In 2005, the US passed the Energy Policy Act of 2005 mandating the construction and operation of a high-temperature gas reactor (HTGR) by 2021. This law was passed after a multiyear study by national experts on what future nuclear technologies should be developed. As a result of the Act, the US Congress chose to develop the so-called Next-Generation Nuclear Plant, which was to be an HTGR designed to produce process heat for hydrogen production. Despite high hopes and expectations, the current status is that high temperature reactors have been relegated to completing research programs on advanced fuels, graphite and materials with no plans to build a demonstration plant as required by the US Congress in 2005. There are many reasons behind this diminution of HTGR development, including but not limited to insufficient government funding requirements for research, unrealistically high temperature requirements for the reactor, the delay in the need for a “hydrogen” economy, competition from light water small modular light water reactors, little utility interest in new technologies, very low natural gas prices in the US, and a challenging licensing process in the US for non-water reactors.
With the popularization of the Internet, permeation of sensor networks, emergence of big data, increase in size of the information community, and interlinking and fusion of data and information throughout human society, physical space, and cyberspace, the information environment related to the current development of artificial intelligence (AI) has profoundly changed. AI faces important adjustments, and scientific foundations are confronted with new breakthroughs, as AI enters a new stage: AI 2.0. This paper briefly reviews the 60-year developmental history of AI, analyzes the external environment promoting the formation of AI 2.0 along with changes in goals, and describes both the beginning of the technology and the core idea behind AI 2.0 development. Furthermore, based on combined social demands and the information environment that exists in relation to Chinese development, suggestions on the development of AI 2.0 are given.
Materials-development projects for advanced ultra-supercritical (A-USC) power plants with steam temperatures of 700 °C and above have been performed in order to achieve high efficiency and low CO2 emissions in Europe, the US, Japan, and recently in China and India as well. These projects involve the replacement of martensitic 9%−12% Cr steels with nickel (Ni)-base alloys for the highest temperature boiler and turbine components in order to provide sufficient creep strength at 700°C and above. To minimize the requirement for expensive Ni-base alloys, martensitic 9%−12% Cr steels can be applied to the next highest temperature components of an A-USC power plant, up to a maximum of 650°C. This paper comprehensively describes the research and development of Ni-base alloys and martensitic 9%−12% Cr steels for thick section boiler and turbine components of A-USC power plants, mainly focusing on the long-term creep-rupture strength of base metal and welded joints, strength loss in welded joints, creep-fatigue properties, and microstructure evolution during exposure at elevated temperatures.
This paper reviews the development of current research in bulk glassy alloys by focusing on the trigger point for the synthesis of the first bulk glassy alloys by the conventional mold casting method. This review covers the background, discovery, characteristics, and applications of bulk glassy alloys, as well as recent topics regarding them. Applications of bulk glassy alloys have been expanding, particularly for Fe-based bulk glassy alloys, due to their unique properties, high glass-forming ability, and low cost. In the near future, the engineering importance of bulk glassy alloys is expected to increase steadily, and continuous interest in these novel metallic materials for basic science research is anticipated.
In order to build a ceramic component by inkjet printing, the object must be fabricated through the interaction and solidification of drops, typically in the range of 10−100 pL. In order to achieve this goal, stable ceramic inks must be developed. These inks should satisfy specific rheological conditions that can be illustrated within a parameter space defined by the Reynolds and Weber numbers. Printed drops initially deform on impact with a surface by dynamic dissipative processes, but then spread to an equilibrium shape defined by capillarity. We can identify the processes by which these drops interact to form linear features during printing, but there is a poorer level of understanding as to how 2D and 3D structures form. The stability of 2D sheets of ink appears to be possible over a more limited range of process conditions that is seen with the formation of lines. In most cases, the ink solidifies through evaporation and there is a need to control the drying process to eliminate the: “coffee ring” defect. Despite these uncertainties, there have been a large number of reports on the successful use of inkjet printing for the manufacture of small ceramic components from a number of different ceramics. This technique offers good prospects as a future manufacturing technique. This review identifies potential areas for future research to improve our understanding of this manufacturing method.
Green process engineering, which is based on the principles of the process intensiﬁcation strategy, can provide an important contribution toward achieving industrial sustainable development. Green process engineering refers to innovative equipment and process methods that are expected to bring about substantial improvements in chemical and any other manufacturing and processing aspects. It includes decreasing production costs, equipment size, energy consumption, and waste generation, and improving remote control, information ﬂuxes, and process ﬂexibility. Membrane-based technology assists in the pursuit of these principles, and the potential of membrane operations has been widely recognized in the last few years. This work starts by presenting an overview of the membrane operations that are utilized in water treatment and in the production of energy and raw materials. Next, it describes the potential advantages of innovative membrane-based integrated systems. A case study on an integrated membrane system (IMS) for seawater desalination coupled with raw materials production is presented. The aim of this work is to show how membrane systems can contribute to the realization of the goals of zero liquid discharge (ZLD), total raw materials utilization, and low energy consumption.
Building cyber-physical system (CPS) models of machine tools is a key technology for intelligent manufacturing. The massive electronic data from a computer numerical control (CNC) system during the work processes of a CNC machine tool is the main source of the big data on which a CPS model is established. In this work-process model, a method based on instruction domain is applied to analyze the electronic big data, and a quantitative description of the numerical control (NC) processes is built according to the G code of the processes. Utilizing the instruction domain, a work-process CPS model is established on the basis of the accurate, real-time mapping of the manufacturing tasks, resources, and status of the CNC machine tool. Using such models, case studies are conducted on intelligent-machining applications, such as the optimization of NC processing parameters and the health assurance of CNC machine tools.
This paper describes the combinational surface kinetics enhancement and surface states passivation of nickel-borate (Ni-Bi) co-catalyst for a hematite (Fe2O3) photoanode. The Ni-Bi-modified Fe2O3 photoanode exhibits a cathodic onset potential shift of 230 mV and a 2.3-fold enhancement of the photocurrent at 1.23 V, versus the reversible hydrogen electrode (RHE). The borate (Bi) in the Ni-Bi film promotes the release of protons for the oxygen evolution reaction (OER).
A high-throughput multi-plume pulsed-laser deposition (MPPLD) system has been demonstrated and compared to previous techniques. Whereas most combinatorial pulsed-laser deposition (PLD) systems have focused on achieving thickness uniformity using sequential multilayer deposition and masking followed by post-deposition annealing, MPPLD directly deposits a compositionally varied library of compounds using the directionality of PLD plumes and the resulting spatial variations of deposition rate. This system is more suitable for high-throughput compound thin-film fabrication.
Metamaterials are composite materials whose material properties (acoustic, electrical, magnetic, or optical, etc.) are determined by their constitutive structural materials, especially the unit cells. The development of metamaterials continues to redefine the boundaries of materials science. In the field of electromagnetic research and beyond, these materials offer excellent design flexibility with their customized properties and their tunability under external stimuli. In this paper, we first provide a literature review of metamaterials with a focus on the technology and its evolution. We then discuss steps in the industrialization process and share our own experience.
Systems for ambient assisted living (AAL) that integrate service robots with sensor networks and user monitoring can help elderly people with their daily activities, allowing them to stay in their homes and live active lives for as long as possible. In this paper, we outline the AAL system currently developed in the European project Robot-Era, and describe the engineering aspects and the service-oriented software architecture of the domestic robot, a service robot with advanced manipulation capabilities. Based on the robot operating system (ROS) middleware, our software integrates a large set of advanced algorithms for navigation, perception, and manipulation. In tests with real end users, the performance and acceptability of the platform are evaluated.
The issues of reducing CO2 levels in the atmosphere, sustainably utilizing natural mineral resources, and dealing with industrial waste offer challenging opportunities for sustainable development in energy and the environment. The latest advances in CO2 mineralization technology involving natural minerals and industrial waste are summarized in this paper, with great emphasis on the advancement of fundamental science, economic evaluation, and engineering applications. We discuss several leading large-scale CO2 mineralization methodologies from a technical and engineering-science perspective. For each technology option, we give an overview of the technical parameters, reaction pathway, reactivity, procedural scheme, and laboratorial and pilot devices. Furthermore, we present a discussion of each technology based on experimental results and the literature. Finally, current gaps in knowledge are identified in the conclusion, and an overview of the challenges and opportunities for future research in this field is provided.
In this paper, progresses of color maintenance, also known as color shift, in solid-state lighting (SSL) systems are thoroughly reviewed. First, color shift is introduced and a few examples are given from different real-life industrial conditions. Different degradation mechanisms in different parts of the system are also explained. Different materials used as lenses/encapsulants in light-emitting diode (LED)-based products are introduced and their contributions to color shift are discussed. Efforts put into standardization, characterizing, and predicting lumen maintenance are also briefly reviewed in this paper.
Given the significant requirements for transforming and promoting the process industry, we present the major limitations of current petrochemical enterprises, including limitations in decision-making, production operation, efficiency and security, information integration, and so forth. To promote a vision of the process industry with efficient, green, and smart production, modern information technology should be utilized throughout the entire optimization process for production, management, and marketing. To focus on smart equipment in manufacturing processes, as well as on the adaptive intelligent optimization of the manufacturing process, operating mode, and supply chain management, we put forward several key scientific problems in engineering in a demand-driven and application-oriented manner, namely: ① intelligent sensing and integration of all process information, including production and management information; ② collaborative decision-making in the supply chain, industry chain, and value chain, driven by knowledge; ③ cooperative control and optimization of plant-wide production processes via human-cyber-physical interaction; and ④life-cycle assessments for safety and environmental footprint monitoring, in addition to tracing analysis and risk control. In order to solve these limitations and core scientific problems, we further present fundamental theories and key technologies for smart and optimal manufacturing in the process industry. Although this paper discusses the process industry in China, the conclusions in this paper can be extended to the process industry around the world.
The rise of big data has led to new demands for machine learning (ML) systems to learn complex models, with millions to billions of parameters, that promise adequate capacity to digest massive datasets and offer powerful predictive analytics (such as high-dimensional latent features, intermediate representations, and decision functions) thereupon. In order to run ML algorithms at such scales, on a distributed cluster with tens to thousands of machines, it is often the case that significant engineering efforts are required—and one might fairly ask whether such engineering truly falls within the domain of ML research. Taking the view that “big” ML systems can benefit greatly from ML-rooted statistical and algorithmic insights—and that ML researchers should therefore not shy away from such systems design—we discuss a series of principles and strategies distilled from our recent efforts on industrial-scale ML solutions. These principles and strategies span a continuum from application, to engineering, and to theoretical research and development of big ML systems and architectures, with the goal of understanding how to make them efficient, generally applicable, and supported with convergence and scaling guarantees. They concern four key questions that traditionally receive little attention in ML research: How can an ML program be distributed over a cluster? How can ML computation be bridged with inter-machine communication? How can such communication be performed? What should be communicated between machines? By exposing underlying statistical and algorithmic characteristics unique to ML programs but not typically seen in traditional computer programs, and by dissecting successful cases to reveal how we have harnessed these principles to design and develop both high-performance distributed ML software as well as general-purpose ML frameworks, we present opportunities for ML researchers and practitioners to further shape and enlarge the area that lies between ML and systems.
This work aims to understand the gasification performance of municipal solid waste (MSW) by means of thermodynamic analysis. Thermodynamic analysis is based on the assumption that the gasification reactions take place at the thermodynamic equilibrium condition, without regard to the reactor and process characteristics. First, model components of MSW including food, green wastes, paper, textiles, rubber, chlorine-free plastic, and polyvinyl chloride were chosen as the feedstock of a steam gasification process, with the steam temperature ranging from 973 K to 2273 K and the steam-to-MSW ratio (STMR) ranging from 1 to 5. It was found that the effect of the STMR on the gasification performance was almost the same as that of the steam temperature. All the differences among the seven types of MSW were caused by the variation of their compositions. Next, the gasification of actual MSW was analyzed using this thermodynamic equilibrium model. It was possible to count the inorganic components of actual MSW as silicon dioxide or aluminum oxide for the purpose of simplification, due to the fact that the inorganic components mainly affected the reactor temperature. A detailed comparison was made of the composition of the gaseous products obtained using steam, hydrogen, and air gasifying agents to provide basic knowledge regarding the appropriate choice of gasifying agent in MSW treatment upon demand.
Crystallization is an important unit operation in the pharmaceutical industry. At present, most pharmaceutical crystallization processes are performed in batches. However, due to product variability from batch to batch and to the low productivity of batch crystallization, continuous crystallization is gaining increasing attention. In the past few years, progress has been made to allow the products of continuous crystallization to meet different requirements. This review summarizes the progress in pharmaceutical continuous crystallization from a product engineering perspective. The advantages and disadvantages of different types of continuous crystallization are compared, with the main difference between the two main types of crystallizers being their difference in residence time distribution. Approaches that use continuous crystallization to meet different quality requirements are summarized. Continuous crystallization has advantages in terms of size and morphology control. However, it also has the problem of a process yield that may be lower than that of a batch process, especially in the production of chirality crystals. Finally, different control strategies are compared.
A growing number of?three-dimensional (3D)-print-ing processes have been applied to tissue engineering. This paper presents a state-of-the-art study of 3D-printing technologies?for tissue-engineering applications, with particular focus on the development of a computer-aided scaffold design system; the direct 3D printing of functionally graded scaffolds; the modeling of selective laser sintering (SLS) and fused deposition modeling (FDM) processes; the indirect additive manufacturing of scaffolds, with both micro and macro features; the development of a bioreactor; and 3D/4D bioprinting. Technological limitations will be discussed so as to highlight the possibility of future improvements for new 3D-printing methodologies for tissue engineering.
In this paper, we review the current state-of-the-art techniques used for understanding the inner workings of the brain at a systems level. The neural activity that governs our everyday lives involves an intricate coordination of many processes that can be attributed to a variety of brain regions. On the surface, many of these functions can appear to be controlled by specific anatomical structures; however, in reality, numerous dynamic networks within the brain contribute to its function through an interconnected web of neuronal and synaptic pathways. The brain, in its healthy or pathological state, can therefore be best understood by taking a systems-level approach. While numerous neuroengineering technologies exist, we focus here on three major thrusts in the field of systems neuroengineering: neuroimaging, neural interfacing, and neuromodulation. Neuroimaging enables us to delineate the structural and functional organization of the brain, which is key in understanding how the neural system functions in both normal and disease states. Based on such knowledge, devices can be used either to communicate with the neural system, as in neural interface systems, or to modulate brain activity, as in neuromodulation systems. The consideration of these three fields is key to the development and application of neuro-devices. Feedback-based neuro-devices require the ability to sense neural activity (via a neuroimaging modality) through a neural interface (invasive or noninvasive) and ultimately to select a set of stimulation parameters in order to alter neural function via a neuromodulation modality. Systems neuroengineering refers to the use of engineering tools and technologies to image, decode, and modulate the brain in order to comprehend its functions and to repair its dysfunction. Interactions between these fields will help to shape the future of systems neuroengineering—to develop neurotechniques for enhancing the understanding of whole-brain function and dysfunction, and the management of neurological and mental disorders.
In 2011, the Chinese Academy of Sciences launched an engineering project to develop an accelerator-driven subcritical system (ADS) for nuclear waste transmutation. The China Lead-based Reactor (CLEAR), proposed by the Institute of Nuclear Energy Safety Technology, was selected as the reference reactor for ADS development, as well as for the technology development of the Generation IV lead-cooled fast reactor. The conceptual design of CLEAR-I with 10 MW thermal power has been completed. KYLIN series lead-bismuth eutectic experimental loops have been constructed to investigate the technologies of the coolant, key components, structural materials, fuel assembly, operation, and control. In order to validate and test the key components and integrated operating technology of the lead-based reactor, the lead alloy-cooled non-nuclear reactor CLEAR-S, the lead-based zero-power nuclear reactor CLEAR-0, and the lead-based virtual reactor CLEAR-V are under realization.
Electron beam selective melting (EBSM) is an additive manufacturing technique that directly fabricates three-dimensional parts in a layerwise fashion by using an electron beam to scan and melt metal powder. In recent years, EBSM has been successfully used in the additive manufacturing of a variety of materials. Previous research focused on the EBSM process of a single material. In this study, a novel EBSM process capable of building a gradient structure with dual metal materials was developed, and a powder-supplying method based on vibration was put forward. Two different powders can be supplied individually and then mixed. Two materials were used in this study: Ti6Al4V powder and Ti47Al2Cr2Nb powder. Ti6Al4V has excellent strength and plasticity at room temperature, while Ti47Al2Cr2Nb has excellent performance at high temperature, but is very brittle. A Ti6Al4V/Ti47Al2Cr2Nb gradient material was successfully fabricated by the developed system. The microstructures and chemical compositions were characterized by optical microscopy, scanning microscopy, and electron microprobe analysis. Results showed that the interface thickness was about 300 μm. The interface was free of cracks, and the chemical compositions exhibited a staircase-like change within the interface.