A Roadmap for Transforming Research to Invent the Batteries of the Future Designed within the European Large Scale Research Initiative BATTERY 2030+

This roadmap presents the transformational research ideas proposed by “BATTERY 2030+,” the European large-scale research initiative for future battery chemistries. A “chemistry-neutral” roadmap to advance battery research, particularly at low technology readiness levels, is outlined, with a time horizon of more than ten years. The roadmap is centered around six themes: 1) accelerated materials discovery platform, 2) battery interface genome, with the integration of smart functionalities such as 3) sensing and 4) self-healing processes. Beyond chemistry related aspects also include crosscutting research regarding 5) manufacturability and 6) recyclability. This roadmap should be seen as an enabling complement to the global battery roadmaps which focus on expected ultrahigh battery performance, especially for the future of transport. Batteries are used in many applications and are considered to be one technology necessary to reach the climate goals. Currently the market is dominated by lithium-ion batteries, which perform well, but despite new generations coming in the near future, they will soon approach their performance limits. Without major breakthroughs, battery performance and production requirements will not be sufficient to enable the building of a climate-neutral society. Through this “chemistry neutral” approach a generic toolbox transforming the way batteries are developed, designed and manufactured, will be created

Small business innovation research: Program solicitation

This, the seventh annual SBIR solicitation by NASA, describes the program, identifies eligibility requirements, outlines the required proposal format and content, states proposal preparation and submission requirements, describes the proposal evaluation and award selection process, and provides other information to assist those interested in participating in NASA's SBIR program. It also identifies the Technical Topics and Subtopics in which SBIR Phase 1 proposals are solicited in 1989. These Topics and Subtopics cover a broad range of current NASA interests, but do not necessarily include all areas in which NASA plans or currently conducts research. High-risk high pay-off innovations are desired

Small Business Innovation Research. Program solicitation. Closing date: July 21, 1992

The National Aeronautics and Space Administration (NASA) invites small businesses to submit Phase 1 proposals in response to its Small Business Innovation Research (SBIR) Program Solicitation 92-1. Firms with research or research and development capabilities (R/R&D) in science or engineering in any of the areas listed are encouraged to participate. This, the tenth annual SBIR solicitation by NASA, describes the program, identifies eligibility requirements, describes the proposal evaluation and award selection process, and provides other information to assist those interested in participating in NASA's SBIR program. It also identifies, in Section 8.0, the technical topics and subtopics in which SBIR Phase 1 proposals are solicited in 1992. These topics and subtopics cover a broad range of current NASA interests but do not necessarily include all areas in which NASA plans or currently conducts research. The NASA SBIR program seeks innovative approaches that respond to the needs, technical requirements, and new opportunities described in the subtopics. The focus is on innovation through the use of emerging technologies, novel applications of existing technologies, exploitation of scientific breakthroughs, or new capabilities or major improvements to existing technologies. NASA plans to select about 320 high-quality research or research and development proposals for Phase 1 contract awards on the basis of this Solicitation. Phase 1 contracts are normally six months in duration and funded up to $50,000, including profit. Selections will be based on the competitive merits of the offers and on NASA needs and priorities

Intelligent Computing: The Latest Advances, Challenges and Future

Computing is a critical driving force in the development of human civilization. In recent years, we have witnessed the emergence of intelligent computing, a new computing paradigm that is reshaping traditional computing and promoting digital revolution in the era of big data, artificial intelligence and internet-of-things with new computing theories, architectures, methods, systems, and applications. Intelligent computing has greatly broadened the scope of computing, extending it from traditional computing on data to increasingly diverse computing paradigms such as perceptual intelligence, cognitive intelligence, autonomous intelligence, and human-computer fusion intelligence. Intelligence and computing have undergone paths of different evolution and development for a long time but have become increasingly intertwined in recent years: intelligent computing is not only intelligence-oriented but also intelligence-driven. Such cross-fertilization has prompted the emergence and rapid advancement of intelligent computing. Intelligent computing is still in its infancy and an abundance of innovations in the theories, systems, and applications of intelligent computing are expected to occur soon. We present the first comprehensive survey of literature on intelligent computing, covering its theory fundamentals, the technological fusion of intelligence and computing, important applications, challenges, and future perspectives. We believe that this survey is highly timely and will provide a comprehensive reference and cast valuable insights into intelligent computing for academic and industrial researchers and practitioners

NASA Tech Briefs, October 2001

Topics include: special coverage section on composites and plastics, electronic components and systems, software, mechanics, physical sciences, information sciences, book and reports, and a special sections of Photonics Tech Briefs and Motion Control Tech Briefs

NASA Tech Briefs, November 2002

Topics include: a technology focus on engineering materials, electronic components and systems, software, mechanics, machinery/automation, manufacturing, bio-medical, physical sciences, information sciences book and reports, and a special section of Photonics Tech Briefs

Machine learning based anomaly detection for industry 4.0 systems.

223 p.This thesis studies anomaly detection in industrial systems using technologies from the Fourth Industrial Revolution (4IR), such as the Internet of Things, Artificial Intelligence, 3D Printing, and Augmented Reality. The goal is to provide tools that can be used in real-world scenarios to detect system anomalies, intending to improve production and maintenance processes. The thesis investigates the applicability and implementation of 4IR technology architectures, AI-driven machine learning systems, and advanced visualization tools to support decision-making based on the detection of anomalies. The work covers a range of topics, including the conception of a 4IR system based on a generic architecture, the design of a data acquisition system for analysis and modelling, the creation of ensemble supervised and semi-supervised models for anomaly detection, the detection of anomalies through frequency analysis, and the visualization of associated data using Visual Analytics. The results show that the proposed methodology for integrating anomaly detection systems in new or existing industries is valid and that combining 4IR architectures, ensemble machine learning models, and Visual Analytics tools significantly enhances theanomaly detection processes for industrial systems. Furthermore, the thesis presents a guiding framework for data engineers and end-users

Unleashing the power of artificial intelligence for climate action in industrial markets

Artificial Intelligence (AI) is a game-changing capability in industrial markets that can accelerate humanity's race against climate change. Positioned in a resource-hungry and pollution-intensive industry, this study explores AI-powered climate service innovation capabilities and their overall effects. The study develops and validates an AI model, identifying three primary dimensions and nine subdimensions. Based on a dataset in the fast fashion industry, the findings show that the AI-powered climate service innovation capabilities significantly influence both environmental and market performance, in which environmental performance acts as a partial mediator. Specifically, the results identify the key elements of an AI-informed framework for climate action and show how this can be used to develop a range of mitigation, adaptation and resilience initiatives in response to climate change

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse