编译 | 冯维维
Nature, 5 February 2026, Volume 650 Issue 8100
《自然》2026年2月5日，第650卷，8100期
物理学Physics
Vacuum ultraviolet second-harmonic generation in NH4B4O6F crystal
氟硼酸铵晶体中的真空紫外二次谐波生成
▲ 作者：Fangfang Zhang, Zilong Chen, Chen Cui, Zhihua Yang, Miriding Mutailipu, Fuming Li, Xueling Hou, Xifa Long & Shilie Pan
▲链接：
https://www.nature.com/articles/s41586-025-10007-z
▲摘要：
真空紫外光（VUV）光源在先进光谱学、量子研究和半导体光刻技术中至关重要。与传统大规模VUV产生技术相比，通过非线性光学晶体进行二次谐波生成（SHG）是最简单、最高效的方法。然而，适用于VUV波段的非线性光学晶体的稀缺限制了通过SHG产生VUV光的能力：现有材料要么无法满足相位匹配要求，要么转换效率低，要么存在严重的生长限制。
研究者报告了氟硼酸铵晶体NH4B4O6F（简称ABF）作为一种具有潜力的VUV产生材料。通过构建特定相位匹配角度的VUV器件，研究实现了创纪录的158.9 纳米相位匹配SHG输出，并在177.3 纳米波长下获得了最大纳秒脉冲能量4.8 mJ，转换效率达5.9%。其增强的非线性光学性能归因于氟基单元优化排列形成的非对称子晶格结构。该研究为非线性光学领域提供了新的材料，有望应用于基于ABF晶体的小型化、高功率VUV激光器。
▲ Abstract：
Vacuum ultraviolet (VUV, 100–200?nm) light sources are crucial for advanced spectroscopy, quantum research and semiconductor lithography. Compared with conventional large-scale VUV generation technologies, second-harmonic generation (SHG) through nonlinear optical (NLO) crystals is the simplest and most efficient method. However, the scarcity of suitable NLO crystals has constrained the production of VUV light through SHG: existing materials fail to meet phase-matching requirements, suffer from low conversion efficiency or have severe growth limitation. In this study, we report the development of the fluorooxoborate crystal NH4B4O6F (abbreviated as ABF) as a promising material for VUV light generation. VUV devices with specific phase-matching angles were constructed, achieving a record 158.9-nm light through phase-matching SHG and a maximum nanosecond pulse energy of 4.8?mJ at 177.3?nm with a conversion efficiency of 5.9%. The enhanced NLO performance is attributed to optimized arrangements of fluorine-based units creating asymmetric sublattices. This work provides further material in the NLO field, with potential for applications in compact, high-power VUV lasers using ABF.
Observation of a superfluid-to-insulator transition of bilayer excitons
双层激子超流—绝缘体转变的观测
▲ 作者：Yihang Zeng, Dihao Sun, Naiyuan J. Zhang, Ron Q. Nguyen, Qianhui Shi, A. Okounkova, K. Watanabe, T. Taniguchi, J. Hone, C. R. Dean & J. I. A. Li
▲链接：
https://www.nature.com/articles/s41586-025-09986-w
▲摘要：
与玻色-爱因斯坦凝聚（BEC）相关的最显著特性之一是超流性，即系统表现出零粘性且流动无耗散。超流相已在广泛的玻色系统中被观测到，涵盖天然量子流体（如液氦）以及人工平台（如双层激子和冷原子系统）。
理论研究表明，相互作用可能驱动BEC基态进入另一种奇异相——超固态，该相同时展现出晶态固体与超流体的特性。然而，迄今为止，尚未在材料系统中发现完全由相互作用驱动（无需外加晶格势）的预测BEC固体相。
研究报道了在双层磁激子层间不平衡体系中观测到超流-绝缘体转变。通过绘制双层凝聚体的输运行为随密度与温度变化的相图，研究者发现绝缘相是由偶极相互作用稳定的稀薄激子有序态。随着温度升高，绝缘体熔融为恢复的超流体，这可能表明低温固体相也是一种量子相干相。
▲ Abstract：
One of the most remarkable properties associated with Bose–Einstein condensation (BEC) is superfluidity, in which the system exhibits zero viscosity and flows without dissipation. The superfluid phase has been observed in wide-ranging bosonic systems spanning naturally occurring quantum fluids, such as liquid helium, to engineered platforms such as bilayer excitons and cold atom systems. Theoretical works have proposed that interactions could drive the BEC ground state into another exotic phase that simultaneously exhibits properties of both a crystalline solid and a superfluid—termed a supersolid. Identifying a material system, however, that hosts the predicted BEC solid phase, driven purely by interactions and without imposing an external lattice potential, has remained unknown. Here we report observation of a superfluid-to-insulator transition in the layer-imbalanced regime of bilayer magnetoexcitons. Mapping the transport behaviour of the bilayer condensate as a function of density and temperature suggests that the insulating phase is an ordered state of dilute excitons, stabilized by dipole interactions. The insulator melts into a recovered superfluid on increasing the temperature, which could indicate that the low-temperature solid is also a quantum coherent phase.
材料科学Material Sciences
Fibre integrated circuits by a multilayered spiral architecture
基于多层螺旋架构的纤维集成电路
▲ 作者：Zhen Wang, Ke Chen et al.
▲链接：
https://www.nature.com/articles/s41586-025-09974-0
▲摘要：
纤维电子器件正在将传统纤维与织物转变为新一代可穿戴设备，使其能够主动与人体及环境交互，从而塑造未来生活方式。目前，纤维电子器件已实现几乎所有预期功能，如供电、传感与显示。然而，作为构建类似于电子产品那样的智能交互纤维系统的核心，真正可用的信息处理纤维仍是一块缺失的拼图。
本研究填补了这一空白，创造了一种具有前所未有的微器件密度和多模态处理能力的纤维集成电路（FIC）。其集成密度达到每厘米10万个晶体管，有效满足了交互式纤维系统的要求。FIC不仅能够像典型的商业运算芯片一样处理数字和模拟信号，还能实现与当前先进存内图像处理器相媲美的高识别精度神经计算。
在严苛使用条件下，FIC仍保持稳定，而传统笨重或平面电路难以承受这些条件：包括1万次反复弯曲与磨损、拉伸30%、180°每厘米的扭转，甚至能承受重达15.6吨的集装箱卡车碾压。FIC的实现使得单一纤维内可构建闭环系统，无需依赖任何外部刚性与笨重的信息处理器。研究证明，这种全柔性纤维系统为实现许多前沿应用（如脑机接口、智能纺织品和虚拟现实可穿戴设备）所需的交互模式铺平了道路。此项工作为推进纤维器件向智能系统发展提供了新的思路。
▲ Abstract：
Fibre electronic devices are transforming traditional fibres and garments into new-generation wearables that can actively interact with human bodies and the environment to shape future life. Fibre electronic devices have achieved almost all of the desired functions, such as powering, sensing and display functions. However, viable information-processing fibres, which lie at the heart of building intelligent interactive fibre systems similar to any electronic product, remain the missing piece of the puzzle. Here we fill this gap by creating a fibre integrated circuit (FIC) with unprecedented microdevice density and multimodal processing capacity. The integration density reaches 100,000 transistors per centimetre, which effectively satisfies the requirements for interactive fibre systems. The FICs can not only process digital and analogue signals similar to typical commercial arithmetic chips but also achieve high-recognition-accuracy neural computing similar to that of the state-of-the-art in-memory image processors. The FICs are stable under harsh service conditions that bulky and planar counterparts have difficulty withstanding, such as repeated bending and abrasion for 10,000 cycles, stretching to 30%, twisting at an angle of 180°?cm?1 and even crushing by a container truck weighing 15.6?tons. The realization of FICs enables closed-loop systems in a single fibre, without the need for any external rigid and bulky information processors. We demonstrate that this fully flexible fibre system paves the way for the interaction pattern desired in many cutting-edge applications, for example, brain–computer interfaces, smart textiles and virtual-reality wearables. This work presents new insights that can promote the development of fibre devices towards intelligent systems.
Discovery Learning predicts battery cycle life from minimal experiments
发现学习仅需少量实验即可预测电池循环寿命
▲ 作者：Jiawei Zhang, Yifei Zhang et al.
▲链接：
https://www.nature.com/articles/s41586-025-09951-7
▲摘要：
在电池等复杂物理系统中，快速可靠地验证新设计方案对于加速技术创新至关重要。然而，电池研发仍受限于评估新设计方案寿命所需的高昂时间与能耗成本，存在瓶颈。需要特别指出的是，现有寿命预测方法需依赖包含目标设计方案寿命标签的数据集以提高准确性，且无法在原型制作前做出可靠预测，从而限制了快速反馈。
受教育心理学启发，研究者提出“发现学习”——一种融合主动学习、物理引导学习与零样本学习的科学机器学习方法，其构建了类人推理闭环。该方法可从历史电池设计方案中学习，减少原型制作需求，从而仅通过少量实验即可预测新设计方案的寿命。为验证发现学习的有效性，研究者提供了包含123个大型锂离子软包电池的工业级电池数据集，涵盖多样化材料-设计组合及循环测试方案。
使用与该研究不同的公开电芯设计数据集进行训练后，发现学习在预测循环寿命时，仅需利用51%电芯原型前50次循环的物理特征，即可达到7.2%的测试误差。在保守假设下，与传统方法相比，这可节省98%的时间与95%的能耗。发现学习标志着电池寿命预测在精度与效率方面取得了重要进展，更广泛而言，有助于实现机器学习加速科学发现的潜力。
▲ Abstract：
Fast and reliable validation of new designs in complex physical systems such as batteries is critical to accelerating technological innovation. However, battery development remains bottlenecked by the high time and energy costs required to evaluate the lifetime of new designs. Notably, existing lifetime forecasting approaches require datasets containing battery lifetime labels for target designs to improve accuracy and cannot make reliable predictions before prototyping, thus limiting rapid feedback.
Here we introduce Discovery Learning, a scientific machine learning approach that integrates active learning, physics-guided learning and zero-shot learning into a human-like reasoning loop, drawing inspiration from educational psychology. Discovery Learning can learn from historical battery designs and reduce the need for prototyping, thereby predicting the lifetime of new designs from minimal experiments. To test Discovery Learning, we present industrial-grade battery data comprising 123 large-format lithium-ion pouch cells, including diverse material–design combinations and cycling protocols. Trained on public datasets of cell designs different from ours, Discovery Learning achieves 7.2% test error in predicting cycle life using physical features from the first 50 cycles of 51% of cell prototypes. Under conservative assumptions, this results in savings of 98% in time and 95% in energy compared with conventional practices. Discovery Learning represents a key advance in accurate and efficient battery lifetime prediction and, more broadly, helps realize the promise of machine learning to accelerate scientific discovery.
行星科学Planetary Science
Core–envelope miscibility in sub-Neptunes and super-Earths
核心—包层混溶性在亚海王星和超级地球中的研究
▲ 作者：Travis Gilmore & Lars Stixrude
▲链接：
https://www.nature.com/articles/s41586-025-09970-4
▲摘要：
亚海王星和超级地球是银河系中最常见的行星类型，其半径介于地球和海王星之间，与太阳系中的任何行星都不同。然而，关于它们的结构和起源，仍存在一些根本性问题。尽管超级地球主要由岩石构成，但亚海王星形成了半径更大的独特种群，被认为由岩石核心覆盖富氢包层构成。
在核心-包层界面极端条件下（超过数千开尔文温度和数吉帕斯卡压力），核心与包层之间可能发生反应，但这些反应的性质和程度尚不清楚。研究基于密度泛函理论的第一性原理分子动力学模拟表明，在核心-包层可能存在的广泛压力-温度条件下，硅酸盐与氢气具有完全混溶性。
结果发现，这种混溶性源于氢与硅酸盐之间广泛的化学反应，产生了硅烷、一氧化硅和水等物质，这些物质可能通过正在进行的或未来的观测任务被探测到。核心-包层的混溶性对亚海王星和超级地球的演化具有深远影响：它会使行星的大部分氢溶解于核心中，并在行星演化过程中驱动氢在核心与包层之间的交换。
▲ Abstract：
Sub-Neptunes and super-Earths, the most abundant types of planet in the galaxy, are unlike anything in the Solar System, with radii between those of Earth and Neptune. Fundamental questions remain regarding their structure and origin. Although super-Earths have a rocky composition, sub-Neptunes form a distinct population at larger radii and are thought to consist of a rocky core overlain by a hydrogen-rich envelope. At the extreme conditions of the core–envelope interface 以低温室气体浓度和覆盖北美及欧洲大部分大陆的冰盖为特征。因此，冰期气候与现今差异显著，全球平均温度更低，赤道至极地的温度梯度增大，可能导致西风带更为强劲。然而，在这种冰期气候强迫下，北大西洋深层海洋的状态仍不确定，尤其是受限于深海温盐数据的匮乏。
研究表明，冰期西北大西洋深层（>1.5公里）水温约为0–2°C（仅比现今低1.8±0.5°C），且在考虑全海洋变化后，海水δ18O值高出0.3±0.1‰，并可追溯至通过副极地东北大西洋和北欧海域输送的副热带表层水。研究中的水文数据揭示了西北大西洋深层的热力与同位素结构，表明末次盛冰期期间持续形成了相对温暖且可能盐度较高的北大西洋深层水。此外，研究结果为用于预测未来气候变化的地球系统模型提供了更新的基准约束。
▲ Abstract：
The Last Glacial Maximum (19–23?thousand years ago) was characterized by low greenhouse gas concentrations and continental ice sheets that covered large parts of North America and Europe. Glacial climate was therefore very different, with colder global mean temperatures and an increased Equator-to-pole temperature gradient, probably resulting in stronger westerlies. However, the state of the deep North Atlantic Ocean under these glacial climate forcings remains uncertain, particularly owing to the rarity of deep-ocean temperature and salinity constraints. Here we show that the temperature of the glacial deep (>1.5?km) Northwest Atlantic was approximately 0–2?°C (only 1.8?±?0.5?°C (2?s.e.) colder than today), and, after accounting for the whole-ocean change, seawater δ18O was 0.3?±?0.1‰ (2?s.e.) higher and can be traced back to the surface subtropics via the subpolar Northeast Atlantic and Nordic Seas. Together, our hydrographic data reveal the thermal and isotopic structure of the deep Northwest Atlantic and suggest sustained production of relatively warm and probably salty North Atlantic Deep Water during the Last Glacial Maximum. Furthermore, our results provide updated constraints for benchmarking Earth system models used to project future climate change.
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