scholarly journals Towards Experimental Handbooks in Catalysis

2020 ◽  
Vol 63 (19-20) ◽  
pp. 1683-1699
Author(s):  
Annette Trunschke ◽  
Giulia Bellini ◽  
Maxime Boniface ◽  
Spencer J. Carey ◽  
Jinhu Dong ◽  
...  
Keyword(s):  
Heterogeneous Catalysis ◽  
High Performance ◽  
Best Practice ◽  
Data Science ◽  
Theoretical Description ◽  
Scientific Data ◽  
Oxidation Catalysis ◽  
Mixed Metal Oxide ◽  
Data Generation ◽  
Mixed Metal Oxide Catalysts

AbstractThe “Seven Pillars” of oxidation catalysis proposed by Robert K. Grasselli represent an early example of phenomenological descriptors in the field of heterogeneous catalysis. Major advances in the theoretical description of catalytic reactions have been achieved in recent years and new catalysts are predicted today by using computational methods. To tackle the immense complexity of high-performance systems in reactions where selectivity is a major issue, analysis of scientific data by artificial intelligence and data science provides new opportunities for achieving improved understanding. Modern data analytics require data of highest quality and sufficient diversity. Existing data, however, frequently do not comply with these constraints. Therefore, new concepts of data generation and management are needed. Herein we present a basic approach in defining best practice procedures of measuring consistent data sets in heterogeneous catalysis using “handbooks”. Selective oxidation of short-chain alkanes over mixed metal oxide catalysts was selected as an example.

scholarly journals Best Practice Data Life Cycle Approaches for the Life Sciences

2017 ◽  
Author(s):  
Philippa C. Griffin ◽  
Jyoti Khadake ◽  
Kate S. LeMay ◽  
Suzanna E. Lewis ◽  
Sandra Orchard ◽  
...  
Keyword(s):  
Life Cycle ◽  
Data Management ◽  
Best Practice ◽  
Data Science ◽  
Management Practices ◽  
Life Sciences ◽  
Heterogeneous Data ◽  
Clear Understanding ◽  
Data Generation ◽  
Data Life Cycle

AbstractThroughout history, the life sciences have been revolutionised by technological advances; in our era this is manifested by advances in instrumentation for data generation, and consequently researchers now routinely handle large amounts of heterogeneous data in digital formats. The simultaneous transitions towards biology as a data science and towards a ‘life cycle’ view of research data pose new challenges. Researchers face a bewildering landscape of data management requirements, recommendations and regulations, without necessarily being able to access data management training or possessing a clear understanding of practical approaches that can assist in data management in their particular research domain.Here we provide an overview of best practice data life cycle approaches for researchers in the life sciences/bioinformatics space with a particular focus on ‘omics’ datasets and computer-based data processing and analysis. We discuss the different stages of the data life cycle and provide practical suggestions for useful tools and resources to improve data management practices.

scholarly journals Best practice data life cycle approaches for the life sciences

F1000Research ◽  
2018 ◽  
Vol 6 ◽  
pp. 1618 ◽  
Author(s):  
Philippa C. Griffin ◽  
Jyoti Khadake ◽  
Kate S. LeMay ◽  
Suzanna E. Lewis ◽  
Sandra Orchard ◽  
...  
Keyword(s):  
Life Cycle ◽  
Data Management ◽  
Best Practice ◽  
Data Science ◽  
Management Practices ◽  
Life Sciences ◽  
Heterogeneous Data ◽  
Clear Understanding ◽  
Data Generation ◽  
Data Life Cycle

Throughout history, the life sciences have been revolutionised by technological advances; in our era this is manifested by advances in instrumentation for data generation, and consequently researchers now routinely handle large amounts of heterogeneous data in digital formats. The simultaneous transitions towards biology as a data science and towards a ‘life cycle’ view of research data pose new challenges. Researchers face a bewildering landscape of data management requirements, recommendations and regulations, without necessarily being able to access data management training or possessing a clear understanding of practical approaches that can assist in data management in their particular research domain. Here we provide an overview of best practice data life cycle approaches for researchers in the life sciences/bioinformatics space with a particular focus on ‘omics’ datasets and computer-based data processing and analysis. We discuss the different stages of the data life cycle and provide practical suggestions for useful tools and resources to improve data management practices.

scholarly journals Best practice data life cycle approaches for the life sciences

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 1618 ◽  
Author(s):  
Philippa C. Griffin ◽  
Jyoti Khadake ◽  
Kate S. LeMay ◽  
Suzanna E. Lewis ◽  
Sandra Orchard ◽  
...  
Keyword(s):  
Life Cycle ◽  
Data Management ◽  
Best Practice ◽  
Data Science ◽  
Management Practices ◽  
Life Sciences ◽  
Heterogeneous Data ◽  
Clear Understanding ◽  
Data Generation ◽  
Data Life Cycle

Throughout history, the life sciences have been revolutionised by technological advances; in our era this is manifested by advances in instrumentation for data generation, and consequently researchers now routinely handle large amounts of heterogeneous data in digital formats. The simultaneous transitions towards biology as a data science and towards a ‘life cycle’ view of research data pose new challenges. Researchers face a bewildering landscape of data management requirements, recommendations and regulations, without necessarily being able to access data management training or possessing a clear understanding of practical approaches that can assist in data management in their particular research domain. Here we provide an overview of best practice data life cycle approaches for researchers in the life sciences/bioinformatics space with a particular focus on ‘omics’ datasets and computer-based data processing and analysis. We discuss the different stages of the data life cycle and provide practical suggestions for useful tools and resources to improve data management practices.

Performance Management Transformation

2020 ◽  
Keyword(s):  
Organizational Performance ◽  
Performance Management ◽  
High Performance ◽  
Best Practice ◽  
Call To Action ◽  
Daily Work ◽  
The Past ◽  
Great Debate ◽  
The Subject ◽  
New Research

No other talent process has been the subject of such great debate and emotion as performance management (PM). For decades, different strategies have been tried to improve PM processes, yielding an endless cycle of reform to capture the next “flavor-of-the-day” PM trend. The past 5 years, however, have brought novel thinking that is different from past trends. Companies are reducing their formal processes, driving performance-based cultures, and embedding effective PM behavior into daily work rather than relying on annual reviews to drive these. Through case studies provided from leading organizations, this book illustrates the range of PM processes that companies are using today. These show a shift away from adopting someone else’s best practice; instead, companies are designing bespoke PM processes that fit their specific strategy, climate, and needs. Leading PM thought leaders offer their views about the state of PM today, what we have learned and where we need to focus future efforts, including provocative new research that shows what matters most in driving high performance. This book is a call to action for talent management professionals to go beyond traditional best practice and provide thought leadership in designing PM processes and systems that will enhance both individual and organizational performance.

Mixed Metal Oxide Catalysts for Rechargeable Lithium-Air Batteries

2019 ◽  
Vol 41 (41) ◽  
pp. 167-174 ◽  
Author(s):  
Venkataramani Anandan ◽  
Robert Kudla ◽  
Andy Drews ◽  
Jim Adams ◽  
Mohan Karulkar
Keyword(s):  
Metal Oxide ◽  
Oxide Catalysts ◽  
Mixed Metal Oxide ◽  
Metal Oxide Catalysts ◽  
Mixed Metal ◽  
Mixed Metal Oxide Catalysts ◽  
Lithium Air Batteries

scholarly journals Nutrition for Travel: From Jet lag To Catering

2019 ◽  
Vol 29 (2) ◽  
pp. 228-235 ◽  
Author(s):  
Shona L. Halson ◽  
Louise M. Burke ◽  
Jeni Pearce
Keyword(s):  
High Performance ◽  
Best Practice ◽  
Light Exposure ◽  
International Travel ◽  
The Body ◽  
Personal Hygiene ◽  
Jet Lag ◽  
Group Management ◽  
Food Needs ◽  
Eating Practices

Domestic and international travel represents a regular challenge to high-performance track-and-field athletes, particularly when associated with the pressure of competition or the need to support specialized training (e.g., altitude or heat adaptation). Jet lag is a challenge for transmeridian travelers, while fatigue and alterations to gastrointestinal comfort are associated with many types of long-haul travel. Planning food and fluid intake that is appropriate to the travel itinerary may help to reduce problems. Resynchronization of the body clock is achieved principally through manipulation of zeitgebers, such as light exposure; more investigation of the effects of melatonin, caffeine, and the timing/composition of meals will allow clearer guidelines for their contribution to be prepared. At the destination, the athlete, the team management, and catering providers each play a role in achieving eating practices that support optimal performance and success in achieving the goals of the trip. Although the athlete is ultimately responsible for his or her nutrition plan, best practice by all parties will include pretrip consideration of risks around the quality, quantity, availability, and hygiene standards of the local food supply and the organization of strategies to deal with general travel nutrition challenges as well as issues that are specific to the area or the special needs of the group. Management of buffet-style eating, destination-appropriate protocols around food/water and personal hygiene, and arrangement of special food needs including access to appropriate nutritional support between the traditional “3 meals a day” schedule should be part of the checklist.

scholarly journals Mechanism of selective benzene hydroxylation catalyzed by iron-containing zeolites

2018 ◽  
Vol 115 (48) ◽  
pp. 12124-12129 ◽  
Author(s):  
Benjamin E. R. Snyder ◽  
Max L. Bols ◽  
Hannah M. Rhoda ◽  
Pieter Vanelderen ◽  
Lars H. Böttger ◽  
...  
Keyword(s):  
High Activity ◽  
Active Site ◽  
Active Sites ◽  
High Performance ◽  
Density Functional ◽  
Catalyst Deactivation ◽  
Density Functional Theory Calculations ◽  
Oxidation Catalysis ◽  
Spectroscopic Techniques ◽  
Benzene Hydroxylation

A direct, catalytic conversion of benzene to phenol would have wide-reaching economic impacts. Fe zeolites exhibit a remarkable combination of high activity and selectivity in this conversion, leading to their past implementation at the pilot plant level. There were, however, issues related to catalyst deactivation for this process. Mechanistic insight could resolve these issues, and also provide a blueprint for achieving high performance in selective oxidation catalysis. Recently, we demonstrated that the active site of selective hydrocarbon oxidation in Fe zeolites, named α-O, is an unusually reactive Fe(IV)=O species. Here, we apply advanced spectroscopic techniques to determine that the reaction of this Fe(IV)=O intermediate with benzene in fact regenerates the reduced Fe(II) active site, enabling catalytic turnover. At the same time, a small fraction of Fe(III)-phenolate poisoned active sites form, defining a mechanism for catalyst deactivation. Density-functional theory calculations provide further insight into the experimentally defined mechanism. The extreme reactivity of α-O significantly tunes down (eliminates) the rate-limiting barrier for aromatic hydroxylation, leading to a diffusion-limited reaction coordinate. This favors hydroxylation of the rapidly diffusing benzene substrate over the slowly diffusing (but more reactive) oxygenated product, thereby enhancing selectivity. This defines a mechanism to simultaneously attain high activity (conversion) and selectivity, enabling the efficient oxidative upgrading of inert hydrocarbon substrates.

Establishment of a Competitive Additive Manufacturing Workshop

2016 ◽  
Author(s):  
Paul Ryan ◽  
Jan Schwerdtfeger ◽  
Markus Rodermann
Keyword(s):  
Additive Manufacturing ◽  
Gas Turbines ◽  
High Performance ◽  
Best Practice ◽  
Process Development ◽  
Process Efficiency ◽  
Development Effort ◽  
Industrial Gas Turbines ◽  
High Level ◽  
Design And Manufacture

Compared to conventional manufacturing processes, additive manufacturing offers a degree of freedom that has the potential to revolutionize the turbine components supply chain. Additive manufacturing facilitates the design and manufacture of highly complex components in high performance materials with features that cannot currently be realized with other processes. In addition, shorter development and manufacturing lead-times are possible due to the flexibility of 3D based processing and the absence of expensive, complicated molds or dies. Having been confined for many years to rapid prototyping or R&D applications, additive manufacturing is now making the move to the factory floor. However, a dearth of manufacturing experience makes the development effort and risk of costly mistakes a deterrent for many organizations that would otherwise be interested in exploring the benefits of additive manufacturing. A former manufacturer of industrial gas turbines recently established an additive manufacturing workshop designed to deliver highly complex engine-ready components that can contribute to increased performance of the gas turbine. A strong emphasis on process validation and implementation of the organization’s best practice Lean and Quality methodologies has laid solid foundations for a highly capable manufacturing environment. This paper describes the approach taken to ensure that the workshop achieves a high level of operational excellence. Process development topics explored in the paper include the following: • Planning of process flow and cell layout to permit the maximum lean performance • Strategy used to determine machine specification and selection method. • Assessment of process capability • Influence of design for manufacture on process efficiency and product quality • Experience gained during actual production of first commercial components

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