《自然》（20230126出版）一周论文导读

▲ 作者：Nitish Mehta, Roman Kuzmin, Cristiano Ciuti & Vladimir E. Manucharyan

▲ 链接：

https://www.nature.com/articles/s41586-022-05615-y

▲ 摘要：

一个粒子衰变成更多粒子是相互作用的量子系统中普遍存在的现象，会发生在对撞机、核反应堆或固体中。在非线性介质中，即使是单个光子也会以费米黄金法则给出的速率，通过下转换（分裂）成具有相同总能量的低频光子而衰减。但如果介质是有限的且只支持量子化模式，则不能精确地匹配能量守恒条件。

作者使用超导多模腔实现了这一实验，其非线性被适应于强烈违反光子数守恒。由此产生的相互作用试图将单光子激发转化为低能量光子簇，但由于多体局部化机制而失败，这表现为在空腔驻波模式频率下的多粒子共振的惊人光谱精细结构。

每个共振都被确定为由宽频率范围的光子组成的多体辐射状态，不遵守费米的黄金法则理论。研究结果引入了一个新的平台来探索多体定位的基本原理，而不必控制许多原子或量子位。

▲ Abstract：

Decay of a particle into more particles is a ubiquitous phenomenon to interacting quantum systems, taking place in colliders, nuclear reactors or solids. In a nonlinear medium, even a single photon would decay by down-converting (splitting) into lower-frequency photons with the same total energy, at a rate given by Fermi’s golden rule. However, the energy-conservation condition cannot be matched precisely if the medium is finite and only supports quantized modes. Here we implement such an experiment using a superconducting multimode cavity, the nonlinearity of which was tailored to strongly violate the photon-number conservation. The resulting interaction attempts to convert a single photon excitation into a shower of low-energy photons but fails owing to the many-body localization mechanism, which manifests as a striking spectral fine structure of multiparticle resonances at the standing-wave-mode frequencies of the cavity. Each resonance was identified as a many-body state of radiation composed of photons from a broad frequency range and not obeying Fermi’s golden rule theory. Our result introduces a new platform to explore the fundamentals of many-body localization without having to control many atoms or qubits.

▲ 作者：Zhongran Liu, Han Wang, Ming Li, Lingling Tao, Tula R. Paudel, Hongyang Yu, Yuxuan Wang, Siyuan Hong, Meng Zhang, Zhaohui Ren, Yanwu Xie, Evgeny Y. Tsymbal, Jingsheng Chen, Ze Zhang & He Tian

▲ 链接：

https://www.nature.com/articles/s41586-022-05503-5

▲ 摘要：

畴壁纳米电子学被认为是非易失性存储器和逻辑技术的一种新范式，在这种技术中，作为有源元件的是畴壁而非域。特别有趣的是铁电结构中的带电畴壁，它具有亚纳米厚度，并表现出非平凡的电子和输运特性，这对于各种纳电子学应用非常有用。

作者报道了一种在几纳米厚的BiFeO₃铁电薄膜中可控地生成和操纵面内带电畴壁的方法。通过在扫描透射电子显微镜中使用原位偏压技术，研究者检测到一种非常规的逐层切换机制，其中铁电畴生长发生在平行于外加电场的方向上。

基于原子分辨电子能量损失谱、在线电子全息图的原位电荷映射和理论计算，他们证明了在带电畴壁积聚的氧空位是畴壁稳定和运动的原因。

BiFeO₃薄膜平面内畴壁位置的电压控制产生了多个非挥发性电阻状态，从而证明了作为几个单位单元厚的忆阻器的关键功能特性。这些结果促进了对铁电开关行为的更好理解，并为制造单位电池级器件提供了新的策略。

▲ Abstract：

Domain-wall nanoelectronics is considered to be a new paradigm for non-volatile memory and logic technologies in which domain walls, rather than domains, serve as an active element. Especially interesting are charged domain walls in ferroelectric structures, which have subnanometre thicknesses and exhibit non-trivial electronic and transport properties that are useful for various nanoelectronics applications. Here we report a strategy for the controllable creation and manipulation of in-plane charged domain walls in BiFeO₃ ferroelectric films a few nanometres thick. By using an in situ biasing technique within a scanning transmission electron microscope, an unconventional layer-by-layer switching mechanism is detected in which ferroelectric domain growth occurs in the direction parallel to an applied electric field. Based on atomically resolved electron energy-loss spectroscopy, in situ charge mapping by in-line electron holography and theoretical calculations, we show that oxygen vacancies accumulating at the charged domain walls are responsible for the domain-wall stability and motion. Voltage control of the in-plane domain-wall position within a BiFeO₃ film gives rise to multiple non-volatile resistance states, thus demonstrating the key functional property of being a memristor a few unit cells thick. These results promote a better understanding of ferroelectric switching behaviour and provide a new strategy for creating unit-cell-scale devices.

▲ 作者：Hao Chen, Aidan Maxwell, Chongwen Li, Sam Teale, Bin Chen, Tong Zhu, Esma Ugur, George Harrison, Luke Grater, Junke Wang, Zaiwei Wang, Lewei Zeng, So Min Park, Lei Chen, Peter Serles, Rasha Abbas Awni, Biwas Subedi, Xiaopeng Zheng, Chuanxiao Xiao, Nikolas J. Podraza, Tobin Filleter, Cheng Liu, Yi Yang, Joseph M. Luther, Edward H. Sargent

▲ 链接：

https://www.nature.com/articles/s41586-022-05541-z

▲ 摘要：

在宽带隙（超过1.7 eV）的钙钛矿太阳能电池中，开路电压（VOC）亏缺比大约1.5 eV的钙钛矿更。准费米能级分裂测量表明，在电子传输层接触处存在VOCs限制复合。

加拿大多伦多大学教授Edward Sargent团队研究发现，这源于不均匀的表面电位和较差的钙钛矿电子传输层能量排列。普通的单铵表面处理无法解决这一问题；作为一种替代方法，他们引入了二铵分子来修饰钙钛矿的表面状态，并实现了更均匀的表面电位空间分布。使用1,3-丙烷二铵，准费米级分裂提高了90 meV，使1.79 eV的钙钛矿太阳能电池具有1.33 V的VOC认证和超过19%的功率转换效率（PCE）。

将该层纳入单片全钙钛矿串联，研究者报告了2.19 V的创纪录VOC（详细平衡VOC限值的89%）和超过27%的PCE（26.3%经过准稳态认证）。这些串联在操作500小时后保留了超过86%的初始PCE。

▲ Abstract：

The open-circuit voltage (VOC) deficit in perovskite solar cells is greater in wide-bandgap (over 1.7 eV) cells than in perovskites of roughly 1.5 eV. Quasi-Fermi-level-splitting measurements show VOC-limiting recombination at the electron-transport-layer contact. This, we find, stems from inhomogeneous surface potential and poor perovskite–electron transport layer energetic alignment. Common monoammonium surface treatments fail to address this; as an alternative, we introduce diammonium molecules to modify perovskite surface states and achieve a more uniform spatial distribution of surface potential. Using 1,3-propane diammonium, quasi-Fermi-level splitting increases by 90 meV, enabling 1.79 eV perovskite solar cells with a certified 1.33 V VOC and over 19% power conversion efficiency (PCE). Incorporating this layer into a monolithic all-perovskite tandem, we report a record VOC of 2.19 V (89% of the detailed balance VOC limit) and over 27% PCE (26.3% certified quasi-steady state). These tandems retained more than 86% of their initial PCE after 500 h of operation.

▲ 作者：Jordi Burés & Igor Larrosa

▲ 链接：

https://www.nature.com/articles/s41586-022-05639-4

▲ 摘要：

对催化有机反应机理的理解对于设计新的催化剂、反应模式和发展更绿色、更可持续的化学过程至关重要。研究者展示了一个深度神经网络模型，进过训练后可以分析普通的动力学数据，并自动阐明相应的机构类，而不需要任何额外的用户输入。

该模型以出色的精度识别了各种各样的机制类别，包括脱离稳态的机制，例如那些涉及催化剂激活和失活步骤的机制，并且即使在动力学数据包含大量误差或只有几个时间点时也能出色地执行。

作者表示，该研究结果表明，人工智能引导的机理分类是一个强大的新工具，可以简化和自动化的机理说明。他们正在将这个模型免费提供给社区，预计该工作将促进全自动有机反应发现和开发的进一步发展。

▲ Abstract：

A mechanistic understanding of catalytic organic reactions is crucial for the design of new catalysts, modes of reactivity and the development of greener and more sustainable chemical processes. Here we show that a deep neural network model can be trained to analyse ordinary kinetic data and automatically elucidate the corresponding mechanism class, without any additional user input. The model identifies a wide variety of classes of mechanism with outstanding accuracy, including mechanisms out of steady state such as those involving catalyst activation and deactivation steps, and performs excellently even when the kinetic data contain substantial error or only a few time points. Our results demonstrate that artificial-intelligence-guided mechanism classification is a powerful new tool that can streamline and automate mechanistic elucidation. We are making this model freely available to the community and we anticipate that this work will lead to further advances in the development of fully automated organic reaction discovery and development.

▲ 作者：Natalie M. Larson, Jochen Mueller, Alex Chortos, Zoey S. Davidson, David R. Clarke & Jennifer A. Lewis

▲ 链接：

https://www.nature.com/articles/s41586-022-05490-7

▲ 摘要：

螺旋结构在自然界中普遍存在，并赋予其独特的机械性能和多功能。目前，模拟这些自然系统的合成结构可以通过缠绕、扭曲和编织单个细丝、微流体、自成型和打印等方法实现。

然而，这些制造方法无法同时创建和图案多材料，螺旋结构的细丝与亚体素控制任意二维和三维图案从广泛的材料。作者报告了一个多材料三维旋转打印平台，能够对方位异质结构细丝的局部方向进行亚体素控制。

通过控制角速度与平动速度的比值连续旋转多材料喷嘴，他们创建了具有可编程螺旋角、层厚度和给定圆柱体素内几种材料之间的界面面积的螺旋细丝。利用这种集成方法，研究者制造了由高保真度的螺旋介电弹性体驱动器和嵌入介电弹性体基质中的可单独寻址的导电螺旋通道组成的功能性人造肌肉。

他们还制作了包含建筑螺旋杆的层次格，在柔顺矩阵中包含刚性弹簧。该增材制造平台为在生物灵感图案中生成多功能建筑材料开辟了新的途径。

▲ Abstract：

Helical structures are ubiquitous in nature and impart unique mechanical properties and multifunctionality. So far, synthetic architectures that mimic these natural systems have been fabricated by winding, twisting and braiding of individual filaments, microfluidics, self-shaping and printing methods. However, those fabrication methods are unable to simultaneously create and pattern multimaterial, helically architected filaments with subvoxel control in arbitrary two-dimensional (2D) and three-dimensional (3D) motifs from a broad range of materials. Here we report a rotational multimaterial 3D printing (RM-3DP) platform that enables subvoxel control over the local orientation of azimuthally heterogeneous architected filaments. By continuously rotating a multimaterial nozzle with a controlled ratio of angular-to-translational velocity, we have created helical filaments with programmable helix angle, layer thickness and interfacial area between several materials within a given cylindrical voxel. Using this integrated method, we have fabricated functional artificial muscles composed of helical dielectric elastomer actuators with high fidelity and individually addressable conductive helical channels embedded within a dielectric elastomer matrix. We have also fabricated hierarchical lattices comprising architected helical struts containing stiff springs within a compliant matrix. Our additive-manufacturing platform opens new avenues to generating multifunctional architected matter in bioinspired motifs.

▲ 作者：Hongjie Hu, Hao Huang, Mohan Li, Xiaoxiang Gao, Lu Yin, Ruixiang Qi, Ray S. Wu, Xiangjun Chen, Yuxiang Ma, Keren Shi, Chenghai Li, Timothy M. Maus, Brady Huang, Chengchangfeng Lu, Muyang Lin, Sai Zhou, Zhiyuan Lou, Yue Gu, Yimu Chen, Yusheng Lei, Xinyu Wang, Ruotao Wang, Wentong Yue, Xinyi Yang, Sheng Xu

▲ 链接：

https://www.nature.com/articles/s41586-022-05498-z

▲ 摘要：

心功能连续成像对于长期心血管健康评估、急性心功能不全检测以及危重患者或外科患者的临床管理非常有价值。然而，传统的非侵入性心功能成像方法由于设备体积大，无法提供连续的测量，现有的可穿戴心脏设备只能捕获皮肤上的信号。

作者报道了一种可穿戴式超声设备，用于连续、实时和直接的心功能评估。他们介绍了设备设计和材料制造方面的创新，改善了设备与人体皮肤之间的机械耦合，允许在运动过程中从不同角度检查左心室。

研究者还开发了一个深度学习模型，从连续的图像记录中自动提取左心室容量，生成关键心脏性能指标的波形，如冲程容量、心排血量和射血分数。该技术能够在各种环境下对心脏性能进行动态可穿戴监测，大大提高了准确性。

▲ Abstract：

Continuous imaging of cardiac functions is highly desirable for the assessment of long-term cardiovascular health, detection of acute cardiac dysfunction and clinical management of critically ill or surgical patients. However, conventional non-invasive approaches to image the cardiac function cannot provide continuous measurements owing to device bulkiness, and existing wearable cardiac devices can only capture signals on the skin. Here we report a wearable ultrasonic device for continuous, real-time and direct cardiac function assessment. We introduce innovations in device design and material fabrication that improve the mechanical coupling between the device and human skin, allowing the left ventricle to be examined from different views during motion. We also develop a deep learning model that automatically extracts the left ventricular volume from the continuous image recording, yielding waveforms of key cardiac performance indices such as stroke volume, cardiac output and ejection fraction. This technology enables dynamic wearable monitoring of cardiac performance with substantially improved accuracy in various environments.