So, You Want to Have a Nanofab? Shared-Use Nanofabrication and Characterization Facilities: Cost-of-Ownership, Toolset, Utilization, and Lessons Learned.

Nanofabrication/characterization facilities enable research and development activities across a host of science and engineering disciplines. The collection of tools and supporting infrastructure necessary to construct, image, and measure micro- and nanoscale materials, devices, and systems is complex and expensive to establish, and it is costly to maintain and optimize. As a result, these facilities are typically operated in a shared-use mode. We discuss the key factors that must be considered to successfully create and sustain such facilities. These include the need for long-term vision and institutional commitment, and the hands-on involvement of managers in facility operations. We consider startup, operating, and recapitalization costs, together with algorithms for cost recovery and tool-time allocation. The acquisition of detailed and comprehensive project and tool-utilization data is essential for understanding and optimizing facility operations. Only such a data-driven decision-making approach can maximize facility impact on institutional goals. We illustrate these concepts using the National Institute of Standards and Technology (NIST) NanoFab as our test case, but the methodologies and resources presented here should be useful to all those faced with this challenging task.

Electric light commercial vehicles: Are they the sleeping giant of electromobility?

Transport emissions need to be drastically decreased in order to put Europe on a path towards a long-term climate neutrality. Commercial transport, and especially last mile delivery is expected to grow because of the rise of e-commerce. In this frame, electric light commercial vehicles (eLCVs) can be a promising low-emission solution. Literature holistically analysing the potential of eLCVs as well as related support policies is sparse. This paper attempts to close this research gap. To this aim, the total cost of ownership (TCO) comparisons for eLCVs and benchmark vehicles are performed and support measures that target the improvement of the eLCV TCO are analysed. Various eLCV deployment scenarios until 2030 are explored and their impact on carbon dioxide (CO2) and other pollutant emissions as well as pollutant concentrations are calculated. It is found that while in several European Union (EU) countries eLCVs are already cost competitive, because of fiscal support, some remaining market barriers need to be overcome to pave the way to mass market deployment of eLCVs. High penetration of eLCVs alone can lead to a reduction of total transport CO2 emissions by more than 3% by 2030. For pollutant emissions, such as nitrogen oxide (NOx) and particulate matter (PM), the reduction would be equal or even higher. In the case of PM, this can translate to reductions in concentrations by nearly 2% in several urban areas by 2030. Carefully designed support policies could help to ensure that the potential of eLCVs as a low-emission alternative is fully leveraged in the EU.

Flying cars economically favor battery electric over fuel cell and internal combustion engine.

Flying cars, essentially vertical takeoff and landing aircraft (VTOL), are an emerging, disruptive technology that is expected to reshape future transportation. VTOLs can be powered by battery electric, fuel cell, or internal combustion engine, which point to entirely different needs for industry expertise, research & development, supply chain, and infrastructure supports. A pre-analysis of the propulsion technology competition is crucial to avoid potential wrong directions of research, investment, and policy making efforts. In this study, we comprehensively examined the cost competitiveness of the three propulsion technologies. Here we show that battery electric has already become the lowest-cost option for below-200-km VTOL applications, covering intra-city and short-range inter-city travels. This cost advantage can be robustly strengthened in the long term under various technology development scenarios. Battery energy density improvement is the key to reducing cost. In particular, a 600 Wh/kg battery energy density provides battery electric with all-range cost advantage, and promises high return in business. Fuel cell and internal combustion engine, under certain technology development scenarios, can obtain cost advantage in long-range applications, but face intense competition from ground transportation such as high-speed rail. The findings suggest a battery-electric-prioritized VTOL development strategy, and the necessity of developing VTOL-customized high-energy-density batteries.

A comparative total cost of ownership analysis of heavy duty on-road and off-road vehicles powered by hydrogen, electricity, and diesel.

This study investigated the cost competitiveness, using total cost of ownership (TCO) analysis, of hydrogen fuel cell electric vehicles (FCEVs) in heavy duty on and off-road fleet applications as a key enabler in the decarbonisation of the transport sector and compares results to battery electric vehicles (BEVs) and diesel internal combustion engine vehicles (ICEVs). Assessments were carried out for a present day (2021) scenario, and a sensitivity analysis assesses the impact of changing input parameters on FCEV TCO. This identified conditions under which FCEVs become competitive. A future outlook is also carried out examining the impact of time-sensitive parameters on TCO, when net zero targets are to be reached in the UK and EU. Several FCEVs are cost competitive with ICEVs in 2021, but not BEVs, under base case conditions. However, FCEVs do have potential to become competitive with BEVs under specific conditions favouring hydrogen, including the application of purchase grants and a reduced hydrogen price. By 2050, a number of FCEVs running on several hydrogen scenarios show a TCO lower than ICEVs and BEVs using rapid chargers, but for the majority of vehicles considered, BEVs remain the lowest in cost, unless specific FCEV incentives are implemented. This paper has identified key factors hindering the deployment of hydrogen and conducted comprehensive TCO analysis in heavy duty on and off-road fleet applications. The output has direct contribution to the decarbonisation of the transport sector.

Cost Profile of Membranes That Use Polymers of Intrinsic Microporosity (PIMs).

Assessing the financial impact of polymers of intrinsic microporosity, otherwise known as PIMs, at the lab scale has been impeded by the absence of a holistic approach that would envelop all related financial parameters, and most importantly any indirect costs, such as laboratory accidents that have been consistently neglected and undervalued in past assessments. To quantify the cost of PIMs in relation to the risks befalling a laboratory, an innovative cost evaluation approach was designed. This approach consists of three stages. Firstly, a two-fold "window of opportunity" (WO) theory is suggested, dividing the total cost profile into two segments, followed up by a qualitative risk analysis to establish the potential cost components. The last stage builds on a total cost of ownership model, incorporating the two types of WO. The total cost of ownership (TCO) approach was selected to ascertain the costs and construct the cost profile of PIMs, according to laboratory experimental data. This model was applied to the synthesis and physicochemical characterization processes. The quantitative analysis revealed that the most influential parameters for synthesis are accidents and energy costs. This is in contrast with the physicochemical characterization process, where the most important determinant is the energy cost.

Optimization data on total cost of ownership for conventional and battery electric heavy vehicles driven by humans and by automated driving systems.

In road freight transport, the emerging technologies such as automated driving systems improve the mobility, productivity and fuel efficiency. However, the improved efficiency is not enough to meet environmental goals due to growing demands of transportation. Combining automated driving systems and electrified propulsion can substantially improve the road freight transport efficiency. However, the high cost of the battery electric heavy vehicles is a barrier hindering their adoption by the transportation companies. Automated driving systems, requiring no human driver on-board, make the battery electric heavy vehicles competitive to their conventional counterparts in a wider range of transportation tasks and use cases compared to the vehicles with human drivers. The presented data identify transportation tasks where the battery electric heavy vehicles driven by humans or by automated driving systems have lower cost of ownership than their conventional counterparts. The data were produced by optimizing the vehicle propulsion system together with the loading/unloading schemes and charging powers, with the objective of minimizing the total cost of ownership on 3072 different transportation scenarios, according to research article "Impact of automated driving systems on road freight transport and electrified propulsion of heavy vehicles" (Ghandriz et al., 2020) [2]. The data help understanding the effects of traveled distance, road hilliness and vehicle size on the total cost of ownership of the vehicles with different propulsion and driving systems. Data also include sensitivity tests on the uncertain parameters.

Cost of ownership assessment for a da Vinci robot based on US real-world data.

BACKGROUND: Despite growth of robotic surgery, published literature lacks assessment of the cost of ownership (CoO) of a da Vinci robot by surgical service line and the associated benefit such data provides. METHODS: Based on real-world data (RWD) from 14 US hospitals and ≈6000 da Vinci robotic cases, CoO was assessed using all relevant fixed and variable cost components, calculated by surgical service line. RESULTS: At a representative hospital with an efficient robotic program (n = 424 cases), the weighted average fixed cost per case was $984. Weighted average variable cost per case was $8025 (range: $3325 for Cholecystectomy-multiport, to $16 986 for Rectal Resection). Assessing weighted average by case, main variable cost drivers were non-da Vinci supplies (49.5%), staff costs (28.6%), and da Vinci supplies (21.9%). CONCLUSIONS: Case mix, annual robotic case volumes, and cut-to-close/patient-in-room time by surgical service line represent core variables influencing robotic program CoO, which help drive profitable program management.