unswsydney OP t1_izz9h5g wrote

Happy holidays r/Futurology,

We're stoked to share new research from our resident solid-state chemistry expert, Associate Professor Neeraj Sharma.

Alongside Professor Naoaki Yabuuchi from Yokohama National University, A/P Sharma has investigated a new type of positive electrode material with unprecedented stability for solid-state batteries.

The researchers discovered the material may offer a high capacity, safe and durable alternative to lithium-ion batteries - properties that make the material an excellent candidate for use in electric vehicles.

The team's work has been published in Nature Materials if you're keen to take a read: https://www.nature.com/articles/s41563-022-01421-z


unswsydney OP t1_iy1v3y4 wrote

Hi, u/chucksutherland - Here's a response from Dr Cristina Martínez-Lombilla


>This fact does not necessarily say anything about the frequency of events (i.e. interactions between galaxies). However, partial tidal stripping of the stars in the outer parts of galaxies (which is what we propose as the main IGL formation driver) is a very likely process as it is more easy to strip some stars from the outer parts of galaxies than a total disruption of a whole galaxy or a major merger, which are other possible scenarios. So, at least for the moment, we cannot say how many interaction events have suffered this group os galaxies but we can say that partial tidal stripping of galaxies if a common process.


unswsydney OP t1_ixjhwkx wrote

Hi r/science!

Researchers from our School of Biotechnology and Biomolecular Sciences have become the first in the world to use CRISPR gene-editing technology to alter a flagellar motor.

They used synthetic biology techniques to engineer a sodium motor onto the genome to create a sodium-driven swimming bacteria. They then tested and tracked the bacteria’s ability to adapt when the environment was starved of sodium, showing the stators were able to rapidly self-repair the flagellar motor and restore movement.

Associate Professor Matthew Baker, a co-author of the paper said the study’s findings can help us better understand the origin of molecular motors in mechanistic detail, how they came together and how they adapt.

Here's a link to the published research if you're keen on having a read: https://www.science.org/doi/10.1126/sciadv.abq2492


unswsydney OP t1_iwiyh4w wrote

Hi r/science, cheers for having us!

A joint study from UNSW and the University of Melbourne has found existing dams will be at greater risk under climate change than what is currently assumed.

Lead author on the research, Johan Visser, said, "some of the worst floods around the world were due to extreme storms overwhelming a dam, causing it to fail and release a wall of water downstream.”

The study was published in Water Resources Research today and is available to read: https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2022WR032247


unswsydney OP t1_iu20zce wrote

Hi,u/Corsair4! Here's a response from Professor François Ladouceur!


>Fascinating indeed and yes, we are also addressing the reverse operation and will be publishing this very soon. It is based on the simple idea of micro-voltaic cells or if you prefer, we have shrunk down solar panels to micron-square size and managed to generate enough voltage to stimulate nerves. Hence we can both “read” and “write” using light. No optogenetics needed.


unswsydney OP t1_itx3cpz wrote

Hi r/Futurology, cheers for having us!

A team of UNSW researchers led by Professor François Ladouceur have demonstrated that sensors built using liquid crystal and integrated optics technologies can measure neural activity using light – rather than electricity – which could lead to a complete reimagining of medical technologies like nerve-operated prosthetics and brain-machine interfaces.

The team's research has been published in the Journal of Neural Engineering: https://iopscience.iop.org/article/10.1088/1741-2552/ac8ed6


unswsydney OP t1_ir7qnvu wrote

Hi r/Futurology, cheers for having us!

New research from UNSW PhD candidate, Karen Kusuma has explored machine learning models and their ability to predict future suicidal behaviours and thoughts.

Published in the Journal of Psychiatric Research, Kusuma's research found machine learning models outperformed traditional risk prediction models in predicting suicide-related outcomes, which have traditionally performed poorly.

Here's a link to the published research if you're keen to read the full findings: https://www.sciencedirect.com/science/article/abs/pii/S0022395622005416