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#materialsscience

3 Beiträge2 Beteiligte0 Beiträge heute

'Revealing unipolar thermoelectric performance in bipolar polymer' - a 'National Science Open' article published by @EDPSciences on #ScienceOpen:

🔗 scienceopen.com/document?vid=b

ScienceOpenRevealing unipolar thermoelectric performance in bipolar polymer<p xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" class="first" dir="auto" id="d10034242e292">Conjugated polymers are attracting increased attention as thermoelectric (TE) materials for energy harvesting applications in low-temperature regimes. However, in many doped ambipolar polymers, the simultaneous transport of both holes and electrons under temperature gradients leads to an offset in thermopower ( <i>S</i>), which suppresses TE performance and complicates intrinsic understanding of bipolar TE conversion. Herein, we quantitatively investigate the p-n polarity transition in FeCl <sub>3</sub>-doped bipolar PDPP4T films by measuring the magneto-thermoelectric Nernst effect, combined with Hall and Seebeck effect analyses. Notably, behind the <i>S =</i> 0 point, we observe a significant thermopower offset originating from the balancing contributions of electrons and holes. This countervailing thermopower value is extracted to reach 400 μV K <sup>−1</sup>, which could ideally produce an estimated maximum unipolar ZT of 0.24 at 175 K, due to rising polaron states and reduced carrier concentration. Our findings reveal the extraordinary hidden unipolar TE performance achievable in doped bipolar polymer towards ultra-low-temperatures thermoelectric. </p>

'Self-confined electrohydrodynamic printing on micro-structured substrate for flexible transparent electrodes with embedded metal mesh' - a 'National Science Open' article published by @EDPSciences on #ScienceOpen:

🔗 scienceopen.com/document?vid=a

ScienceOpenSelf-confined electrohydrodynamic printing on micro-structured substrate for flexible transparent electrodes with embedded metal mesh<p xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" class="first" dir="auto" id="d10034240e234">Flexible transparent electrodes (FTEs) have attracted much attention due to their advantages of excellent optical/electrical conductivities and good mechanical fatigue strength. However, their fabrication presents several challenges, including fabricating wires with a high aspect ratio and sufficient tensile resistance. In this study, an embedded Ag/Cu metal-mesh FTE with a high figure of merit 24,708 (sheet resistance 0.08 Ω/sq and 83.4% optical transmittance) is fabricated through the proposed method called self-confined electrohydrodynamic printing and selective electroplating of Cu. This method employs structured surfaces and patterned hydrophilic/hydrophobic properties to enable highly controllable deposition of solutions (e.g., positioning, line width, consistency), allowing the complete filling of imprinted microgrooves with a high aspect ratio of 2 (e.g., 4 μm width and 8 μm depth) with Ag/Cu metal. Moreover, the resulting FTEs demonstrate good resistance stability under repetitive bending and stretching and exhibit excellent performance in flexible transparent heaters and electromagnetic shielding films. </p>

"The Massachusetts Institute of Technology said Friday it can no longer stand behind a widely circulated paper on artificial intelligence written by a doctoral student in its economics program.

The paper said that the introduction of an AI tool in a materials-science lab led to gains in new discoveries, but had more ambiguous effects on the scientists who used it.

MIT didn’t name the student in its statement Friday, but it did name the paper. That paper, by Aidan Toner-Rodgers, was covered by The Wall Street Journal and other media outlets.
In a press release, MIT said it “has no confidence in the provenance, reliability or validity of the data and has no confidence in the veracity of the research contained in the paper.”

The university said the author of the paper is no longer at MIT.
Toner-Rodgers didn’t respond to requests for comment.

The paper said that after an AI tool was implemented at a large materials-science lab, researchers discovered significantly more materials—a result that suggested that, in certain settings, AI could substantially improve worker productivity. But it also showed that most of the productivity gains went to scientists who were already highly effective, and that overall the AI tool made scientists less happy about their work."

wsj.com/tech/ai/mit-says-it-no

#AI#GenerativeAI#MIT