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Historically, energy resources have evolved from high carbon to lower carbon fuels (from coal to oil to natural gas), then to non-carbon (hydroelectric, geothermal, wind power and solar). This dynamic process has reflected the evolution of human civilization and industrialization. As one of the most useful and classical energy resources, what is the outlook for the coal industry in the future? What factors will have a great impact on the outlook? Can new technologies in coal production make the coal industry cleaner and more competitive and increase its demand in the world market? How effective are CO2 capture technologies for coal power plants? This editorial work attempts to provide insights into these issues. 1. The future outlook for the coal industry Limiting global warming to 2 ◦C versus pre-industrial levels would imply reducing carbon dioxide (CO2) emissions by 80% of the 1990 level by 2050 and a net-zero emission by the end of this century. To make this happen requires a fast transition of traditional fossil fuels to renewable energy such as wind and solar. In this framework, coal demand is expected to decline by about 8% by 2030 compared to the pre-crisis level in 2019. Advanced economies will cut their demand by 45% compared to 2019. China is still the largest consumer and producer, and the coal usage in China is expected to rebound in the near term and achieve its peak around 2025 followed by a gradual decline after 2025. In the Asia Pacific area, India, Indonesia and Southeast Asian countries will increase their coal demand for power and industrial usage in the next decade (IEA, 2020). By 2030 the global coal demand is projected to decrease by about 400 million tonnes of coal equivalent compared to 2019. 2. The impact of major factors on the outlook Environmental concerns to reduce CO2 emissions from coal-fired plants, declining coal usage in the power sector due to renewables expansion and a cheap natural gas price, and policies that phase out coal to achieve carbon neutralities are the three major factors leading to the coal market downturn. The power sector accounts for nearly 65% of coal demand. By 2030, advanced economies will consume 50% less coal compared to their level in 2019 mainly due to policy-driven requirements. The increasing supply of renewables and natural gas has diversified the power generation sources, and significantly reduced the coal usage in this sector. Coal is the largest source of CO2 emissions and will be responsible for approximately 38% of the global CO2 emissions from 2020 to 2030. The policy-driven changes are significantly affecting coal usage worldwide (IEA, 2020; IMF, 2020). 3. Development of new technologies in the coal industry Potential technologies are emerging in the coal industry, such as hydraulic fracturing to improve the coalbed methane production; the CO2 capture, utilization and sequestration (CCUS) to reduce CO2 emissions from coal combustion; the coal-to-liquid and coal-to-gas fuel conversion technologies to improve the fuel efficiency and reduce the CO2 emissions; internet of things, big data analytics, artificial intelligence, and automation to reduce operational costs and improve safety concerns and production efficiency in coal operations; and, underground coal gasification (UCG) to recover unminable coal. Particularly, UCG has been attempted for over a century, and has not yet achieved a commercial-scale development. Successful development and utilization of this technology would make the coal industry more competitive and increase its demand in the world market. A UCG operation consists of a series of injection and production wells drilled into a coal seam; the coal is ignited after certain air and/or oxygen is injected. Chemical reactions convert the coal to syngas by pyrolysis, combustion and gasification reactions in a manner similar to those processes in a surface gasifier. The produced syngas is a mixture of mainly carbon monoxide and hydrogen, which can be used as fuel for power generation and feedstock for various chemical products (i.e., hydrogen and ammonia) (Nourozieh et al., 2010; Seifi et al., 2015). The carbon captured during syngas utilization can be used for enhanced oil recovery. Emissions from syngas combustion are generally cleaner and less greenhouse gas emissions than coal-fired facilities. The UCG process is less costly than conventional surficial coal gasification because no coal mining, processing and transport are required, and no ash and slag removal or disposal is necessary. The environmental impact of UCG is relatively low compared to surficial gasification, as major disturbances in landscape and surface disposal of ash and coal tailings are not required. A properly designed UCG site will recognize and address potential groundwater pollution and subsidence issues; tests related to the cap rock integrity and highly cemented wells should be performed to avoid these issues. UCG can have obvious advantages compared with other in situ coal applications, including mining, coalbed methane exploration and development; the cavities after UCG can be used as CO2 storage (Jiang et al., 2019). 4. CO2 capture technologies for coal power plants Five main types of CO2 capture technologies from flue gas are proven. The average capture efficiency is from 80% to 90%. Cryogenic separation can provide the highest capture efficiency up to 99.99%. The CO2 capture step represents 70-80% of the overall CO2 capture and sequestration costs. Economic analysis shows that US $70-100 are needed to capture one tonne CO2 from flue gas (the average CO2 concentration is about 3-14%) on average. On the other hand, it costs between US $300 to $1,500 to capture CO2 directly from air (Brandl et al., 2021). It would be possible to commercialize the capture efficiency beyond 90%. However, operators are not able to make benefits under the current policies because of the high associated capital and operational costs. The capture approaches include post-combustion, pre-combustion, oxyfuel combustion, chemical looping combustion and from air. The post-combustion technology is a mature technology, and has been widely applied. Future CO2 capture technologies are likely to focus on hybrid capture technologies, such as integrated CO2 capture and conversion. The coal use in the power sector surpassed 10 Gt CO2 emissions globally in 2018, and a successful application of carbon capture technologies can help the world reduce up to 8-10 Gt CO2 emissions annually. CCUS has received much research attention over the past two decades. Cited as : Ma, H., Chen, S., Xue, D., Chen, Y., Chen, Z. Outlook for the coal industry and new coal production technologies. Advances in Geo-Energy Research, 2021, 5(2): 119-120, doi: 10.46690/ager.2021.02.01

Since the environment for the CBM development in China has been changing in recent years, it is necessary to re-consider the relevant strategies. Through investigations, surveys, geologic assessment, strategic decision-making and other techniques, the strategies for CBM development in China were discussed in respect to present situations, opportunities, challenges, proved reserves, producing reserves, strategic principles, strategic countermeasures, time-spatial allocation of strategies, risk assessments, and elimination of relevant risks. Some research results were obtained. Firstly, still in its initial development stage with fast growth, the CBM industry in China has made outstanding achievements in six aspects and also faces challenges in six aspects. Secondly, strategic focus can be summarized as constructing six CBM production bases in Qinshui, Eastern margin of Ordos Basin, Southwest China, Changqing, Northwest China, and Northeast China, respectively, according to the principles of “steadily developing middle-high rank coals, accelerating the development of low-rank coals and strengthening the comprehensive utilization of mining gas wells”. It is expected that the producing reserves and peak-production rate will be 3–4 trillion m3 and 35–45 billion m3/a, respectively. Thirdly, major strategic risks in CBM development in China include low productivities of individual wells, improper understandings of geologic conditions, decline in investments and lack of technical reserves. To eliminate these risks, it is necessary to reinforce work in the following five aspects, namely, strengthening comprehensive exploration and development of coal-bearing formations, creating favorable environments for the development of private oil companies, expanding spaces for the growth of technical service companies, conducting more researches for the development of innovative technologies in more areas and intensifying law enforcement.

At node 28nm and beyond, metal layer have the smallest pitch and the most flexible in design of the critical layer. Various layout patterns on metal layers are challenging to runtime, OPC tools and OPC engineers. The OPC verification played as the role of highlighting fail patterns, and feeding back to the OPC Engineer for further learning and enhancing in the OPC recipe. In this paper the authors presented metal layer OPC repair flow for 28nm node and beyond. An automatic analysis methodology for the pinching, the bridging and the coverage errors were discussed. Next, according to the automated analysis of the error, the OPC repair flow is applied on all locations. This helped in cutting down the total runtime and reached the status of zero errors. This paper also compared the OPC verify result and total runtime of without OPC repair flow and using OPC repair flow. After using OPC repair flow, the OPC verify results are acceptable, and total runtime is reduced greatly.

At advanced node of metal layer, defocus conditions need to be taken into account in OPC in order to guarantee metal layer process window. Process window OPC (PWOPC) must be considered for the model-based OPC models under special conditions within a lithographic process window. In this paper, we studied several OPC simulation issues in the application of PWOPC in metal layer. The test run results showed that preparatory work and parameters setting were very important for PWOPC application. Without preparatory work or unbefitting parameters setting, the OPC simulation may lead to undesired results. The depth of focus (DOF) of several hot spots was examined. The pinch and bridge error are hot spots while only OPC model under nominal conditions is employed. These hot spots can be resolved while PWOPC models are in consideration. In addition of PWOPC precision study, PWOPC runtime is also evaluated. The use of PWOPC extends OPC runtime at least 50%, which is unacceptable in the environment of longer OPC runtime for the advanced tech node and continuing pull-in tapeout schedule. The runtime speeding up method is studied to reduce the total runtime.

In 28nm technology node, developing an enough lithographic process window of VIA layer became a major challenge in order to meet the requirements of the connectivity between metal lines. It is widely used to size up VIA in order to enlarge VIA process window if the space between VIA holes and VIA enclosed by metal is big enough. But the traditional retarget method has its own limits as the retarget rule table cannot deal with every complex environment for each VIA hole. In this paper, we studied several issues in the application of CALIBRE auto-retarget function in VIA model-based OPC correction after the traditional retarget treatment. The parameters of the auto-retarget function are optimized based on simulated results and the SEM data of the corresponding VIA holes are collected for DOF verification. The impact of the auto-retarget function on model-based OPC runtime is also evaluated. It is shown in the simulation result that the DOF of certain SRAM patterns can be enlarged as much as to 30nm after applying the auto-retarget function. The silicon data confirms the simulation prediction and that the DOF of the patterns become enough for lithographic process. Meanwhile, auto-retarget has little impact on model-based OPC runtime.

With minimum half-pitch shrinking to 28nm, the accuracy requirement imposed on OPC model is getting harder to achieve. In order to meet the much more challenging requirement, uncertainty in the modeling should be diminished as much as possible. The major factors of OPC modeling accuracy consist of OPC model calibration flow, data analysis of mask modeling, lithographic process parameters, and photoresist CD. In this paper, the parameters of mask modeling are analyzed and the mask induced errors are calculated, such as mask bias, mask corner rounding, and mask 3D effect. Furthermore, the interactive relations among these mask parameters are also investigated. A 28nm test model was constructed with optimized mask modeling approaches. The rms of the test model is significantly reduced to half of that of the traditional modeling approaches.

The double-gimbal control moment gyro (DGCMG) demands that the gimbal servosystem should have fast response and small overshoot. But due to the low and nonlinear torsional stiffness of harmonic drive, the gimbal servo-system has poor dynamic performance with large overshoot and low bandwidth. In order to improve the dynamic performance of gimbal servo-system, a model reference adaptive control (MRAC) law is introduced in this paper. The model of DGCMG gimbal servo-system with harmonic drive is established, and the adaptive control law based on POPOV super stable theory is designed. The MATLAB simulation results are provided to verify the effectiveness of the proposed control algorithm. The experimental results indicate that the MRAC could increase the bandwidth of gimbal servo-system to 3 Hz and improve the dynamic performance with small overshoot.

It is needed to transmit a large amount of image information stably at a high speed for storage and process when design a testing system. Image data acquired by remote CCD can be transmitted serially in form of LVDS or Hotlink. The data is buffered by ping-pong operation with two SRAMs. And then it is serially transmitted at a high speed to the grabber via Camera Link interface. The grabber can acquire a frame of 128×130 pixels image at a speed of 150 fps (frames-per-second) in LVDS format, or 250×320 pixels image at a speed of 500 fps (frames-per-second) in Hotlink. The top transmission speed can reach 320 Mbps (Mega-bits-per-second). At the same time, it can maintain the stability of high data correctness in the process of high-speed transmission. It is demonstrated that Camera Link can be conveniently applied in high-speed, serial image acquisition. And the experiment results verify that the image acquisition system can realize expected functions.

High-speed image capture technology is widely used in image signal transmission, processing, pattern recognition and industrial control. LVDS signal transmission technology and Hotlink transmission technology are two kinds of image signal transmission method who has been widely used in different areas because its own strengths. Because of its high-speed and strong interference immunity, LVDS signals have became the ideal choice in industrial on-site for high-speed signal long-term transmission. Hotlink, a new generation interface for point to point high-speed serial signal transmission, is gradually being accepted by the users because of the promotion of Cypress. FPGA, field programmable gate array, is used as the core of the design PCB for its low cost, flexible. We take advantage of their strengths, use FPGA collect the signal from LVDS interface or Hotlink interface, and translate the signal into the form that meets the USB protocol, then translate the image data to the computer throw USB interface.