These issues are especially prominent in aqueous electrolytes, as hydrogen evolution reaction readily occurs at such low potentials and water molecules act as an oxygen source for oxide film formation. [4] Remarkably, two recent works have seemingly been able to address these challenges by engineering a solid electrolyte interphase (SEI) on Al, either "in situ" by 5 m (mol kg −1 ) Al(OTF) 3 (aluminum triflate) water-in-salt electrolyte (Al-WiSE), [5] or "ex situ" by IL pretreatment. [6] These two pioneering studies have since led a surge in reports of fully reversible aqueous AMBs (AAMB). [7][8][9][10][11][12] There are however concerns regarding the validity and effectiveness of the two SEI engineering methods. First, there has not been any experimental or computational characterizations that support an SEI can form on Al from 5 m Al(OTF) 3 , especially given its low concentration compared with alkali metal WiSE. [13,14] The only reason an SEI is believed to exist is by observing a delayed onset of hydrogen evolution reaction on a glassy carbon electrode, which is not a reliable indicator given its high hydrogen evolution reaction overpotentials, particularly relative to Al. [15] On the other hand, while it is proven that IL treatment can form a residue layer on Al, its fundamental ion and electron transport properties as well as its stability in aqueous electrolytes were not investigated; hence, its ability to function as an artificial SEI, is practically unknown. To address these concerns, in this work we critically evaluated each SEI engineering method, elucidated their underlying mechanisms, and revealed whether they can allow for truly rechargeable AAMBs.

The critical need for cost‐effective and sustainable large‐scale battery technologies for harvesting renewable energy has led to a new research wave on novel batteries made of low‐cost, high‐abundance, high‐performance, and safe components. Among the emerging candidates for post‐lithium‐ion batteries, aluminum‐based batteries are particularly promising due to the high theoretical capacities, low cost, and high abundance of raw materials. Most advanced nonaqueous rechargeable Al batteries rely on costly dialkylimidazolium chloride‐based chloroaluminate ionic liquids and this added cost inevitably diminishes various benefits of utilizing Al as the anode material. Here, a high‐performance Al battery made of Al anode, graphene nanoplatelets (GNPs) cathode, and a cost‐effective AlCl3‐trimethylamine hydrochloride (AlCl3‐TMAHCl) ionic liquid electrolyte is reported. The battery delivers a high specific capacity of 134 mAh g−1 at 2000 mA g−1 while maintaining Coulombic efficiency (CE) above 98% over 3000 cycles. Moreover, it delivers a specific capacity of 83 mAh g−1 with a CE of 97% under ultrafast charging at 4000 mA g−1 (1 min) and slow discharging at 100 mA g−1 (50 min) conditions. Considering the low cost and high performance, AlCl3‐TMAHCl electrolyte opens up a new avenue for the development of next‐generation Al batteries.

Machine learning (ML) is a versatile technique to rapidly and efficiently generate insights from multidimensional data. It offers a much-needed avenue to accelerate the exploration and investigation of new materials to address timesensitive global challenges such as climate change. The availability of large datasets in recent years has enabled the development of ML algorithms for various applications including experimental/device optimization and material discovery. This perspective provides a summary of the recent applications of ML in material discovery in a range of fields, from optoelectronics to batteries and electrocatalysis, as well as an overview of the methods behind these advances. The paper also attempts to summarize some key challenges and trends in current research methodologies.

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Titanium alloys are advanced lightweight materials, indispensable for many critical applications1,2. The mainstay of the titanium industry is the α–β titanium alloys, which are formulated through alloying additions that stabilize the α and β phases3–5. Our work focuses on harnessing two of the most powerful stabilizing elements and strengtheners for α–β titanium alloys, oxygen and iron1–5, which are readily abundant. However, the embrittling effect of oxygen6,7, described colloquially as ‘the kryptonite to titanium’8, and the microsegregation of iron9 have hindered their combination for the development of strong and ductile α–β titanium–oxygen–iron alloys. Here we integrate alloy design with additive manufacturing (AM) process design to demonstrate a series of titanium–oxygen–iron compositions that exhibit outstanding tensile properties. We explain the atomic-scale origins of these properties using various characterization techniques. The abundance of oxygen and iron and the process simplicity for net-shape or near-net-shape manufacturing by AM make these α–β titanium–oxygen–iron alloys attractive for a diverse range of applications. Furthermore, they offer promise for industrial-scale use of off-grade sponge titanium or sponge titanium–oxygen–iron10,11, an industrial waste product at present. The economic and environmental potential to reduce the carbon footprint of the energy-intensive sponge titanium production12 is substantial.