Accelerating the experimental cycle for new materials development is vital for addressing the grand energy challenges of the 21st century. We fabricate and characterize 75 unique perovskite-inspired ...compositions within a 2-month period, with 87% exhibiting band gaps between 1.2 and 2.4 eV, which are of interest for energy-harvesting applications. We utilize a fully connected deep neural network to classify compounds based on experimental X-ray diffraction data into 0D, 2D, and 3D structures, more than 10 times faster than human analysis and with 90% accuracy. We validate our methods using lead-halide perovskites and extend the application to lead-free compositions. The wider synthesis window and faster cycle of learning enables the realization of a multi-site lead-free alloy series, Cs3(Bi1-xSbx)2(I1-xBrx)9. We reveal the non-linear band-gap behavior and transition in dimensionality upon simultaneous alloying on the B-site and X-site of Cs3Bi2I9 with Sb and Br.
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•Investigation of 75 perovskite-inspired compositions in thin-film form (41 Pb free)•A deep neural network classifies perovskites into 0D, 2D, and 3D structures•Non-linear band-gap behavior discovered in Cs3(Bi1-xSbx)2(I1-xBrx)9 dual-site alloys
To meet increasing global energy demand, it is critical yet challenging to accelerate the development of novel energy materials. High-throughput experimentation (HTE) and machine-learning techniques have become increasingly accessible to scientific researchers. We herein demonstrate a case study on perovskite-inspired materials, where a combination of fast synthesis and machine-learning-assisted data diagnostics of 75 compositions achieves an acceleration of over an order of magnitude per experimental learning cycle over our laboratory baseline. The increased throughput and streamlined workflow enable the realization of new candidate photovoltaic materials, which sheds light on the search for lead-free perovskites in this multi-parameter chemical space. Our study demonstrates that combining an accelerated experimental cycle of learning and machine-learning-based diagnosis represents an important step toward realizing fully automated laboratories for materials discovery and development.
Fast experimental cycles enable exploration of wide chemical space and data-driven analysis.
Nanotechnology is utilized well in the development and improvement of the performance in Solid Oxide Fuel Cells (SOFCs). The high operating temperature of SOFCs (700–900°C) has resulted in serious ...demerits regarding their overall performance and durability. Therefore, the operating temperature has been reduced to an intermediate temperature range of approximately 400–700°C which improved performance and, subsequently, commercialized SOFCs as portable power sources. However, at reduced temperature, challenges such as an increase in internal resistance of the fuel cell components arise. Although, this may not be as serious as problems encountered at high temperature, it still significantly affects the performance of SOFCs. This review paper addresses the work of researchers in the application of nanotechnology in fabricating SOFCs through distinct methods. These methods have successfully omitted or at least reduced the internal resistance and showed considerable improvement in power density of the SOFCs at reduced temperatures.
Successful materials innovations can transform society. However, materials research often involves long timelines and low success probabilities, dissuading investors who have expectations of shorter ...times from bench to business. A combination of emergent technologies could accelerate the pace of novel materials development by ten times or more, aligning the timelines of stakeholders (investors and researchers), markets, and the environment, while increasing return on investment. First, tool automation enables rapid experimental testing of candidate materials. Second, high-performance computing concentrates experimental bandwidth on promising compounds by predicting and inferring bulk, interface, and defect-related properties. Third, machine learning connects the former two, where experimental outputs automatically refine theory and help define next experiments. We describe state-of-the-art attempts to realize this vision and identify resource gaps. We posit that over the coming decade, this combination of tools will transform the way we perform materials research, with considerable first-mover advantages at stake.
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The convergence of high-performance computing, automation, and machine learning promises to accelerate the rate of materials discovery by ≥10 times, better aligning investor and stakeholder timelines. Infrastructure and human-capital investments are discussed, including equipment capabilities, data management, education, and incentives. As our field transitions from thinking “data poor” to thinking “data rich,” we envision a scientific laboratory where the process of materials discovery continues without disruptions, aided by computational power augmenting the human mind, and freeing the latter to perform research closer to the speed of imagination, addressing societal challenges in market-relevant timeframes.
A combination of emergent technologies promises to accelerate novel materials development by ten times or more: tool automation, high-performance computing, and machine learning. We describe state-of-the-art attempts to realize this vision and identify resource gaps, including required infrastructure and human-capital investments.
Organic solar cells (OSCs) have made dramatic advancements during the past decades owing to the innovative material design and device structure optimization, with power conversion efficiencies ...surpassing 19% and 20% for single‐junction and tandem devices, respectively. Interface engineering, by modifying interface properties between different layers for OSCs, has become a vital part to promote the device efficiency. It is essential to elucidate the intrinsic working mechanism of interface layers, as well as the related physical and chemical processes that manipulate device performance and long‐term stability. In this article, the advances in interface engineering aimed to pursue high‐performance OSCs are reviewed. The specific functions and corresponding design principles of interface layers are summarized first. Then, the anode interface layer, cathode interface layer in single‐junction OSCs, and interconnecting layer of tandem devices are discussed in separate categories, and the interface engineering‐related improvements on device efficiency and stability are analyzed. Finally, the challenges and prospects associated with application of interface engineering are discussed with the emphasis on large‐area, high‐performance, and low‐cost device manufacturing.
Organic solar cells (OSCs) have made dramatic improvements and interface engineering plays a crucial role. This review provides a comprehensive summary of the advancements in interface engineering, including the design of interfaces, the functionalities they offer, and their impact on device performance. Future challenges and potential research directions are outlined associated with interface engineering for large‐area, high‐performance, and cost‐effective OSCs.
The purposes of this study are to describe the students’ needs and to design the supplementary materials for reading skill by using local wisdom for second grade students of MTs Al Khairaat ...Gorontalo. By using Research and Development Method, the results of this study show that 1) students need materials which were related to decription of tourism objects, warning about cleanliness and the local story. 2) Students preffer to read text which consisted of 200-300 words. 3) Students want to answer 5 W + 1 H questions and True False questions in reading activities. 4) Students want to match the vocabularies with the pictures in vocabulary building activity. 5) Students want to fill in the blank sentences in Grammar activity. 6) Students want to work in group and the teacher should help them when they had a problem in the classroom. The content of the materials should be developed in interesting and easy way, language used must be appropriate with the students’ language level, build cultural awareness and motivated students to read. Therefore, by integrating local wisdom into supplementary reading materials, the students and the teacher feel easy and motivated in teaching and learning process.
In recent years, microfluidic technologies have emerged as a powerful approach for the advanced synthesis and rapid optimization of various solution‐processed nanomaterials, including semiconductor ...quantum dots and nanoplatelets, and metal plasmonic and reticular framework nanoparticles. These fluidic systems offer access to previously unattainable measurements and synthesis conditions at unparalleled efficiencies and sampling rates. Despite these advantages, microfluidic systems have yet to be extensively adopted by the colloidal nanomaterial community. To help bridge the gap, this progress report details the basic principles of microfluidic reactor design and performance, as well as the current state of online diagnostics and autonomous robotic experimentation strategies, toward the size, shape, and composition‐controlled synthesis of various colloidal nanomaterials. By discussing the application of fluidic platforms in recent high‐priority colloidal nanomaterial studies and their potential for integration with rapidly emerging artificial intelligence‐based decision‐making strategies, this report seeks to encourage interdisciplinary collaborations between microfluidic reactor engineers and colloidal nanomaterial chemists. Full convergence of these two research efforts offers significantly expedited and enhanced nanomaterial discovery, optimization, and manufacturing.
In recent years, microfluidic technologies have increasingly been applied toward accelerated synthesis science studies of solution‐processed nanomaterials, allowing greater control over synthesis conditions, lower reagent consumption, and unique data access through online monitoring techniques. Adoption of microfluidic synthesis technologies offers potential access to higher‐performing nanomaterials through autonomous robotic experimentation.
Recent years are showing a rapid adoption of digital manufacturing techniques to the construction industry, with a focus on additive manufacturing. Although 3D printing for construction (3DPC) has ...notably advanced in recent years, publications on the subject are recent and date a growth in 2019, indicating that it is a promising technology as it enables greater efficiency with fair consumption of material, minimization of waste generation, encouraging the construction industrialization and enhancing and accelerating the constructive process. This new building system not only gives an optimization of the building process but provides a new approach to the building design materiality. The direct connection between design and manufacturing allows the reduction in the number of the various construction phases needed. It is opening a new and wide range of options both formal and chromatic in customization, avoiding complex formworks, reducing costs and manufacturing time. The creative process has a strict and direct link with the constructive process, straightening design with its materiality. Cement-based materials lead the way, but new alternatives are being explored to further reduce its carbon footprint. In order to leverage its sustainability and enhance the system capacity, initiatives are being pursued to allow the reduction of the use of PC. Geopolimers are taking the first steps in 3DPC. Construction and Demolition Waste (CDW) materials are used to substitute natural aggregates. Even soil is being explored has a structural and aesthetic material. These research trends are opening a wider range of possibilities for architecture and design, broadening the spectrum of color, texture, and formal variations. The concern about textures and colours is not yet evident in many the structures already printed, opening the opportunity for future research. More can be done in the mixture and formal design of this building system, “discovering” other raw materials in others waste. This article aims to make a critical review of technologies, materials and methodologies to support the development of new sustainable materials to be used as a plastic element in the printed structure. A roadmap of 3D printing for construction is presented, and an approach on mix design, properties in the fresh and hardened state, highlighting the possibilities for obtaining alternative materials are pointed. With this review possible directions are presented to find solutions to enhance the sustainability of this system discovering “new” materiality for architecture and design.
In this commentary, I discuss the value of Chan's (2009) research-informed checklists for evaluating business English materials by providing a practitioner's approach to using the checklists. I ...adapted the checklists for three different uses. The first was to evaluate the teaching methodology followed in a business English textbook from an ESP series. The second use was as a guide and evaluation tool for my in-house business English material development. The final use was also to support the design and then evaluation of custom-made banking English course materials. In conclusion, I found that adapting these research-informed checklists, based on local needs, creates opportunities for professional development, tailored courses, and transferability to other ESP genres.
•Pedagogical examples of Chan's (2009) frameworks in use.•Empowering practitioners to tailor frameworks to meet different needs.•Implications for research-based checklist adaptability.
The production of cashew nuts has been increasing globally, leading to a greater volume of waste materials that require proper management. Nevertheless, cashew nutshells (CNS), currently considered ...waste by most processors, offer a noteworthy opportunity for alternative applications owing to their distinct physical, chemical, and thermal properties. This article reviews alternative applications for CNS that can leverage these properties, while evaluating research gaps. The potential uses are classified into three categories: material development, energy production, and substance absorption. In the materials segment, various examples are discussed where CNS serves as raw material to synthesize biopolymers, cementitious materials, and a broad range of composites. The energy production section discusses various processes that utilize CNS, including pyrolysis, gasification, and briquette production. The absorption section presents CNS and activated carbon derived from CNS as effective absorbents for liquid-phase and gas-phase applications. While this review highlights numerous research-level possibilities for CNS utilization, only a few of these options have been implemented within the industry. Consequently, further research is essential, particularly in CNS characterization, economic and environmental assessment, and real-life implementation, to broaden and enhance the integration of this biomass into applications that can contribute to the value of both its production and processing chain.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
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