Second-harmonic generation (SHG) is a coherent second-order nonlinear optical technique that provides interface-specific information about molecular orientation, surface structure and electrostatics across a broad range of interfaces. This Primer describes conventional intensity-based nonresonant SHG and modern phase-resolved SHG, with an emphasis on the fundamentals and instrumentation, and discusses aspects in data collection, processing and analysis. Representative applications in acid–base interfacial chemistry, biological sensing, electrochemistry and high-resolution imaging illustrate the scope of SHG. Practical guidance on reproducibility, current limitations and future directions is also provided. Second-harmonic generation (SHG) is a second-order nonlinear optical technique for probing molecular organization and electrostatics at interfaces. This Primer introduces intensity-based nonresonant and phase-resolved SHG and discusses how these approaches are implemented in practice, from experimental design and data collection to analysis, applications, reproducibility and future developments.
Artificial intelligence (AI) agents are emerging in scientific research as systems that can transform the accumulated decisions of scientists into traceable workflows. In fact, modern scientific practice depends on continual coordination of knowledge dispersed across literature, data, theory and experiment, which, however, is often made through manual, case-by-case judgement. This Primer introduces agentic AI systems as a general method to structure this process through natural language interfaces, serving as a computational brain in the laboratory. Central to this framework are practical workflows for in-depth literature search and knowledge mining, orchestration of physics-based simulations, and integration with automated experimental platforms. We begin by describing the foundations of AI agents, including task decomposition, memory, tool use and communication between agents, and by distinguishing single-agent and multi-agent designs, as well as fully autonomous and human-in-the-loop configurations. Equally important are the means by which these systems are evaluated, documented and reported reproducibly. Finally, we examine major bottlenecks, including hallucination, tool misuse, limited interpretability and safety risks, and outline a future in which coordinated networks of agents, instruments and researchers transform scientific discovery from isolated tasks into continuous adaptive experimentation. Agentic artificial intelligence (AI) systems enhance scientific workflows by structuring knowledge coordination through natural language interfaces. In this Primer, Feng et al. examine the challenges and opportunities involved in integrating AI agents in the laboratory.
Cell-free DNA (cfDNA) carries extensive biological and clinical information, reflecting cell death, immune processes and tissue-specific chromatin organization. However, its short-fragment size and low abundance limit comprehensive molecular characterization by conventional approaches. Nanopore sequencing enables direct, single-molecule analysis of cfDNA, preserving sequence, methylation and fragmentation features without amplification bias. Recent advances in pore chemistry, basecalling and library preparation have made nanopore-based cfDNA analysis increasingly feasible across applications including oncology, prenatal diagnostics, transplantation monitoring and infectious disease. This Primer provides a methodological framework for cfDNA nanopore sequencing, covering pre-analytical variables, library preparation for short DNA fragments, sequencing strategies and downstream data analysis. Emphasis is placed on basecalling, methylation detection, fragmentomic profiling and integration of multi-omic signals. We discuss key technical challenges, including sequencing accuracy, fragment-length bias and limitations in detecting low-frequency variants, and highlight practical considerations for reproducibility, quality control and reporting. Finally, we outline emerging directions, including single-molecule methylome analysis, improved computational models and integration of multilayer cfDNA signals for diagnostic applications. Cell-free DNA is generally fragmented and present in low abundance, making its detection and characterization challenging. In this Primer, Korabečná et al. discuss the use of nanopore sequencing for cell-free analysis from blood samples, as well as associated technical challenges.
Thermogels are temperature-responsive polymer systems that undergo reversible sol–gel transitions under physiologically relevant conditions, driven by temperature-induced changes in polymer hydration, hydrophilic–hydrophobic balance and molecular association. The study of thermogels encompasses a spectrum of design strategies that couple polymer chemistry and tunable molecular architecture with physicochemical characterization, gelation mapping and application-specific testing. This Primer focuses on synthetic thermogels, with poly(ethylene glycol)–polyester-based, polyurethane-based and polypeptide-based thermogels serving as three principal methodological paradigms for detailed discussion. Other synthetic thermogels, including poloxamers, poly(organophosphazene) and lower critical solution temperature-type polymers, are discussed where relevant to provide broader context, whereas thermogelling systems based primarily on naturally derived polymers, such as chitosan-based formulations, fall outside the principal scope of this Primer. We outline experimental methods used to design, synthesize and characterize thermogels, including approaches for mapping gelation behaviour, resolving microstructure, quantifying mechanical and transport properties and assessing stability and biodegradation. Emphasis is placed on how experimental choices influence gelation windows, mechanical readouts and performance across different use scenarios. Application-oriented workflows are summarized for drug delivery, tissue engineering and medical devices. We further discuss factors affecting reproducibility, propose minimum reporting standards and outline strategies for data deposition to enable cross-study comparison. Finally, we discuss how standardized high-throughput workflows and data-driven formulation mapping may support more systematic and predictive thermogel development. Together, these approaches provide a framework for improving the reproducibility, comparability and application-specific development of thermogels. Thermogels are polymeric materials that transition between sol and gel states in response to temperature changes. In this Primer, Wang et al. outline the design, synthesis and characterization of synthetic thermogels.
