International Journal of Pharmaceutics, Journal Year: 2025, Volume and Issue: unknown, P. 125625 - 125625
Published: April 1, 2025
Language: Английский
Joule, Journal Year: 2024, Volume and Issue: 8(7), P. 1958 - 1981
Published: June 7, 2024
Language: Английский
Citations
69
Journal of the American Chemical Society, Journal Year: 2023, Volume and Issue: 145(40), P. 21699 - 21716
Published: Sept. 27, 2023
Exceptional molecules and materials with one or more extraordinary properties are both technologically valuable fundamentally interesting, because they often involve new physical phenomena compositions that defy expectations. Historically, exceptionality has been achieved through serendipity, but recently, machine learning (ML) automated experimentation have widely proposed to accelerate target identification synthesis planning. In this Perspective, we argue the data-driven methods commonly used today well-suited for optimization not realization of exceptional molecules. Finding such outliers should be possible using ML, only by shifting away from traditional ML approaches tweak composition, crystal structure, reaction pathway. We highlight case studies high-Tc oxide superconductors superhard demonstrate challenges ML-guided discovery discuss limitations automation task. then provide six recommendations development capable discovery: (i) Avoid tyranny middle focus on extrema; (ii) When data limited, qualitative predictions direction than interpolative accuracy; (iii) Sample what can made how make it defer optimization; (iv) Create room (and look) unexpected while pursuing your goal; (v) Try fill-in-the-blanks input output space; (vi) Do confuse human understanding model interpretability. conclude a description these integrated into workflows, which enable materials.
Language: Английский
Citations
47
Chemical Reviews, Journal Year: 2024, Volume and Issue: 124(17), P. 9899 - 9948
Published: Aug. 28, 2024
Electronic skins (e-skins) have seen intense research and rapid development in the past two decades. To mimic capabilities of human skin, a multitude flexible/stretchable sensors that detect physiological environmental signals been designed integrated into functional systems. Recently, researchers increasingly deployed machine learning other artificial intelligence (AI) technologies to neural system for processing analysis sensory data collected by e-skins. Integrating AI has potential enable advanced applications robotics, healthcare, human–machine interfaces but also presents challenges such as diversity model robustness. In this review, we first summarize functions features e-skins, followed feature extraction different models. Next, discuss utilization design e-skin address key topic implementation e-skins accomplish range tasks. Subsequently, explore hardware-layer in-skin before concluding with an opportunities various aspects AI-enabled
Language: Английский
Citations
30
Materials Today, Journal Year: 2024, Volume and Issue: unknown
Published: Sept. 1, 2024
Language: Английский
Citations
27
Science and Technology of Advanced Materials Methods, Journal Year: 2024, Volume and Issue: 4(1)
Published: Feb. 5, 2024
The acceleration of materials discovery has gained paramount importance due to its potential overcome constraints in emerging technologies. Extensive exploration been undertaken into three pivotal approaches: combinatorial synthesis, high-throughput characterization, and computational techniques, all aimed at unveiling new materials. This review article delves recent progress these domains. Combinatorial especially the development thin-film libraries, emerges as a potent method for efficiently generating comprehensive multinary systems composition gradients spanning entire spectrum required compositions. High-throughput characterization techniques play role assessing compositional, structural, functional attributes within yielding multidimensional datasets. Concurrently, advancements science have notably expedited process by enabling calculations simulations systems. These collective endeavors foster more robust correlation between composition, processing, structure, properties, facilitating forecast design future through data-driven discovery. approach allows efficient optimization newly identified Furthermore, informatics, an integral element this process, plays crucial managing extracting valuable insights from vast data generated during
Language: Английский
Citations
21
Chinese Chemical Letters, Journal Year: 2024, Volume and Issue: unknown, P. 110100 - 110100
Published: June 1, 2024
Language: Английский
Citations
16
Applied Physics Reviews, Journal Year: 2024, Volume and Issue: 11(1)
Published: March 1, 2024
Experimental science is enabled by the combination of synthesis, imaging, and functional characterization organized into evolving discovery loop. Synthesis new material typically followed a set steps aiming to provide feedback for optimization or discover fundamental mechanisms. However, sequence synthesis methods their interpretation, research workflow, has traditionally been driven human intuition highly domain specific. Here, we explore concepts scientific workflows that emerge at interface between theory, characterization, imaging. We discuss criteria which these can be constructed special cases multiresolution structural imaging as part more general workflows. Some considerations theory–experiment are provided. further pose emergence user facilities cloud labs disrupts classical progression from ideation, orchestration, execution stages workflow development. To accelerate this transition, propose framework design, including universal hyperlanguages describing laboratory operation, ontological matching, reward functions integration domains, policy development optimization. These tools will enable knowledge-based optimization; lateral instrumental networks, sequential parallel orchestration dissimilar facilities; empower distributed research.
Language: Английский
Citations
12
The Innovation Materials, Journal Year: 2024, Volume and Issue: unknown, P. 100090 - 100090
Published: Jan. 1, 2024
<p>Anthropogenic climate and environmental changes increasingly threaten the sustainability of life on Earth, hindering sustainable development human societies. These detrimental ecological are driven by activities that have elevated atmospheric levels greenhouse gases toxic substances, increased inorganic organic pollutants in water bodies, led to accumulation solid waste soils. Over next two three decades, impacts change, pollution, soil contamination expected intensify, posing increasing risks health global stability. Considering these trends, it is essential implement robust mitigation adaptation strategies. This paper analyzes pollution problems from perspectives atmospheric, water, contamination. It summarizes current research heterogeneous catalysis for treating gaseous, liquid, phases, with an emphasis key challenges applying catalytic conversion technologies cost-effective industrial settings. Finally, strategies mitigating via discussed material flow, energy data flow. aims offer scientific insights enhance future practice remediation.</p>
Language: Английский
Citations
11
Digital Discovery, Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 1, 2025
Archerfish is a low-cost, high-throughput tool for combinatorial materials research. Retrofitted with in situ mixing, prints 250 unique compositions per min—a 100× acceleration factor—for aqueous, nanoparticle, and crystalline materials.
Language: Английский
Citations
2
Surface and Coatings Technology, Journal Year: 2025, Volume and Issue: unknown, P. 131998 - 131998
Published: March 1, 2025
Language: Английский
Citations
2