Materials Research Science and Engineering Centers (MRSEC) UPENN

宾夕法尼亚大学物质结构研究实验室(LRSM)是材料研究和教育的卓越中心。它促进了来自不同学科-物理、化学、工程和生物学-的研究人员之间的合作，以推进变革性的科学项目和解决社会挑战。一项研究工作从大脑的学习能力中获得灵感，设计出能够适应周围环境和复杂刺激的新材料。潜在的应用范围从制造能够转移锤击能量的柔性材料到制造能够执行复杂任务的软机器人。这些进展将导致新材料的设计具有自然系统中找不到的特性，从而实现全新的技术。第二项研究利用了材料自然分解成油和水等不同阶段的优势。研究小组利用分离的物理学来操纵蛋白质、细胞和其他软材料的组装，以设计生物物质。潜在的应用包括细胞内关键分子的分割和受控释放的新途径，类似于药物输送，以及创造新的组织状材料，从而显著促进合成生物学、生物技术和医学的发展。LRSM教育和激励下一代材料科学家和工程师，扩大了对材料研究企业的参与。LRSM为从小学到研究生的所有级别的学生提供课程和活动，并提供博士后级别的专业培训。这些活动包括通过动手实验和演示向学生介绍令人兴奋的材料科学世界的夏令营和讲习班，允许学生参与科学项目并向该领域的专家学习的研究机会和指导，以及向更广泛的公众突出材料科学的多样性和影响的外联活动和在线资源。LRSM还为材料研究提供了最先进的设施和设备，使宾夕法尼亚大学、地区和国家大学、政府实验室和行业的研究人员能够推进自己的研究活动。技术简介-1：学习超材料(NSF大想法：理解生活规则，利用数据革命)开发和利用学习策略，模拟大脑如何使用本地规则来改变其结构，以创建和破坏突触，以进行分布式和稳健的学习。研究团队提出并应用局部自适应学习来创建新型微流控超材料和软机器人，了解生物聚合物网络在体内的功能，并开发具有功能和复杂变形和应力重分布行为的机械超材料。研究活动还通过探索利用动力学和非线性的作用的新的学习策略来推进学习理论。IRG-2：浓缩蛋白中间相和细胞集体的生物启发工程(NSF大想法：理解生命规则)发现由多肽或细胞构件组成的浓缩中间相的生命规律，并使用这些原理来设计从微米到厘米长尺度的合成生物材料的结构和动力学。研究小组了解并利用相划分在生物物质中创建多个长度尺度的结构组织，包括如何将大分子分离到细胞中的生化隔间，以及如何在组织中细胞彼此分离。LRSM在培养一支具有竞争力和多样化的科学和工程劳动力方面处于全国领先地位，以满足学术界、政府和行业的需求。它提供广泛的教育、外展和人力资源开发计划，面向所有级别的人，重点是代表性不足的少数族裔、妇女、残疾人和第一代/低收入学生，从K-16到博士后学生、博士后、教师、学术界、工业和政府的科学家以及普通公众。LRSM将管理和共享其研究、教育和外展数据。此外，LRSM还为美国技术竞争力关键领域的博士生和博士后研究人员提供独特的跨学科培训。它开发并促进地方、地区和国家科学界使用独特的科学实验设施。由IRGS&amp；Seed产生的发现和理解将为利用主动学习来构建新的超材料提供根本的新方法，并将利用相分配的热力学和动力学来以前所未有的控制合成生物材料。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

NON-TECHNICAL ABSTRACTThe Laboratory for Research on the Structure of Matter (LRSM) at the University of Pennsylvania is a center of excellence for materials research and education. It facilitates collaboration between researchers from different disciplines – physics, chemistry, engineering, and biology – to advance transformative scientific projects and solve societal challenges. One research effort takes inspiration from the brain’s ability to learn, designing new materials that can adapt to their surroundings and complex stimuli. Potential applications range from making flexible materials that can deflect the energy of a hammer blow to creating soft robots that can perform complex tasks. These advances will result in the design of new materials with properties not found in naturally occurring systems, enabling entirely new technologies. A second research effort takes advantage of how materials naturally separate into distinct phases like oil and water. The research team leverages the physics of demixing to manipulate the assembly of proteins, cells, and other soft materials to engineer living matter. Potential applications include new avenues for partitioning and controlled release of key molecules inside cells, akin to drug delivery, and creating new tissue-like materials, thereby significantly advancing synthetic biology, biotechnology, and medicine. The LRSM educates and inspires the next generation of materials scientists and engineers, broadening participation in the materials research enterprise. The LRSM offers programs and activities for students at all levels, from elementary school to graduate school, and provides professional training at the post-doctoral level. These activities include summer camps and workshops that introduce students to the exciting world of materials science through hands-on experiments and demonstrations, research opportunities and mentorship that allows students to participate in scientific projects and learn from experts in the field, and outreach events and online resources that highlight the diversity and impact of materials science to the broader public. The LRSM also provides access to state-of-the-art facilities and equipment for materials research, allowing researchers at Penn, regional and national universities, government laboratories, and industries to advance their own research activities. TECHNICAL ABSTRACTIRG-1: Learning Metamaterials (NSF Big Ideas: Understanding the Rules of Life, Harnessing the Data Revolution) develops and exploits learning strategies that mimic how the brain uses local rules to change its structure to create and destroy synapses for distributed and robust learning. The research team advances and applies local adaptive learning to create novel microfluidic metamaterials and soft robots, understand how biopolymer networks function in vivo, and develop mechanical metamaterials with functional and complex deformation and stress redistribution behavior. Research activity also advances the theory of learning by exploring new learning strategies that capitalize on the role of dynamics and non-linearities. IRG-2: Bioinspired Engineering of Condensed Protein Mesophases and Cell Collectives (NSF Big Ideas: Understanding the Rules of Life) discovers Rules of Life for condensed mesophases composed of polypeptide or cellular building blocks and uses these principles to engineer the structure and dynamics of synthetic biomaterials over micron to centimeter length scales. The research team understands and utilizes phase partitioning to create structural organization over multiple length scales in living matter, including how macromolecules can be segregated into biochemical compartments in cells and how cells can segregate from one another in tissues. LRSM is a national leader in developing a competitive and diverse science and engineering workforce in demand by academia, government, and industry. It provides a wide range of education, outreach, and human resource development programs that target people at all levels, with emphasis on underrepresented minorities, women, persons with disabilities, and first-generation/low-income students, from K-16 to Ph.D. students, post-docs, teachers, scientists in academia, industry, & government, and the general public. LRSM will curate and share its research, education, and outreach data. In addition, the LRSM provides unique interdisciplinary training for doctoral students and post-doctoral researchers in critical fields for US technological competitiveness. It develops and facilitates the use of unique scientific experimental facilities by the local, regional, and national scientific community. The discoveries and understanding generated by the IRGs & Seeds will provide fundamentally new ways to harness active learning to build novel metamaterials and will exploit the thermodynamics and kinetics of phase partitioning to synthesize biomaterials with unprecedented control.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.