科学20241018出版一周论文导读
《科学》（20241018出版）一周论文导读
Science, 18 OCT 2024, Volume 386 Issue 6719
《科学》2024年10月18日，第386卷，6719期
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材料科学Material Sciences
Capacity recovery by transient voltage pulse in silicon-anode batteries
硅阳极电池瞬态电压脉冲的容量恢复
▲ 作者：YUFEI YANG, SRIJA BISWAS, RONG XU et al.
▲链接：
https://www.science.org/doi/10.1126/science.adn1749
▲摘要：
我们开发了一种方法来回收硅电极中隔离的活性材料，并使用电压脉冲将隔离的锂硅（LixSi）颗粒重新连接到导电网络中。通过使用5秒脉冲，我们在Li-Si和Si–磷酸铁锂（Si-LFP）电池中实现了30%以上的容量恢复。
通过多个脉冲维持和复制恢复的电容量，并能提供恒定的容量优势。我们验证了恢复机制是中性分离的LixSi粒子在局部非均匀电场下的运动，这种现象被称为介电电泳。
▲ Abstract：
We developed an approach to substantially recover the isolated active materials in silicon electrodes and used a voltage pulse to reconnect the isolated lithium-silicon (LixSi) particles back to the conductive network. Using a 5-second pulse, we achieved >30% of capacity recovery in both Li-Si and Si–lithium iron phosphate (Si-LFP) batteries. The recovered capacity sustains and replicates through multiple pulses, providing a constant capacity advantage. We validated the recovery mechanism as the movement of the neutral isolated LixSi particles under a localized nonuniform electric field, a phenomenon known as dielectrophoresis.
Multicore memristor from electrically readable nanoscopic racetracks
来自电可读纳米级赛道的多核忆阻器
▲ 作者：JAE-CHUN JEON, ANDREA MIGLIORINI et al.
▲链接：
https://www.science.org/doi/10.1126/science.adh3419
▲摘要：
在这项研究中，我们利用一组集成在赛道中的异常霍尔探测器，展示了纳米赛道中多个移动畴壁的空间分辨率优于40 nm的电跟踪系统。
来自霍尔探测器的电时序信号允许对一个或多个畴壁的动态进行静态和动态相空间可视化，这些畴壁可以通过多核忆阻器模型展示。在赛道中，畴壁动力学和随机性甚至可以控制到深亚微米尺度。
▲ Abstract：
In this study, we demonstrated the electrical tracking with a spatial resolution of better than 40 nm of multiple mobile domain walls in nanoscopic racetracks, using a set of anomalous Hall detectors integrated into the racetracks. Electrical time-series signals from the Hall detectors allow for the static and dynamic phase space visualization of the dynamics of a domain wall or multiple domain walls that can be described by a multicore memristor model. The domain wall dynamics and stochasticity can be controlled in racetracks even to deep submicron dimensions.
地球科学Earth Science
Unexpected far-field deformation of the 2023 Kahramanmara earthquakes revealed by space geodesy
空间大地测量揭示的2023年土耳其地震的远场变形
▲ 作者：S. ERGINTAV, P. VERNANT et al.
▲链接：
https://www.science.org/doi/10.1126/science.ado4220
▲摘要：
通过在2023年2月6日土耳其7.8和7.6级地震时使用全球导航卫星系统（GNSS），我们表明大地震可以诱发远场地壳变形（大于700公里），超过目前弹性位错模型的预测。
它们可以导致构造板块的移动和远场地震的触发，这对地震危险性评估具有深远的影响，并且需要从新的角度来研究地壳变形和地震力学。
▲ Abstract：
Using Türkiye’s extensive and continuous global navigation satellite system (GNSS) network during the moment magnitude 7.8 and 7.6 Kahramanmara earthquakes on 6 February 2023, we show that large earthquakes can induce far-field crustal deformations (>700 kilometers), exceeding current predictions from elastic dislocation models. They can lead to the mobilization of tectonic plates and the triggering of far-field earthquakes, which carries profound implications for seismic hazard assessments and necessitates a new perspective on crustal deformation and earthquake mechanics.
Global rise in forest fire emissions linked to climate change in the extratropics
全球森林火灾排放量的增加与温带地区的气候变化有关
▲ 作者：MATTHEW W. JONES, SANDER VERAVERBEKE et al.
▲链接：
https://www.science.org/doi/10.1126/science.adl5889
▲摘要：
我们使用机器学习系统地将森林生态区分为12个全球森林群落，每个群落都显示出了对对气候、人类和植被控制不同的敏感性。这表明，在2001年至2023年期间，与气候变化有关的热带焦树中迅速增加的森林火灾排放抵消了热带焦树中下降的排放。
由于容易着火的天气及森林覆盖率和生产力的增加，一个温带地区的年排放量增加了两倍。这导致全球森林生态区的森林火灾碳排放量增加了60%。我们的研究结果强调了在气候变化的情况下，森林及其碳储量对火灾干扰的脆弱性日益增加。
▲ Abstract：
We use machine learning to systematically group forest ecoregions into 12 global forest pyromes, with each showing distinct sensitivities to climatic, human, and vegetation controls. This delineation revealed that rapidly increasing forest fire emissions in extratropical pyromes, linked to climate change, offset declining emissions in tropical pyromes during 2001 to 2023. Annual emissions tripled in one extratropical pyrome due to increases in fire-favorable weather, compounded by increased forest cover and productivity. This contributed to a 60% increase in forest fire carbon emissions from forest ecoregions globally. Our results highlight the increasing vulnerability of forests and their carbon stocks to fire disturbance under climate change.
Direct optical measurement of intramolecular distances with angstrom precision
消费者的生物多样性增加了水生和陆地生态系统中有机养分的可利用性
▲ 作者：J. RYAN SHIPLEY, REBECCA OESTER et al.
▲链接：
https://www.science.org/doi/10.1126/science.adp6198
▲摘要：
昆虫和蜘蛛通过积累和合成有机营养物质在生态系统中起着至关重要的作用，如多不饱和脂肪酸（PUFA）。然而，生物多样性与昆虫和蜘蛛群落的营养成分之间的联系尚未被量化。我们将昆虫和蜘蛛的丰富度与包括9种土地利用方式的河流和陆地群落的生物量和多不饱和脂肪酸质量联系起来。
多不饱和脂肪酸的质量和生物量与生态系统的生物多样性呈正相关。水生生态系统的多不饱和脂肪酸质量始终高于陆地生态系统。我们的研究结果加强了保护生物多样性的重要性，并强调了水生生物多样性的独特益处。
▲ Abstract：
Insects and spiders play critical roles in ecosystems by accumulating and synthesizing organic nutrients such as polyunsaturated fatty acids (PUFAs). However, links between biodiversity and nutrient content of insect and spider communities have yet to be quantified. We relate insect and spider richness to biomass and PUFA-mass from stream and terrestrial communities encompassing nine land uses. PUFA-mass and biomass relate positively to biodiversity across ecosystems. In terrestrial systems, human-dominated areas have lower biomass and PUFA-mass than more natural areas, even at equivalent levels of richness. Aquatic ecosystems have consistently higher PUFA-mass than terrestrial ecosystems. Our findings reinforce the importance of conserving biodiversity and highlight the distinctive benefits of aquatic biodiversity.
人工智能Artificial Intelligence
AI can help humans find common ground in democratic deliberation
人工智能可以帮助人在审议中找到共同点
▲ 作者：MICHAEL HENRY TESSLER, MICHIEL A. BAKKER et al.
▲链接：
https://www.science.org/doi/10.1126/science.adq2852
▲摘要：
在这项研究中，我们训练了一个人工智能（AI）来调解人类议事过程。利用参与者的个人意见和批评，人工智能调解员迭代地生成和完善陈述，以表达群体在社会或问题上的共同立场。
参与者（N=5734）更喜欢人工智能生成的语句，而不是由人类调解人编写的内容，认为它们更有信息量、更清晰公正。讨论者经常在讨论后更新他们的想法，形成一个共同的观点。文本嵌入显示，成功的集体声明在尊重多数人立场的同时包含了不同的声音。
▲ Abstract：
In this study, we trained an artificial intelligence (AI) to mediate human deliberation. Using participants’ personal opinions and critiques, the AI mediator iteratively generates and refines statements that express common ground among the group on social or political issues. Participants (N = 5734) preferred AI-generated statements to those written by human mediators, rating them as more informative, clear, and unbiased. Discussants often updated their views after the deliberation, converging on a shared perspective. Text embeddings revealed that successful group statements incorporated dissenting voices while respecting the majority position.
