system known as MorphoHawk for automatic feature detection and classification across a host of applications in changing environmental conditions. In general, MorphoHawk can be trained to identify features of interest, and will then group features in a scene (e.g. image, signal, etc) and categorize them according to the rules it was conditioned with. After it has categorized an image or other multi-dimentional data set, it can compare the features it has identified with subsequent data sets, allowing it to detect changes (e.g. manufacturing quality control) or detect the introduction of new features (e.g. a tumor in medical scans or a person entering a scene monitored by a camera). It has shown that it can discern between an object and its shadow, meaning it can handle differences in registration and light conditions in dynamic environments. This is possible because MorphoHawk algorithms characterize and compare morphological features, rather than conducting a binary analysis (e.g. light vs. dark).
MorphoHawk has shown utility as a signal filtering tool to differentiate between noise and meaningful data in analysis of digital images and electronic signals, resulting in sharp, cleaned images and clearly extracting the message of the signals while removing the noise. MorphoHawk can be applied to analyze images for manufacturing defects, enhancing the capability of existing inspection systems. Feature extraction is another unique capability of MorphoHawk. For example, metal surface topology can be separated into effects of rolling and grinding, allowing discrepancies to be assigned to the appropriate process. It has even been used to identify a facture path in materials and examine structural changes in battery electrodes to predict battery lifetime.INL Technology ID: BA-481
ISU and Ames Laboratory scientists have developed a metal chalcogenide material for use as a water electrolysis catalyst for the generation of hydrogen.
Hydrogen is a unique energy carrier in that it can be produced from a number of diverse pathways utilizing a variety of domestically available feedstock, including natural gas, biomass, and water. The electrochemical splitting of water (electrolysis) is among the most versatile and greenest methods of hydrogen generation that will play a significant role in long-term, high-volume hydrogen gas production. Iowa State University and Ames Laboratory scientists have developed a catalyst to assist in the generation of hydrogen from water electrolysis. The mixed-metal chalcogenide catalyst shows promise as a cathode material, able to operate in highly acidic conditions. When compared to other non-precious metal catalysts, such as Molybdenum Sulfide, these catalysts offer far superior performance, able to operate far more efficiently. http://isurftech.technologypublisher.com/technology/31310 This technology is related to ISURF 4629: Preparation of mixed metal chalcogenides by mechanochemical processing and exfoliation https://isurftech.technologypublisher.com/techcase/4629
Concentrating Solar Power (CSP) technologies use mirrors to concentrate focused sunlight onto a collection point where it can be converted into heat, the thermal energy of which can be used to produce electricity. To further the next generation of CSP technologies, in May 2018, the U.S. Department of Energy (DOE) announced a funding push for projects that would extend current research on various design components, then develop and test new integrated assemblies.
As companies, research institutions, and national laboratories rise to this challenge to improve the efficiency of this technology, the DOE’s Office of Energy Efficiency & Renewable Energy submits that such a surge of innovative ideas has potential to lower the cost of a CSP system by $0.02 per kilowatt-hour, thus making the technology far more economically viable.
NREL and Deutsches Zentrum für Luft- und Raumfahrt (DLR) have been collaborating to advance technology and processes for integrated liquid systems in CSP technology. One such advancement is the electrochemical purification of molten salts containing MgCl2 under flowing conditions in the return pipe to a CSP’s cold tank. As oxygen and water can permeate through a CSP system during periods of maintenance and operation, if they are not properly removed in time, metallic components in the system can experience corrosion from magnesium hyroxychloride (MgOHCl) and chlorates that form in the molten media. To counteract this, NREL scientists have developed a process to control corrosion using sacrificial anodes made of bulk metallic magnesium (Mg) under controlled cathodic potentials to eliminate corrosive impurities such as MgOHCl. The approach is easy to control because Mg will remain solid at temperatures of 540oC, and will be consumed as needed based on the amount of oxygen/water present.
For more information on this technology, contact Erin Beaumont at:
Although research is currently inactive on the patented technology "Low Temperature Sorbents for Removal of Sulfur Compounds from Fluid Feed Streams," the technology is available for licensing from the U.S. Department of Energy’s National Energy Technology Laboratory (NETL).
Disclosed in this patent is a process consisting of a material reactive with sulfur, a binder unreactive with sulfur, and an inert material that in combination can absorb sulfur from fluid feed gas streams at temperatures ranging between 30 and 200 degrees Centigrade. Research has shown that the sulfur absorption capacity has reached as high as 22 weight percent through the application of this process.
Although vapor-phase fuel streams provide valuable commodities, such as liquefied petroleum gases, these commodities cannot be commercially used until contaminants within them are removed. The most typical contaminants are sulfur-containing compounds, such as hydrogen sulfide and others. Removal of the sulfur is necessary to preserve the environment and protect components, such as catalysts, fuel cells, and turbines, contained in power generation systems. Some techniques currently exist for sulfur removal but are limited by only incorporating high temperature ranges. Low temperature processes for removing sulfur also exist but are limited by low sulfur capacities.
The NETL-developed technology provides a solid sorbent that removes sulfur compounds at low temperatures. The process operates at temperatures ranging between 30 degrees and 200 degrees Centigrade, while exhibiting the capacity to absorb high levels of sulfur. In addition, the sorbent itself is relatively inexpensive to manufacture and maintain. The process features a combination of readily available sulfur-reactive materials with diluents and support materials to produce a porous sulfur-absorbing substrate, resulting in the use of less materials and minimal costs.
Xiaogan Liang of Berkeley Lab has invented an inexpensive, high-throughput process for depositing pure few-layer-graphene (FLG) in a desired pattern onto substrates, such as silicon wafers. This method uses electrostatic forces to print FLG in dimensions ranging from less than 20 nm to 100 μm and has the potential to be combined with step-and-repeat technology to cover large areas.
In the Berkeley Lab technology, the desired pattern is created on the pristine surface of a highly oriented pyrolytic graphite (HOPG) stamp. The stamp is brought into contact with the substrate, and one to three layers of graphene are deposited with great accuracy by the application of electrostatic forces. The stamp is removed and the graphene remains bonded to the substrate by van de Waals forces alone.
The invention was used to create 1.4 μm pillars and 18 nm-wide nanolines of FLG on SiO2/Si substrates. These structures were visualized with scanning electron microscopy and atomic force microscopy, and their graphene composition was confirmed with Raman spectroscopy. The nanolines were used to create transistors that had excellent transport properties with highly mobile holes and electrons. The rapid current in the FLG nanolines and nanoribbons and their high sensitivity to electric fields may also allow for applications in biosensors, antennae, and photovoltaics.
Graphene offers significant advantages over silicon as a potential semiconductor because of its exceptional electronic properties: high carrier mobility, stable 2D structure, and the potential to enable scatter-free electron movement at room temperature. However, several obstacles have prevented graphene from being used for commercial electronics. Primarily, it is difficult to deposit graphene in a precise and electronically useful pattern over the relatively large (6 in., 8 in., or 12 in.) surface of a standard silicon wafer or other substrate. Current methods such as epitaxial growth, adhesive application, and reactive deposition are either expensive or risk contamination of the deposited material. The Berkeley Lab technology overcomes these limitations to make graphene a viable semiconductor material.
Iowa State University researchers have developed a flexible pathway to turn glucose into nylon or PET using inexpensive catalysts and moderate reaction conditions.
Using a combination of biological, electrochemical, and catalytic processes, ISU researchers have developed a pathway to convert glucose into precursors for both nylon and PET manufacture. The first phase utilizes an engineered strain of Saccharomyces cerevisiae to produce high levels of muconic acid from a glucose feedstock (a titer of 752mg/L). Next, muconic acid can be partially hydrogenated to hexenedioic acid or fully hydrogenated to adipic acid via an electrochemical process. Both hexenedioic acid and adipic acid can be combined with hexaminediamine to make Nylon 6,6. If hexenedioic acid is used in the nylon backbone, the remaining double bond can be further modified using controlled radical polymerization to create a functionalized nylon with potential applications in packaging and other areas. Alternately the muconic acid can undergo a series of reactions to produce terephthalic acid (one of the building blocks for PET, the most common thermoplastic polyester). These steps include electrocatalytically isomerizing the cis,cis- or cis,trans- muconic acid to the trans,trans- variant for PET and other high-value chemical production. This suite of technologies enables the production of a variety of similar polymers with different physical characteristics that can be targeted toward specialized end products. This technology is related to ISURF #4289: Electrocatalytic Hydrogenation of Muconic Acid for the Production of Biorenewable Synthetic Polymer Precursors (http://isurftech.technologypublisher.com/techcase/4289), and ISURF #4402: Electrochemical Isomerization of Muconic Acid (http://isurftech.technologypublisher.com/techcase/4402)
Argonne scientists have developed a super hard and slick nanocomposite coating (SSC) that significantly reduces friction and wear and can eliminate scuffing-related failures. The coating can be used in components of moving mechanical systems, including engines. Eliminating scuffing is especially important because it is a life-limiting factor in many components used under heavy loading or in heavy machinery, such as earth-moving and mining equipment. The SSC also increases energy efficiency by reducing friction by as much as 80%. SSCs can be produced at moderate temperatures (200–400°C) on almost any kind of metallic substrates at high growth rates.
Argonne’s SSCs are based on special formulations of hard and soft phases that provide friction coefficients of 0.02 to 0.05 under boundary lubricated sliding conditions and prevent wear. Therefore, the SSCs can extend wear life, reduce maintenance costs, and reduce environmental emissions by reducing fuel consumption.
Argonne researchers have collaborated with Galleon International and Hauzer Technocoating to develop a production-scale deposition system to meet the demands of large-volume applications in the transportation and manufacturing sectors. The new system uses a modified version of existing plasma coating equipment that is well-suited for demonstrating flexible, production-scale coating for large-volume industrial applications. The SSC is unique in that the ingredients used in its synthesis were predicted by using a crystal-chemical model proposed by the developers of the SSC technology. In the collaborations, the scientists are using special coating ingredients that are predicted by using the crystal-chemical model.
Thermal expansion differences between the porous anode/active anode and dense electrolyte in an anode supported solid oxide fuel cell (SOFC) result in a camber (out of plane deflection) after high-temperature heat treatments. Researchers at PNNL have devised two methods to reduce the camber by applying a symmetrical thermal expansion design to the planar cell assembly.
The first method (13536-E) focuses on placing an equilibrating thermal expansion layer on the back of the anode in a designed pattern which enables functionality of the cell to be maintained. The other (13851-B) is a low-thermal expansion additive to the anode that counterbalances the camber during the cooling down phase of cell operation.
Either method or a combination of both inventions provides several benefits in the manufacturing of anode-supported SOFCs.
Sandia’s neutron scatter camera is an innovative design which combines the benefits of gamma ray imaging with fast neutron imaging. The camera detects special nuclear material (SNM) and rejects backgrounds from naturally occurring radiation sources that can produce false alarms. Additionally, the camera can detect and localize neutrons at greater distances and through shielding since fast neutrons are more penetrating than gamma rays. One of the key advantages is higher signal to background over non imaging detectors.
Sandia’s neutron camera design is sensitive, has good angular resolution, portable, and non hazardous. The design is scalable for shorter dwell times and longer stand-off detection.