It’s possible that I shall make an ass of myself. But in that case one can always get out of it with a little dialectic. I have, of course, so worded my proposition as to be right either way (K.Marx, Letter to F.Engels on the Indian Mutiny)
Thursday, March 26, 2026
Insights from past cold and warm periods: Larger interannual temperature variability over China
Institute of Atmospheric Physics, Chinese Academy of Sciences
Interannual temperature variability plays a critical role in determining the frequency and intensity of extreme climate events. Understanding how this variability responds to different external forcings is essential for assessing future climate risks. However, the short length of instrumental records limits our knowledge of its behavior and mechanisms at long-term scales.
As past representative warm and cold periods respectively, the Last Interglacial (LIG, ~129–116 ka) and Last Glacial Maximum (LGM, ~23–19 ka) offer two ideal natural experiments for investigating how temperature variability responds to distinct forcings. However, changes in interannual temperature variability over China during these periods have not been systematically quantified, nor have the underlying mechanisms been compared across different climate backgrounds. In particular, it remains unclear whether the temperature variability responded uniformly across seasons and regions, and which energy balance components dominated the changes.
To address these questions, researchers from the Shanghai Regional Climate Center, China, and Institute of Atmospheric Physics, Chinese Academy of Sciences, China, quantified the changes in interannual temperature variability over China during the past warm period of the Last Interglacial and the cold period of the Last Glacial Maximum, as well as the associated mechanisms, using all available simulations performed by 12 state-of-the-art global climate models. The results have recently been published in Atmospheric and Oceanic Science Letters.
Using seven models chosen for their good performance, the study shows that the interannual temperature variability increased over China during both the LIG and LGM, with national average increases of 8% and 15%, respectively. Seasonally, the LIG exhibits a greater variability increase in summer than in winter, whereas the LGM shows a stronger winter than summer variability increase. These asymmetric seasonal patterns are primarily driven by different responses of atmospheric energy budget components to external forcings of LIG insolation changes and LGM reduced greenhouse gas concentrations, respectively, which are particularly pronounced in eastern China.
"These paleoclimate insights reveal that changes in interannual temperature variability and their driving mechanisms are closely linked to the background climate state with specific external forcings," explains the corresponding author, Associate Prof. Zhiping Tian. "Therefore, this study provides a critical long-term perspective for understanding future changes in extreme temperature events."
Increased interannual variability of temperature over China during the last interglacial and last glacial maximum: Magnitudes and asymmetric seasonal patterns
Article Publication Date
25-Mar-2026
New holographic data storage approach packs more data into the same space
Researchers combine amplitude, phase and polarization for faster, higher-capacity 3D data storage
Researchers developed a holographic data storage approach that stores and retrieves information in three dimensions by combining the amplitude, phase and polarization properties of light.
Credit: Xiaodi Tan, Fujian Normal University in China
WASHINGTON — Researchers have developed a holographic data storage approach that stores and retrieves information in three dimensions by combining three properties of light — amplitude, phase and polarization. By allowing more data to be stored in the same space, the new approach could help advance efforts to meet the growing global demand for data storage.
Holographic data storage uses laser light to store digital information inside a material. Instead of recording data only on a surface, like a hard drive or optical disc, it stores many overlapping light patterns throughout the volume of the material, allowing much higher storage density and faster data transmission.
“In conventional holographic data storage, data encoding typically uses one light dimension such as amplitude or phase alone, or, at most, combines two of these dimensions,” said research team leader Xiaodi Tan from Fujian Normal University in China. “Based on the principle of polarization holography, we used a deep learning architecture known as a convolutional neural network model to enable the use of polarization as an independent information dimension.”
In Optica, Optica Publishing Group’s journal for high-impact research, the researchers describe their new holographic data storage technique and demonstrate that it can increase information density while also simplifying readout.
“With further development and commercialization, this type of multidimensional holographic data storage could enable smaller data centers and more efficient large-scale archival storage, while also enhancing data processing and transmission efficiency,” said Tan. “It could also contribute to safer data transmission, optical encryption and advanced imaging.”
Using polarization to store information
Holographic data storage records information as image-like data pages formed by laser light patterns. Encoding converts digital data into these pages for recording, and decoding restores the recorded pages back into user data.
Although multiple properties of light can theoretically be used to encode more information in each data page, doing so in practice is challenging. To address this, the researchers have spent years refining tensor-based polarization holography, which preserves the polarization state recorded in the hologram during reconstruction. This allows polarization to serve as a reliable channel for storing information.
In the new work, they developed a 3D modulation encoding scheme by controlling the intensity and phase of two orthogonal polarization states and using a double-phase hologram approach. This enabled a single phase-only spatial light modulator to encode amplitude, phase and polarization information in the optical field.
Decoding combined amplitude, phase and polarization (3D) information is difficult because sensors only detect light intensity (amplitude) and cannot directly sense phase and polarization. The researchers solved this problem by utilizing tensor-polarization holography theory and designing a convolutional neural network model to simultaneously retrieve 3D information directly from diffraction intensity images.
The model learns the amplitude, phase and polarization features of the optical field from two complementary diffraction images: one captured with a vertical polarizer and one without. By using these intensity images as inputs, the trained neural network can simultaneously decode amplitude, phase and polarization, which achieves increasing storage density and enhancing transmission speed.
Decoding with a neural network
After validating the theory behind the new method, the researchers built a compact setup to record and reconstruct the encoded optical field in a polarization-sensitive medium. During evaluation and decoding, the recorded intensity images were analyzed to identify amplitude, phase and polarization signatures in the intensity distributions. These signatures were then used as inputs for neural network decoding so that 3D data could be reconstructed simultaneously from intensity-only measurements.
“Overall, our results showed that multidimensional joint encoding substantially increased the information carried by a single holographic data page, thereby improving storage capacity,” said Tan. “In addition, neural network synchronous decoding reduced the need for complex measurements and step-by-step reconstruction, supporting more efficient readout and decoding. This could enable a practical route toward high-capacity, high-throughput holographic data storage.”
The researchers note that this work remains a research-stage demonstration, with further work needed before commercialization. To make it more practical for real-world operating conditions, they plan to increase the gray levels of coding to further expand capacity and improve the recording media’s long-term stability, uniformity and repeatability. They also want to combine the system with volumetric holographic multiplexing approaches to enable multi-page, multi-channel storage and strengthen the co-integration of optical hardware and decoding algorithms for faster, more robust data retrieval under practical conditions.
Paper: R. Chen, J. Wang, H. Wu, M. Song, Y. Yang, D. Lin, X. Tan, “Encoding and decoding of multidimensional optical field modulation in holographic data storage” 13, (2026).
Optica is an open-access journal dedicated to the rapid dissemination of high-impact peer-reviewed research across the entire spectrum of optics and photonics. Published monthly by Optica Publishing Group, the Journal provides a forum for pioneering research to be swiftly accessed by the international community, whether that research is theoretical or experimental, fundamental or applied. Optica maintains a distinguished editorial board of more than 60 associate editors from around the world and is overseen by Editor-in-Chief Thomas Krauss, University of York, UK. For more information, visit Optica.
About Optica Publishing Group
Optica Publishing Group is a division of the society, Optica, Advancing Optics and Photonics Worldwide. It publishes the largest collection of peer-reviewed and most-cited content in optics and photonics, including 18 prestigious journals, the society’s flagship member magazine, and papers and videos from more than 835 conferences. With over 400,000 journal articles, conference papers and videos to search, discover and access, our publications portfolio represents the full range of research in the field from around the globe.
Encoding and decoding of multidimensional optical field modulation in holographic data storage
The image shows (a) the holographic data storage system schematic diagram, (b) a schematic diagram illustrating the complex plane for double-phase decomposition of complex amplitude and (c) an example of a checkerboard pattern for two phase valuesm andn.Alsoshown are (d) an example of the intensity distribution at the image plane and (e) an example of phase distribution at the image plane. In (f), the first (I) and second (II) records are shown, with the readout shown in (g).
Credit
Xiaodi Tan, Fujian Normal University in China
The research team involved in developing the new holographic data storage approach.
This image created using Gemini Pro, depicts an activated carbon fiber functionalized with amine groups (–NH2) at adjacent positions. This arrangement improves the energy efficacy of key interactions, enabling the desorption of captured carbon dioxide at lower temperatures.
Credit: Associate Professor Yasuhiro Yamada from Chiba University, Japan
Capturing carbon dioxide (CO2) before it reaches the atmosphere is a key strategy for reducing greenhouse gas emissions. Even though carbon capture technologies have existed for decades, their widespread adoption has been slow for a straightforward reason: most of them are expensive and inefficient. For example, aqueous amine scrubbing, which is the most common industrial method, requires heating large volumes of liquid above 100 °C to release captured CO2 and reset the system for reuse. These energy demands translate directly into operating costs, making large-scale deployment challenging.
Carbon-based solid adsorbents have emerged as a promising alternative. These solid, inexpensive materials with large surface area can bind CO2 and then release it with less heat under low temperature, especially when featuring nitrogen-containing functional groups. Unfortunately, while the performance benefits of these functional groups are apparent, standard synthesis methods can only deposit them randomly and in mixed configurations, making it difficult to know which specific arrangement actually drives efficient performance and why.
Against this backdrop, a research team led by Associate Professor Yasuhiro Yamada from the Graduate School of Engineering and Associate Professor Tomonori Ohba from the Graduate School of Science at Chiba University, Japan, tackled this problem. Their work reports the synthesis and thorough characterization of a new class of carbon materials called 'viciazites,' which contain a carefully controlled configuration of nitrogen groups in adjacent positions. The paper, published online in the journal Carbon on February 27, 2026, was co-authored by Mr. Kota Kondo, also from Chiba University.
The team synthesized three distinct viciazites, each carrying a different type of adjacent nitrogen pairing. To introduce adjacent primary amine groups (–NH2 groups), they carbonized a compound called coronene at high temperature, then treated the material with bromine and finally with ammonia gas. This three-step process produced adjacent –NH2 groups with 76% selectivity, meaning that the vast majority of introduced nitrogen ended up in the target configuration. The other two materials were made using different precursors: one carrying adjacent pyrrolic nitrogen was synthesized at 82% selectivity, and the other with adjacent pyridinic nitrogen was synthesized at 60% selectivity.
All three materials were coated onto activated carbon fibers to create practical adsorbent samples. The researchers used several techniques, including nuclear magnetic resonance spectroscopy, X-ray photoelectron spectroscopy, and computational modeling to confirm that the introduced nitrogen groups were indeed positioned next to each other in an adjacent manner and not scattered randomly.
Performance tests showed clear differences between the three configurations. The materials with adjacent –NH2 groups and adjacent pyrrolic nitrogen both outperformed untreated carbon fibers in CO2 uptake, while adjacent pyridinic nitrogen groups showed little benefit. The most striking result was observed with desorption, which is the process of releasing the captured CO2 to regenerate the material. "Performance evaluation revealed that in carbon materials where NH2 groups are introduced adjacently, most of the adsorbed CO2 desorbs at temperatures below 60 °C. By combining this property with industrial waste heat, it may be possible to achieve efficient CO2 capture processes with substantially reduced operating costs," highlights Dr. Yamada. Additionally, the pyrrolic nitrogen-containing material, though releasing CO2 at a higher temperature, may prove more durable in the long run owing to the superior chemical stability of that functional group.
Overall, by showing that adjacent nitrogen configurations can be built deliberately and reproducibly, this study establishes a promising design framework for the next generation of carbon capture materials. "Our motivation is to contribute to the future society and to utilize our recently developed carbon materials with controlled structures. This work provides validated pathways to synthesize designer nitrogen-doped carbon materials, offering the molecular-level control essential for developing next-generation, cost-effective, and advanced CO2 capture technologies," concludes Dr. Yamada. The researchers also note that viciazite materials may find uses beyond CO2 capture, such as adsorbents for metal ions and catalysts, given the precise and tunable nature of their surface chemistry.
To see more news from Chiba University, click here.
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Reference: Authors: Kota Kondo1, Ayane Uchizono2, Lizhi Pu1, Itsuki Takahashi3, Ryoshin Suzuki1, Sota Nakamura1, Kai Kan4, Kazuma Gotoh4, Tetsuro Soejima5, Satoshi Sato1, Tomonori Ohba3, and Yasuhiro Yamada1 Affiliations: (1) Department of Applied Chemistry and Biotechnology, Graduate School of Engineering, Chiba University; (2) Faculty of Engineering, Chiba University; (3) Graduate School of Science, Chiba University; (4) Center for Nano Materials and Technology, Japan Advanced Institute of Science and Technology (JAIST); (5) Department of Applied Chemistry, Faculty of Science and Engineering, Kindai University DOI: 10.1016/j.carbon.2026.121405
About Associate Professor Yasuhiro Yamada from Chiba University Dr. Yasuhiro Yamada obtained his PhD in February 2008 from The State University of New York at Buffalo. He currently serves at the Graduate School of Engineering, Chiba University. He conducts research on structurally controlled carbon materials, focusing on developing techniques for structural control and analysis and unraveling the mysteries of high-performance carbon materials. He has published more than 150 papers to his name.
About Associate Professor Tomonori Ohba from Chiba University Dr. Tomonori Ohba obtained his PhD in March 2002 from Chiba University. He currently serves at the Graduate School of Science, Chiba University. He conducts research on the molecular systems at the interfaces of nanoscale materials and nanoscale material chemistry. He has published more than 214 articles to his name.
Funding: This work was supported by Mukai Science and Technology Foundation, Japan Society for the Promotion of Science (JSPS KAKENHI Grant Number JP24K01251), and the "Advanced Research Infrastructure for Materials and Nanotechnology in Japan (ARIM)" of the Ministry of Education, Culture, Sports, Science and Technology (MEXT) under Grant Number JPMXP1225JI0008.
